1 st International Congress of Applied Ichthyology & Aquatic Environment November 13 th -15 th, Volos, Greece

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1 1 st International Congress of Applied Ichthyology & Aquatic Environment November 13 th -15 th, Volos, Greece

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3 Table of Contents THEMATIC FIELD: INLAND AQUATIC RESOURCES... 8 ORAL PRESENTATIONS IN GREEK... 8 THE IMPACT OF STOCKING ACTIVITIES ON THE NATIVE BROWN TROUT POPULATIONS OF THE NESTOS RIVER... 9 ASSESSMENT OF WATER QUALITY MONITORING BASED ON TWO YEARS DATA (2008 & 2011) IN LAKE KASTORIA, WESTERN MACEDONIA, GREECE MONITORING PARAMETERS Tw, DO AND ENVIRONMENTAL EVALUATION OF THE ARTIFICIAL LAKE OF THESAURUS FOR THE YEARS ORAL PRESENTATIONS IN ENGLISH INTERRELATIONSHIP BETWEEN TOC, IC, TC AND DO, BOD, COD OF WATER IN REGARD TO STRATIFICATION OF AN ABANDONED OCP AT RANIGANJ COAL FIELD AREA, BURDWAN, WEST BENGAL TRANSCRIPTION RESPONSES IN THE KILLIFISH (Aphanius dispar) DURING LONG-TERM EXPOSURE TO HIGH TEMPERATURE OF HOT SPRING... THEMATIC FIELD: AQUACULTURE ORAL PRESENTATIONS IN GREEK CONVENTIONAL AND ORGANIC FISH FARMING EFFECTS ON MACROFAUNA COMMUNITIES IN EVOIKOS GULF (LARYMNA) THE EFFECT OF FOOD PARTICLE SIZE ON GROWTH AND SIZE VARIATION OF JUVENILE SEA BASS TRENDS AND TYPOLOGY OF WORK ACCIDENTS IN GREEK MARICULTURE: THE ROLE OF GENDER STUDY ON THE SEASONAL ENERGY INVESTMENT IN RED PORGY Pagrus pagrus (LINNAUES, 1758) COMPARISON OF TWO INJECTABLE BIVALENT COMMERCIAL VACCINES (ANTI-VIBRIO- PHOTOBACTERIUM) IN CULTURED SEA BASS ( Dicentrarchus labrax, L. 1758) LYMPHOCYSTIS DISEASE VIRUS (LCDV) DΕTECTION IN GILTHEAD SEABREAM EGGS AND LARVAE VOLATILE METABOLITES AS POTENTIAL CHEMICAL SPOILAGE INDICES OF GREEK AQUACULTURED FISH SPECIES RESEARCH OF THE COOLING EFFECT WITH EVAPORATION IN THE MICROCLIMATE OF NET-COVERED GREENHOUSE AND IN THE GROWTH OF FARMED SNAILS ORAL PRESENTATIONS IN ENGLISH HOW GREEN CAN AQUACULTURE BE? FROM RISK ANALYSIS TO GREEK CRISIS MANAGEMENT IN AQUACULTURE: THE CASE OF THE MEDITERRANEAN MUSSEL FARMING IN GREECE CAN WE OPTIMIZE OXYGENATION IN AQUACULTURE IN THE MEDITERRANEAN REGION BY USING A NOVEL AIR DIFFUSION SYSTEM?

4 CONTENTS OF As, Cd, Hg AND Pb IN TWO CULTURED FISH SPECIES FROM TURKEY EFFECT OF DIETARY SUPPLEMENTATION OF Spirulina platensis ON THE GROWTH AND HAEMATOLOGY OF THE STRESSED CATFISH Clarias gariepinus SUBSTITUTION OF FISHMEAL BY FLY Hermetia illucens PREPUP AE MEAL IN THE DIET OF GILTHEAD SEABREAM (Sparus aurata) HIGH-THROUGHPUT SEQUENCING IN AQUACULTURE: THE COMPLEXITIES OF SEX DETERMINATION IN FARMED FISH WITH SEXUAL DIMORPHISM THEMATIC FIELD: ENVIRONMENTAL MANAGEMENT ORAL PRESENTATIONS IN ENGLISH METHODOLOGICAL CONTRIBUTION TO THE FORMATION OF MARITIME SPATIAL PLANS AS A MANAGEMENT TOOL TO MINIMISE CONFLICTS BETWEEN AQUACULTURE AND OTHER COASTAL ACTIVITIES ASSESSMENT OF CONSECUTIVE PLANKTON BLOOMS ON MARCH AND APRIL 2014 IN IZMIT BAY (THE MARMARA SEA) THE COMPREHENSIVE CHARACTERISTIC OF POPULATION PARAMETERS OF HIGH BODY PICKAREL Spicara flexuosa FROM DIFFERENT BAYS IN COASTAL AREA OF SEVASTOPOL (BLACK SEA) UNDERWATER TRAILS: INNOVATIVE ACTIVITY IN SITHONIA (CHALKIDIKI, GREECE) IMPLEMENTING STANDRAD EU METHOD FOR SAMPLING FRESHWATER FISH WITH MULTI-MESH GILLNETS IN A LAKE'S SUB-BASINS (PRESPA LAKE, ALBANIA) Cu AND Zn CONTENT IN WILD SEA BREAM AND SEA BASS FROM THE PAGASITIKOS GULF (EASTERN MEDITERRANEAN) THE EFFECTS OF RAINBOW TROUT (Oncorhynchus mykiss) FARMS ON WATER QUALITY OF KHALKAI RIVER, MASAL, GUILAN BIOCHEMICAL EFFECTS OF ALMIX HERBICIDE IN THREE FRESHWATER TELEOSTEAN FISHES EFFECTS OF CHROMIUM ON TISSUE-SPECIFIC BIOCHEMICAL PARAMETERS IN FRESHWATER CATFISH, Anabas testudineus (Bloch) ORAL PRESENTATIONS IN GREEK TOLERANCE OF SEAGRASS Cymodocea nodosa PHOTOSYNTHETIC ACTIVITY ΤΟ SALINITY.175 PRELIMINARY RESULTS ON THE BENEFITS FROM THE RESTORATION OF LAKE KARLA TO ITS WIDER PROTECTED AREA POPULATION COASTAL WATER POLLUTION FROM THE URBAN RUNOFF NETWORK IN CHANIA, GREECE CHEMICAL WATER QUALITY OF LAKE AND LAGOON OF VISTONIS (PORTO LAGOS, N. GREECE) EFFECTS OF BISPHENOL-A (BPA) ON SEX DIFFERENTIATION AND ON GROWTH OF F1 GENERATION NAYPLII OF THE AMPHIGONIC POPULATION Artemia franciscana TEMPORAL CHANCES OF THE TECHNICAL AND SPATIAL FEATURES OF AQUACULTURE FARMS IN GREECE AND TURKEY

5 SEASONALITY HAS AN IMPACT ON HEAVY METAL CONCENTRATION IN PAGASITIKOS GULF FISH SPECIMENS THEMATIC FIELD: FISHERIES TECHNOLOGY ORAL PRESENTATIONS IN ENGLISH ANALYSIS OF TRAWL RESOURCES WITHIN MEDITS SURVEY 2013 ALONG THE MONTENEGRIN COAST (SOUTH ADRIATIC SEA) IDENTIFICATION OF FISHING GROUNDS FOR THE TARGET SPECIES OF BOTTOM TRAWL IN THE HELLENIC WATERS COMPARISON OF SOME BIOLOGICAL CHARACTERISTICS OF EUROPEAN ANCHOVY, Engraulis encrasicolus (Linnaeus, 1758), BETWEEN BOKA KOTORSKA BAY AND OPEN SEA, SOUTH ADRIATIC SEA, MONTENEGRO MORPHOLOGICAL STUDY OF Parapenaeus longirostris (Penaidae), IN THE EASTERN MEDITERRANEAN SEA PHYSICOMECHANICAL PROPERTIES OF BLACK MOUTH CROAKER SURIMI KAMABAKO GEL MADE FROM VARIOUS HYDROCOLLOIDS SOME BIOLOGICAL CHARACTERISTICS OF BOGUE, Boops boops (LINNAUES, 1758) FROM BOKA KOTORSKA BAY, SOUTH ADRIATIC SEA (MONTENEGRO) THE INVESTIGATION OF BROWN TROUT FEEDING REGIME IN TONEKABON RIVER INTERACTION BETWEEN FISH SPOILAGE BACTERIA AND PATHOGEN Yersinia enterocolitica IN SEA BREAM FILLETS AND MODEL SUBSTRATES ORAL PRESENTATIONS IN GREEK PRELIMINARY RESULTS ON AGE AND GROWTH OF COMMON PANDORA (Pagellus erythrinus) IN THE SOUTHERN AEGEAN SEA AGE ESTIMATION OF RED MULLET (Mullus barbatus) IN THE EASTERN MEDITTERANEAN SEA PRELIMINARY STUDY OF JUVENILE PICAREL, Spicara smaris (LINNAUES 1758), GROWTH FROM OTOLITH MICROSTRUCTURE DOCUMENTARY APPEARANCE OF Tylosurus acus imperialis INDIVIDUALS IN THERMAIKOS GULF ESTIMATION OF AGE AND GROWTH OF EUROPEAN HAKE IN THE AEGEAN AND IONIAN SEA THEMATIC FIELD: FISHERIES ECONOMICS ORAL PRESENTATIONS IN ENGLISH ESTIMATES OF THE ECONOMIC IMPACTS OF SEA LEVEL RISE ON PAROS AND NAXOS ISLANDS (CYCLADES ARCHIPELAGO GREECE) INVESTIGATION OF THE FACTORS AFFECTING FARMED FISH CONSUMPTION ASSESSING THE EFFICIENCY OF BOTTOM TRAWLERS AND SMALL-SCALE FISHING VESSELS IN GREECE 301 SCIENTIFIC DIVING AND APPLICABLE LAW FRESHWATER HABITATS AND FISHING ACTIVITIES IN THE BURIGANGA RIVER, DHAKA, BANGLADESH 318 5

6 ANALYSIS OF VISITORS WILLINGNESS TO PAY CONCERNING A COASTAL RECREATIONAL SITE IN CENTRAL GREECE ORAL PRESENTATIONS IN GREEK AN INVESTIGATION OF THE COMPETITIVENESS OF GREEK GILT-HEAD SEA BREAM IN EU MARKET POSTERS THEMATIC FIELD: AQUACULTURE REFERENCE BLOOD PARAMETERS VALUES FOR SIBERIAN STURGEON, Acipenser baeri (Brandt) GILTHEAD SEABREAMS (Sparus aurata) WITH LORDOSIS DEFORMITY. WHAT ABOUT VERTEBRAS COLLAGEN FIBRILS? THE EFFECT OF DRIED CITRUS EXTRACT ON GROWTH, BODY PROXIMATE COMPOSITION, LIVER HISTOLOGY AND FILLET SHELF LIFE OF GILTHEAD SEA BREAM (Sparus aurata) POPULATION GENETIC STRUCTURE OF COMMON CARP Cyprinus carpio IN ANZALI WETLAND AND GORGANROUD ESTUARY USING MICROSATELLITE MARKERS MICROSCOPIC STRUCTURE OF SPLEEN IN PERSIAN STURGEON Acipencer persicus EFFECT OF EXOGENOUS LPS ADMINISTRATION ON MOLECULAR MECHANISMS IN GILTHEAD SEABREAM, Sparus aurata SPERM QUALITY CHARACTERISTICS OF WILD THICK LIPPED GREY MULLET Chelon labrosus ΙNVESTIGATION OF THE POSSIBILITY OF ESTABLISHING AND OPERATING, INTENSIVE, SEMI-INTENSIVE AND SEMI-EXTENSIVE LAND-BASED SYSTEM OF PRODUCTION OF MARINE FISHES IN SUITABLE LOCATION OF PAGASITIKOS GULF INVESTIGATING THE POTENTIAL OF FRESHWATER AQUACULTURE PRODUCTION IN TWO ECUADORIAN PROVINCES: OPPORTUNITΙES & CHALLENGES COMPARATIVE HISTOPATHOLOGICAL AND IMMUNOHISTOCHEMICAL EVALUATIONS IN JUVENILE SEA BASS (Dicentrarchus labrax) AND GILTHEAD SEA BREAM (Sparus aurata) NATURALLY INFECTED WITH PHOTOBACTERIUM DAMSELAE Photobacterium damselae subsp. piscicida DEVELOPMENT OF A DIGITAL CHECKLIST OF GREEK FISH FAUNA THEMATIC FIELD: FISHERIES TECHNOLOGY SOME CHARACTERISTICS OF BOGUE, Boops boops (Linnaeus, 1758) FROM BOKA KOTORSKA BAY, SOUTH ADRIATIC SEA DIFFERENCE BETWEEN BAYESIAN AND CLASSICAL ESTIMATION OF GROWTH PARAMETERS OF Mullus barbatus barbatus (Linnaeus, 1758) DIET COMPOSITION OF GOLDEN GREY MULLET, Liza aurata (Risso, 1810) IN THE MAZANDARAN COSTLINE, CASPIAN SEA PRELIMINARY STUDY ON THE REPRODUCTIVE BIOLOGY AND LENGTH-WEIGHT RELATIONSHIPS OF Galeus melastomus IN THE EASTERN IONIAN SEA MSY ASSESSMENT IN DATA-SCARCE SITUATIONS: TWO CASE STUDIES SEXUAL MATURITY OF THE AGUJON NEEDLEFISH Tylosurus acus imperialis

7 THEMATIC FIELD: ENVIROMENTAL MANAGEMENT ANALYSIS OF GENETIC VARIABILITY AND DIFFERENTIONIN OF STALLATE STURGEON, Acipenser stellatus (Pallas, 1771), USING MICROSATELLITE MARKERS FISHERMEN AND SEA TURTLE INTERACTION IN A PROTECTED AREA GENETIC STRUCTURE OF GOLDEN MULLET, Liza aurata, USING MICROSATELLITE MARKERS CONTENTS OF Cu AND Zn IN BOGUE, Boops boops AND PICAREL, Spicara smaris FROM THE KISSAMOS GULF, CRETE EVALUATING THE SENSITIVITY OF CERTAIN EVENNESS INDICES TO SPECIES RARITY IN SIMULATED MACROBENTHIC COMMUNITIES OF DIFFERENT STRUCTURE NEW PRACTICES IMPROVING BREEDING SELECTION PROGRAMMES FOR EUROPEAN SEA BASS (Dicentrarchus labrax) AND GILTHEAD SEA BREAM (Sparus aurata) THEMATIC FIELD: INLAND AQUATIC RESOURCES & FISHERIES ECONOMICS GROWTH, AGE AND SIZE STRUCTURE OF THE ROUND GOBY (Neogobius melanostomus) FROM ITS MAIN HABITATS IN BULGARIAN WATERS EFFECTS OF SODIUM BICARBONATE ON CRITICAL SWIMMING SPEED OF RAINBOW TROUT (Oncorhynchus mykiss) WHAT IS THE PROBLEM ON REPRODUCTIVE PERFORMANCE? AN ASSESSMENT ON QUALITY PARAMETERS AND FATTY ACIDS PROFILE IN EGGS IN RAINBOW TROUT AND BROWN TROUT SNAIL FARMING IN CYPRUS: AN OVERVIEW OF THE CURRENT SITUATION ORGANIZING COMMITTEE SCIENTIFIC COMMITTEE

8 THEMATIC FIELD: INLAND AQUATIC RESOURCES ORAL PRESENTATIONS IN GREEK 8

9 THE IMPACT OF STOCKING ACTIVITIES ON THE NATIVE BROWN TROUT POPULATIONS OF THE NESTOS RIVER Iakovaki D. 1, Giantsis Η.Α. 1, Sapounidis Α. 2, Koutrakis Μ. 2, Apostolidis Α.P. 1 * 1 Lab of Ichthyology & Fisheries, Department of Animal Production, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece 2 Fisheries Research Institute-NAGREF, Nea Peramos, 64007, Kavala, Greece ABSTRACT The aim of the present study was to evaluate the impact of stocking activities, which were carried out during the last decades with fingerlings from Acheloos hatcheries, on the native brown trout (Salmo sp.) populations of Nestos river. In total, 60 trout individuals collected in the years from seven sampling sites of the Nestos river system were included in the analysis. The PCR-RFLP technique was applied on a c bp mitochondrial DNA segment containing the ND5 and ND6 genes. Two restriction enzymes, which discriminate the indigenous individuals from the intruders, were used. The results revealed that the indigenous trout populations of three tributaries (Arkoudorema, Mousda, Vathyrema-Kalikarpo) were strongly affected by the stoking from Acheloos river. However, all individuals collected from higher sampling sites (Diavolorema, Farasino, Vathyrema-Elatia Forest) seem to be pure i.e. without being mixed with those of Acheloos. Our data suggest the urgent need of appropriate strategies in order to conserve and protect these native populations. Key words: Salmo sp., River Nestos, fish stocking, PCR-RFLP *Corresponding author: Apostolidis P. Apostolos (apaposto@agro.auth.gr) EΠΗΠΣΧΔΗ ΣΧΝ ΔΜΠΛΟΤΣΗΜΧΝ ΣΟΤ ΦΤΗΚΟΤ ΠΛΖΘΤΜΟΤ ΑΓΡΗΑ ΠΔΣΡΟΦΑ ΣΟ ΤΣΖΜΑ ΣΟΤ ΠΟΣΑΜΟΤ ΝΔΣΟΤ Ηαθσβάθε Γ. 1, Γηάληζεο Η.Α. 1, απνπλίδεο Α. 2, Κνπηξάθεο Μ. 2, Απνζηνιίδεο Α.Π. 1 * 1 Δνβαζηήνζμ Ηπεομημιίαξ & Αθζείαξ, Σμιέαξ Εςζηήξ Παναβςβήξ, πμθή Γεςπμκίαξ, Γαζμθμβίαξ & Φοζζημφ Πενζαάθθμκημξ, Ανζζημηέθεζμ Πακεπζζηήιζμ Θεζζαθμκίηδξ, 54124, Θεζζαθμκίηδ, Δθθάδα 2 Ηκζηζημφημ Αθζεοηζηήξ Ένεοκαξ ΔΛΓΟ ΓΖΜΖΣΡΑ, Νέα Πέναιμξ, 64007, Κααάθα, Δθθάδα ΠΔΡΗΛΖΦΖ ηδκ ενβαζία ιεθεηήεδηε δ έηηαζδ ηαζ μζ ζοκέπεζεξ ηςκ ειπθμοηζζιχκ ιε αθθυπεμκα ζπεφδζα πέζηνμθαξ ζημοξ εκδδιζημφξ πθδεοζιμφξ πέζηνμθαξ ημο Νέζημο. οκμθζηά, ζηδκ ακάθοζδ ζοιπενζθήθεδηακ 60 άημια άβνζαξ πέζηνμθαξ, πμο ζοθθέπεδηακ ηα έηδ απυ 7 ζηαειμφξ δεζβιαημθδρίαξ ημο ζοζηήιαημξ ημο Νέζημο, υπμο ηζξ πνμδβμφιεκεξ δεηαεηίεξ είπακ απεθεοεενςεεί αθθυπεμκα ζπεφδζα πέζηνμθαξ απυ ημ ζφζηδια ημο Απεθχμο. Ζ ακάθοζδ πναβιαημπμζήεδηε ιε ηδ πνήζδ ηδξ PCR-RFLP ιεεμδμθμβίαξ, ζε πενζμπή ημο ιζημπμκδνζαημφ DNA πμο πενζθαιαάκεζ ηα βμκίδζα ND5 ηαζ ND6, πνδζζιμπμζχκηαξ 2 έκγοια πενζμνζζιμφ. Σα έκγοια αοηά ζηδ ζοβηεηνζιέκδ πενζμπή, δζαηνίκμοκ 2 απθυηοπμοξ παναηηδνζζηζημφξ βζα ηα αοηυπεμκα άημια ημο Νέζημο ηαζ αοηά πμο πνμένπμκηαζ απυ ημκ Απεθχμ. Σα απμηεθέζιαηα απμηάθορακ έκημκδ πανμοζία ηςκ εζζαπεέκηςκ αηυιςκ πέζηνμθαξ ζημοξ εκδδιζημφξ πθδεοζιμφξ ημο Νέζημο, ηαεχξ ζε ηνεζξ παναπμηάιμοξ ημο δ πθεζμκυηδηα ηςκ αηυιςκ πμο ιεθεηήεδηακ ειθάκζζε ημκ απθυηοπμ πμο παναηηδνίγεζ ηδκ πέζηνμθα ημο Απεθχμο. Πανυθα αοηά, ζε δείβιαηα πμο ζοθθέπεδηακ απυ ζδιεία ιε ιεβαθφηενμ ορυιεηνμ δεκ ανέεδηε ηακέκα άημιμ ιε ημκ απθυηοπμ ημο Απεθχμο. οκεπχξ, ηαηαδεζηκφεηαζ δ άιεζδ ακάβηδ θήρδξ ηαηάθθδθςκ δζαπεζνζζηζηχκ ιέηνςκ βζα ηδκ πνμζηαζία ηςκ εκδδιζηχκ πθδεοζιχκ πέζηνμθαξ πμο δεκ έπμοκ επδνεαζηεί απυ ημοξ ειπθμοηζζιμφξ ημο πανεθευκημξ ηαζ πμο απμηεθμφκ πμθφηζιμ βεκεηζηυ οθζηυ. Λέξειρ κλειδιά: Salmo sp., Νέζηνο, εκπινπηηζκνί, PCR-RFLP *οββναθέαξ επζημζκςκίαξ: Απμζημθίδδξ Π. Απυζημθμξ (apaposto@agro.auth.gr) 1. Δηζαγσγή Ζ ζπεομπακίδα ηςκ εζςηενζηχκ οδάηςκ ηδξ Δθθάδαξ εεςνείηαζ ιζα απυ ηζξ πθμοζζυηενεξ ηδξ Δονχπδξ, ανζειχκηαξ πενζζζυηενα απυ 170 είδδ (Λεμκάνδμξ & Μπυιπμνδ 2013). Χζηυζμ, πμθθά απυ ηα είδδ αοηά απακηχκηαζ απμιμκςιέκα ηαζ ζε ιζηνμφξ πθδεοζιμφξ, ιε απμηέθεζια κα ανίζημκηαζ οπυ ηδκ απεζθή ελαθάκζζδξ (Κμοηνάηδξ 2013). Χξ ιέεμδμζ βζα ηδκ εκίζποζδ ηςκ ζπεομαπμεειάηςκ, ηυζμ ζηδ πχνα ιαξ υζμ ηαζ ζε παβηυζιζμ επίπεδμ, πνδζζιμπμζήεδηακ μζ εζζαβςβέξ λεκζηχκ εζδχκ ηαεχξ ηαζ μζ ιεηαηζκήζεζξ πθδεοζιχκ απυ έκα οδάηζκμ μζημζφζηδια πνμξ έκα άθθμ, εκένβεζεξ πμο, πανυηζ ζε ανηεηέξ πενζπηχζεζξ απμδείπηδηακ εοενβεηζηέξ (Economidis et al. 2000), 9

10 δδιζμφνβδζακ ηαζ έκα απυ ηα ζδιακηζηυηενα πνμαθήιαηα ιε ηα μπμία ανίζηεηαζ ζήιενα ακηζιέηςπδ δ εθθδκζηή ζπεομπακίδα (Economidis et al. 2000, Λεμκάνδμξ & Μπυιπμνδ 2013). Ζ πενίπηςζδ ηδξ Μαηεδμκζηήξ πέζηνμθαξ πμο δζααζεί ζημ ζφζηδια ημο πμηαιμφ Νέζημο (Π.Δ. Γνάιαξ) απμηεθεί παναηηδνζζηζηυ πανάδεζβια εκυξ εκδδιζημφ είδμοξ πέζηνμθαξ (Salmo sp), ημο μπμίμο δ ζοζηδιαηζηή ηαηάηαλδ δεκ έπεζ λεηαεανζζηεί πθήνςξ (Koutrakis et al. 2013) εκχ μζ θοζζημί πθδεοζιμί ημο έπμοκ δζαηαναπεεί ζδιακηζηά απυ ηδκ εζζαβςβή αηυιςκ πέζηνμθαξ απυ άθθα οδάηζκα μζημζοζηήιαηα ηδξ πχναξ. Δζδζηυηενα, ζηα ιέζα ηαζ ηέθδ ηδξ δεηαεηίαξ ημο 1970, ζπεφδζα άβνζαξ πέζηνμθαξ πνμενπυιεκα απυ ζπεομβεκκδηζηυ ζηαειυ ημο Απεθχμο, απεθεοεενχεδηακ ζηδ θεηάκδ ημο Νέζημο (Apostolidis et al. 1996) ηαζ ζοβηεηνζιέκα ζημοξ παναπμηάιμοξ Ανημοδυνεια ηαζ Γζααμθυνεια (Δζηυκα 1) (Economidis et al. 2000). Δπζπθέμκ, είκαζ πζεακυ κα έπμοκ θάαεζ πχνα ηαζ ιεηαβεκέζηενεξ, ιδ ηαηαβεβναιιέκεξ, εζζαβςβέξ άβνζαξ πέζηνμθαξ πνδζζιμπμζχκηαξ ζπεφδζα πνμενπυιεκα απυ ημκ ίδζμ ζπεομβεκκδηζηυ ζηαειυ ή ηαζ απυ άθθεξ πενζμπέξ ηδξ Δθθάδαξ. Σέημζεξ ιεηαηζκήζεζξ έπμοκ απμδεζπεεί πμθφ επζαθααείξ βζα ημοξ ημπζημφξ αοηυπεμκμοξ πθδεοζιμφξ, ζε ζδιείμ πμο, ζε ηάπμζεξ πενζπηχζεζξ, κα παναηηδνζζεμφκ ςξ βεκεηζηή νφπακζδ (Economidis et al. 2000). ηδκ πνχηδ εηηεκή βεκεηζηή ένεοκα εθθδκζηχκ πθδεοζιχκ άβνζαξ πέζηνμθαξ πμο δζελήπεδ ζε επίπεδμ DNA (Apostolidis et al. 1996), ιεθεηήεδηακ βζα πνχηδ θμνά μζ ιεηαηζκήζεζξ ειπθμοηζζιμί πμο πναβιαημπμζήεδηακ ζημοξ ημπζημφξ πθδεοζιμφξ ημο Νέζημο. φιθςκα ιε ηα απμηεθέζιαηα ηδξ ακάθοζδξ πμο ααζίζηδηε ζηδκ PCR-RFLP ιεεμδμθμβία, ηα 17 απυ ηα 22 άημια πέζηνμθαξ πμο ελεηάζηδηακ απυ ημ Νέζημ είπακ ημκ ίδζμ βεκυηοπμ ιε ηα άημια ημο Απεθχμο, απμηεθμφζακ δδθαδή απμβυκμοξ ηςκ εζζαπεέκηςκ ρανζχκ. ημπυξ ηδξ πανμφζαξ ενβαζίαξ ήηακ δ δζενεφκδζδ ηδξ πανμοζίαξ αηυιςκ πέζηνμθαξ πμο πνμένπμκηαζ απυ ημκ Απεθχμ ζε υθμοξ ημοξ παναπμηάιμοξ ημο ζοζηήιαημξ ημο Νέζημο ηαεχξ ηαζ ηδξ πμνείαξ ηςκ ειπθμοηζζιχκ πμο έθααακ πχνα ηζξ πνμδβμφιεκεξ δεηαεηίεξ, πνδζζιμπμζχκηαξ ημοξ ίδζμοξ ιμνζαημφξ δείηηεξ, χζηε κα ηαηαζηεί εθζηηή δ ζφβηνζζδ ηςκ απμηεθεζιάηςκ. 2. Τιηθά θαη Μέζνδνη οκμθζηά, ζηδκ ενβαζία αοηή ζοιπενζθήθεδηακ 60 δείβιαηα πέζηνμθαξ απυ 7 ζηαειμφξ δεζβιαημθδρίαξ (Δζηυκα 1) ημο Νέζημο. Σα δείβιαηα ζοθθέπεδηακ ηα έηδ ιε ηδ πνήζδ ζοζηεοήξ δθεηηναθζείαξ (Πίκαηαξ 1). Αλίγεζ κα ζδιεζςεεί πςξ υθα ηα νέιαηα ηαζ παναπυηαιμζ απυ υπμο ζοθθέπεδηακ δείβιαηα ανίζημκηαζ εκηυξ ηςκ μνίςκ ηδξ πνμζηαηεουιεκδξ πενζμπήξ ημο Δεκζημφ Πάνημο Ονμζεζνάξ Ρμδυπδξ. Απυ ηάεε ράνζ αθαζνέεδηε έκα ιζηνυ ημιιάηζ ημο εδνζημφ πηενοβίμο, ηέημζμ χζηε κα ελαζθαθίγεηαζ δ επζαίςζδ ημο ιεηά ηδκ απεθεοεένςζή ημο ζημ κενυ. Σμ ημιιάηζ αοηυ πνδζζιμπμζήεδηε βζα απμιυκςζδ μθζημφ DNA ζφιθςκα ιε ημ πνςηυημθθμ ηςκ Hillis et al. (1996). Καηυπζκ πναβιαημπμζήεδηε εκίζποζδ ηιήιαημξ ημο ιζημπμκδνζαημφ DNA (mtdna) πμο πενζεθάιαακε δφμ βμκίδζα ηδξ αθοδνμβμκάζδξ ημο NADH (ND5 ηαζ ND6), ιε ημ γεφβμξ εηηζκδηχκ ND5/6-A ηαζ ND5/6-B. Οζ εηηζκδηέξ αοημί ηαεχξ ηαζ μζ ζοκεήηεξ ηδξ PCR πμο πνδζζιμπμζήεδηακ πενζβνάθμκηαζ απυ ημοξ Nielsen et al. (1998). ημ ηιήια πμο εκζζπφεδηε, ιήημοξ πενίπμο 2500 γεοβχκ αάζεςκ, εθανιυζηδηε πέρδ ιε ηζξ πενζμνζζηζηέξ εκδμκμοηθεάζεξ AluI ηαζ HaeIII, ηαζ ηα πνυηοπα πμο πνμέηορακ παναηδνήεδηακ ζε πδηηέξ αβανυγδξ πενζεηηζηυηδηαξ 2,5%. πςξ πενζβνάθεηαζ απυ ημοξ Apostolidis et al. (1996), ηα δφμ αοηά έκγοια πανμοζζάγμοκ πμθοιμνθζζιυ ηαζ λεπςνίγμοκ ημκ αοηυπεμκμ βεκυηοπμ πέζηνμθαξ ημο Νέζημο απυ αοηυκ ημο Απεθχμο. 10

11 Δηθφλα 1. Οη παξαπφηακνη ηνπ Νέζηνπ ζηνπο νπνίνπο πξαγκαηνπνηήζεθαλ νη δεηγκαηνιεςίεο Πίλαθαο 1. Κσδηθφο (Κ), πεξηνρή δεηγκαηνιεςίαο (S), αξηζκφο αηφκσλ πνπ ζπιιέρζεθαλ απφ θάζε πεξηνρή (Ν) θαη εκεξνκελία δεηγκαηνιεςίαο (t) γηα θάζε δείγκα. K S Ν T ΜΟΤ Ρέια Μμφζδα 9 Ημφθζμξ 2008 ΒΑΘ1.1 Βαεφνεια (Καθθίηανπμ) 5 Μάζμξ 2007 ΒΑΘ1.2 Βαεφνεια (Καθθίηανπμ) 3 επηέιανζμξ 2008 ΒΑΘ1.3 Βαεφνεια (Καθθίηανπμ) 5 Ημφκζμξ 2012 ΒΑΘ2 Βαεφνεια (Γάζμξ Δθαηζάξ) 7 Ημφθζμξ 2013 ΜΤΛ Μφθμο Ρέια 3 Ημφκζμξ 2006 ΓΗΑΒ Γζααμθυνεια 6 Ημφκζμξ 2012 ΑΡΚ Ανημοδυνεια 11 Ημφκζμξ 2012 ΦΑΡ Φαναζζκυ 11 Ημφκζμξ Απνηειέζκαηα Σα πενζμνζζηζηά πνυηοπα πμο πνμέηορακ βζα ηα δφμ έκγοια πμο ελεηάζηδηακ θαίκμκηαζ ζημκ Πίκαηα 2 ηαζ ηδκ Δζηυκα 2. Σα ίδζα αηνζαχξ πνυηοπα, ζηα ίδζα έκγοια, ανέεδηακ απυ ημοξ Apostolidis et al. (1996). θα ηα άημια απυ ημ νέια Μμφζδα, υπςξ επίζδξ ηαζ ηα πενζζζυηενα απυ ημ Ανημοδυνεια ηαζ ημ Βαεφνεια ζημ φρμξ ημο Καθθίηανπμο ειθάκζζακ ημκ ίδζμ απθυηοπμ (ζφκεεημ βεκυηοπμ ΒΒ) ιε ηα άημια ημο Απεθχμο, εκχ υθα ηα δείβιαηα απυ ημ Φαναζζκυ, ημ Γζααμθυνεια ηαζ ημ νέια Μφθμο ειθάκζζακ ημκ απθυηοπμ ΑΑ (Πίκαηαξ 3). 11

12 Πίλαθαο 2. Πξφηππα πνπ πξνέθπςαλ (ζε δεχγε βάζεσλ) απφ ηηο πέςεηο κε ηα δχν έλδπκα. Πξντφληα πέςεο κηθξφηεξα ησλ 100 δεπγψλ βάζεσλ δελ παξνπζηάδνληαη AluI HaeIII A B A B Δηθφλα 2. Ζιεθηξνθφξεζε ζε πεθηή αγαξφδεο φπνπ δηαθξίλνληαη ηα δχν πξφηππα πνπ πξνέθπςαλ απφ πέςε κε ην έλδπκν HaeIII Πίλαθαο 3. Απιφηππνη (ζχλζεηνη γελφηππνη) θαη απινηππηθέο ζπρλφηεηεο ησλ ππφ εμέηαζε δεηγκάησλ. Απθυηοπμξ φκεεημξ βεκυηοπμξ Γείβια ΜΟΤ ΒΑΘ1.1 ΒΑΘ1.2 ΒΑΘ1.3 ΒΑΘ 2 ΜΤ Λ ΓΗΑΒ ΑΡΚ ΦΑΡ Type 1 AA 1/5 7/7 3/3 6/6 3/11 11/11 Type 2 BB 9/9 5/5 3/3 4/5 8/11 4. πδήηεζε Οζ πθδεοζιμί άβνζαξ πέζηνμθαξ ηδξ κυηζαξ Βαθηακζηήξ πενζμκήζμο πανμοζζάγμοκ ζδζαίηενα εηηεηαιέκδ βεκεηζηή πμζηζθυηδηα (Apostolidis et al. 1996, Apostolidis et al. 1997). Με αάζδ πνμδβμφιεκεξ ιεθέηεξ ημο mtdna, μζ πθδεοζιμί ημο Απεθχμο ακήημοκ, ςξ επί ημ πθείζημκ, ζηδ θοθμβεκεηζηή μιάδα marmoratus (Ma), εκχ μζ αοηυπεμκεξ πέζηνμθεξ ημο Νέζημο ζε αοηήκ ηδξ Αδνζαηζηήξ (Ad). Δκημφημζξ, ζημ Νέζημ ηαζ ζοβηεηνζιέκα ζημ Ανημοδυνεια έπμοκ ανεεεί άημια marmoratus ηα μπμία ελδβμφκηαζ απυ ημοξ ειπθμοηζζιμφξ ιε ζπεφδζα απυ ημκ Απεθχμ (Apostolidis et al. 1996, Apostolidis et al. 1997). ηδκ πανμφζα ενβαζία, εηηυξ απυ ηδκ πθεζμκυηδηα ηςκ δεζβιάηςκ απυ ημ Ανημοδυνεια, υθα ηα άημια απυ ημ νέια Μμφζδα ηαζ ηα πενζζζυηενα απυ ημ Βαεφνεια ζε παιδθυ ορυιεηνμ (ημκηά ζημ πςνζυ Καθθίηανπμ, Δζηυκα 1), είπακ ημκ απθυηοπμ 2 (Πίκαηαξ 3) δδθαδή απμηεθμφκ απμβυκμοξ ηςκ ζπεοδίςκ πμο πνμήθεακ απυ ημκ Απεθχμ. Καηά ζοκέπεζα μζ ειπθμοηζζιμί ζηζξ πενζμπέξ αοηέξ επδνέαζακ ζδιακηζηά ημοξ εκδδιζημφξ πθδεοζιμφξ ιε πζεακυ εκδεπυιεκμ ηδκ μθμηθδνςηζηή ελαθάκζζή ημοξ. Ακηίεεηα, μζ ημπζημί πθδεοζιμί άβνζαξ πέζηνμθαξ απυ ημοξ παναπμηάιμοξ Γζααμθυνεια, Φαναζζκυ ηαζ Βαεφνεια (πθδζίμκ ημο Γάζμοξ Δθαηζάξ), πμο ανίζημκηαζ ζε ορδθυ ορυιεηνμ, θαίκεηαζ υηζ δεκ επδνεάζηδηακ απυ ειπθμοηζζιμφξ ηαεχξ δεκ ανέεδηε ζε αοημφξ ηακέκα άημιμ πμο κα θένεζ ημ βεκυηοπμ ημο Απεθχμο. ε υηζ αθμνά ημ Μφθμο Ρέια, δ πανμοζία βέθοναξ ζημ ζδιείμ ηςκ δεζβιαημθδρζχκ, ιάθθμκ ειπυδζγε ηδκ πνμξ ηα ακάκηδ ιεηακάζηεοζδ ηδξ πέζηνμθαξ, ζοκηεθχκηαξ ζηδκ ακαπαναβςβζηή ηδξ απμιυκςζδ, δζαηδνχκηαξ έηζζ ημκ αοηυπεμκμ πθδεοζιυ, ημοθάπζζημκ ιέπνζ ηδ πνμκζηή ζηζβιή ηδξ δεζβιαημθδρίαξ (Ημφκζμξ 2006, Πίκαηαξ 1). Έηημηε εκημφημζξ, δεκ έπεζ ανεεεί ηακέκα άημιμ άβνζαξ πέζηνμθαξ ζηζξ επυιεκεξ δεζβιαημθδρίεξ πμο πναβιαημπμζήεδηακ, ηαεζζηχκηαξ έκημκδ ηδκ πζεακυηδηα ελαθάκζζδξ ημο πθδεοζιμφ άβνζαξ πέζηνμθαξ απυ ημ νέια αοηυ. Δπμιέκςξ, ζδζαίηενδ πνμζμπή πνέπεζ κα δμεεί απυ ηζξ δζαπεζνζζηζηέξ ανπέξ έηζζ χζηε κα απμηναπεί μπμζαδήπμηε ιεηαηίκδζδ ζπεομπθδεοζιμφ πνμξ ηα νέιαηα αοηά ζημ ιέθθμκ. 12

13 οιπεναζιαηζηά, ανηεημί ημπζημί πθδεοζιμί άβνζαξ πέζηνμθαξ ημο ζοζηήιαημξ ημο πμηαιμφ Νέζημο θαίκεηαζ πςξ έπμοκ δζαηαναπεεί ζδιακηζηά, εκχ ζε μνζζιέκα ζδιεία ηείκμοκ πνμξ ελαθάκζζδ ή ακηζηαηάζηαζδ απυ άθθμοξ πμο πνμήθεακ απυ ειπθμοηζζιμφξ. Καηαδεζηκφεηαζ επμιέκςξ δ ακάβηδ εθανιμβήξ ηαηάθθδθςκ δζαπεζνζζηζηχκ ιέηνςκ ηέημζςκ χζηε κα απμηναπμφκ ιεθθμκηζηέξ ιεηαηζκήζεζξ, εζδζηυηενα ζε πενζμπέξ υπςξ ημ Φαναζζκυ, ημ Γζααμθυνεια, αθθά ηαζ ζηα μνεζκά ηιήιαηα ημο Βαεονέιαημξ, υπμο δζαηδνμφκηαζ ημπζημί - ιμκαδζημί πθδεοζιμί άβνζαξ πέζηνμθαξ. Βηβιηνγξαθία Κμοηνάηδξ Μ. (2013). Δπζπηχζεζξ ηςκ θναβιάηςκ ζηδκ ζπεομπακίδα ηςκ πμηαιχκ. Πναηηζηά 15μο Πακεθθδκίμο οκεδνίμο Ηπεομθυβςκ, Θεζζαθμκίηδ, (2013), ζεθ Λεμκάνδμξ Η., Μπυιπμνδ Γ. (2013). Ζ ζπεομπακίδα ηςκ εζςηενζηχκ οδάηςκ ηδξ Δθθάδαξ. Πναηηζηά 15μο Πακεθθδκίμο οκεδνίμο Ηπεομθυβςκ, Θεζζαθμκίηδ, (2013), ζεθ Apostolidis A.P., Karakousis Y., Triantaphyllidis C. (1996). Genetic differentiation and phylogenetic relationships among Greek Salmo trutta L. (brown trout) populations as revealed by RFLP analysis of PCR amplified mitochondrial DNA segments. Heredity 77, Apostolidis A.P., Trantaphyllidis C., Kouvatsi A., Economidis P.S. (1997). Mitochondrial DNA sequence variation and phylogeography among Salmo trutta L. (Greek brown trout) populations. Molecular Ecology 6, Economidis P.S., Dimitriou E., Pagoni R., Michaloudi E., Natsis L. (2000). Introduced and tranlocated fish species in the inland waters of Greece. Fisheries management and Ecology 7, Hillis D.M., Moritz C., Mable B.K. (1996). Molecular Systematics, 2nd edn. Sinauer Associates, Sunderland, MA Koutrakis E.T., Sapounidis A., Apostolou A., Vassilev M., Pehlivanov L., Leontarakis P., Tsekov A., Sylaios G., Economidis P.S. (2013). An integrated ichthyofaunal survey in a heavily-modified, cross-borded watershed. Journal of Biological Research-Thessaloniki 20, Nielsen E.E. Hansen M.M., Mensberg K.LD. (1998). Improved primer sequences for the mitochondrial ND1, ND3/4 and ND5/6 segments in salmonid fishes: Application to RFLP analysis of Atlantic salmon. Journal of Fish Biology 53,

14 ASSESSMENT OF WATER QUALITY MONITORING BASED ON TWO YEARS DATA (2008 & 2011) IN LAKE KASTORIA, WESTERN MACEDONIA, GREECE Matzafleri N. 1, Psilovikos Ar. 2 1 Departement of Fisheries Region of Magnisia & N.Sporades Iolkou & Analipseos Volos, Greece 2 University of Thessaly, School of Agricultural Sciences, Department of Ichthyology and Aquatic Environment, Fytoko st., 38466, N. Ionia Magnisias, Greece. ABSTRACT Lake Kastoria is a very important aquatic ecosystem, situated in the Region of Western Macedonia, Greece. A two years monthly monitoring program (2008 and 2011) in 5 Sampling Stations in the Lake area is demonstrated in this study as a part of a twelve years monitoring programme, that is operated in order to collect water quality and quantity data. The study is focused on the water quality parameters of Water Temperature (Tw), Dissolved Oxygen (DO), ph, Water Transparency (Wt), Total Nitrogen (TΝ), Total Phosphorus (TP), Chl-a and BOD 5. The time fluctuation, the impacts and the assessments of this monitoring data are presented here. Keywords: Lake Kastoria, eutrophication, monitoring data, water-quality. Corresponding author:: Psilovikos Ar ( psiloviko@uth.gr) ΑΠΟΣΗΜΖΖ ΣΖ ΠΟΗΟΣΖΣΑ ΣΟΤ ΝΔΡΟΤ ΜΔ ΒΑΖ ΣΑ ΓΔΓΟΜΔΝΑ ΓΤΟ ΔΣΧΝ (2008 ΚΑΗ 2011) ΣΖΝ ΛΗΜΝΖ ΚΑΣΟΡΗΑ ΓΤΣΗΚΖ ΜΑΚΔΓΟΝΗΑ Μαηδαθιέξε Ν. 1 Φηινβίθνο Ά. 2 1 Σιήια Αθζείαξ Πενζθενεζαηήξ Δκυηδηαξ Μαβκδζίαξ ηαζ Βμνείςκ πμνάδςκ Ηςθημφ & Ακαθήρεςξ, 38001,Βυθμξ,Δθθάδα 2 Πακεπζζηήιζμ Θεζζαθίαξ, πμθή Γεςπμκζηχκ Δπζζηδιχκ, Σιήια Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ Οδυξ Φοηυημο, Ν.Ηςκία Μαβκδζίαξ, 38466, Δθθάδα Πεξίιεςε Η λίμνθ τθσ Καςτοριάσ είναι ζνα ςθμαντικό υδάτινο λιμναίο οικοςφςτθμα που βρίςκεται ςτθν Δυτικι Μακεδονία. Στθν παροφςα εργαςία παρουςιάηονται τα δεδομζνα προγράμματοσ παρακολοφκθςθσ αβιοτικϊν και βιοτικϊν παραμζτρων δυο ετϊν (2008 και 2011) ςε 5 ςτακμοφσ δειγματολθψίασ, τα οποία αποτελοφν μζροσ των δεδομζνων δωδεκαετοφσ παρακολοφκθςθσ. Η μελζτθ επικεντρϊκθκε ςε ποιοτικζσ παραμζτρουσ του νεροφ ειδικότερα ςτθν κερμοκραςία νεροφ (Tw), ςτο διαλυμζνο οξυγόνο (DO), το ph, τθν διαφάνεια νεροφ (Wt), το ολικό άηωτο (TΝ), τον ολικό φϊςφορο (TP) τθν χλωροφφλλθ-α (Chl-a) και το BOD 5. Η μζτρθςθ των παραπάνω αβιοτικϊν και βιοτικϊν παραμζτρων και θ χρονικι διακφμανςθ τουσ εκτιμοφνται και παρουςιάηονται. Λζξεισ Κλειδιά: Λίμνη Καςτοριάσ, ευτροφιςμόσ, δεδομζνα παρακολοφθηςησ. Συγγραφζασ επικοινωνίασ: Ψιλοβίκοσ Άρθσ ( psiloviko@uth.gr) 1.Δηζαγσγή Ζ μζημθμβζηή ηαηάζηαζδ είκαζ έκα ζφκεεημ απμηέθεζια θοζζηχκ ηαζ ακενςπμβεκχκ δζενβαζζχκ αθθά ηαζ ηςκ αθθδθεπζδνάζεςκ ημοξ ζημ πχνμ ηαζ ζημκ πνυκμ. Ο ζημπυξ ηδξ παναημθμφεδζδξ πμζμηζηχκ ηαζ πμζμηζηχκ παναιέηνςκ ζηα οδάηζκα μζημζοζηήιαηα (πδβέξ, πμηάιζα, εηαμθέξ, εζςηενζηά κενά, εάθαζζεξ, ςηεακμφξ) είκαζ δ πνμζέββζζδ ηαζ δ εηηίιδζδ ηδξ μζημθμβζηήξ ηαηάζηαζδξ ηαζ ηςκ ηάζεςκ πμο παναηδνμφκηαζ. Έκα ηαθμζπεδζαζιέκμ πνυβναιια παναημθμφεδζδξ ιπμνεί κα απμηεθέζεζ ηδκ αάζδ ηαζ ημκ ηαεμνζζιυ ηδξ επζηοπίαξ ή ηδξ απμηοπίαξ δνάζεςκ απμηαηάζηαζδξ ηαζ ιπμνεί κα ηαεμνίζεζ ηδκ ακαπνμζανιμβή αοηχκ (Bruns & Wiersma 2004). Ζ θίικδ Καζημνζάξ είκαζ ιζα νδπή ιεζμβεζαηή θίικδ δ μπμία ανίζηεηαζ ζηδκ πενζθένεζα ηδξ Γοηζηήξ Μαηεδμκίαξ. Ζ θίικδ Καζημνζάξ (40 30 N, E), είκαζ πμθοιζηηζηή ιε επζθάκεζα 27,9 km², ιέβζζημ αάεμξ 9 m,ηαζ ιέζμ αάεμξ 4 m,ηαζ πνυκμ παναιμκήξ > 2 yr. Δίκαζ ιζα αζηζηή θίικδ ζηδκ μπμία πανμπεηεφμκηακ ηα αζηζηά απυαθδηα έςξ ηδκ ίδνοζδ ηαζ θεζημονβία ημο αζμθμβζημφ 14

15 ηαεανζζιμφ ημ 1991 (Moustaka Gouni et al 2006). Ακηίεεηα απυ άθθεξ θοζζηέξ θίικεξ, δ θίικδ ηδξ Καζημνζάξ έπεζ οδναοθζηυ ζφζηδια νφειζζδξ ηδξ ζηάειδξ ημο κενμφ ιε ηδκ πνήζδ ηαζ θεζημονβία εονμθναβιάηςκ, ζδζαίηενα υηακ μ υβημξ ημο κενμφ αολάκεζ ελαζηίαξ ηςκ πεζιενζκχκ εζζνμχκ. Ζ ιδκζαία δζαηφιακζδ ηδξ ζηάειδξ ημο κενμφ ελανηάηαζ απυ ηζξ επμπζηέξ ιεηααμθέξ ηδξ εενιμηναζίαξ ηαζ ηςκ ανμπμπηχζεςκ. Ζ θίικδ ηδξ Καζημνζάξ έπεζ ιεβάθδ μζημθμβζηή αλία ηαεχξ ζηδνίγεζ ηδκ ημπζηή πνςημβεκή παναβςβή αθθά ηαζ ηδκ ημονζζηζηή δναζηδνζυηδηα. Καηά ηδκ δζάνηεζα ηςκ ηεθεοηαίςκ δεηαεηζχκ δεπυηακ έκημκεξ ακενςπμβεκείξ πζέζεζξ υπςξ άνδεοζδ, πανμπέηεοζδ ηςκ αηαηένβαζηςκ αζηζηχκ απμαθήηςκ, εκαπυεεζδ ζγήιαημξ ηα μπμία πνμηάθεζακ ζμαανά πνμαθήιαηα ηαζ ηδκ μζημθμβζηή οπμαάειζζδ ηδξ. Ζ θεηάκδ απμννμήξ ηδξ είκαζ ηονίςξ αβνμηζηή ηαζ εηπθφζεζξ ηςκ αβνμηζηχκ πενζμπχκ απμηεθμφκ ηφνζα πδβή ενεπηζηχκ ζοζηαηζηχκ ιε απμηέθεζια ηα θαζκυιεκα εοηνμθζζιμφ. Ζ αζηζηή νφπακζδ πνμένπεηαζ απυ ηδκ πυθδ ηδξ Καζημνζάξ (πθδεοζιμφ ) δ μπμία εηηείκεηαζ ηαηά ιήημξ ηδξ αηημβναιιήξ ηδξ θίικδξ. Σα εοηνμθζηά επεζζυδζα είκαζ ζοπκά ζηδκ θίικδ, ζοκμδεφμκηαζ ιε ηδκ εθάηηςζδ ημο δζαθοιέκμο μλοβυκμο ηαζ ηδκ ιεβάθδ αφλδζδ ηςκ θοηχκ. Ζ άκεζζδ ηςκ ηοακμθοηχκ ηαζ μζ ημλίκεξ ημοξ ηαοημπμζήεδηακ ζηδκ θίικδ βζα πνχηδ θμνά ημ 1987 (Lanaras et al.1989). Ζ απμηαηάζηαζδ νδπχκ εοηνμθζηχκ θζικχκ πανμοζζάγεζ ιεβαθφηενδ δοζημθία ζοβηνζηζηά ιε ηζξ ααεζέξ θίικεξ ελαζηίαξ ηδξ ζζπονήξ αθθδθεπίδναζδ πμο παναηδνείηαζ ιεηαλφ ημο ζγήιαημξ ημο ποειέκα ηαζ ηδξ οδάηζκδξ ζηήθδξ (Bengtsson. 1975, Threlked 1994). ηζξ νδπέξ θίικεξ δ εζςηενζηή ακαηνμθμδυηδζδ ενεπηζηχκ ζοζηαηζηχκ απυ ημ ίγδια ζηδκ οδάηζκδ ζηήθδ ζοιααίκεζ αηυιδ ηαζ υηακ ζηδκ οδάηζκδ ζηήθδ οπάνπεζ μλοβυκμ (Kleebery & Kozerski 1997). Πνζκ ηδκ εηπυκδζδ ζηναηδβζημφ ζπεδίμο απμηαηάζηαζδξ ιζα θίικδξ είκαζ ακαβηαία δ ζοβηέκηνςζδ δεδμιέκςκ βζα ηδκ εηηίιδζδ ηδξ οδνμθμβζηήξ ηαζ μζημθμβζηήξ ηαηάζηαζήξ ηδξ (Heyman et al. 1984). H μζημθμβζηή ηαηάζηαζδ επδνεάγεηαζ ηυζμ απυ ημοξ ααζμηζημφξ, υζμ ηαζ απυ ημοξ αζμηζημφξ παναιέηνμοξ (Hutulla & Noges 1998, Huszar & Caracao 1998). Ζ δζαεεζζιυηδηα ηςκ ενεπηζηχκ,ζδζαίηενα ημο θςζθυνμο (Schindler 1997) ηαεμνίγεζ ηδκ δοκαιζηή ηδξ θοημπθαβηημκζηήξ αζμιάγαξ (Carpenter 1991). ηδκ πανμφζα ιεθέηδ ιεηνήεδηακ ααζμηζημί ηαζ αζμηζημί πανάβμκηεξ βζα δομ έηδ ιε ζημπυ ηδκ δδιζμονβία ιζαξ αάζδξ δεδμιέκςκ βζα ηδκ θίικδ Καζημνζάξ. Σα αηυθμοεα δεδμιέκα απμηεθμφκ έκα ιυκμ ιένμξ απυ ηδκ δςδεηαεηή αάζδ δεδμιέκςκ πμο έπεζ ζοιπθδνςεεί ηαζ ανίζηεηαζ ζε ζηάδζμ επελενβαζίαξ, ιε ζημπυ ηδκ ηαηακυδζδ ηδξ δμιήξ ηαζ θεζημονβίαξ ημο μζημζοζηήιαημξ ηδξ θίικδξ Καζημνζάξ, ηδκ αλζμθυβδζδ ηδξ μζημθμβζηήξ ηδξ ηαηάζηαζδξ ηαζ ηςκ ιεηααμθχκ ηδξ ζημ πχνμ ηαζ ζημ πνυκμ, αθθά ηαζ ηδκ εηπυκδζδ δζαπεζνζζηζημφ ζπεδίμο ιε ζηυπμ ηδκ ελοβίακζδ ηαζ απμηαηάζηαζήξ ημο θζικαίμο μζημζοζηήιαημξ ηδξ. 2.Τιηθά θαη Μέζνδνη Ζ δεζβιαημθδρία πναβιαημπμζήεδηε ζε πέκηε ζηαειμφξ ζηα ααεφηενα ηιήιαηα ηδξ θίικδξ (αάεμξ 4m). Ζ Tw ηαζ ημ DO ιεηνήεδηακ ζημ πεδίμ ιε ηδκ πνήζδ θμνδημφ μνβάκμο Oxy330 VTV, δ Wt ιεηνήεδηε ιε ηδκ πνήζδ δίζημο ημο Secchi. Σμ ph ιεηνήεδηε ιε Orion ph-meter. Οζ δεζβιαημθδρίεξ πναβιαημπμζήεδηακ απυ ημκ Ηακμοάνζμ 2008 έςξ ημκ Γεηέιανζμ ημο 2008 ηαζ απυ ημκ Ηακμοάνζμ ημο 2011 έςξ ημκ Γεηέιανζμ ημο 2011 ιδκζαία. Σα δείβιαηα κενμφ θαιαάκμκηακ ζε αάεμξ 30 cm απυ ηδκ επζθάκεζα. Ο πμζμηζηυξ πνμζδζμνζζιυξ ημο ΣΝ ηαζ ημο TP, πναβιαημπμζήεδηε ιε θαζιαημθςηυιεηνμ ηφπμο Merck, ζφιθςκα ιε ηζξ πζζημπμζδιέκεξ ηαζ εβηεηνζιέκεξ APHA ιεευδμοξ (APHA 2000). Γζα ημκ πνμζδζμνζζιυ ηδξ Cl-a, ηα δείβιαηα θζθηνάνμκηακ ιε θίθηνα ηφπμο Whatman GF/A αιέζςξ ιεηά ηδκ ζοθθμβή. Ζ ελαβςβή πνχιαημξ βζκυηακ ιε ηδκ πνήζδ 90% αηεηυκδξ ηαζ μζ ζοβηεκηνχζεζξ πνμζδζμνζγυηακ θαζιαημθςημιεηνζηά. To BOD 5 ιεηνήεδηε ζφιθςκα ιε ηζξ ιεευδμοξ APHA Οζ ιέζεξ ιδκζαίεξ ηζιέξ πνδζζιμπμζήεδηακ βζα ηδκ επμπζηή δζαηφιακζδ ηςκ οπυ ελέηαζδ παναιέηνςκ. 3. Απνηειέζκαηα ηδκ δζεηή πενίμδμ παναημθμφεδζδξ πανυιμζεξ επμπζηέξ δζαηοιάκζεζξ παναηδνήεδηακ βζα ηδκ Tw, δ μπμία ηοιάκεδηε ιεηαλφ 3.04 o C ζηζξ ηνφεξ πενζυδμοξ έςξ o C ζηζξ εενιέξ πενζυδμοξ (πήια 1). Σμ DO ηοιάκεδηε ιεηαλφ 2.92 mg/l ημκ Ημφκζμ ημο 2008 ηαζ mg/l ημκ Ημφθζμ Οζ εθάπζζηεξ ηζιέξ παναηδνμφκηαζ ηονίςξ ιεηαλφ ηςκ εενιχκ πενζυδςκ υπμο μζ δζαδζηαζίαξ απμζημδυιδζδξ ηαζ μζ απαζηήζεζξ ημο ζγήιαημξ ζε μλοβυκμ πνμηαθμφκ ηδκ παιδθή πενζεηηζηυηδηα δζαθοιέκμο μλοβυκμο ζηδκ οδάηζκδ ζηήθδ ηαηά ηδκ δζάνηεζα ημο ηαθμηαζνζμφ. (πήια 2) ηαζ μζ ιέβζζηεξ ηζιέξ ειθακίγμκηαζ ηονίςξ ημοξ πεζιενζκμφξ ιήκεξ. Ζ Wt ήηακ βεκζηά παιδθή. Κοιάκεδηε ιεηαλφ 0.45 m ημκ Αφβμοζημ ημο 2008 ηαζ 4.05 m ημ Γεηέιανζμ ημο 2011 (πήια 3). Οζ ορδθυηενεξ ηζιέξ πζεακά ζοκδέεηαζ ιε ηδκ παιδθή πενζεηηζηυηδηα θοημπθαβηημκζηήξ αζμιάγαξ. Πανάβμκηεξ πμο πνμηαθμφκ εμθενυηδηα ζηδκ θίικδ Καζημνζάξ, είκαζ δ αζμιάγα ηςκ θοηχκ ηαζ δ ακαηάναλδ ημο ζγήιαημξ ημο ποειέκα έπεζηα απυ ζζπονμφξ ακέιμοξ ηαζ έκημκεξ ανμπμπηχζεζξ. Ζ επμπζηή δζαηφιακζδ ηδξ Wt αημθμοεεί ημ ίδζμ ιμηίαμ. Καηά ηδκ δζάνηεζα ημο ηαθμηαζνζμφ 15

16 ηαζ ηςκ ανπχκ θεζκμπχνμο, παναηδνμφκηαζ μζ ιζηνυηενεξ ηζιέξ, εκχ μζ ορδθυηενεξ ηζιέξ παναηδνμφκηαζ ημκ πεζιχκα ηαζ ηδκ άκμζλδ. Ζ ιζηνυηενδ ηζιή ημο ph ήηακ 7.6 ημκ Ηακμοάνζμ ημο 2008 ηαζ δ ορδθυηενδ ηζιή ημ επηέιανζμ ημο 2011 (πήια 4). Οζ ηζιέξ ημο ph επδνεάγμκηαζ απυ ηδκ θςημζοκεεηζηή δναζηδνζυηδηα ηαζ ημκ ιζηνμαζμθμβζηυ ιεηααμθζζιυ ηαζ αολάκμοκ ιε ηζξ δζενβαζία ηδξ απμκζηνμπμίδζδξ. ρήκα 1. Δπνρηθή δηαθχκαλζε Tw ρήκα 2. Δπνρηθή δηαθχκαλζε DO ρήκα 3.Δπνρηθή δηαθχκαλζε Wt ρήκα 4. Δπνρηθή δηαθχκαλζε ph Οζ ζοβηεκηνχζεζξ ημο TN παναηδνμφκηαζ ζδζαίηενα ορδθέξ ζηζξ οβνέξ πενζυδμοξ (Απνίθζμξ ηαζ Μάζμξ) ηαζ πνμξ ημ ηέθμξ ημο ηαθμηαζνζμφ (Αφβμοζημξ ηαζ επηέιανζμξ) (πήια 5). Αοηυ ιπμνεί κα μθείθεηαζ απυ ηζξ εζζαβςβέξ αγχημο ιε ηζξ εηπθφζεζξ ηςκ βεςνβζηχκ εδαθχκ είηε θυβς ανμπμπηχζεςκ είηε θυβς άνδεοζδξ. Καηά ηδκ δζάνηεζα ημο ηαθμηαζνζμφ, μζ παιδθυηενεξ ηζιέξ ηοιάκεδηακ απυ 36.8 ιg/l ημκ Ημφθζμ ημο 2011 έςξ 19.1 ιg/l ημκ Αφβμοζημ ημο ρήκα 5. Δπνρηθή δηαθχκαλζε TN ρήκα 6. Δπνρηθή δηαθχκαλζε TP Οζ ζοβηεκηνχζεζξ ημο TP είπακ επμπζηή δζαηφιακζδ απυ 2 ιg/l ημκ Ηακμοάνζμ ημο 2008 έςξ 200 ιg/l ημκ Ημφθζμ ημο 2008 ζημ επζθακεζαηυ κενυ, ιε ηζξ ιέβζζηεξ ηζιέξ κα ειθακίγμκηαζ ηονίςξ ημοξ ιήκεξ Ημφθζμ, Αφβμοζημ ηαζ επηειανίμο (πήια 6), πζεακά απυ ηδκ επίδναζδ ηδξ θοημπθαβηημκζηήξ δοκαιζηήξ ηαζ ηδκ εζςηενζηή επακαηνμθμδυηδζδ. Καηά ηδκ εενιή πενίμδμ μζ ηζιέξ ημο δζαθοιέκμο μλοβυκμο DO ηαζ ημο ph, εκεαννφκμοκ ηζξ δζενβαζίεξ απεθεοεένςζδξ θςζθυνμο απυ ημ ίγδια ειπθμοηίγμκηαξ ηδκ οδάηζκδ ζηήθδ (Bengtsson 1975). Οζ ζοβηεκηνχζεζξ ηςκ ενεπηζηχκ ζοζηαηζηχκ ειθακίγμκηαζ κα επδνεάγμκηαζ απυ ηδκ αζμιάγα ηςκ θοηχκ, ηδ δζάνηεζα ηδξ εενιήξ ηαζ οβνήξ πενζυδμο, ημ DO ηαζ ηζξ ηζιέξ ημο ph. Τρδθέξ ηζιέξ ημο ph ζοκδέμκηαζ ιε ορδθέξ ζοβηεκηνχζεζξ TN, ηαεχξ δ αζμθμβζηή δναζηδνζυηδηα αολάκεζ ημ ph. πςξ ηαζ μζ ορδθέξ ηζιέξ ημο TP ζοκδέμκηαζ ιε ηδκ παιδθή πενζεηηζηυηδηα DO ζηδκ οδάηζκδ ζηήθδ ηαζ εκζζπφεζ ηδκ απεθεοεένςζδ ημο θςζθυνμο απυ ημ ίγδια. H επμπζηή δζαηφιακζδ ημο BOD 5 ειθακίγεζ ηδκ ίδζα επακαθδρζιυηδηα ιε παιδθέξ ηζιέξ ηαηά ηδκ δζάνηεζα ημο πεζιχκα, ελαζηίαξ ηδξ ιζηνήξ θοημπθαβηημκζηήξ αζμιάγαξ, εκχ αολάκεζ ημ ηαθμηαίνζ, υπμο δ απαίηδζδ ζε μλοβυκμ απυ ημοξ ιζηνμνβακζζιμφξ βζα κα μθμηθδνχζμοκ ηδκ αενυαζα δζάζπαζδ αολάκεζ (πήια 7). Οζ ηζιέξ ηδξ Chl-a, ζδιείςζακ 16

17 επμπζηή δζαηφιακζδ ιε ιέβζζηεξ ηζιέξ ηαηά ηδκ δζάνηεζα ημο ηαθμηαζνζμφ ελαζηίαξ ηδξ ακάπηολδξ ημο θοημπθαβηημφ (πήια 8). Δπίζδξ μζ ορδθέξ ηζιέξ πθςνμθφθθδξ ειθακίζηδηακ ημ επηέιανζμ. Πανυιμζεξ ηζιέξ παναηδνήεδηακ ηαζ ζημ πανεθευκ (Moustaka et al. 2006, Stefanidis, & Papastergiadou 2010). φιθςκα ιε ημοξ πίκαηεξ ηαηάηαλδξ μζημθμβζηήξ πμζυηδηαξ θζικχκ (Vollenweider 1968, OECD 1982, Vollenweider & Kerekes 1982, Straskraba & Tundisi 1999, Wetzel 2001) δ θίικδ Καζημνζάξ ηαλζκμιείηαζ ςξ εοηνμθζηή ιε ζδιάδζα οπενεοηνμθζζιμφ ηαηά ηδκ δζάνηεζα ημο ηαθμηαζνζμφ ημο 2011 υπμο δ Chl-a πανμοζζάγεζ ιέβζζηδ ηζιή ημκ Αφβμοζημ ημο Απυ ηδκ ενβαζία ηςκ Kagalou & Psilovikos (2014) πνμηφπηεζ υηζ δ θίικδ ηδξ Καζημνζάξ ηαζ βζα ημ έημξ 2008 πανμοζζάγεηαζ απυ εοηνμθζηή ιέπνζ οπενεοηνμθζηή, πνδζζιμπμζχκηαξ υπζ ιυκμ ημοξ πίκαηεξ ηαηάηαλδξ ηδξ μζημθμβζηήξ ηαηάζηαζδξ ηςκ θζικχκ αθθά ηαζ ημοξ δείηηεξ ηαηά Carlson (1977). οβηνίκμκηαξ ηα απμηεθέζιαηα ηαζ ζημοξ πέκηε ζηαειμφξ πνμηφπηεζ υηζ μζ ζηαειμί πμο ανίζημκηαζ ημκηά ζηζξ βεςνβζηέξ εηηάζεζξ ειθακίγμοκ αολδιέκεξ ηζιέξ ενεπηζηχκ ( TN, TP) ηαηά ηδκ άκμζλδ ηαζ ημ θεζκυπςνμ, πζεακά ελαζηίαξ ηςκ εηπθφζεςκ ηςκ βεςνβζηχκ εδαθχκ. Δπζπνυζεεηα μ ζηαειυξ μ μπμίμξ ανίζηεηαζ ζηδκ Β.Παναθία πανμοζζάγεζ ηζξ πνχηεξ εκδείλεζξ ηςκ επεζζμδίςκ ημο εοηνμθζζιμφ. ρήκα 7. Δπνρηθή δηαθχκαλζε BOD 5 ρήκα 8. Δπνρηθή δηαθχκαλζε Chl-a 4.πδήηεζε ηδκ πανμφζα ενβαζία πανμοζζάζηδηε δ επμπζηή δζαηφιακζδ ααζζηχκ αζμηζηχκ ηαζ ααζμηζηχκ παναιέηνςκ ηδξ θίικδξ Καζημνζάξ Σα ενεπηζηά ζοζηαηζηά ειθάκζζακ επμπζηή δζαηφιακζδ υπςξ ζ υθεξ ηζξ νδπέξ εοηνμθζηέξ θίικεξ (Kagalou et al. 2008). Έηζζ ηαηά ηδκ δζάνηεζα ηδξ άκμζλδξ αολάκμκηαζ ηα ενεπηζηά ζημζπεία ελαζηίαξ ηςκ εζζνμχκ απυ αζηζηή ηαζ βεςνβζηή νφπακζδ ιε απμηέθεζια ηδκ ακάπηολδ ημο θοημπθαβηημφ. Ζ ζοβηέκηνςζδ πνμκμζεζνχκ δεδμιέκςκ, απμηεθεί ενβαθείμ εηηίιδζδξ ηδξ μζημθμβζηήξ ηαηάζηαζδξ ημο θζικαίμο μζημζοζηήιαημξ αθεκυξ ηαζ αθεηένμο δζαπεζνζζηζηυ ενβαθείμ επζαμθήξ ιέηνςκ ελοβίακζδξ. ηδ ζοκέπεζα βζα κα ελεηαζηεί δ επάνηεζα ηαζ δ επζηοπία ηςκ θδθεέκηςκ ιέηνςκ, είκαζ ζηυπζιδ δ παναημθμφεδζδ υθςκ ηςκ αζμηζηχκ ηαζ ααζμηζηχκ παναιέηνςκ, μζ μπμίμζ ανίζημκηαζ ζε άιεζδ αθθδθεπίδναζδ ιε ηζξ αζμθμβζηέξ δζενβαζίεξ ημο ζοζηήιαημξ. Ο ηεθζηυξ ζηυπμξ είκαζ δ εθανιμβή απμηεθεζιαηζηχκ ιέηνςκ ηαζ δ ηεθζηή αεθηίςζδ ηδξ μζημθμβζηήξ ηαηάζηαζδξ ηδξ θίικδξ, ζηυπμξ πμο επζαάθθεηαζ ηαζ απυ ηδκ εθανιμβή ηδξ Δονςπασηήξ Οδδβίαξ 60/2000 βζα ηα οδάηζκα ζχιαηα (water bodies) ηδξ Δονχπδξ. Έηζζ είκαζ επζαεαθδιέκδ δ ζοκεπήξ παναημθμφεδζδ ηςκ αζμηζηχκ ηαζ ααζμηζηχκ παναιέηνςκ, δ μπμία ζε αάεμξ πνυκμο εα είκαζ ζε εέζδ κα πνμαθέπεζ ηδκ ακηαπυηνζζδ ημο μζημζοζηήιαημξ ζφιθςκα ιε ηζξ ζοκεήηεξ πμο επζηναημφκ π.π παναηεηαιέκδ λδναζία, ορδθέξ εενιμηναζίεξ ημοξ ηαθμηαζνζκμφξ ιήκεξ, πεζιχκεξ ιε ιεζςιέκδ πζμκυπηςζδ ηθπ (Matzafleri 2007, Matzafleri et al. 2009). Βηβιηνγξαθία: 1. APHA, Standard Methods for the Examination of Water and Wastewater, 20 th ed. American Public Health Association, Washington DC. 2. Bengtsson L., Phosphorus release from a highly eutrophic lake sediment, Verh. Int. Ver. Limnol., 19, Bruns D. & Wiersma G., Conceptual Basis of Environmental Monitoring Systems: A Geospatial Perspective, in Wiersma G.B. (Ed.), Environmental Monitoring, CRC Press, Florida. 4. Carpenter S., Patterns of primary production and herbivory in 25 North American lake ecosystems, In: J.Cole et al (eds), Springer,USA. 17

18 5. Carlson R.E., A trophic state index for lakes. Limnology & Oceanography, 22, 2, p European Parliament Council (2000). Directive 2000/60/EC of the European Parliamentb and of the council of 23 October 2000 establishing a framework for community action in the field of water policy.official journal of the European Communities,L327, Heyman U, Ryding S. & Forsberg C., Frequency distribution of water quality variable, Water Research, 18, Hutulla J. & Noges J., Present state and future fate of Lake Vortsjary, In: Finish- Estorian Report: The Finish Environment, Tampere, Finland. 9. Huszar V. & Caracao N., The relationship between phytoplankton composition and Physical - Chemical variables, Freshwater Biology, 40, Kagalou I., Papastergiadou E. & Leonardos I., Long term changes in the eutrophication process in a shallow Mediterranean lake ecosystem of W. Greece. Response after the reduction of extended load, Journal of Environmental Management, 87, Kagalou I. & Psilovikos A., Assessment of the Typology and the Trophic Status of Two Mediterranean Lake Ecosystems in Northwestern Greece. Water Resources, 41, 3, Kleebery A. & Kozerski H.P Phosphorous release in Lake Grosser Muggelsee and its implications for lake restoration, Hydrobiologia, 342, Lanaras T., Tsitsamis C., Chilichilia & Cook C., Toxic cyanobacteria in Greek freshwaters. Journal of Applied Phycology, 1, Matzafleri N., Geographic Simulation of the Water Quality of Lake Kastoria. Postgraduate Dissertation, Dept. of Agriculture Ichthyology & Aquatic Environment, University of Thessaly (in Greek), 257p. 15. Matzafleri N., Psilovikos Ar. & Blanta A., Water Quality Simulation Model in Lake Kastoria (Western Macedonia Greece), using Monitoring Data and GIS. Assessment and Management of Pollution Sources, Water Resources Management, DOI: /s Moustaka Gouni M., Vardaka E., Michaloudi E., Kormas K., Tryfon E., Mihalatou H., Gkelis S. & Lanaras T., Plankton Food Web Structure in a Eutrophic Polymictic Lake with a History of Toxic Cyanobacterial Blooms. Limnololy & Oceanography, 51 (1, part 2), Organization for Economic Cooperation and Development (OECD), Eutrophication of Waters: Monitoring, Assessment and Control. Cooperative Program on Monitoring of Inland Waters (Eutrophication Control). Environment Directorate OECD, Paris France. 18. Schindler D., The evolution of phosphorus limitation in Lakes, Science, 195, Stefanidis K. & Papastergiadou E., Influence of hydrophyte abudance on the spatial distribution of zooplankton in selected lakes in Greece. Hydrobiologia 656: Straskraba M. & Tundisi J., Guidelines of lake management, International Lake Environment Committee, Japan, Threlked S., Benthic-pelagic interactions in shallow water columns: and experimentalist s perspective, Hydrobiologia, 275/276, Vollenweider R., Scientific Fundamentals of the Eutrophication of lakes and flowing waters with particular reference to nitrogen and phosphorus as factors in Eutrophication, OECD, Paris. 23. Vollenweider R. & Kerekes J., Eutrophication of Waters. Monitoring, Assessment and Control, OECD, Paris. 24. Wetzel R.G., Limnology, Lake and River Ecosystems, Amsterdam, Elsevier. 18

19 MONITORING PARAMETERS Tw, DO AND ENVIRONMENTAL EVALUATION OF THE ARTIFICIAL LAKE OF THESAURUS FOR THE YEARS Sentas Α.ˡ, Psilovikos Αrˡ. University of Thessaly, School of Agricultural Sciences, Department of Ichthyology and Aquatic Environment, Fytoko st., 38466, N. Ionia Magnisias, Greece ABSTRACT The average flow of the river Nestos is the area of the river with the largest anthropogenic interference, because a system of two dams (Thesaurus and Platanovrisi) is operated in this region. Our study area is the reservoir of the Thesaurus. The assessment and evaluation of the water reservoir is achieved by analyzing data at four different depths (1, 20, 40 and 70m). Applying statistical analysis extracted the following conclusion about the situation and the natural function of the reservoir. Upwelling and turnover phenomena were detected once a year, especially during early spring months (March), so Thesaurus Lake is characterized as a monomictic lake.for the rest of the seasons, strong stratification was observed at these three water bodies: Epilimnion, Metalimnion, Hypolimnion. Based on the water temperature at different depths and the varying thickness of thermocline during the year, Thesaurus can be characterized as a deep lake. The high values of DO on the surface (1m) from mid-march to end of April and from mid-june to mid-july are observed, meaning photosynthesis phenomena which occur during spring and early summer, due to the evolvement of phytoplankton. Key words: Nestos, Thesaurus, lake stratification, dissolved oxygen, water temperature *Corresponding author: Sentas Antonis (antsentas@yahoo.gr) ΠΑΡΑΚΟΛΟΤΘΖΖ ΣΧΝ ΠΑΡΑΜΔΣΡΧΝ T W, DO ΚΑΗ ΠΔΡΗΒΑΛΛΟΝΣΗΚΖ ΑΞΗΟΛΟΓΖΖ ΣΖ ΣΔΥΝΖΣΖ ΛΗΜΝΖ ΣΟΤ ΘΖΑΤΡΟΤ ΓΗΑ ΣΑ ΔΣΖ 2004 ΔΧ 2007 έληαο Α. *, Φηινβίθνο Αξ. Σιήια Γεςπμκίαξ Ηπεομθμβίαξ & Τδάηζκμο Πενζαάθθμκημξ, Πακεπζζηήιζμ Θεζζαθίαξ, Οδυξ Φοηυημο, Ν. Ηςκία Μαβκδζίαξ, 38446, Βυθμξ, Δθθάδα. ΠΔΡΗΛΖΦΖ Ο ιέζμξ νμοξ ημο πμηαιμφ Νέζημο απμηεθεί ηδκ πενζμπή ημο πμηαιμφ ιε ηδ ιεβαθφηενδ ακενςπμβεκή πανέιααζδ ηαεχξ ζηδκ πενζμπή αοηή θεζημονβεί ζφζηδια δφμ θναβιάηςκ ημο Θδζαονμφ ηαζ ηδξ Πθαηακυανοζδξ. Πενζμπή ιεθέηδξ απμηεθεί δ ηεπκδηή θίικδ ημο Θδζαονμφ. Ζ εηηίιδζδ ηαζ αλζμθυβδζδ ηςκ οδάηςκ ηδξ ηεπκδηήξ θίικδξ επζηοβπάκεηαζ ακαθφμκηαξ δεδμιέκα ζε ηέζζενα δζαθμνεηζηά αάεδ (1, 20, 40 ηαζ 70m). Δθανιυγμκηαξ ζηαηζζηζηή ακάθοζδ ελάβεηαζ ημ παναηάης ζοιπέναζια βζα ηδκ ηαηάζηαζδ ηαζ ηδ θοζζηή θεζημονβία ηδξ. Ζ ηεπκδηή θίικδ ημο Θδζαονμφ είκαζ ιία ιμκμιζηηζηή θίικδ, ιε ηδκ ακαζηνμθή ηςκ οδάηςκ κα ηαηαβνάθεηαζ ιία θμνά εηδζίςξ ηαηά ημοξ ιήκεξ Φεανμοάνζμ Μάνηζμ. Σμκ οπυθμζπμ πνυκμ πανμοζζάγεζ ζζπονή ζηνςιάηςζδ, δδιζμονβχκηαξ ηνία ζηνχιαηα (επζθίικζμ, ιεηαθίικζμ, οπμθίικζμ). Βάζεζ ηδξ εενιμηναζίαξ ζηα δζάθμνα αάεδ ηαζ ηδξ ιεηααμθήξ ημο πάπμοξ ημο εενιμηθζκμφξ ηαηά ηδ δζάνηεζα ημο έημοξ, ιπμνεί κα παναηηδνζζηεί ςξ ααεζά θίικδ. Καηά ηδκ πενίμδμ Μανηίμο έςξ Απνζθίμο ηαζ απυ ηα ιέζα Ημοκίμο ςξ ηα ιέζα Ημοθίμο, ηαηαβνάθμκηαζ ορδθέξ ηζιέξ δζαθοιέκμο μλοβυκμο μζ μπμίεξ μθείθμκηαζ ζημ θαζκυιεκμ ηδξ θςημζφκεεζδξ θυβς ηδξ ακάπηολδξ ημο θοημπθαβηημφ. Λέξειρ Κλειδιά: Νέζηνο, Θεζαπξόο, ζηξσκάησζε ιίκλεο, δηαιπκέλν νμπγόλν, ζεξκνθξαζία λεξνύ * οββναθέαξ επζημζκςκίαξ: έκηαξ Ακηχκδξ (antsentas@yahoo.gr) 19

20 1. Δηζαγσγή Ο πμηαιυξ Νέζημξ είκαζ έκαξ απυ ημοξ ιεβαθφηενμοξ πμηαιμφξ ηδξ Δθθάδαξ ηαεχξ είκαζ μ πέιπημξ ζε ιέβεεμξ θεηάκδξ απμννμήξ. οκζζηά δζαζοκμνζαηυ οδαηζηυ πυνμ ζηδ Βαθηακζηή πενζυκδζμ, υπμο ιμζνάγεηαζ ιεηαλφ ηςκ πςνχκ Βμοθβανίαξ ηαζ Δθθάδαξ. πεηζηά πνυζθαηα ( ) ζημ πχνμ ηδξ εκδμμνεζκήξ ημζθάδαξ ηαζ θεηάκδξ ημο Νέζημο ηαηαζηεοάζηδηακ ηαζ θεζημφνβδζακ απυ ηδ Γ.Δ.Ζ. μζ δ ηεπκδηέξ θίικεξ ημο Θεζαπξνύ, ηδξ Πιαηαλόβξπζεο ηαζ ημο Σεκέλνπο (οπυ ηαηαζηεοή ακαννοειζζηζηυ ένβμ ηαηάκηδ ηδξ Πθαηακυανοζδξ). Σα ένβα αοηά, ηα μπμία δέπηδηακ ηνζηζηή απυ επζζηήιμκεξ ηαζ θμνείξ βζα πζεακέξ δοζιεκείξ επζπηχζεζξ ημοξ ζημ θοζζηυ πενζαάθθμκ, ηαηαζηεοάζηδηακ πνμηεζιέκμο κα αλζμπμζδεεί ημ οδαηζηυ δοκαιζηυ ημο πμηαιμφ βζα ηδκ παναβςβή εκένβεζαξ, ηδκ ακηζπθδιιονζηή πνμζηαζία ηδξ δεθηασηήξ πεδζάδαξ, ηδκ άνδεοζδ ηςκ ηαθθζενβεζχκ ηδξ ηαζ ηδκ οπμζηήνζλδ ημο οβνμημπζημφ ηδξ πενζαάθθμκημξ. Ζ ηαηαζηεοή ηςκ θναβιάηςκ ζηδκ εκδμμνεζκή πενζμπή, έπεζ επζθένεζ ζδιακηζηέξ πενζααθθμκηζηέξ αθθαβέξ ζημ νμο ημο πμηαιμφ ηαζ ημοξ μνβακζζιμφξ πμο γμοκ ζε αοηυκ, ηαεχξ ημ ιεβαθφηενμ ηιήια ημο ιεηαηνάπδηε απυ πμηάιζμ ζε θζικαίμ. Ζ αλζμπμίδζδ ηςκ ιεηνήζεςκ ηςκ παναιέηνςκ ηςκ οδάηςκ ηδξ ηεπκδηήξ θίικδξ ημο Θδζαονμφ, ημ αάεμξ ηδξ μπμίαξ θηάκεζ πενίπμο ηα 140 ιέηνα, βεβμκυξ πμο ηδκ ηαεζζηά ηδκ πζμ ααεζά θίικδ ζημκ Δθθαδζηυ πχνμ, απμηηά ζδζαίηενμ εκδζαθένμκ βζα ημκ εκημπζζιυ ηαζ ηδ δζενεφκδζδ ζδιακηζηχκ θαζκμιέκςκ πμο θαιαάκμοκ πχνα ζηδκ οδάηζκδ ζηήθδ. 2. Τιηθά θαη Μέζνδνη Πενζμπή ιεθέηδξ ηδξ πανμφζδξ ενβαζίαξ απμηεθεί μ ηαιζεοηήναξ ημο Θδζαονμφ, δ έκανλδ θεζημονβίαξ ημο μπμίμο έθααε πχνα ημ Πνζκ απυ ηδκ ηαηαζηεοή ηςκ θναβιάηςκ μ πμηαιυξ ακαπηοζζυηακ ζε ορυιεηνμ m. Μεηά ηδκ ηαηαζηεοή ηςκ θναβιάηςκ, πένα απυ ηζξ ηεπκδηέξ θίικεξ πμο δδιζμονβήεδηακ, έπεζ πθδιιονίζεζ ιζα εονφηενδ γχκδ ιήημοξ πενίπμο 50 km ηαζ ιέζμο πθάημοξ 250m (ημ ιέβζζημ πθάημξ λεπενκά ηαηά ηυπμοξ ηα 400m), εκχ δ ιέζδ ζηάειδ ηςκ οδάηςκ αημθμοεεί ηδκ ζζμτρή ηαιπφθδ ηςκ 360m (Albanakis et al. 2001, Sentas & Psilovikos 2010). Ο Θδζαονυξ απμηεθεί έκα ρδθυ πςιάηζκμ θνάβια (θζευννζπημ) ιε αδζαπέναζημ ανβζθζηυ πονήκα, ημ φρμξ ημο θηάκεζ ηα 175m, βεβμκυξ πμο ημ ηαεζζηά έκα απυ ηα ορδθυηενα βεςθνάβιαηα ηδξ Δονχπδξ. Ζ επζθάκεζα ημο ηαιζεοηήνα είκαζ 18km 2, εκχ δ ιέβζζηδ πνήζζιδ ζηακυηδηα απμεήηεοζδξ κενμφ, είκαζ ηδξ ηάλδξ ηςκ 700x10 6 m 3. Σμ αάεμξ ηδξ θίικδξ θηάκεζ πενίπμο ηα 140m, πνάβια πμο ηδκ ηαεζζηά ηδκ πζμ ααεζά θίικδ ζημκ Δθθαδζηυ πχνμ. Ο ηφνζμξ ζημπυξ ημο θνάβιαημξ είκαζ δ παναβςβή οδνμδθεηηνζηήξ εκένβεζαξ. Έηζζ έπεζ ηαηαζηεοαζηεί οδνμδθεηηνζηυ ενβμζηάζζμ, ημ μπμίμ είκαζ εβηαηεζηδιέκμ ζημ δελζυ ακηένεζζια ζε αάεμξ 400m. Λεζημονβμφκ ηνεζξ ιμκάδεξ ηςκ 100 MW δ ηαεειζά ηαζ δ παναβυιεκδ εηήζζα εκένβεζα είκαζ πενίπμο 400 GWh. Γζα ηδκ μνεμθμβζηή δζαπείνζζδ ηςκ οδάηςκ ημο πμηαιμφ ζηδκ ηεπκδηή θίικδ, αθθά ηαζ βζα ηδ ζςζηή θεζημονβία ημο οδνμδθεηηνζημφ ζηαειμφ Θδζαονμφ (ΤΖ), εα πνέπεζ κα βίκεζ αλζμθυβδζδ ηςκ θαζκμιέκςκ πμο θαιαάκμοκ πχνα ζηδκ οδάηζκδ ζηήθδ. Γζα ημ ζημπυ αοηυ, έβζκε ακάθοζδ ηςκ διενήζζςκ ηζιχκ ηςκ παναιέηνςκ δηαιπκέλν νμπγφλν (DO) ηαζ ζεξκνθξαζίαο λεξνχ (Tw), λεπςνζζηά βζα ηάεε έημξ. Οζ ιεηνήζεζξ πνμένπμκηαζ απυ ζφζηδια παναημθμφεδζδξ οδάηςκ, ημ μπμίμ εβηαηαζηάεδηε ζηδκ εκδμμνεζκή ημζθάδα ημ 2001, απυ ηδκ ενεοκδηζηή μιάδα ΠΔΡΔΑ ημο ΑΠΘ. Απμηεθείηαζ απυ έκα ηαειυ Βάζδξ (.Β.), έκακ Πενζθενεζαηυ (Π..) ηαζ έκα Μεηεςνμθμβζηυ ηαειυ (Μ..). Ο.Β. ηαζ μ Μ.. ανίζημκηαζ ζηδ ζηέρδ ημο θνάβιαημξ ημο Θδζαονμφ, εκχ μ Π.. ιέζα ζηδ θίικδ (πθςηυξ). 3. Απνηειέζκαηα Γζα ημ 2004, δ πανάιεηνμξ Tw ζηδκ ανπή ημο έημοξ ειθακίγεζ ήπζα πηςηζηή ηάζδ ζε υθα ηα ζηνχιαηα, δ μπμία ζοκεπίγεηαζ ιέπνζ ηα ιέζα Μανηίμο μπυηε μζ ηζιέξ ζηαεενμπμζμφκηαζ, ιε ημ ακχηενμ ζηνχια ημο 1m κα ανίζηεηαζ ζημοξ 7 o C ηαζ ημ ηαηχηενμ ηςκ 70m ζημοξ 5 o C (πήια 1α). Δίκαζ πνμθακχξ δ πενίμδμξ ηδξ ακαζηνμθήξ ηςκ οδάηςκ ηαζ ηδξ εενιμηναζζαηήξ μιμζμβέκεζαξ ηδξ ζηήθδξ ημο κενμφ. Γζα ημ οπυθμζπμ ημο έημοξ παναηδνείηαζ ζζπονή ζηνςιάηςζδ, ιε απμηέθεζια ηδ δδιζμονβία ηνζχκ ζηνςιάηςκ: επζθίικζμ, ιεηαθίικζμ (εενιμηθζκέξ) ηαζ οπμθίικζμ. Δζδζηά βζα ηα ααεφηενα ζηνχιαηα ηςκ 70m δ Tw δζαηδνείηαζ ζε πμθφ παιδθά επίπεδα, ιε εθάπζζηεξ δζαηοιάκζεζξ, πανμοζζάγμκηαξ ηδ ιέβζζηδ ηζιή ζημ ηέθμξ Ημοθίμο εκχ ηαηά ημ ηέθμξ θεζκμπχνμο μδδβείηαζ ζε ζηαζζιυηδηα. Δπζζδιαίκεηαζ επίζδξ ημ βεβμκυξ υηζ, ηαηά ηα ιέζα Οηηςανίμο μζ εενιμηναζίεξ ημο επζθακεζαημφ ζηνχιαημξ είκαζ παιδθυηενεξ απυ ηζξ εενιμηναζίεξ ημο ζηνχιαημξ ημο αάεμοξ ηςκ 20m. Αοηυ ελδβείηαζ απυ ημ βεβμκυξ υηζ ημκ Οηηχανζμ, εκχ ημ επζθακεζαηυ ζηνχια έπεζ ήδδ ανπίζεζ κα ρφπεηαζ ζηαδζαηά, ημ ζηνχια ηςκ 20m ελαημθμοεεί κα εενιαίκεηαζ ηαζ κα πθδζζάγεζ ηζξ ιέβζζηεξ ηζιέξ ημο, ιε δζαθμνά θάζδξ οζηένδζδ. Αοηά ηα θαζκυιεκα ειθακίγμκηαζ θυβς ηδξ ιεβάθδξ εενιμπςνδηζηυηδηαξ ημο κενμφ, ημο ιεβάθμο υβημο ημο ηαιζεοηήνα (700 x 10 6 m 3 ) ηαζ ημο αάεμοξ ημο (140m). Γζα ηδκ πανάιεηνμ DO, υπςξ παναηδνείηαζ ζημ ζπήια 1α, ημ πνχημ ελάιδκμ ημο 2004 οπήνλε ζηακμπμζδηζηή μλοβυκςζδ υθδξ 20

21 ηδξ ζηήθδξ ημο κενμφ, βεβμκυξ πμο απμδίδεηαζ ζηζξ ζηακμπμζδηζηέξ εζζνμέξ ροπνμφ μλοβμκςιέκμο κενμφ ημο Νέζημο ζημκ ηαιζεοηήνα. Καηά ηα ιέζα Μανηίμο ιέζα Απνζθίμο ηαηαβνάθμκηαζ ορδθέξ ηζιέξ DO ζημ επζθίικζμ, πμο μθείθμκηαζ ζε αζμθμβζηέξ δζενβαζίεξ ηαηά ηδκ πενίμδμ ηδξ άκμζλδξ, πμο έπμοκ κα ηάκμοκ ιε ακάπηολδ θοημπθαβηημφ ηαζ θαζκυιεκα θςημζφκεεζδξ. ηζξ ανπέξ Μανηίμο παναηδνείηαζ ημ πανάδμλμ θαζκυιεκμ ηα ααεφηενα ζηνχιαηα ηςκ 40 ηαζ 70m κα οπενααίκμοκ ηζξ ηζιέξ ημο DO ηςκ επζθακεζαηχκ ζηνςιάηςκ ημο 1 ηαζ 20m, πνάβια πμο απμδεζηκφεζ υηζ ηαηά ηδκ πενίμδμ αοηή οπήνλε ιζα ακαζηνμθή ηςκ οδάηςκ, ιε μλοβυκςζδ ηαζ ηςκ ααεφηενςκ ζηνςιάηςκ, πμο ηεηιδνζχκεηαζ ηαζ απυ ηδκ ελίζςζδ ηςκ εενιμηναζζχκ ζε υθμ ημ εφνμξ ηδξ ζηήθδξ. Μζα πνχηδ ενιδκεία ημο θαζκμιέκμο αοημφ ιπμνεί κα απμδμεεί ζηδκ εζζνμή ιεβάθςκ υβηςκ ροπνμφ κενμφ απυ ημ Νέζημ ζημ Θδζαονυ θυβς ηήλδξ πζμκζμφ ή εηδήθςζδξ πθδιιονζηχκ θαζκμιέκςκ. Δπίζδξ, ηαηά ημοξ ιήκεξ επηέιανζμ ηαζ Οηηχανζμ παναηδνείηαζ πενίπμο ηαφηζζδ ηςκ ηζιχκ ημο DO ζηα 40 ηαζ 70m, εκχ πνμξ ημ ηέθμξ ημο έημοξ μζ ηζιέξ ζηα 20 ηαζ 40m οπενααίκμοκ αοηέξ ημο επζθακεζαημφ ζηνχιαημξ υπςξ αηνζαχξ παναηδνήεδηε ηαζ ζηδκ πενίπηςζδ ηδξ Tw. ρήκα 1: Μεηξήζεηο ησλ παξακέηξσλ (α) Tw θαη (β) DO, ζηα ηέζζεξα βάζε, γηα ην έηνο 2004 ηδκ ανπή ημο έημοξ 2005, δ πανάιεηνμξ Tw ειθακίγεζ ηδκ ίδζα ζοιπενζθμνά ιε ημ έημξ 2004, ιε ιυκδ δζαθμνά υηζ δ πενίμδμξ ζφβηθζζδξ ηςκ Tw ζηα 4 αάεδ, εκημπίγεηαζ ζηζξ ανπέξ Φεανμοανίμο (πήια 2α). ημ δζάζηδια αοηυ μζ ηζιέξ ζημ αάεμξ 1m ηοιαίκμκηαζ βφνς ζημοξ 9 μ C, εκχ ζημ οπμθίικζμ ανίζημκηαζ ζημοξ 6,5 ιε 7 μ C. Γζα ημ οπυθμζπμ ημο έημοξ παναηδνείηαζ ζζπονή δζααάειζζδ ηδξ Tw ιε ημ αάεμξ. Οζ Tw ημο επζθακεζαημφ ζηνχιαημξ, ηαηά ηα ιέζα Οηηςανίμο ηαζ βζα ημ έημξ 2005, ειθακίγμκηαζ παιδθυηενεξ απυ ηζξ ακηίζημζπεξ ημο ζηνχιαημξ αάεμοξ 20m, βζα ημοξ ίδζμοξ θυβμοξ πμο ελδβήεδηακ πνμδβμφιεκα. Γζα ημ DO μζ ηζιέξ ηαηά ημ πνχημ ελάιδκμ ημο 2005 πανμοζζάγμοκ ακμδζηέξ ηάζεζξ, ιε έκημκεξ δζαηοιάκζεζξ εκχ ζηαεενμπμζμφκηαζ απυ ημ ηέθμξ Μανηίμο έςξ ηαζ ημ Μάζμ. Δπίζδξ παναηηδνζζηζηυ ηδξ πενζυδμο αοηήξ είκαζ μζ ζδζαίηενα ορδθέξ ηζιέξ ημο DO ζε αάεμξ 70m (πήια 2α). Καηά ηα ιέζα Μανηίμο παναηδνείηαζ ακαζηνμθή ηςκ οδάηςκ ηδξ ζηήθδξ, ιε ηζξ ηζιέξ ζηα 40 ηαζ 70m κα οπενααίκμοκ αοηέξ ηςκ επζθακεζαηχκ ζηνςιάηςκ. Ζ ενιδκεία ημο θαζκμιέκμο είκαζ αοηή πμο ακαπηφπεδηε ηαζ ζηδκ πενίπηςζδ ημο έημοξ Απυ ημ ηέθμξ Μαΐμο ηαηαβνάθεηαζ έκημκα πηςηζηή ηάζδ ηςκ ηζιχκ βζα υθα ηα αάεδ, ιε εκημκυηενδ βζα ηα 70m. Δπίζδξ, ηαηά ημοξ ιήκεξ επηέιανζμ ηαζ Οηηχανζμ παναηδνείηαζ πενίπμο ηαφηζζδ ηςκ ηζιχκ ημο DO ζηα 40 ηαζ 70m. Πνμξ ημ ηέθμξ ημο έημοξ, μζ ηζιέξ ζηα 20 ηαζ 40m οπενααίκμοκ αοηέξ ημο επζθακεζαημφ ζηνχιαημξ, βζα ημοξ θυβμοξ πμο ακαθφεδηακ βζα ηδκ πενίπηςζδ ημο Αλζμζδιείςηδ είκαζ δ ορδθή πενζεηηζηυηδηα DO ςξ ηαζ ηα ααεφηενα ζηνχιαηα ημο κενμφ, βεβμκυξ ελαζνεηζηά εεηζηυ βζα ηδκ ηαθή θεζημονβία ημο ηαιζεοηήνα ηαζ ημο ΤΖ. Απμηεθεί ακαζηαθηζηυ πανάβμκηα δδιζμονβίαξ θαζκμιέκςκ ζηαζζιυηδηαξ, οπμλίαξ ηαζ πζεακήξ ακμλίαξ ηαζ δδιζμονβίαξ ημλζηχκ εκχζεςκ (CH 4, NH 3, H 2 S), θυβς ακαβςβζηχκ δζενβαζζχκ ζοκμδεουιεκςκ ιε ηδκ πανμοζία εεζμααηηδνίςκ, υπςξ είπε παναηδνδεεί ηαηά ηα πνχηα ζηάδζα ηδξ θεζημονβίαξ ημο (Moustaka et al. 2000, Albanakis et al. 2001). 21

22 ρήκα 2: Μεηξήζεηο ησλ παξακέηξσλ (α) Tw θαη (β) DO, ζηα ηέζζεξα βάζε, γηα ην έηνο 2005 Γζα ημ 2006 δ πενίμδμξ ελίζςζδξ ηδξ Tw ζηα 4 αάεδ, πναβιαημπμζείηαζ ζηα ηέθδ Ηακμοανίμο ιε ανπέξ Φεανμοανίμο, ιε ηζιέξ απυ 6 έςξ 8,5 μ C (πήια 3α). Υαναηηδνζζηζηυ είκαζ υηζ μζ ηζιέξ ζηα 70m είκαζ ίζεξ ή ιεβαθφηενεξ απυ ηζξ ακηίζημζπεξ ηςκ 40m, απυ ηέθδ Ηακμοανίμο έςξ ιέζα Απνζθίμο. Γζα ημ οπυθμζπμ ημο έημοξ παναηδνείηαζ ζηνςιάηςζδ ηδξ ζηήθδξ ηςκ οδάηςκ υιμζα ιε αοηή ημο 2004 ηαζ πςξ ηαζ ηα πνμδβμφιεκα έηδ, έηζζ ηαζ ζηδκ πενίπηςζδ ημο 2006 ημ DO πανμοζζάγεζ ακμδζηέξ ηάζεζξ ημοξ πνχημοξ ιήκεξ ημο έημοξ έςξ ηα ιέζα Απνζθίμο. ηζξ 20 ιε 25 Ηακμοανίμο παναηδνείηαζ ιζα πνμζέββζζδ ηςκ ηζιχκ ημο ζηα ηέζζενα αάεδ, ιε ηζιέξ πμο ηοιαίκμκηαζ απυ 8 έςξ 8,5 mg/l, βεβμκυξ πμο ηαηαδεζηκφεζ ακαζηνμθή ηςκ οδάηςκ δ μπμία ηαηαβνάθεηαζ πνμκζηά κςνίηενα απυ ηα πνμδβμφιεκα έηδ (πήια. 3α). Αοηυ είκαζ πζεακυ κα μθείθεηαζ ζημ δνζιφ ρφπμξ πμο παναηδνήεδηε ημ ιήκα Ηακμοάνζμ ημο 2006, ιε πμθφ παιδθέξ εενιμηναζίεξ αένα ηαζ κενμφ. ημ επζθακεζαηυ ζηνχια, κςνίηενα απυ ηα πνμδβμφιεκα έηδ έπεζε δ εενιμηναζία ζηα επίπεδα ημο οπμθζικίμο, μπυηε επήθεε ηαζ δ ζηνςιάηςζδ έκα ιήκα πζμ κςνίξ. Απυ ηα ιέζα Απνζθίμο έςξ ηζξ ανπέξ Οηηςανίμο παναηδνείηαζ ιείςζδ ηςκ ηζιχκ ημο DO, ζε υθα ηα αάεδ. Ζ ιείςζδ αοηή δεκ είκαζ ίδζα, ηαεχξ μζ ηζιέξ ζηα 70m δζαηδνμφκηαζ ζε ορδθά βζα ηδκ επμπή επίπεδα. Αοηυ έπεζ ςξ απμηέθεζια κα ηαηαβνάθμκηαζ ιζηνυηενεξ ηζιέξ απυ ηζξ ανπέξ Αοβμφζημο έςξ ανπέξ Οηηςανίμο βζα ηα 20m ηαζ απυ ηζξ ανπέξ Αοβμφζημο έςξ ηέθδ Οηηςανίμο βζα ηα 40m. Σέθμξ, απυ ηα ιέζα Οηηςανίμο έςξ ηα ιέζα Νμειανίμο, ακηίζημζπα, ιεζςιέκεξ ηζιέξ παναηδνμφκηαζ ηαζ βζα ημ επζθακεζαηυ ζηνχια. ρήκα 3: Μεηξήζεηο ησλ παξακέηξσλ (α) Tw θαη (β) DO, ζηα ηέζζεξα βάζε, γηα ην έηνο 2006 Οζ ιεηνήζεζξ ημο ηεθεοηαίμο έημοξ 2007 δζαθμνμπμζμφκηαζ ζε ζπέζδ ιε ηα πνμδβμφιεκα έηδ. Έηζζ δ πανάιεηνμξ Tw ζηζξ ανπέξ ημο έημοξ πανμοζζάγεζ πηςηζηή ηάζδ, αθθά ιυκμ βζα ηα ηνία πνχηα αάεδ, εκχ μζ ιεηνήζεζξ ηςκ 70m πανμοζζάγμοκ ακμδζηή ηάζδ ζε υθμ ημ πνχημ ελάιδκμ ημο έημοξ (πήια 4α). Ζ ζπέζδ δ μπμία παναηδνήεδηε ακάιεζα ζηζξ εενιμηναζίεξ ηςκ 40 ηαζ 70m ανπέξ ημο 2006 παναηδνείηαζ ηαζ ημ έημξ 2007 ιε ιεβαθφηενδ υιςξ δζάνηεζα (απυ 26/3 έςξ 25/6). Καηά ημοξ εενζκμφξ ιήκεξ ηαηαβνάθμκηαζ ορδθέξ ηζιέξ εενιμηναζζχκ ζημ επζθακεζαηυ ζηνχια ηαζ έκημκδ ζηνςιάηςζδ βζα ηα οπυθμζπα αάεδ. Απυ ηα ιέζα Οηηςανίμο παναηδνμφκηαζ παιδθυηενεξ ηζιέξ βζα ηζξ εενιμηναζίεξ ζε αάεμξ 1m απυ ηζξ ακηίζημζπεξ ηςκ 20m. Πνμξ ημ ηέθμξ ημο έημοξ ημ οπμθίικζμ πανμοζζάγεζ ορδθέξ βζα ηδκ επμπή εενιμηναζίεξ, μζ μπμίεξ ημκ ηεθεοηαίμ ιήκα είκαζ ορδθυηενεξ ηςκ ακηίζημζπςκ ηςκ 40m. Γζα ημ 2007 ημ DO πανμοζζάγεζ έκημκεξ δζαηοιάκζεζξ ηαε υθδ ηδ δζάνηεζα ημο έημοξ, ηονίςξ ζημ επζθίικζμ ηαζ οπμθίικζμ. Σμοξ ιήκεξ Απνίθζμ ηαζ Μάζμ ηαηαβνάθμκηαζ μνζζιέκεξ ηζιέξ ζημ 1m ιζηνυηενεξ απυ αοηέξ ηςκ 70m. Ηδζαίηενα ορδθέξ ηζιέξ παναηδνμφκηαζ ζημ επζθακεζαηυ ζηνχια απυ ανπέξ Ημοκίμο έςξ ιέζα Οηηςανίμο. Σμ ακηίζημζπμ δζάζηδια ζηα 70m ηαηαβνάθμκηαζ πμθφ παιδθέξ ηζιέξ, ιε θαζκυιεκα οπμλίαξ ηαζ ακμλίαξ ζημ οπμθίικζμ απυ ηζξ 27/8 έςξ ηζξ 23/11. 22

23 4. πδήηεζε ρήκα 4: Μεηξήζεηο ησλ παξακέηξσλ (α) Tw θαη (β) DO, ζηα ηέζζεξα βάζε, γηα ην έηνο 2007 Ζ ακά έημξ ακάθοζδ μδδβεί ζηα ελήξ ζοιπενάζιαηα βζα ηδκ ηεπκδηή θίικδ ημο Θδζαονμφ: 1. Υαναηηδνίγεηαζ ςξ ιμκμιζηηζηή θίικδ, ηαεχξ ιζα θμνά ημ πνυκμ ηαζ ζοκήεςξ ηαηά ημοξ ιήκεξ Φεανμοάνζμ Μάνηζμ, πανμοζζάγεηαζ ημ θαζκυιεκμ ηδξ ακαζηνμθήξ ηςκ οδάηςκ ιε απμηέθεζια ηδκ ακάιζλδ ηδξ οδάηζκδξ ζηήθδξ. Ζ ακάιζλδ ηςκ οδάηςκ έπεζ ζα ζοκέπεζα ηδκ ηοηθμθμνία ηςκ ενεπηζηχκ ζημζπείςκ πμο οπάνπμοκ ζηδκ επζθάκεζα ηδξ θίικδξ, ζε υθδ ηδ ιάγα ημο κενμφ, εκζζπφμκηαξ ηδκ μιμζυιμνθδ ηαηακμιή ηςκ ενεπηζηχκ ζημζπείςκ ηαζ ημο δζαθοιέκμο μλοβυκμο ζε υθδ ηδ ζηήθδ ημο κενμφ ηαηά ηδκ πενίμδμ ηδξ ακαζηνμθήξ. Σμ ζοιπέναζια αοηυ ζοιθςκεί ηαζ ιε παθαζυηενεξ ιεθέηεξ πμο έπμοκ βίκεζ (Moustaka Gouni et al. 2000, Albanakis et al. 2001, Sentas & Psilovikos 2010). 2. Γζα ημοξ οπυθμζπμοξ ιήκεξ παναηδνείηαζ ζζπονή ζηνςιάηςζδ ζηδκ οδάηζκδ ζηήθδ, δδιζμονβχκηαξ ηνία ζηνχιαηα. i. Δπηιίκλην: απακηάηαζ ζηα 0 5 έςξ 0 40m ακαθυβςξ ηδξ επμπήξ, ιε αάζδ ηδκ παναπάκς ακάθοζδ. ii. Μεηαιίκλην ή ζεξκνθιηλέο: είκαζ ημ ιεηαααηζηυ ζηνχια κενμφ, ιεηααθδημφ πάπμοξ πμο πανμοζζάγεζ έκημκδ δζααάειζζδ εενιμηναζίαξ ηαζ εκημπίγεηαζ ζε δζαθμνεηζηά αάεδ ηαε υθδ ηδ δζάνηεζα ημο πνυκμο. Υαναηηδνίγεηαζ απυ απυημιεξ δζαααειίζεζξ ημο DO, εκχ ηαζ μζ δφμ πανάιεηνμζ ιεζχκμκηαζ ιε ηδκ αφλδζδ ημο αάεμοξ. Παναηδνείηαζ ιεηαλφ ηςκ 5 ηαζ 60m. iii. Τπνιίκλην: απακηάηαζ απυ ηα 60 70m ηαζ ηάης, απμηεθεί ημ ααεφηενμ, ροπνυηενμ ηαζ αδζαηάναηημ ζηνχια ηδξ θίικδξ ηαζ έπεζ ηζξ παιδθυηενεξ ηζιέξ DO ηαζ Tw. Παναηδνήεδηακ ζε εθάπζζηεξ πενζπηχζεζξ ιζηνήξ πνμκζηήξ δζάνηεζαξ ακμλζηέξ ζοκεήηεξ. 3. Ζ Tw βζα ηδκ πενίμδμ ιεθέηδξ ειθακίγεζ ημ αλζμζδιείςημ θαζκυιεκμ ηαηά ημ μπμίμ ηα ζηνχιαηα ημο κενμφ ζε αάεδ 20 ηαζ 40m απμννμθμφκ ηαζ απμηαιζεφμοκ εενιυηδηα ηαηά ηδ δζάνηεζα ηδξ εενζκήξ πενζυδμο ηαζ ηαηαβνάθμοκ ηζξ ιέβζζηεξ ηζιέξ ηδξ εενιμηναζίαξ ζηα ιέζα ημο θεζκμπχνμο. Σα παναπάκς επζαεααζχκμοκ ημ βεβμκυξ υηζ μ ηαιζεοηήναξ ημο Θδζαονμφ θεζημονβεί ζα ιζα θοζζηή ααεζά θίικδ, υπμο ημοξ ακμζλζάηζημοξ ιήκεξ ημ εενιμηθζκέξ ζοκακηάηαζ ζε νδπά αάεδ εκχ ημοξ θεζκμπςνζκμφξ ιεηαημπίγεηαζ ααεφηενα, ηάης απυ ηα 40m, αθμφ ιέπνζ αοηυ ημ αάεμξ θηάκεζ δ εένιακζδ απυ ημ επζθακεζαηυ ζηνχια. 4. Οζ ορδθέξ ηζιέξ ημο DO ζημ 1m, απυ ηα ιέζα Μανηίμο έςξ ηα ιέζα Ημοθίμο πενίπμο, πμο παναηδνμφκηαζ ζε υθα ηα έηδ, μθείθμκηαζ ζημ θαζκυιεκμ ηδξ θςημζφκεεζδξ ημ μπμίμ ζοιααίκεζ ηαηά ηδ δζάνηεζα ηδξ άκμζλδξ ηαζ κςνίξ ημ ηαθμηαίνζ ελαζηίαξ ηδξ ακάπηολδξ θοημπθαβηημφ. ηδ ζοκέπεζα, θυβς ηδξ ακάπηολδξ ημο θοημπθαβηημφ ιε βεςιεηνζηή πνυμδμ, μζ ακάβηεξ ζε DO βζα ηδκ απμζημδυιδζδ ηςκ ενεπηζηχκ είκαζ πμθφ ιεβαθφηενεξ απυ ηδκ πνμζθμνά θυβς θςημζφκεεζδξ, ιε απμηέθεζια κα ιεζχκμκηαζ μζ πμζυηδηεξ ημο δζαθοιέκμο μλοβυκμο ηαζ ζηαδζαηά ημ θοημπθαβηηυ κα εακαηχκεηαζ, μπυηε ηαζ παναηδνμφκηαζ μζ παιδθυηενεξ ηζιέξ ημο DO, ιεηαλφ Οηηςανίμο Γεηειανίμο. 5. Καηά ηδ δζάνηεζα ημο πνχημο ελαιήκμο ηάεε έημοξ, παναηδνείηαζ ζηακμπμζδηζηή μλοβυκςζδ ηδξ οδάηζκδξ ζηήθδξ, ιε ελαίνεζδ ηα 70m αάεμξ, ηα μπμία υπςξ έπεζ είδδ ακαθενεεί απμηεθμφκ ημ οπμθίικζμ ζηνχια. Καηά πενζυδμοξ ηαζ ζημ οπμθίικζμ έπμοκ ηαηαβναθεί ηζιέξ ιεβαθφηενεξ απυ 7 ςξ 8,2 mg/l. 6. Απυημιεξ δζαηοιάκζεζξ ημο DO παναηδνμφκηαζ ζημ επζθακεζαηυ ζηνχια ηαζ βζα ηα ηέζζενα έηδ. Οζ έκημκεξ αοηέξ ιεηααμθέξ ημο ζηδκ επζθάκεζα, μθείθμκηαζ ζηζξ έκημκεξ ιεηααμθέξ πμο θαιαάκμοκ πχνα ηαηά ηδ δζάνηεζα ηδξ διέναξ. Γεκζηά εα ιπμνμφζαιε κα πμφιε υηζ δ πενζεηηζηυηδηα ζε DO ζε υθδ ηδκ οδάηζκδ ζηήθδ είκαζ ζηακμπμζδηζηή. 23

24 Βηβιηνγξαθία έκηαξ Α., (2013). ημπαζηζηά ιμκηέθα πνμζμιμίςζδξ ζηδκ Πμζυηδηα Δπζθακεζαηχκ Τδάηςκ ζημκ Πμηαιυ Νέζημ. Γζδαηημνζηή Γζαηνζαή, Πακεπζζηήιζμ Θεζζαθίαξ, Σιήια ΓΗΤΠ, ζεθ Albanakis K., Mitrakas M., Moustaka-Gouni M., Psilovikos A. (2001) Determination of the environmental parameters that influence sulphide formation in the newly formed Thesaurus reservoir, in Nestos River, Greece. Fresenius Environmental Bulletin, 10(6): Anastassopoulos K. (2006) Treatment of big landslides affecting construction of Thissavros hydroelectric project. Proceedings of Hydro 2006, Maximizing the Benefits of Hydropower, 2006, Greece. Paper Sentas A., Psilovikos A. (2010) Comparison of ARIMA and Transfer Function (TF) Models in Water Temperature Simulation in Dam Lake Thesaurus, Eastern Macedonia, Greece. Proceedings International Symposium: Environmental Hydraulics, Athens, Greece, June 23-25, pp Sentas A., Psilovikos A. (2012) Dissolved oxygen assessment in Dam-Lake Thesaurus using stochastic modeling. Proceedings International Conference: PRE XI, Thessaloniki, Greece, July 2012, pp Μitsiou Κ.Α., Antonopoulos, V.Ε., Papamichail, D.Μ. (1999). Statistical Analysis of Water Quality Parameters Time Series of Strymon River. Hydrotechnika, 9: pp (in Greek). Moustaka Gouni M., Albanakis K., Mitrakas M., Psilovikos A. (2000) Planktic autotrophs and environmental conditions in the newly-formed hydroelectric Thesaurus reservoir, Greece. Archiv. Hydrobiol., 149(3):

25 ORAL PRESENTATIONS IN ENGLISH INTERRELATIONSHIP BETWEEN TOC, IC, TC AND DO, BOD, COD OF WATER IN REGARD TO STRATIFICATION OF AN ABANDONED OCP AT RANIGANJ COAL FIELD AREA, BURDWAN, WEST BENGAL Mondal S. 1, Mukherjee A. K. 2, Senapati T. 3, Haque S. 1, Ghosh A. R. 1 * 1 Ecotoxicology Lab, Department of Environmental Science, The University of Burdwan, Golapbag, Burdwan , West Bengal, India 2 P.G. Department of Conservation Biology, Durgapur Govt. College, Durgapur 14, West Bengal, India 3 School of Basic and Applied Sciences, Poornima University, Jaipur , Rajasthan, India Abstract This paper studied the stratification of an abandoned Opencast Coal Pit (OCP) locally called khadan to establish a relationship between the carbon content of an ecosystem and other ecological parameters like dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD). The carbon content of an aquatic ecosystem indicates the productivity of the system and is mainly determined by the parameters like total organic carbon (TOC), inorganic carbon (IC) and total carbon (TC). The reactions like photosynthesis, respiration and oxidative degradation of organic matters are caused through chemical and biological reactions, so, the values of other ecological parameters like DO, BOD and COD are changing according to the stratification of the OCP water body which may affect the total amount of organic and inorganic carbon throughout the water column. DO, BOD, and COD show their changes in concentration with the depths, temperature and seasons. Present study shows that TC and IC are positively correlated with COD and BOD but negatively correlated with DO concentration. TOC is negatively correlated with COD and BOD but positively related with DO concentration. This present investigation has intended to establish the mathematical correlation and changing patterns of the ecological parameters according to the depth and seasonal variation of the OCP water column. Keywords: Opencast Coal Pit (OCP), Stratification, Carbon forms, Ecological parameters * Corresponding author: Apurba Ratan Ghosh (apurbaghosh2010@gmail.com) 1. Introduction All living organisms consist of complex molecules built on a framework of carbon atoms which are able to bind readily with other carbon atoms along with other major elements like hydrogen, oxygen, nitrogen, phosphorus and sulfur to keep the structure, energetics, and function of life forms (Reddy & Delaune 2008). The hydrological features with the carbon content of lakes can influence to alter its basic appearance (Cre taux et al. 2005), or stratification pattern all through the column due to adverse anthropogenic activities (Jellison & Melack 1993). In an aquatic ecosystem, there is a connection between the hydrological and carbon cycles along with the exchange of materials between terrestrial and aquatic systems (Walling 2006; Cole et al. 2007). The amount of carbon in an aquatic ecosystem and productivity of the system are intermingling with each other. Organic and inorganic carbons constitute the main component of total amount of the carbon in systems which are broken down through the biological action mainly by bacteria (Findlay et al. 1993; Vervier et al. 1993; Jones et al. 1995) and by biogeochemical processes, occurring within soil aquatic interfaces (Hedin et al. 1998). On the other side, another main component of the surface water, the dissolved oxygen, requires for both biodegradation of complex carbon components into simpler form as well as survival of these microbes like, bacteria, and other aquatic organisms. So, biochemical oxygen demand (BOD) is concerned with the amount of oxygen consumed by microorganisms to decompose the organic matters under aerobic conditions while chemical oxygen demand (COD) relates the oxygen requirement to oxidize all organic materials both biologically available and inert organic matter into carbon dioxide and water. Usually, there is a hydrological relation between DO, BOD and COD which can affect the total amount of organic (TOC) and inorganic carbon (IC) in an ecosystem. In deep water body, according to its feature of thermal stratification, DO concentration changes with depth, temperature and season. Over the last decades, not only have new large water bodies, e.g., reservoirs, been created on the earth s surface, but also entirely novel aquatic systems developed in the aftermath of mining in abandoned opencasts (Miller et al. 1996; Kru ger et al. 2002). Abandoned opencast coal pits (OCPs) of Raniganj-Asansol coal field area are the important water resource of the area. The present study is proposed to establish the mathematical correlation and changing pattern of these parameters along with the depths of OCP water column and the seasonal variations. 25

26 2. Materials and Methods The experimental Opencast Coal Pits (OCPs) or so-called lakes, locally called khadans, a potential source of water reserve at Raniganj-Asansol Coalfield Areas (RCF Areas), situated in the Bankola Colliery under the Bankola area of Eastern Coal field Limited in Burdwan district of West Bengal, India. A special type of graduated glass bottle water sampler was used to collect the water samples at desired depth of the OCP. The water samples were collected at a regular interval of 10 ft (3.048 m) in bottles from surface up to 60 ft depth and defined as U0, U1, U2, U3, U4, U5 and U6 with gradual depths. The following parameters like DO, BOD and COD of different depth as per stratification were measured by following the methods of APHA (2005). Total organic carbon (TOC), total carbon (TC) and inorganic carbon (IC) were estimated by TOC analyzer Shimadzu TOC-V CPH. 3. Results and Discussions Results of the limnological parameters have been represented in Table 1. Regression equations between limnological among parameters are mentioned in the Table 2. Interrelationship among the parameters and different forms of carbon and their exchange pathway in an aquatic ecosystem has been represented in Figure 1-7. In the present study dissolved oxygen (DO) concentration (3.914 ± mg/l) showed a regular decrease in postmonsoon and monsoon while there is a mixing in thermocline zone in summer season (Figure 1). DO concentration showed a slight decrease primarily (U1) and then it maintained its regularity throughout the water column. BOD concentration (1.350 to mg/l) showed more or less regular increase with depth except U1 in summer and U3 in monsoon (Figure 2). COD always indicated a regular increasing pattern throughout the water column in every season (Figure 3). There was a decreasing pattern in TOC value (1.244 ± mg/l) in monsoon and summer but it increased in case of winter. In case of postmonsoon the values showed more or less decreasing pattern (Figure 4). Though the total inorganic carbon (29.95 to mg/l) and total carbon values ( to mg/l) did not show any regular pattern but it tend to increase in IC in monsoon and in postmonsoon and decreased in winter (Figure 5), whereas, in total carbon value relatively increased in monsoon and postmonsoon (Figure 6). Formation of organic matter in the aquatic ecosystem is not only performed by photosynthesis by green algae and cyanobacteria but also photosynthetic sulphur bacteria (Schwoerbel, 1999; Wetzel, 2001). Total organic carbon (TOC) showed in higher concentration in monsoon season (1.915 mg/l) in the upper layer because of some allochthonous material input occurred through runoff from the side by agricultural lands (Figure 4). The surrounding geological formations release substances that are also carried into the lake as also supported by Jellison et al. (1999). In winter season result showed a little change in TOC concentration throughout the layers (Figure 1) due to the temperature and density of the water column which remain almost the same. A clear stratification is maintained in monsoon and summer seasons in the middle layer (U3-U5) i.e., in thermocline zone, as there is a temperature gradient in pit water column (Boehrer & Schultze 2008) and vertical mixing. In relation to other related parameters, TOC is highly negatively correlated with COD, BOD, total carbon (TC) and inorganic carbon (IC) but positive with DO (Table 1). Dissolved oxygen is required to degrade the organic carbon, so, in the upper layers degradation occurs more rapidly. The concentration of dissolved oxygen is reduced at lower zone i.e, hypolimnion, because rate of gaseous exchange become low. Change of BOD (Figure 2) and COD (Figure 3) exhibit similar changes throughout the water column. In the present study, significant positive change (r = 0.991) occurs between COD and BOD but both are negatively related with dissolved oxygen. TC (Tables 1 and 2) is the sum total of organic and inorganic carbon and positively related with COD (r = 0.868) and BOD (r = 0.928). The DO profile (Figure 1) of the OCP, according to the result revealed that the change of concentration in postmonsoon and monsoon gradually reduced through the water column but there is a very little change in winter season. In summer, it has a clear zone of mixing in thermocline region, but there is a large difference between hypolimnion and epilimnion layers in regard to DO concentration in monsoon and post monsoon seasons. DO illustrates the gross primary productivity and ecosystem respiration as reported by Hanson et al. (2003). In OCP water, inorganic carbon (Figure 5) showed highly negative correlation with TOC but positive with COD, BOD and TC (Table 1). TC (Figure 6) also showed more or less same pattern of concentration throughout the year. Present analysis shows a strong positive correlation with COD, BOD and TC but a weak negative correlation with DO (Table 1). There are two other important factors related to the inorganic carbon concentration of aquatic system i.e., settlement and re-suspension. In the OCP water, phytoplankton, submerged and floating macrophytes and algae are the prime carbon assimilators. Photosynthesis by aquatic plants utilizes carbon dioxide from the water and also releases free oxygen in water which is the major source of oxygen for biological and chemical processes. So, the amount of increased DO concentration is proportional to the rate of photosynthesis which ultimately related to the carbon assimilator or primary producer of the system (Figure 7). Here, the rate of photosynthesis decreased with the depth of the water body because of absence of light; IC concentration increased with depth, being negatively proportional to each other. In the upper layer i.e., in epilimnion oxygen concentration is usually increased in aquatic system through the gas exchange at air-water interface from the atmosphere. This study showed that in monsoon and postmonsoon, DO concentration was gradually decreasing and IC concentration increasing with depth. This oxygen is used directly or indirectly by aquatic organisms of different levels for their respiration. DO level was reduced at lower depth i.e., hypolimnion due to respiration of aquatic organisms, reduced rate of gaseous exchange, and degradation of organic and inorganic carbon into their simpler forms 26

27 by microbes. BOD is the oxygen consumption in water bodies required for TOC degradation, and increased with the depth. COD, is also an associated indicator to consume oxygen for different chemical reactions along with oxygen taken for respiration. In both the conditions, CO 2 is generated from the containing organics, which ultimately increases the inorganic carbon concentration in aquatic medium. Metabolic CO 2 and air CO 2 are dissolved in water and produce carbonate (CO 3 = ) and bicarbonate (HCO 3 - ), resulting into production of inorganic carbon (IC) content in water bodies. These ICs are also taking part to generate the organic carbons. These assimilated and dissolved organic carbons collectively termed as total organic carbons (TOC) and ultimately TOC and IC form the total carbon (TC) concentration in an aquatic system. Buffering capacity of water by carbon dioxide through carbonate and bicarbonate, sometimes must have taken influential role in total carbon concentrations in water. 4. Conclusion The results obtained from this opencast coal mine water body are maintaining a prominent carbon cycle at epilimnion zone throughout the water column which can be otherwise potentially used as a valuable source of water for pisciculture by adopting a special indigenous technique called cage culture. Because at the higher depth as the concentration of the dissolved oxygen is very low which may affect the respiration of the aquatic organisms. The schematic diagram represents the source, labile forms of carbon in a coal mine aquatic system and also their pathway of assimilation through the organisms. The total carbon concentration remains in equilibrium stage throughout the column where inflow occurs from both atmospheric exchanges as well as runoff from terrestrial system but outflow in gaseous exchange. 5. Acknowledgements The authors are grateful to the Head, Department of Environmental Science, The University of Burdwan, West Bengal, India. The authors are also grateful to West Bengal Pollution Control Board; Paribesh Bhavan, India for rendering helps in the analysis of TC, IC and TOC. 6. Reference APHA. Standard methods for the examination of water and wastewater. (2005). 21st. Ed. American Public Health Association, the American Water Works Association and the Water Pollution ControlFederation (APHA, AWWA, WPCF), Washington, D. C., USA. Boehrer B., Schultze M. (2008). Stratification of lakes. Rev. Geophys 46, RG2005, doi: /2006rg Cole J.J., Prairie Y.T., Caraco N.F., McDowell W.H., Tranvik L.J., Striegl R.G., Duarte C.M., Kortelainen P., Downing J.A., Middelburg J.J., Melack J. (2007). Plumbing the global carbon cycle: integrating inland waters into the terrestrial carbon budget. Ecosystems 10, Cre taux J.F., Kouraev A.V., Papa F., Berge -Nguyen M., Cazenave A., Aladin N., Plotnikov I.S. (2005). Water balance of the Big Aral Sea from satellite remote sensing and in situ observations. J Great Lakes Res 31(4), Findlay S., Strayer D., Goumbala C., Gould K. (1993). Metabolism of streamwater dissolved organic carbon in the shallow hyporheic zone. Limnol Oceanogr 38, Hanson P.C., Bade D.L., Carpenter S.R., Kratz T.K. (2003). Lake metabolism: relationships with dissolved organic carbon and phosphorus. Limnology and oceanography 48, Hedin L.O., von Fischer J.C., Ostrom N.E., Kennedy B.P., Brown M.G., Robertson G.P. (1998). Thermodynamic constraints on nitrogen transformations and other biogeochemical processes at soil stream interfaces. Ecology Jellison R., Macintyre S., Millero F.J. (1999). Density and conductivity properties of Na-CO 3 -Cl-SO 4 brine from Monolake, California, USA. int J Salt lake; res 8, doi: /bf Jones J.B., Jr Fisher S.G., Grimm N.B. (1995). Vertical hydrologic exchange and ecosystem metabolism in a sonoran desert stream. Ecology 76, Kru ger B., Kadler A., Fischer M. (2002) The creation of post-mining landscapes of lignite mining in the New Federal States, Surface Mining-Braunkohle and other minerals. 54, Miller G.C, Lyons W.B., Davis A. (1996) Understanding pit water quality. Environ. Sci Technol 30, Reddy K.R., Delaune R.D. (2008). Biogeochemistry of wetlands science and application. Crc press, Boca Raton, FL. Schwoerbel J. (1999). einfu hrung in die limnologie, 6th edn. gustav fischer, stuttgart, Germany. Vervier P., Dobson M., Pinay G. (1993). Role of interaction zones between surface and ground waters in doc transport and processing: considerations for river restoration. Freshwat Biol, 29, Walling D.E. (2006). Human impact on land-ocean sediment transfer by the world s rivers. Geomorphology 79, Wetzel R.G. (2001). limnology: lake and river ecosystems, 3rd edn. Academic. san diego, calif. 27

28 Table: 1. Descriptive statistics of the limnological parameters and their Correlation Variable Mean sd SE Mean Min Max COD BOD DO TC IC Descriptive statistics Correlation BOD COD DO TOC TC IC sd = Standard deviation, SE Mean = Standard error of mean, Min = minimum, Max = maximum Table: 2. Regression equations between limnological parameters Regression equations R-Sq (%) log (COD)= log(bod) 95.7 log (BOD) = log (TC) 85.1 log (BOD) = log (IC) 86.6 log (TC) = log (IC) 99.9 log (COD) = log (TOC) 95.7 log (BOD) = log (TOC) 97.8 log (TOC) = log (TC) 83.9 log (TOC) = log (IC)

29 Figure 1. Analysis of DO as per Figure 2. Analysis of BOD as per Figure 3. Analysis of COD as per season and depth season and depth season and depth Figure 4. Analysis of TOC as per Figure 5. Analysis of BOD as per Figure 6. Analysis of COD as per season and depth season and depth season and depth Figure 7. Interrelationship among the different forms of carbon and their exchange pathway in an aquatic ecosystem 29

30 TRANSCRIPTION RESPONSES IN THE KILLIFISH (Aphanius dispar) DURING LONG-TERM EXPOSURE TO HIGH TEMPERATURE OF HOT SPRING Akbarzadeh A. 1,2*, Leder E, 2 1 Department of Fisheries, Faculty of Marine and Atmospheric Sciences, University of Hormozgan, Bandar Abbas, Iran. P.O. Box: Department of Biology, Division of Genetics and Physiology, University of Turku, Turku, Finland. ABSTRACT In the present study, we investigated the hypothesis that adaptation of killifish to thermal extreme of hot spring is associated with the regulation of genes involved in stress response and metabolic regulation. We exposed a killifish species Aphanius dispar to long term (44 days) thermal regime of hot spring environment (37-40 C) and examined the liver mrna expression of heat shock proteins (Hsp70, Hsp90ɑ, Hsp90b), glucokinase (gck), and high mobility group b1 (hmgb1) protein using quantitative real-time PCR. Our results showed that the transcripts of Hsp70 and Hsp90b were mildly induced (>twofold) the time when temperature reached to C, while the transcripts of other homologous encoding for Hsp90a was strongly induced (17 fold increase). After 44 days of keeping in extreme, the levels of Hsp90ɑ was dramatically up regulated, so that it was approximately 42 foldchange higher than the ambient temperature, but Hsp90b was only two foldchange more upregulated. Our results showed a significant up regulation of hmgb1 (2-fold increase) during the first day of exposure to thermal extreme compared with fish kept at ambient temperature. Moreover, liver gck transcript levels were strongly affected by temperature, so that significant downregulation of gck transcripts was observed at the time when temperature was raised to C (80-fold decrease) and during exposure to long term thermal extreme (56-fold decrease). The preliminary conclusion can be drawn that killifish has hsp90ɑ is likely to be responsible for an adaptive heat shock response during extended exposure to thermal extreme of hot spring environment. Keywords: killifish, thermal extremes, gene expression, heat shock proteins * Corresponding author: Akbarzadeh Arash (akbarzadeh@ut.ac.ir) 1. Introduction With reference to temperature, thermal waters are normally considered as those having temperatures sufficiently high so that members of the general freshwater fauna do not usually live in them. Nevertheless, some fish species have successfully survived and acclimated to the high temperature of hot springs. The presence of a few cyprinid, cyprinodont and cichilid species in the hot spring environment (Coad, 1980; Piazzini et al., 2010; Tutar and Okan, 2012) seems to be a remarkable phenomenon as prolonged exposure to such thermal extremes may result in rapid deterioration in physiologic state (LeMoullac and Haffner, 2000). Because these thermal effects have such major consequences for cellular function, fish in thermal waters are assumed to manifest extensive evolutionary adaptations that establish distinct thermal optima and limits for physiological function, as well as the capacity for altering the phenotype in response to constant thermal extremes that could vastly impact various life-history stages (e.g. early development, reproduction). Thermal acclimation responses in teleosts commonly result in gene expression changes at a large number of loci associated with protein processing, transcription and translation (Narum et al., 2013). Current molecular and genomic tools provide the opportunity to investigate the heat shock response of fishes from varying thermal regimes and link that information with adaptive regions of the genome that may be under selection. It is known that changes in expression of the genes involved in protein homeostasis, cell cycle control, cytoskeletal reorganization, cell growth and proliferation, and signal transduction, as well as several other categories have been associated with thermal acclimation in fish (e.g. Podrabsky and Somero, 2004; Buckley et al., 2006). Specifically, the heat-shock protein (HSP) response has been demonstrated to be one of the most important cellular mechanisms to prevent the damaging effects of thermal cellular 30

31 stress (Feige et al. 1996). Hsp70 and Hsp90 are known to be the most strongly upregulated genes in response to chronic high temperatures in fish (Podrabsky and Somero, 2004). The regulatory factors and signaling pathways shaping metabolism and mitochondrial functioning may be also important for thermal adaptation or sensitivity (Windisch et al., 2011). The expression of genes involved in regulating metabolism may be expected to respond to heat shock, as cellular energy pools are accessed to fuel stress response and repair mechanisms. In south of Iran, there exists a geothermal hot spring, called Geno hot spring where a killifish species Aphanius ginaonis occurs (Reichenbacher et al., 2009). A. ginaonis is exclusive to the Geno hot spring, where it is the only native species (Coad, 2000). It has been stated that A. ginaonis is the sister taxon to a geographically close A. dispar population from Hormozgan, Iran in which was introduced to this stream many years ago (Hrbek and Meyer, 2003). According to our monthly measurements, the water temperature of this hot spring is almost in the range of C throughout the year. Despite the importance of hot springs as unique environments with constant thermal extremes beyond the tolerance of many fish species, little is known about the adaptation of fish to such high temperature in this ecosystem. Because of its ability to thrive in this high temperature environment, we reasoned that killifish would be an excellent study organism for examining the adaptive responses of fish to extreme environmental conditions of hot springs. Here, in an effort to elucidate the mechanisms that may be responsible for the capacities of killifish to cope so successfully with thermal extremes similar to hot springs, we exposed A. dispar to long term thermal regime similar to Geno hot spring environment and studied and compared the profile of the expression of some candidate genes associated with stress response and metabolic regulation. heat shock proteins (Hsp70, Hsp90ɑ, Hsp90b), glucokinase (gck), and high mobility group b1 (hmgb1) protein have been chosen as genes in which the transcription changes were studied. 2. Material and methods The procedure of sampling and common garden experiments has earlier been described by Akbarzadeh et al (2014). Briefly, the samples of killifish were collected from adjacent rivers near to the Geno hot spring Hormozgan, Iran using a small seine net in November Fish were transferred to the Aquaculture laboratory of University of Hormozgan, where they were held in 300-l circular tanks at ambient temperature (24 C). Following a week of holding at ambient temperature, 114 uniform sized animals were equally distributed between two groups including a control group (24 C) and a treatment group (37-40 C) with each replicated three times in 100 L tanks with a stocking density of 25 individuals/100 L water. Treatment tanks were raised gradually to C over the course of seven days at a rate of 2 C per day. Once at this temperature, 10 individuals were sampled and killed with an overdose of anesthetic (MS-222 tricaine methanesulfonate) and the liver tissue was dissected from each fish and immediately deep-frozen in liquid nitrogen, and stored in a 80 C freezer until RNA extraction. This temperature regime was designed to mimic the natural temperature experienced daily by A. ginaonis in Geno hot spring. The animals in control and thermal tanks were then maintained for a further 44 days. After 44 days, 10 specimens of killifish from both stressed exposed and control groups were sampled as described before. Prior to the tissue sampling, the length and weight of each fish were determined and the growth parameters of both control and thermal stress treatments were measured (Akbarzadeh et al., 2014). For RNA preparation, 100 mg portion of liver tissue from six individual (n = 6) under each of the thermal conditions was cut and homogenized in a Qiagen Tissue Lyser using 1 ml Tri Reagent TRI Reagent (Ambion, Austin, TX, USA), treated with DNase (Promega, USA) in accordance with the manufacturers instructions. RNA quantification was carried out with a NanoDrop ND-1000 Spectrophotometer (Thermo Scientific, Wilmington, DE, USA) reading at 260/280 nm and the quality of the RNA checked with the Bioanalyzer 2100 using the 6000 Nano LabChip kit (Agilent Technologies). All RNA integrity number values obtained were >8, indicative of excellent RNA integrity and quality. One microgram of total RNA was used to synthesize first-strand cdnas using iscript cdna Synthesis kit (BioRad) for RT-PCR, following the manufacturer s instructions and a mixture of oligo-dt as primer. The qpcr primers for Hsp70, Hsp90ɑ, Hsp90b, gck, hmgb1, actin beta (ACTB) and elongation factor alpha (EF1A) were designed based on the sequences from killifish species and conserved regions of the teleost sequences available in the GenBank. Multiple qpcr primer combinations were designed for each gene using Primer3 and tested (Table 1). The specificity and size of the amplicons obtained with primer pairs was checked on a 1.5% agarose gel. The 31

32 fragments were sequenced using the ABI 3130 Genetic Analyzer (Applied Biosystems). The identities of the sequences were verified by BLAST search against the GenBank database ( Quantitative real-time PCR was run on QuantStudio 12K Flex Real-Time PCR System (Applied Biosystems) with itaq Universal SYBR Green supermix (2x) (BioRad) and all primers at 100 nm using standard protocol: initial denaturation at 95 C for 10 min, 40 cycles of denaturation at 95 C for 15 s and annealing/ extension at 60 C for 1 min. All reactions were run in triplicate. The mrna expression levels of genes were recorded as Ct values that corresponded to the number of cycles at which the fluorescence signal can be detected above a threshold value. Baseline and threshold for Ct calculation were set automatically using the QuantStudio 12K Flex Software v1.2.1 (Applied Biosystems). Conversion of Ct values to relative quantities was done using standard curves. Standard curves were constructed from dilution series of pooled cdna (including five dilutions from 1/10 to 1/1000), and the PCR efficiency was calculated using the equation E% = (10 1/slope _ 1) 100. Data of each target gene were then normalized with the geometric mean of the two reference genes. Differences in normalized mrna expression levels of Hsp70, Hsp90ɑ, Hsp90b, gck and hmgb1 between control and treatment groups were analyzed by a one-way analysis of variance (ANOVA), followed by a Tukey s HSD post hoc analysis for multiple comparisons. Differences were considered statistically significant at P < SPSS software (version 18.0) was used for statistical analysis. Table 1. Primers used for qpcr reference and target genes in the present study. Gene qpcr primers, forward/reverse Amplicon (bp) hsp70 hsp90a hsp90b hmgb1 Gck ACTB EF1A TCTTGGTGGTGGCACTTTTGA GCCCTCTTGTTGTCTCTGATGT GGTGGCCAACTCTGCCTT CTCGTCCTCAGGCAGCTC CTACCACAGCTCCCAGTCTG GCTCGACGAATGCAGAGTT GACCACCGTCTGCATTCTTC CCTTGTCATATTTCTCCTTCAGC GCACTGGCTGTAATGCTTGTT ACTCCGTGTTCACACACATCC CCCACCAGAGCGTAAATACTC CTCCTGCTTGCTGATCCACA ACCACGAGTCTCTACCCGA GCCTTGGGTGGGTCGTTC

33 3. Results There was a significant increase in hsp70 mrna expression at the time when temperature was raised to C. After 44 days at this temperature, the level of hsp70 transcripts remained higher compared with control group (Figure 1). However, in treatment d44t, hsp70 transcripts decrease but it was not statistically significant. The transcription of both isoforms of Hsp90 (Hsp90a and Hsp90b) was constant during the 44 days of our experiment on fish kept at normal temperature. There was a significant increase in Hsp90a in fish (17 fold increase) at the time temperature reached to C. After 44 days, the levels of hsp90ɑ was strongly up regulated during exposure to long term thermal extreme so that it was approximately 42 foldchange higher than the ambient temperature (Figure 1). In thermal stress temperature, Hsp90b was significantly up regulated at the time when temperature was raised to C and after 44 days at this temperature. However, the amount of increase in Hsp90b levels was not as high as Hsp90a and it was only about two foldchange more upregulated (Figure 1). In fish exposed to the temperature of hot spring, a significant increase (2-fold increase) was found in the hmgb1 mrna levels when compared with control group. After 44 days, hmgb1 transcripts were elevated significantly in both fish kept at ambient temperature and C compared with control group at the first day of exposure. There was a significant decrease (80-fold increase) in gck mrna expression at the time when temperature was raised to C. After 44 days of the beginning of our experiment, gck transcripts were significantly increased (8-fold increase) in fish kept at ambient temperature. Moreover, gck mrna expression was dramatically down regulated during exposure to long term thermal extreme so that it was approximately 56 foldchange lower than the ambient temperature (Figure 2). 4. Discussion Very little currently is known about the molecular mechanisms underlying the adaptation of organisms to extreme environmental conditions such as geothermal springs. Some killifish species could successfully acclimate to extreme environmental conditions of hot spring. So, we reasoned that killifish would be an excellent study organism for examining the adaptive responses of fish to extreme environmental conditions. In the present study, we exposed a killifish species A. dispar to constant thermal regime of hot spring environment (37-40 C) and examined the liver mrna expression of some candidate genes involved in heat shock response and metabolism. The results of the current study in killifish demonstrates that a portion of individual fish may acclimate to thermal extremes and survive, but also that experimental fish have evolved an adaptive heat shock response in the environment similar to the temperature of hot spring. Overall, results of our molecular data showed that the mrna expression of Hsp70, Hsp90a, Hsp90b and hmgb1 were significantly upregulated as soon as the fish exposed to On the contrary, the transcripts of gck were dramatically declined during which fish exposed to the thermal regime of hot spring. 33

34 Figure 1. Relative mrna expression levels (means ± SE) of hsp70, hsp90a, hsp90b and hmgb1 in killifish kept in thermal extreme. d1c: Control day 1, d1t: Thermal day 1, d44c: Control day 44, d44t: Thermal day 44. Treatments with different letters are significantly different at P < Figure 2. Relative mrna expression levels (means ± SE) of gck in killifish kept in thermal extreme. d1c: Control day 1, d1t: Thermal day 1, d44c: Control day 44, d44t: Thermal day 44. Treatments with different letters are significantly different at P < Our results showed that heat-shock proteins Hsp70 and one isoform of Hsp90 (Hsp90b) were mildly induced (>twofold) by elevated temperatures, while the transcripts of other homologous encoding for Hsp90a was strongly induced when fish exposed to long term thermal regime of hot spring. If the mrna levels indicate differences in functionally active proteins, the correlation between HSP expression and temperature elevation might reflect a direct role of the heat shock proteins in thermal tolerance in hot spring by killifish. The HSP response has been demonstrated to be one of the most important cellular mechanisms to prevent the damaging effects of thermal cellular stress (Feige et al. 1996; Sorensen, 2010). HSPs are molecular chaperones which are involved in maintaining regular cellular functions with a crucial role in protein folding, unfolding, aggregation, degradation, and transport (Sorensen et al. 2003). The role of HSPs in cell protection and as stress markers has been well-recognized in many organisms, although considerable variability in the HSPs stress response was also observed in some marine organisms depend on species, tissue, HSP 34

35 family, developmental stage, and stressor (Iwama et al. 2004; Rosic et al., 2011). Both Hsp70 and Hsp90 are known to be the most strongly upregulated genes in response to chronic high temperatures in fish (e.g. Podrabsky and Somero, 2004; Buckley et al., 2006). Our results in killifish showed that one isoform of hsp90 (hsp90a) is transcriptionally more regulated during which fish maintained in thermal extreme, whereas the transcription of the other isoform was mildly induced. HSP90α, is an abundant, well conserved cytosolic protein that accounts for 1 2% of all cellular proteins in most cells under basal, non stress conditions and the levels increase in response to heat stress and other proteotoxic insults (Bagatell et al., 2000). HSP90α plays a key role in the response of cells to stress and is thought to be important in buffering cells against the effects of mutation (Maloney and Workman, 2002; Padmini and Rani, 2009). Consistent with these, our results provide evidence that keeping in thermal extreme differentially modulate HSP90α expression in fish hepatocytes. Our results showed a significant up regulation of hmgb1 gene during the first day of exposure to thermal extreme compared with fish kept at ambient temperature. However, unlike the thermal treatment, the transcript levels for hmgb1 significantly increased after keeping at constant 25 C for 44 days. These results provide further evidence that this gene is involved in temperature responses. It has been known that HMGB1 binds DNAs and functions as a DNA chaperone, modulating multiple processes in chromatin, including transcription, replication, recombination, DNA repair, and genomic stability (Stros, 2010; Tsan, 2011). A study of transcriptome changes in the liver of the eurythermal killifish, Australofundulus limnaeus during thermal acclimation (Podrabsky and Somero 2004) has revealed a role for HMGB1 as a putative global regulator of transcription in response to temperature (Podrabsky and Somero, 2004). According to Podrabsky and Somero (2004), HMGB1 mrna content increases in response to a temperature decrease (either diurnal or seasonal) to effectively counteract the tendency of DNA to assume a more closed configuration at lower temperatures. HMGB1 promotes transcription, not in a global non-targeted fashion but by maintaining an open DNA configuration of transcription factors and thereby allowing sequence-specific access to gene promoter regions (Roelofs, et al., 2010). In this study, we also found that gck mrna expression was dramatically declined during which fish exposed to thermal stress. Our results indicate that liver gck transcript levels were strongly affected by temperature. The remarkable downregulation of gck during keeping in thermal extreme in killifish is likely to be associated with the concentration of glucose. Glucokinase is an enzyme that catalyzes the phosphorylation of glucose to glucose 6-phosphate and is mainly expressed in liver and pancreatic α-cells, where it plays a key role in glucose metabolism (Caseras et al., 2000). G6P, the product of glucokinase, is the principal substrate of glycogen synthesis, and glucokinase has a close functional and regulatory association with glycogen synthesis. When ample glucose is available, glycogen synthesis proceeds at the periphery of the hepatocytes until the cells are replete with glycogen. When killifish held in a high temperature of hot spring, it is possible that hepatic glycogen stores are depleted as a result of this chronic thermal stress. So, higher activities of glycolytic enzymes after exposure to high temperature may be necessary to cope with the increased energy demand of the liver, including enhanced gluconeogenesis, which is required to re-establish homeostasis. On the contrary, the activity of enzymes involved in glycogen synthesis like glucokinase might be decreased under thermal stress. Therefore, the remarkable downregulation of glucokinase in hepatocites of killifish under thermal extreme can be associated with a decrease in glucose 6-phosphate activity and depletion in glycogen synthesis. In a killifish, species A. limnaeus the levels of gck were also reduced during chronic thermal acclimation (Podrabsky and Somero 2004). In another study, hepatic Glucokinase showed different pattern of mrna expression in two populations of Fundulus heteroclitus in response to handling stress. In one population, glucokinase mrna increased significantly in response to stress, while in other population glucokinase mrna declined (Picard and Schulte, 2004). References Akbarzadeh A., Mosayebi A.N., Noori A., Parto P., Asadi M., Yousefzadi M., Dehghani H., Kamrani E., (2014). Responses of killifish (Aphanius dispar) to long-term exposure to elevated temperatures: growth, survival and microstructure of gill and heart tissues. Marine and Freshwater Behaviour and Physiology / Bagatell R., Paine-Murrieta G.D., Taylor C.W., Puccini E.J., Acing S., Benjamin I.J., Whitesell L. (2000). Induction of a heat shock factor1-dependent stress response alters the cytotoxic activity of HSP90-binding agents. Clin. Cancer Res. 6,

36 Buckley B.A., Gracey A.W., Somero G.N. (2006). The cellular response to heat stress in the goby Gillichthys mirabilis: a cdna microarray and protein-level analysis. Journal of Experimental Biology 209, Caseras A., Meton I., Fernandez F., Baanante I.V. (2000). Glucokinase gene expression is nutritionally regulated in liver of gilthead sea bream (Sparus aurata). Biochimica et Biophysica Acta 1493, Coad B.W. (1980). A re-description of Aphanius ginaonis (Holly, 1929) from southern Iran (Osteichthyes: Cyprinodontiformes). Journal of Natural History 14, Coad B.W., (2000). Distribution of Aphanius species in Iran. Journal of the American Killifish Association 33, Feige U., Morimoto R.I., Yahara I., Polla B.S. (1996). Stress-inducible cellular responses. Birkhauser Verlag, Basel, Switzerland. Hrbek T., Meyer A. (2003). Closing of the Tethys Sea and the phylogeny of Eurasian killifishes (Cyprinodontiformes: Cyprinodontidae). Journal of Evolutionary Biology 16, Iwama G.K., Afonso L.O.B., Todgham A., Ackerman P., Nakano K. (2004). Are Hsp suitable for indicating stressed states in fish? Journal of Experimental Biology. 207, LeMoullac G., Haffner P. (2000). Environmental factors affecting immune responses in Crustacea. Acluaculture 191, Maloney A., Workman P. (2002). HSP90 as a new therapeutic target for cancer therapy: the story unfolds. Expert Opin. Biol. Ther. 2, Narum S.R., Campbell N.R., Meyer K.A., Miller M.R., Hardy R.W. (2013). Thermal adaptation and acclimation of ectotherms from differing aquatic climates. Molecular Ecology 22, Padmini E., Rani M.U. (2009). Seasonal influence on heat shock protein 90α and heat shock factor 1 expression during oxidative stress in fish hepatocytes from polluted estuary. Journal of Experimental Marine Biology and Ecology 372, 1 8. Podrabsky J.E., Somero G.N. (2004). Changes in gene expression associated with acclimation to constant temperatures and fluctuating daily temperatures in an annual killifish Austrofundulus limnaeus. Journal of Experimental Biology 207, Piazzini S.,Lori E., Favilli, L., Cianfanelli S., Vanni S., Manganelli G. (2010). A tropical fish community in thermal waters of southern Tuscany. Biological Invasions 12, Picard D.J., Schulte P.M. (2004). Variation in gene expression in response to stress in two populations of Fundulus heteroclitus. Comparative Biochemistry and Physiology Part A 137, Reichenbacher B., Kamrani E., Esmaeili H.R., Teimori A. (2009). The endangered cyprinodont Aphanius ginaonis (Holly, 1929) from southern Iran is a valid species: evidence from otolith morphology. Environmental Biology of Fishes 86, Roelofs D., Morgan J., Sturzenbaum S. (2010). The significance of genome-wide transcriptional regulation in the evolution of stress tolerance. Evol Ecol 24, Rosic N.N., Pernice M., Dove S., Dunn S., Hoegh-Guldberg O. (2011). Gene expression profiles of cytosolic heat shock proteins Hsp70 and Hsp90 from symbiotic dinoflagellates in response to thermal stress: possible implications for coral bleaching. Cell Stress Chaperones 16, Sorensen J.G., Kristensen T.N. Loeschcke, V. (2003). The evolutionary and ecological role of heat shock proteins. Ecol. Lett. 6, Stros M. (2010). HMGB proteins: interactions with DNA and chromatin. Biochim Biophys. Acta 1799, Tsan M. F. (2001). Heat shock proteins and high mobility group box 1 protein lack cytokine function. Journal of Leukocyte Biology 89, Tutar Y., Okan S. (2012). Heat shock protein 70 purification and characterization from Cyprinion macrastomus macrastomus and Garra rufa obtusa. Journal of Thermal Biology 37, Windisch H.S., Kathöver R., Pörtner H.O., Frickenhaus S., Lucassen M. (2011). Thermal acclimation in Antarctic fish: transcriptomic profiling of metabolic pathways. American Journal of Physiology - Regulatory, Integrative and Comparative Physiology 301, R1453 R1466. akbarzadeh@alumni.ut.ac.ir 36

37 THEMATIC FIELD: AQUACULTURE 37

38 ORAL PRESENTATIONS IN GREEK CONVENTIONAL AND ORGANIC FISH FARMING EFFECTS ON MACROFAUNA COMMUNITIES IN EVOIKOS GULF (LARYMNA) Syvri R. 1*, Neofitou N. 1, Vafidis D. 1, Mente E. 1, Panagiotaki P. 1, Tziantziou L. 1 1 Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Fytokou str., N. Ionia, Volos, Greece ABSTRACT The effects of conventional and organic fish farming on macrofauna communities in Evoikos gulf, in Larymna were investigated. In the area three sampling stations were selected. At each station seasonal sediment samples were collected for analysis of grain-size, organic matter, organic carbon and benthic community parameters. Samples were separated and sorted and benthic community parameters were calculated. The results of statistical comparisons between concentrations of organic matter and organic carbon indicated no significant interaction among stations and seasons (two-way ANOVA), while the one-way ANOVA indicated significant differences between stations. Species diversity and evenness were higher at organic farm station and control station than at conventional farm station. The polychaete Capitella capitata was the most dominant species. The SIMPER analysis indicated that the highest dissimilarity observed between conventional and organic farm stations and the species mainly responsible for the dissimilarity was principally the polychaete C. capitata. The two-way ANOVA showed significant interaction among stations and seasons for all benthic community parameters, except for species number and species richness. Furthermore, one-way ANOVA indicated that the significant differences detected in the biotic data, were spatial for Shannon s diversity index and species evenness. According to the results of this study the conclusion was that the organic farming could reduce the negative effects of aquaculture on macrofauna communities. Key words: Larymna, organic aquaculture, macrofauna. *Corresponding author: Syvri Rafailia (r.sivri@yahoo.gr) 1 ΔΠΗΓΡΑΖ ΤΜΒΑΣΗΚΖ ΚΑΗ ΒΗΟΛΟΓΗΚΖ ΤΓΑΣΟΚΑΛΛΗΔΡΓΔΗΑ ΣΟ ΜΑΚΡΟΕΧΟΒΔΝΘΟ ΣΖΝ ΠΔΡΗΟΥΖ ΣΖ ΛΑΡΤΜΝΑ πβξή Ρ. 1*, Νενθχηνπ Ν. 1, Βαθείδεο Γ. 1, Μεληέ Δ. 1, Παλαγησηάθε Π. 1, Σδηάληδηνπ Λ. 1 Σιήια Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ, πμθή Γεςπμκζηχκ Δπζζηδιχκ, Πακεπζζηήιζμ Θεζζαθίαξ, Οδυξ Φοηυημο, Ν. Ηςκία, 38446, Βυθμξ, Δθθάδα ΠΔΡΗΛΖΦΖ Με ζημπυ ηδκ εηηίιδζδ ηδξ επίδναζδξ ηδξ ζοιααηζηήξ ηαζ αζμθμβζηήξ οδαημηαθθζένβεζαξ ζημ ιαηνμγςμαέκεμξ ζηδκ πενζμπή ηδξ Λάνοικαξ, επζθέπεδηακ ηνεζξ δεζβιαημθδπηζημί ζηαειμί, απυ ημοξ μπμίμοξ θήθεδηακ επμπζηά δείβιαηα ζγήιαημξ βζα ημκ πνμζδζμνζζιυ ηδξ ημηημιεηνζηήξ ζφζηαζδξ, ημο μνβακζημφ οθζημφ, ημο μνβακζημφ άκεναηα ηαζ ημο ιαηνμγςμαέκεμοξ. Έβζκε δζαπςνζζιυξ ηαζ ηαλζκυιδζδ ηςκ μνβακζζιχκ ημο ιαηνμγςμαέκεμοξ ηαζ εηηίιδζδ ηδξ ηαηάζηαζδξ ηςκ εζδχκ ιε μζημθμβζημφξ δείηηεξ. Ζ πμθοπαναβμκηζηή ακάθοζδ δζαηφιακζδξ έδεζλε ιδ ζδιακηζηή αθθδθεπίδναζδ ιεηαλφ ζηαειχκ ηαζ επμπχκ ηυζμ βζα ημ μνβακζηυ οθζηυ υζμ ηαζ βζα ημκ μνβακζηυ άκεναηα, εκχ δ ιμκμπαναβμκηζηή ακάθοζδ δζαηφιακζδξ έδεζλε υηζ οπάνπμοκ ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ ιεηαλφ ηςκ ζηαειχκ. Ο ζηαειυξ εθέβπμο ηαζ μ ζηαειυξ ηδξ αζμθμβζηήξ εηηνμθήξ πανμοζζάγμοκ ιεβαθφηενδ πμζηζθμιμνθία εζδχκ ηαζ είκαζ πζμ μιμζμβεκείξ υζμκ αθμνά ηδ ιαηνμγςμαεκεζηή ημοξ ζφζηαζδ, ζε ζπέζδ ιε ημ ζηαειυ ηδξ ζοιααηζηήξ εηηνμθήξ. Δπζηναηέζηενμ είδμξ είκαζ μ πμθφπαζημξ Capitella capitata. φιθςκα ιε ηδκ ακάθοζδ πμζμζημφ μιμζυηδηαξ ηςκ 38

39 ιαηνμγςμαεκεζηχκ εζδχκ ημ ορδθυηενμ πμζμζηυ ακμιμζυηδηαξ παναηδνείηαζ ιεηαλφ ηςκ ζηαειχκ ηδξ ζοιααηζηήξ ηαζ αζμθμβζηήξ εηηνμθήξ ηαζ μθείθεηαζ ηονίςξ ζηδκ πανμοζία ημο είδμοξ C. capitata. Ζ πμθοπαναβμκηζηή ακάθοζδ δζαηφιακζδξ ηςκ δζαθυνςκ παναηηδνζζηζηχκ ημο ιαηνμγςμαέκεμοξ έδεζλε ζδιακηζηή αθθδθεπίδναζδ ιεηαλφ ζηαειχκ ηαζ επμπχκ βζα υθεξ ηζξ παναιέηνμοξ, εηηυξ απυ ημκ ανζειυ ηςκ εζδχκ ηαζ ημ δείηηδ αθεμκίαξ. Ζ ιμκμπαναβμκηζηή ακάθοζδ δζαηφιακζδξ έδεζλε υηζ μζ δζαθμνέξ πμο παναηδνμφκηαζ ζημοξ δείηηεξ πμζηζθυηδηαξ ηαζ μιμζμιμνθίαξ είκαζ πςνζηέξ. Σα απμηεθέζιαηα ηδξ πανμφζαξ ένεοκαξ δείπκμοκ υηζ μ ααειυξ επίδναζδξ ηδξ αζμθμβζηήξ οδαημηαθθζένβεζαξ ζημ ιαηνμγςμαέκεμξ είκαζ ιζηνυηενμξ απυ αοηυκ ηδξ ζοιααηζηήξ. Λέξειρ κλειδιά: Λάξπκλα, βηνινγηθή πδαηνθαιιηέξγεηα, καθξνδσνβέλζνο. *οββναθέαξ επζημζκςκίαξ: οανή Ραθαδθία 1. Δηζαγσγή Ζ ναβδαία ακάπηολδ ηςκ οδαημηαθθζενβεζχκ ηζξ ηεθεοηαίεξ δεηαεηίεξ έπεζ πνμηαθέζεζ ζε ανηεηέξ πενζπηχζεζξ έκημκμ πνμαθδιαηζζιυ υζμκ αθμνά ηδκ επίδναζδ ημοξ ζημ πενζαάθθμκ. Ζ πθέμκ δζαδεδμιέκδ επίδναζδ ηςκ ζπεομηαθθζενβεζχκ αθμνά ημκ μνβακζηυ ειπθμοηζζιυ ηςκ ζγδιάηςκ (Karakassis et al. 2000). Σμ ορδθυ πμζμζηυ ημο μνβακζημφ οθζημφ ζημ ίγδια ιπμνεί κα επδνεάζεζ άιεζα ηδ ζφκεεζδ ηαζ ηα παναηηδνζζηζηά ηςκ αεκεζηχκ ημζκμηήηςκ (Klaoudatos et al. 2006, Yucel-Gier et al. 2007). Πμθθέξ ένεοκεξ έπμοκ δζελαπεεί ζπεηζηά ιε ηδκ επίδναζδ ηςκ ζπεομηαθθζενβεζχκ ζημ ιαηνμγςμαέκεμξ, αθμφ εεςνείηαζ ςξ έκαξ απυ ημοξ πζμ εοαίζεδημοξ δείηηεξ πενζααθθμκηζηχκ αθθαβχκ (Bilyard 1987). ηζξ πενζζζυηενεξ πενζπηχζεζξ έπεζ ηαηαβναθεί ιζα επζηνάηδζδ ηαζνμζημπζηχκ ηαζ ακεεηηζηχκ ζηδ νφπακζδ εζδχκ (Weston 1990). Ζ αζμθμβζηή εηηνμθή ζημκ ηθάδμ ηςκ οδαημηαθθζενβεζχκ απμηεθεί ιζα ζπεηζηά κέα ιέεμδμ, δ μπμία δδιζμονβήεδηε απυ ημ εκδζαθένμκ ηςκ ηαηακαθςηχκ βζα γδηήιαηα οβείαξ, αζθάθεζαξ ηςκ ηνμθίιςκ ηαζ οπμαάειζζδξ ημο πενζαάθθμκημξ. Σμ ζπεηζηά ιζηνυ πνμκζηυ δζάζηδια πμο εθανιυγεηαζ δ αζμθμβζηή οδαημηαθθζένβεζα δεκ έπεζ δχζεζ ηδ δοκαηυηαηα δζελαβςβήξ εκδεθεπμφξ ένεοκαξ υζμκ αθμνά ηζξ επζπηχζεζξ ηδξ ζημ πενζαάθθμκ, ζε ακηίεεζδ ιε ηδ ζοιααηζηή δ μπμία έπεζ ιεθεηδεεί βζα πμθθέξ δεηαεηίεξ. Με ζημπυ ηδκ εηηίιδζδ ηδξ επίδναζδξ ηδξ ζοιααηζηήξ ηαζ αζμθμβζηήξ οδαημηαθθζένβεζαξ ζημ ιαηνμγςμαέκεμξ ζοθθέπεδηακ δείβιαηα ζγήιαημξ απυ ηδκ πενζμπή ηδξ Λάνοικαξ. 2. Τιηθά θαη Μέζνδνη ηδκ πενζμπή ηδξ Λάνοικαξ ημο αυνεζμο Δοαμσημφ ηυθπμο, ζε ιμκάδα εηηνμθήξ ηζζπμφναξ (Sparus aurata) ηαζ θααναηζμφ (Dicentrarchus labrax) δζελήπεδ ιζα πεζναιαηζηή αζμθμβζηή εηηνμθή ηζζπμφναξ ζηα πθαίζζα ενεοκδηζημφ πνμβνάιιαημξ. Υνδζζιμπμζήεδηακ δομ ιέεμδμζ εηηνμθήξ: δ ζοιααηζηή (Beveridge 2004) ηαζ δ αζμθμβζηή (Mente et al. 2012). Γζα ηδ δζελαβςβή ηδξ ένεοκαξ επζθέπεδηακ ηνείξ δεζβιαημθδπηζημί ζηαειμί. Οζ ζηαειμί S1 ηαζ S2 ςξ ηφνζμζ ζηαειμί ιεηνήζεςκ ηδξ ηάεε εηηνμθήξ (ζοιααηζηήξ ηαζ αζμθμβζηήξ) ηαζ μ S3 ςξ ζηαειυξ εθέβπμο. Δπμπζηά δείβιαηα ζγήιαημξ θήθεδηακ βζα ημκ πνμζδζμνζζιυ ημο μνβακζημφ οθζημφ, ημο μνβακζημφ άκεναηα ηαζ ημο ιαηνμγςμαέκεμοξ ιε ηδ πνήζδ δεζβιαημθήπηδ ηφπμο Van Veen (επζθάκεζαξ 0,25m 2 ). Απυ ηάεε ζηαειυ ζοθθέπεδηακ ηνία επακαθδπηζηά δείβιαηα, ηδκ άκμζλδ ηαζ ημ ηαθμηαίνζ ημο Ο πνμζδζμνζζιυξ ηδξ ημηημιεηνζηήξ ζφζηαζδξ έβζκε ζφιθςκα ιε ηδ ιέεμδμ Bouyoucou (1962). Σμ πμζμζηυ ημο μνβακζημφ οθζημφ πνμζδζμνίζεδηε ιεηά ηδκ απμλήνακζδ ηαζ μιμβεκμπμίδζδ, απυ ηδ δζαθμνά αάνμοξ πνζκ ηαζ ιεηά ηδκ ηαφζδ (Byers et al. 1978). Ζ ιέεμδμξ πμο πνδζζιμπμζήεδηε βζα ηδ ιέηνδζδ ημο πμζμζημφ ημο μνβακζημφ άκεναηα ζημ ίγδια ζηδνίγεηαζ ζηδκ οβνή μλείδςζδ ηςκ μνβακζηχκ μοζζχκ ιε δζπνςιζηυ ηάθζμ ηαζ εεζζηυ μλφ (Gaudette et al. 1974). Πνμηεζιέκμο κα εηηζιδεεί δ επίδναζδ ηςκ οδαημηαθθζενβεζχκ ζημ ιαηνμγςμαέκεμξ έβζκε δζαπςνζζιυξ ηαζ ηαλζκυιδζδ ηςκ μνβακζζιχκ ζε πέκηε μιάδεξ: πμθφπαζημζ, βαζηενυπμδα, δίεονα, ηανηζκμεζδή ηαζ δζάθμνα ηαζ εηηίιδζδ ηδξ ηαηάζηαζδξ ηςκ εζδχκ ιε μζημθμβζημφξ δείηηεξ. Ο πνμζδζμνζζιυξ ηςκ μνβακζζιχκ έβζκε ζημ παιδθυηενμ δοκαηυ ηαλζκμιζηυ επίπεδμ (είδμοξ ή βέκμοξ) ιε ηδ πνήζδ ζηενεμζημπίμο ηαζ δζαθυνςκ έβηονςκ ηαλζκμιζηχκ ηθεζδχκ (Fauvel 1923, 1927, Day 1967a, b, Fauchald 1977, D' Angelo & Gargiullo 1978, Ruffo 1982, 1989, 1993). Γζα ηδκ ακμιμζυηδηα ιεηαλφ ηςκ ζηαειχκ έβζκε δ ακάθοζδ ημο πμζμζημφ μιμζυηδηαξ (SIMPER). Με ηδ αμήεεζα ημο δείηηδ μιμζυηδηαξ ηςκ Bray & Curtis (1957), έβζκε μιαδμπμίδζδ ηςκ ζηαειχκ ηδξ πενζμπήξ ένεοκαξ ιε αάζδ ημ ααειυ 39

40 ζοββέκεζαξ ημο ιαηνμγςμαέκεμοξ. Γζα ηδ δζζδζάζηαηδ απεζηυκζζδ ηςκ πςνζηχκ ηαζ πνμκζηχκ δζαθμνχκ ζηδ ζφκεεζδ ηςκ εζδχκ ζημοξ ζηαειμφξ πμο ενεοκήεδηακ ηαηαζηεοάζηδηε δζάβναιια πμθοδζάζηαηδξ δζάηαλδξ (MDS) (Field et al. 1982). Δπίζδξ ηαηαζηεοάζηδηε δζάβναιια αενμζζηζηήξ ηονζανπίαξ ηςκ εζδχκ (K-dominance) ζε ζπέζδ ιε ηδ ιέεμδμ εηηνμθήξ (ζοιααηζηή ηαζ αζμθμβζηή), ζφιθςκα ιε ηδ ιέεμδμ πμο ακαθένεηαζ απυ ημκ Warwick (1986). Γζα ηδ ζηαηζζηζηή ζφβηνζζδ ημο πμζμζημφ ημο μνβακζημφ οθζημφ ηαζ ημο μνβακζημφ άκεναηα ζημ ίγδια, ηαεχξ ηαζ ηςκ δζαθυνςκ παναηηδνζζηζηχκ ημο ιαηνμγςμαέκεμοξ ιεηαλφ ηςκ ζηαειχκ ηαζ ιεηαλφ ηςκ επμπχκ πνδζζιμπμζήεδηε δ ιμκμπαναβμκηζηή ακάθοζδ δζαηφιακζδξ (one-way ANOVA), εκχ βζα ηδκ αθθδθεπίδναζδ ιεηαλφ ζηαειχκ ηαζ επμπχκ δ πμθοπαναβμκηζηή ακάθοζδ δζαηφιακζδξ (two-way ANOVA) (Zar 1996). Οζ οπμθμβζζιμί έβζκακ ιε ηδ πνήζδ ημο PRIMER. 3. Απνηειέζκαηα Ζ ημηημιεηνζηή ακάθοζδ έδεζλε υηζ ημ ίγδια ηςκ ηνζχκ δεζβιαημθδπηζηχκ ζηαειχκ είκαζ αιιχδεξ. Σα ορδθυηενα πμζμζηά ημο μνβακζημφ οθζημφ ηαζ ημο μνβακζημφ άκεναηα ηαηαβνάθμκηαζ ζημ ζηαειυ ηδξ ζοιααηζηήξ εηηνμθήξ, εκχ ηα παιδθυηενα ζημ ζηαειυ εθέβπμο. Ζ πμθοπαναβμκηζηή ακάθοζδ δζαηφιακζδξ έδεζλε ιδ ζδιακηζηή αθθδθεπίδναζδ ιεηαλφ ζηαειχκ ηαζ επμπχκ, ηυζμ βζα ημ μνβακζηυ οθζηυ υζμ ηαζ βζα ημκ μνβακζηυ άκεναηα. Ζ ιμκμπαναβμκηζηή ακάθοζδ δζαηφιακζδξ έδεζλε υηζ οπάνπμοκ ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ ζηα πμζμζηά ημο μνβακζημφ οθζημφ ηαζ ημο μνβακζημφ άκεναηα ιεηαλφ ηςκ ζηαειχκ (Πζκ. 1). Ο ζοκμθζηυξ ανζειυξ ηςκ αηυιςκ πμο ακαβκςνίζεδηε είκαζ 4.322, ηα μπμία ακήημοκ ζε 180 είδδ. Οζ ορδθυηενεξ ηζιέξ ηςκ δεζηηχκ αθεμκίαξ, μιμζμιμνθίαξ ηαζ πμζηζθυηδηαξ ηαηαβνάθμκηαζ ζημ ζηαειυ S3, εκχ μζ παιδθυηενεξ ζημ ζηαειυ S1. Ζ πμθοπαναβμκηζηή ακάθοζδ δζαηφιακζδξ ηςκ δζαθυνςκ παναηηδνζζηζηχκ ημο ιαηνμγςμαέκεμοξ έδεζλε ζδιακηζηή αθθδθεπίδναζδ ιεηαλφ ζηαειχκ ηαζ επμπχκ βζα υθεξ ηζξ παναιέηνμοξ, εηηυξ απυ ημκ ανζειυ ηςκ εζδχκ ηαζ ημ δείηηδ αθεμκίαξ. Ζ ιμκμπαναβμκηζηή ακάθοζδ δζαηφιακζδξ έδεζλε υηζ μζ δζαθμνέξ πμο παναηδνμφκηαζ ζημοξ δείηηεξ μιμζμιμνθίαξ ηαζ πμζηζθυηδηαξ είκαζ πςνζηέξ (Πζκ. 1). Πίκαηαξ 1. Δπμπζηή ζφβηνζζδ ημο μνβακζημφ οθζημφ, ημο μνβακζημφ άκεναηα ηαζ ηςκ παναιέηνςκ ημο ιαηνμγςμαέκεμοξ ιεηαλφ ηςκ ζηαειχκ ηδξ πενζμπήξ ένεοκαξ (F: Λυβμξ, P level: Δπίπεδμ ζδιακηζηυηδηαξ). Μεηααθδηή Βαειμί εθεοεενίαξ ηαειυξ Δπμπή ηαειυξ X Δπμπή F P level F P level F P level Ονβακζηυ οθζηυ (OM) ,26 ** 0,39 Μ 1,99 Μ Ονβακζηυξ άκεναηαξ 17 34,44 ** 2,22 Μ 0,77 Μ (OC) Ανζειυξ εζδχκ (S) 17 10,52 ** 3,95 Μ 0,83 Μ Ανζειυξ αηυιςκ (N) 17 3,44 Μ 4,18 Μ 26,66 ** Γείηηδξ αθεμκίαξ εζδχκ 17 20,21 ** 1,77 Μ 0,09 Μ (d) Γείηηδξ πμζηζθυηδηαξ 17 21,44 ** 0,53 Μ 13,53 ** (H') Γείηηδξ μιμζμιμνθίαξ 17 7,14 * 2,55 Μ 16,83 ** * P<0,05, (J') ** P<0,001, Μ: Μδ ζδιακηζηυ Δπζηναηέζηενμ είδμξ είκαζ μ πμθφπαζημξ Capitella capitata, ημο μπμίμο ημ πμζμζηυ ειθάκζζδξ ζημ ζηαειυ S1 θεάκεζ ημ 74,14%, ζημ ζηαειυ S2 ιυθζξ ημ 1,15%, εκχ ζημ ζηαειυ S3 δεκ ηαηαβνάθεηαζ δ πανμοζία ημο. ημ ζηαειυ S2 επζηναηέζηενα είκαζ ηα βαζηενυπμδα ημο βέκμοξ Bittium sp. ιε πμζμζηυ 18,51%, εκχ ζημ ζηαειυ S3 ημ επζηναηέζηενμ είδμξ ακήηεζ ζηα επζκμεζδή ηαζ είκαζ ημ Echinocyamus pusillus ιε 9,42%. Ζ ακάθοζδ ημο πμζμζημφ μιμζυηδηαξ ηςκ ιαηνμγςμαεκεζηχκ εζδχκ (SIMPER), έδεζλε υηζ ημ ορδθυηενμ πμζμζηυ ακμιμζυηδηαξ παναηδνείηαζ ιεηαλφ ηςκ ζηαειχκ S1 ηαζ S2 (81,09%), εκχ ημ παιδθυηενμ ιεηαλφ ηςκ ζηαειχκ S2 ηαζ S3 (52,13%). Ζ ακμιμζυηδηα ιεηαλφ ηςκ ζηαειχκ S1 ηαζ S2, ηαεχξ επίζδξ ηαζ ιεηαλφ ηςκ ζηαειχκ S1 ηαζ S3 μθείθεηαζ ηονίςξ ζηδκ πανμοζία ημο είδμοξ C. capitata, εκχ ιεηαλφ ηςκ ζηαειχκ S2 ηαζ S3 μθείθεηαζ ηονίςξ ζηδκ πανμοζία ηςκ εζδχκ ημο βέκμοξ Bittium sp. ηαζ E. pusillus. 40

41 Απυ ημ δζάβναιια πμθοδζάζηαηδξ δζάηαλδξ (MDS) (π. 1), ιε αάζδ ημ ααειυ ζοββέκεζαξ ημο ιαηνμγςμαέκεμοξ, πνμηφπηεζ έκαξ ζαθήξ δζαπςνζζιυξ ημο ζηαειμφ S1 απυ ημοξ μιαδμπμζδιέκμοξ ζηαειμφξ S2 ηαζ S3 ηαηά ηδ δζάνηεζα ηαζ ηςκ δομ επμπχκ. πήια 1. Γζάβναιια πμθοδζάζηαηδξ δζάηαλδξ (MDS) ηςκ δεζβιαημθδπηζηχκ ζηαειχκ ηδξ πενζμπήξ ένεοκαξ ιε αάζδ ημ ααειυ ζοββέκεζαξ ημο ιαηνμγςμαέκεμοξ ηαηά ηδ δζάνηεζα ηςκ δομ επμπχκ (Sp: Άκμζλδ, S: Καθμηαίνζ). Σμ δζάβναιια αενμζζηζηήξ ηονζανπίαξ ηςκ ιαηνμγςμαεκεζηχκ εζδχκ (K-dominance) (π. 2), δείπκεζ έκα ζαθή δζαπςνζζιυ ηςκ ζηαειχκ, ιε ημοξ ζηαειμφξ S2 ηαζ S3 κα ειθακίγμοκ ιζηνυηενδ αενμζζηζηή ηονζανπία εζδχκ. πήια 2. Γζάβναιια αενμζζηζηήξ ηονζανπίαξ ηςκ ιαηνμγςμαεκεζηχκ εζδχκ ζημοξ ζηαειμφξ S1, S2 ηαζ S3. 4. πδήηεζε Tα ορδθυηενα πμζμζηά ημο μνβακζημφ οθζημφ ηαζ ημο μνβακζημφ άκεναηα ηαηαβνάθμκηαζ ζημ ζηαειυ ηδξ ζοιααηζηήξ εηηνμθήξ, εκχ ηα παιδθυηενα ζημ ζηαειυ εθέβπμο. Δπίζδξ, ηα πμζμζηά ζημ ζηαειυ ηδξ αζμθμβζηήξ εηηνμθήξ είκαζ παιδθυηενα απυ αοηά ημο ζηαειμφ ηδξ ζοιααηζηήξ. Ζ ιμκμπαναβμκηζηή ακάθοζδ δζαηφιακζδξ έδεζλε ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ ιεηαλφ ηςκ ζηαειχκ. Οζ Neofitou et al. (2010), ζε ένεοκα πμο δζελήπεδ ζε δομ πενζμπέξ ημο Παβαζδηζημφ ηυθπμο, δζαπίζηςζακ υηζ ηα πμζμζηά ημο μνβακζημφ οθζημφ ηαζ ημο μνβακζημφ άκεναηα ήηακ ορδθυηενα ζημ ζηαειυ ηδξ ζοιααηζηήξ εηηνμθήξ απυ ημ ζηαειυ εθέβπμο, ιε ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ. Οζ ορδθυηενεξ ηζιέξ υθςκ ηςκ παναιέηνςκ ημο ιαηνμγςμαέκεμοξ ιε ελαίνεζδ ηςκ ανζειυ ηςκ αηυιςκ ηαηαβνάθμκηαζ ζημ ζηαειυ εθέβπμο, εκχ μζ παιδθυηενεξ ζημ ζηαειυ ηδξ ζοιααηζηήξ εηηνμθήξ. Ο ζηαειυξ εθέβπμο ηαζ μ ζηαειυξ ηδξ αζμθμβζηήξ εηηνμθήξ πανμοζζάγμοκ ιεβαθφηενδ πμζηζθμιμνθία εζδχκ ηαζ είκαζ πζμ μιμζμβεκείξ υζμκ αθμνά ηδ ιαηνμγςμαεκεζηή ημοξ ζφζηαζδ, ζε ζπέζδ ιε αοηυκ ηδξ ζοιααηζηήξ. Ζ ζηαηζζηζηή ακάθοζδ έδεζλε ζδιακηζηή αθθδθεπίδναζδ ιεηαλφ ζηαειχκ ηαζ επμπχκ ζημοξ δείηηεξ πμζηζθυηδηαξ ηαζ μιμζμιμνθίαξ δ μπμία θαίκεηαζ κα είκαζ πςνζηή. Σα ακςηένς απμηεθέζιαηα είκαζ ζφιθςκα ιε άθθεξ ακάθμβεξ ένεοκεξ (Klaoudatos et al. 2006, Neofitou et al. 2010). Δπζηναηέζηενμ είδμξ είκαζ μ πμθφπαζημξ Capitella capitata. To είδμξ αοηυ είκαζ ηαζνμζημπζηυ ηαζ απακηάηαζ ζε επζαανοιέκα ζγήιαηα ιε ορδθά πμζμζηά μνβακζημφ οθζημφ (Karakassis et al. 2000). φιθςκα ιε ημοξ Karakassis et al. (2000), ημ πμζμζηυ ειθάκζζδξ αοημφ ημο είδμοξ ιπμνεί κα θηάζεζ έςξ ηαζ ημ 75%. ηδκ πανμφζα ένεοκα ημ πμζμζηυ αοηυ θεάκεζ ημ 74,14% ζημ ζηαειυ ηδξ ζοιααηζηήξ εηηνμθήξ, εκχ ζημ ζηαειυ ηδξ αζμθμβζηήξ ιυθζξ ημ 1,15%. Ζ 41

42 πανμοζία αοημφ ημο είδμοξ δεκ ηαηαβνάθεηαζ ζημ ζηαειυ εθέβπμο. Σμ βεβμκυξ αοηυ οπμδεζηκφεζ υηζ μ ααειυξ επίδναζδξ ηδξ ζοιααηζηήξ οδαημηαθθζένβεζαξ ζημ ιαηνμγςμαέκεμξ είκαζ ιεβαθφηενμξ απυ αοηυκ ηδξ αζμθμβζηήξ. φιθςκα ιε ηδκ ακάθοζδ SIMPER ημ ορδθυηενμ πμζμζηυ ακμιμζυηδηαξ παναηδνείηαζ ιεηαλφ ηςκ ζηαειχκ ηδξ ζοιααηζηήξ ηαζ αζμθμβζηήξ εηηνμθήξ, εκχ ημ παιδθυηενμ ιεηαλφ ημο ζηαειμφ ηδξ αζμθμβζηήξ εηηνμθήξ ηαζ ημο ζηαειμφ εθέβπμο. Ζ ακμιμζυηδηα ιεηαλφ ηςκ ζηαειχκ S1 ηαζ S2, ηαεχξ επίζδξ ηαζ ιεηαλφ ηςκ ζηαειχκ S1 ηαζ S3 μθείθεηαζ ηονίςξ ζηδκ πανμοζία ημο είδμοξ C. capitata, εκχ ιεηαλφ ηςκ ζηαειχκ S2 ηαζ S3 μθείθεηαζ ηονίςξ ζηδκ πανμοζία ηςκ εζδχκ ημο βέκμοξ Bittium sp. ηαζ E. pusillus. φιθςκα ιε ένεοκεξ πμο έπμοκ δζελαπεεί ζηδκ Ακαημθζηή Μεζυβεζμ βζα ηζξ επζδνάζεζξ ηδξ ζοιααηζηήξ εηηνμθήξ ζημ αέκεμξ (Klaoudatos et al. 2006, Neofitou et al. 2010), δ ακμιμζυηδηα ιεηαλφ ηςκ ζηαειχκ ζοιααηζηήξ εηηνμθήξ ηαζ ημο ζηαειμφ εθέβπμο μθείθεηαζ ηονίςξ ζηδκ πανμοζία πμθφπαζηςκ, υπςξ ημο είδμοξ C. capitata. Απυ ηδκ μιαδμπμίδζδ ηςκ ζηαειχκ ηδξ πενζμπήξ ένεοκαξ ιε αάζδ ημ ααειυ ζοββέκεζαξ ημο ιαηνμγςμαέκεμοξ, πνμηφπηεζ έκαξ ζαθήξ δζαπςνζζιυξ ημο ζηαειμφ ηδξ ζοιααηζηήξ εηηνμθήξ απυ ημ ζηαειυ ηδξ αζμθμβζηήξ ηαζ ημ ζηαειυ εθέβπμο βεβμκυξ πμο είκαζ ζφιθςκμ ηαζ ιε άθθεξ ένεοκεξ (Klaoudatos et al. 2006, Neofitou et al. 2010). Απυ ηδκ ακάθοζδ ηςκ απμηεθεζιάηςκ ζοιπεναίκεηαζ υηζ δ εθανιμβή αζμθμβζηήξ εηηνμθήξ ζηδκ οδαημηαθθζένβεζα ιπμνεί κα πενζμνίζεζ ζδιακηζηά ηζξ ανκδηζηέξ επζπηχζεζξ ζημ οδάηζκμ πενζαάθθμκ. Πανυθα αοηά, δ εθανιμβή ηδξ αζμθμβζηήξ εηηνμθήξ ζε εονεία ηθίιαηα απαζηεί πεναζηένς ένεοκα πνμηεζιέκμο κα εηηζιδεεί πθήνςξ δ έηηαζδ ηαζ ημ εφνμξ ηςκ επζπηχζεςκ πμο ιπμνεί κα έπεζ ζημ οδάηζκμ πενζαάθθμκ. Βηβιηνγξαθία Beveridge M.C. (2004). Cage aquaculture. Third edition. Blackwell, p 377. Bilyard G.R. (1987). The value of benthic infauna in marine pollution monitoring studies. Marine Pollution Bulletin 18, Bouyoucos G.J. (1962). Hydrometer method improved for making particle size analysis of soils. Agronomy Journal 54, Bray J.R., Curtis J.T. (1957). An ordination of the upland forest communities of southern Wisconsin. Ecological Monographs 27, Byers S.C., Mills E.L., Stewart L. (1978). A comparison of methods for determining organic carbon in marine sediments, with suggestion for a standard method. Hydrobiologia 58, D'Angelo G., Gargiullo S. (1978). Guida alle conchiglie Mediterranee. Conoscerle cercarle collezionarle. Fabbri, Milano, p 224. Day J.H. (1967a). A monograph on the polychaeta of southern Africa Part I. Errantia. Trustees of the British Museum (Natural History). London 656, Day J.H. (1967b). A monograph on the polychaeta of southern Africa Part II. Sedentaria. Trustees of the British Museum (Natural History). London 656, Fauchald K. (1977). The polychaete worms. Definitions and keys to the orders, families and genera. Natural History Museum of Los Angeles County. Science Series 28, Fauvel P. (1923). Faune de France - Polychètes errantes. Fédération Française des Sociétés de Sciences Naturelles, Office Central de Faunistique. Paris 5, Fauvel P. (1927). Faune de France - Polychètes sédentaires. Fédération Française des Sociétés de Sciences Naturelles, Office Central de Faunistique. Paris 16, Field J.G., Clarke K.R., Warwick R.M. (1982). A practical strategy for analysing multispecies distribution patterns. Marine Ecology Progress Series 8, Gaudette H.E., Flight W.R., Toner L., Floger D.W. (1974). An inexpensive titration method for the determination of organic carbon in recent sediments. Journal of Sedimentary Research 44, Karakassis I., Tsapakis M., Hatziyanni E., Papadopoulou K.N., Plaiti W. (2000). Impact of cage farming of fish on the seabed in three Mediterranean coastal areas. Journal of Marine Science 57, Klaoudatos S.D., Klaoudatos D.S., Smith J., Bogdanos K., Papageorgiou E. (2006). Assessment of site specific benthic impact of floating cage farming in the eastern Hios island, Eastern Aegean Sea, Greece. Journal of Experimental Marine Biology and Ecology 338,

43 Mente E., Stratakos A., Boziaris I.S., Kormas K.A., Karalazos V., Karapanagiotidis I.T., Catsiki V.A., Leondiadis L. (2012). The effect of organic and conventional production methods on sea bream growth, health and body composition: a field experiment. Scientia Marina, Barcelona 76, Neofitou N., Vafidis D., Klaoudatos S. (2010). Spatial and temporal effects of fish farming on benthic community structure in a semi-enclosed gulf of the Eastern Mediterranean. Aquaculture Environment Interactions 1, Ruffo S. (1982). The amphipoda of the Mediterranean. Part 1. Gammaridea Acanthonotozomatidae to gammaridae. Mémoires de l Institut Océanographique. Monaco 13, Ruffo S. (1989). The amphipoda of the Mediterranean. Part 2. Gammaridea Haustoriidae to lysianassidae. Mémoires de l Institut Océanographique. Monaco 13, Ruffo S. (1993). The amphipoda of the Mediterranean. Part 3. Gammaridea Melphidippidae to talitridae. Mémoires de l Institut Océanographique. Monaco 13, Yucel-Gier G., Kucuksezgin F., Kocak F. (2007). Effects of fish farming on nutrients and benthic community structure in the Eastern Aegean (Turkey). Aquaculture Research 38, Warwick R.M. (1986). A new method for detecting pollution effects on marine macrobenthic communities. Marine Biology 92, Weston D.P. (1990). Quantitative examination of macrobenthic community changes along an organic enrichment gradient. Marine Ecology Progress Series 61, Zar J.H. (1996). Biostatistical analysis. Third edition. Prentice Hall, New Jersey, p

44 THE EFFECT OF FOOD PARTICLE SIZE ON GROWTH AND SIZE VARIATION OF JUVENILE SEA BASS Smpiliri E. 1*, Golomazou E. 2, Exadactylos A. 2, Malandrakis E. 2, Fleris G. 3, Dimopoulos D. 1, Panagiotaki P. 2 1 Dias S.A. Achladi, , Stylida, Greece. 2 Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Fytokou St., 38446, N. Ionia, Magnesia, Greece. 3 Faculty of Animal Science and Aquaculture, Laboratory of Applied Hydrobiology, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece. ABSTRACT The experiment took place in real scale, large-capacity hatchery. During the experiment, lasting 90 days, six bass (Dicentrarchus labrax), populations of common origin were used. The populations were divided into 2 experimental groups (O and O ) with 3 replicates each. Group O fed with dry feed particle size ranging from 200 to 300 micrometers and group O with a grain size from 200 to 400 micrometers respectively. The experiment was divided into two phases: from the beginning to the size grading (day 47) and grading by the end of the experiment. After grading the fish populations were separated into two sizes - groups: large (ΓΜ and ΓM ) and small individuals (Γι and Γι ). Every three days a sample of each population was measured in length and weight. The parameters evaluated in this study were: growth rate and its size variability. By first grading the fish group O grew faster, with statistically significant differences compared to the fish group O The variation in group O although it was higher showed no statistically significant differences compared with the group O After grading, fish in the group ΓΜ developed faster in length and weight than those in the ΓM group, with statistically significant differences. The differences in growth (length) was statistically significant. Keywords: Bass, Dicentrarchus labrax, food size, growth rate variability, size variation. *Corresponding author: Smpiliri Evangelia ( l_smp@hotmail.com) Ζ ΔΠΗΓΡΑΖ ΣΖ ΚΟΚΚΟΜΔΣΡΗΑ ΤΜΠΖΚΣΧΝ ΣΖΝ ΑΝΑΠΣΤΞΖ ΚΑΗ ΣΖΝ ΔΞΔΛΗΞΖ ΠΑΡΑΛΛΑΚΣΗΚΟΣΖΣΑ ΜΔΓΔΘΧΝ Δ ΗΥΘΤΓΗΑ ΛΑΒΡΑΚΗΟΤ κπηιίξε Δ. 1*, Γθνινκάδνπ Δ. 2, Δμαδάθηπινο Α. 2, Μαιαλδξάθεο Δ. 2, Φιέξεο Γ. 3, Γεκφπνπινο Γ. 1, Παλαγησηάθε Π. 2 1 Γίαξ Ηπεομηαθθζένβεζεξ Α.Β.Δ.Δ. Απθάδζ, , ηοθίδα, Δθθάδα. 2 Σιήια Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ, πμθή Γεςπμκζηχκ Δπζζηδιχκ, Πακεπζζηήιζμ Θεζζαθίαξ, Οδυξ Φοηυημο, 38446, Νέα Ηςκία Μαβκδζία, Δθθάδα. 3Σιήια Δπζζηήιδξ Εςζηήξ Παναβςβήξ ηαζ Τδαημηαθθζενβεζχκ, Δνβαζηήνζμ Δθδνιμζιέκδξ Τδνμαζμθμβίαξ, Γεςπμκζηυ Πακεπζζηήιζμ Αεδκχκ, Ηενά Οδυξ 75, Αεήκα, Δθθάδα. Πεξίιεςε Σμ πείναια έθααε πχνα ζε πναβιαηζηέξ ζοκεήηεξ ιεβάθδξ δοκαιζηυηδηαξ Ηπεομβεκκδηζημφ ζηαειμφ. Υνδζζιμπμζήεδηακ 6 πθδεοζιμί θααναηζμφ (Dicentrarchus labrax), ημζκήξ πνμέθεοζδξ υπμο πςνίζηδηακ ζε 2 πεζναιαηζηέξ μιάδεξ (Ο ηαζ Ο ) ηαζ ιε 3 επακαθήρεζξ ζηδκ ηάεε ιία. Ζ πνχηδ μιάδα (Ο ) δζαηνάθδηε ιε λδνή ηνμθή ιε εφνμξ ημηημιεηνίαξ ιm εκχ ζηδ δεφηενδ μιάδα (Ο ) πμνδβήεδηε λδνή ηνμθή ιε ιέβεεμξ ηυηημο ιm. Σμ πείναια πςνίζηδηε ζε δομ θάζεζξ: απυ ηδκ έκανλδ έςξ ηδ δζαθμβή ιεβέεμοξ (διένα 47) ηαζ απυ ηδ δζαθμβή έςξ ημ ηέθμξ ημο πεζνάιαημξ. Μεηά ηδ δζαθμβή μζ πθδεοζιμί ηςκ ρανζχκ δζαπςνίζηδηακ ζε δομ ιεβέεδ - μιάδεξ: ηα ιεβάθα ηδξ δζαθμβήξ (ΓΜ ηαζ ΓΜ ) ηαζ ηα ιζηνά ηδξ δζαθμβήξ (Γι ηαζ Γι ). Κάεε ηνεζξ ιένεξ θαιαάκμκηακ έκα δείβια ημο ηάεε πθδεοζιμφ ηαζ βζκυηακ ιέηνδζδ ιήημοξ. Μεηά ηδ δζαθμβή δ δεζβιαημθδρία πενζεθάιαακε ηαζ ιέηνδζδ αάνμοξ. Οζ πανάιεηνμζ πμο εηηζιήεδηακ ήηακ: δ αφλδζδ ηςκ πθδεοζιχκ, μ νοειυξ αφλδζδξ ημοξ ηαζ δ παναθθαηηζηυηδηα ημοξ. Μέπνζ ηδκ πνχηδ δζαθμβή ηα ράνζα ηδξ μιάδαξ Ο αολήεδηακ ηαπφηενα, ιε ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ, ζε ζπέζδ ιε ηα ράνζα ηδξ μιάδαξ Ο Ζ παναθθαηηζηυηδηα ζηδκ μιάδα Ο ακ ηαζ ήηακ ιεβαθφηενδ δεκ είπε ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ ζε ζπέζδ ιε ηδκ μιάδα Ο Μεηά ηδ δζαθμβή πμο πναβιαημπμζήεδηε, ηα άημια ηδξ μιάδαξ ΓΜ ακαπηφπεδηακ βνδβμνυηενα ηαζ ζε ιήημξ ηαζ ζε αάνμξ ζε ζπέζδ ιε ηα άημια ηδξ μιάδαξ ΓΜ , ιε ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ. Ζ δζαθμνά ζηδκ ακάπηολδ ημο ιήημοξ ήηακ ζηαηζζηζηά ζδιακηζηή εκχ ζημ αάνμξ ιδ ζηαηζζηζηά ζδιακηζηή. Λέξειρ κλειδιά: Λαβξάθη, Dicentrarchus labrax, κέγεζνο θόθθνπ ηξνθήο, αύμεζε, ξπζκόο αύμεζεο, παξαιιαθηηθόηεηα κεγεζώλ. *οββναθέαξ επζημζκςκίαξ: ιπζθίνδ Δοαββεθία ( l_smp@hotmail.com 44

45 1. Δηζαγσγή Ζ παναθθαηηζηυηδηα ζημ ιέβεεμξ ηςκ ζπεοδίςκ απμηεθεί έκα απυ ηα ζδιακηζηυηενα πνμαθήιαηα ημο ηθάδμο ηςκ ζπεομηαθθζενβεζχκ. Σμ πνυαθδια εκημπίγεηαζ ζημοξ ζπεομβεκκδηζημφξ ζηαειμφξ ηαζ δζεονφκεηαζ υζμ πνμπςνάεζ δ εηηνμθή ηςκ ζπεοδίςκ. Σμ θαζκυιεκμ ηδξ ακμιμζμιμνθίαξ ακαθένεηαζ βζα πνχηδ θμνά ζηδ αζαθζμβναθία ςξ Tobi-Koi phenomenon ημ 1955 (Νakamura & Kasahara 1955). Έηημηε έπμοκ βίκεζ ακαθμνέξ ζε πμθθά είδδ ρανζχκ: ζημ πνοζυρανμ, Carassius auratus L (Welty 1934), ζηδκ πέζηνμθα, Salmo trutta L. (Brown 1946), ζημ βαηυρανμ Ictalurus punctatus, (Schwedler et al. 1990). Οζ αζηίεξ πμο ζοιαάθμοκ ζηδ δζαθμνμπμίδζδ ημο νοειμφ ακάπηολδξ ηαζ έπμοκ ςξ ζοκέπεζα ηδκ ακμιμζμιμνθία ηςκ ιεβεεχκ είκαζ: μζ βεκεηζημί πανάβμκηεξ, μ νοειυξ αφλδζδξ, ημ ιέβεεμξ ημο αοβμφ, μζ ημζκςκζηέξ ζπέζεζξ ιεηαλφ ηςκ αηυιςκ ηδξ ίδζαξ μιάδαξ, δ ηαηακάθςζδ ηδξ ηνμθήξ, δ ζπεομποηκυηδηα, δ αλζμπμίδζδ εκένβεζαξ ηδξ ηνμθήξ, μζ ζοκεήηεξ εηηνμθήξ, δ εκδζζιυηδηα ηαεχξ ηαζ μζ πενζααθθμκηζημί πανάβμκηεξ. ημπυξ ηδξ ενβαζίαξ είκαζ δ ιεθέηδ ηδξ επίδναζδξ ημο εφνμοξ ηδξ ημηημιεηνίαξ ηςκ πμνδβμφιεκςκ ζφιπδηηςκ ζηδκ ακάπηολδ ηαζ ζηδκ παναθθαηηζηυηδηα ηςκ ζπεοδίςκ ημο θααναηζμφ ζε πναβιαηζηέξ ζοκεήηεξ ιεβάθδξ δοκαιζηυηδηαξ Ηπεομβεκκδηζημφ ζηαειμφ. 2. Τιηθά θαη κέζνδνη Υνδζζιμπμζήεδηακ 6 πθδεοζιμί αηυιςκ θααναηζμφ (Dicentrarchus labrax), ημζκήξ πνμέθεοζδξ. Οζ πθδεοζιμί πςνίζηδηακ ζε 2 πεζναιαηζηέξ μιάδεξ: ηδκ μιάδα Ο (ιάνηονεξ) ηαζ ηδκ μιάδα Ο Πναβιαημπμζήεδηακ 3 επακαθήρεζξ ζηδκ ηάεε ιία. Έςξ ηδκ διένα 27 αημθμοεήεδηε ημζκυ πνςηυημθθμ εηηνμθήξ ζηζξ δομ μιάδεξ. Απυ 28 διενχκ λεηίκδζε δ δζαθμνμπμίδζδ ημο πνςημηυθθμο βζα ηζξ δομ πεζναιαηζηέξ μιάδεξ. Ζ μιάδα Ο δζαηνάθδηε ζφιθςκα ιε ημ πνςηυημθθμ ηδξ εηαζνείαξ: πμνήβδζδ λδνήξ ηνμθήξ ιε ιέβεεμξ ηυηημο ιm. ηδ δεφηενδ μιάδα Ο πμνδβήεδηε λδνή ηνμθή ιε ιεβαθφηενμ εφνμξ ημηημιεηνίαξ ιm. Καζ ζηζξ δομ μιάδεξ έβζκε δζαθμβή ιεβέεμοξ ιε ζπάνα 1,5 mm ζηδκ δθζηία ηςκ 47 διενχκ υπμο μζ πθδεοζιμί ηςκ ρανζχκ δζαπςνίζηδηακ ζε δομ ιεβέεδ - μιάδεξ: ηα ιεβάθα ηδξ δζαθμβήξ (ΓΜ ηαζ ΓΜ ) ηαζ ηα ιζηνά ηδξ δζαθμβήξ (Γι ηαζ Γι ). Απυ ηδκ δθζηία ηςκ 60 διενχκ πενίπμο ηαζ έπεζηα αημθμοεήεδηε ημζκή δζαπείνζζδ ηαζ βζα ηζξ δφμ μιάδεξ. Οζ ιεηνήζεζξ λεηίκδζακ ηδκ διένα 3 απυ ηδκ εηηυθαρδ (dph) ηαζ επακαθαιαάκμκηακ ηάεε ηνεζξ ιένεξ. Κάεε δεζβιαημθδρία πενζθάιαακε πενίπμο 100 άημια. Απυ ηδκ 47δ ιένα ηαζ πανάθθδθα ιε ηδ ιέηνδζδ ιήημοξ βζκυηακ ηαζ αημιζηή ιέηνδζδ αάνμοξ ηςκ ζπεοδίςκ. Σμ πεζναιαηζηυ πνςηυημθθμ πενζεθάιαακε ηδκ πενζβναθή ιήημοξ ηαζ αάνμοξ ηςκ ρανζχκ ιε βναιιζηέξ ελζζχζεζξ, ηδκ εηηίιδζδ ημο νοειμφ αφλδζδξ ηαζ ηδξ παναθθαηηζηυηδηαξ ιήημοξ ηαζ αάνμοξ εηθναζιέκδ ςξ CV%. Χξ επίπεδμ ζδιακηζηυηδηαξ επεθέβδ ημ α = 0,05 ( P < 0,05). Σα άημια ηάεε δεζβιαημθδρίαξ πςνίζηδηακ ζε επζιένμοξ μιάδεξ: ηα ιζηνά άημια (ι) πμο πενζεθάιαακε υθα ηα ζπεφδζα ηςκ μπμίςκ ημ ιήημξ ή ημ αάνμξ ήηακ ιζηνυηενμ απυ ηδκ ηζιή x - 1,96 Υ ηοπζηή απυηθζζδ ηαζ ηα ιεβάθα άημια (Μ) ηα μπμία ημ ιήημξ ή ημ αάνμξ ημοξ ήηακ ιεβαθφηενμ απυ ηδκ ηζιή + 1,96 Υ ηοπζηή απυηθζζδ. Γζα ηδ ζηαηζζηζηή ακάθοζδ ηςκ απμηεθεζιάηςκ πνδζζιμπμζήεδηακ ηα ηνζηήνζα ANOVA ηαζ ANCOVA, ηαεχξ ηαζ ημ θμβζζιζηυ Excel. 3. Απνηειέζκαηα Έςξ ηδκ 47 δ διένα Ζ ακάπηολδ ηςκ ρανζχκ πενζβνάθδηε ιε βναιιζηέξ ελζζχζεζξ βζα ημ πνμκζηυ δζάζηδια απυ 3 έςξ 47 διενχκ ιε ηδ ιμνθή Y = α + αx, υπμο Y: ιήημξ (mm), X: δθζηία (διένεξ), α: νοειυξ αφλδζδξ. Ο Πίκαηαξ 1 πανμοζζάγεζ ηζξ βναιιζηέξ ελζζχζεζξ βζα ηάεε μιάδα. Ζ ελέθζλδ ηδξ παναθθαηηζηυηδηαξ πενζβνάθδηε ιε βναιιζηέξ ελζζχζεζξ ηδξ ιμνθήξ Τ = α + αυ (υπμο Τ: ηοπζηή απυηθζζδ, Υ: δθζηία (διένεξ) ηαζ α: ιέζμξ νοειυξ παναθθαηηζηυηδηαξ ιήημοξ. Οζ βναιιζηέξ ελζζχζεζξ πμο πενζβνάθμοκ ηδκ ελέθζλδ ηδξ παναθθαηηζηυηαξ πανμοζζάγμκηαζ ζημκ Πίκαηα 2. Ζ παναθθαηηζηυηδηα ζηα άημια ηαζ ηςκ δφμ πεζναιαηζηχκ μιάδςκ ιο , ιο , ΜΟ , ΜΟ πανέιεζκε ζπεδυκ ζηαεενή ηαζ δεκ ήηακ δοκαηυκ κα πενζβναθεί ιε βναιιζηέξ ελζζχζεζξ. Πίλαθαο 1. Γξακκηθέο εμηζψζεηο εμέιημεο κήθνπο θαη ζπληειεζηέο ζπζρέηηζεο ησλ πεηξακαηηθψλ νκάδσλ έσο ηε δηαινγή. Οιάδα Δλίζςζδ r 2 Ο Τ = 2, ,9842 SS Ο Τ = 2, ,9859 ιο Τ = 2, ,9741 SNS ιο Τ = 2, ,9592 ΜΟ Τ = 2, ,9852 ΜΟ Τ = 2, ,9851 SS 45

46 Πίλαθαο 2. Γξακκηθέο εμηζψζεηο εμέιημεο παξαιιαθηηθφηεηαο θαη ζπληειεζηέο ζπζρέηηζεο ησλ πεηξακαηηθψλ νκάδσλ έσο ηε δηαινγή. Οιάδα Δλίζςζδ r 2 Ο Τ = 0, ,9544 Ο Τ = 0, ,9336 SNS Μεβάθα άημια απυ ηδ δζαθμβή Ζ αφλδζδ ημο ιήημοξ ηςκ ιεβάθςκ αηυιςκ ΓΜ ηαζ ΓΜ , ηαεχξ ηαζ ηςκ μιάδςκ ΓΜΜ , ΓΜΜ πμο πνμέηορακ απυ ηδ δζαθμβή ηαζ βζα ηζξ δομ μιάδεξ πενζβνάθδηε ιε βναιιζηέξ ελζζχζεζξ πμο πανμοζζάγμκηαζ ζημκ Πίκαηα 3. Ο Πίκαηαξ 4 πανμοζζάγεζ ηζξ βναιιζηέξ ελζζχζεζξ αφλδζδξ αάνμοξ ηςκ ακηίζημζπςκ αηυιςκ ιεηά ηδ δζαθμβή. Πίλαθαο 3. Γξακκηθέο εμηζψζεηο εμέιημεο κήθνπο θαη ζπληειεζηέο ζπζρέηηζεο ησλ πεηξακαηηθψλ νκάδσλ ησλ κεγάισλ αηφκσλ κεηά ηε δηαινγή. Οιάδα Δλίζςζδ r ΓΜ Τ 1, ,881 ΓΜ Τ = 2, ,9284 = SS ΓΜΜ 200- Τ =-12,084 0,9485 ΓΜΜ 200- Τ =-4, ,8678 SS Πίλαθαο 4. Γξακκηθέο εμηζψζεηο εμέιημεο βάξνπο θαη ζπληειεζηέο ζπζρέηηζεο ησλ πεηξακαηηθψλ νκάδσλ ησλ κεγάισλ αηφκσλ κεηά ηε δηαινγή. Οιάδα Δλίζςζδ r ΓΜ Τ -0, ,7711 ΓΜ Τ = -0, ,8299 = SS ΓΜΜ 200- Τ =-1,9564 0,8425 ΓΜΜ 200- Τ =-1, ,7069 SNS 46

47 Ζ ελέθζλδ ηδξ παναθθαηηζηυηδηαξ ιήημοξ ηαζ αάνμοξ βζα ηάεε ιένα ηδξ ιέηνδζδξ ακαθένμκηαζ ζημκ Πίκαηα 5 ηαζ Πίκαηα 6. Πίλαθαο 5. Γξακκηθέο εμηζψζεηο εμέιημεο παξαιιαθηηθφηεηαο κήθνπο θαη ζπληειεζηέο ζπζρέηηζεο ησλ πεηξακαηηθψλ νκάδσλ ησλ κεγάισλ αηφκσλ κεηά ηε δηαινγή. Οιάδα Δλίζςζδ r 2 ΓΜ Τ = -3, ,906 = ΓΜ Τ -2, ,8479 SΝS ΓΜΜ 200- Τ =-1,4724 0,2948 ΓΜΜ 200- Τ =-0, ,1306 SΝS Πίλαθαο 6. Γξακκηθέο εμηζψζεηο εμέιημεο παξαιιαθηηθφηεηαο βάξνπο θαη ζπληειεζηέο ζπζρέηηζεο ησλ πεηξακαηηθψλ νκάδσλ ησλ κεγάισλ αηφκσλ κεηά ηε δηαινγή. Οιάδα Δλίζςζδ r ΓΜ Τ -0, ,7127 ΓΜ Τ = -0, ,8299 = SΝS ΓΜΜ 200- Τ =-0,3327 0,5508 ΓΜΜ 200- Τ =-0, ,2343 SNS Μζηνά άημια απυ ηδ δζαθμβή Ζ αφλδζδ ημο ιήημοξ ηςκ αηυιςκ ηςκ μιάδςκ Γι ηαζ Γι πενζβνάθδηε ιε βναιιζηέξ ελζζχζεζξ πμο πανμοζζάγμκηαζ ζημκ Πίκαηα 7. Ακηίζημζπα δ αφλδζδ ημο αάνμοξ πανμοζζάγεηαζ ζημκ Πίκαηα 8. Οζ ελζζχζεζξ πμο πενζβνάθμοκ ηδκ ελέθζλδ ηδξ παναθθαηηζηυηδηαξ ιήημοξ ηαζ αάνμοξ πανμοζζάγμκηαζ ζημοξ Πίκαηεξ 9 ηαζ 10 ακηίζημζπα. Πίλαθαο 7. Γξακκηθέο εμηζψζεηο εμέιημε κήθνπο θαη ζπληειεζηέο ζπζρέηηζεο ησλ πεηξακαηηθψλ νκάδσλ ησλ κηθξψλ αηφκσλ κεηά ηε δηαινγή. Οιάδα Δλίζςζδ r 2 Γι Τ = -3, ,987 SS Γι Τ = -0, ,874 6 Πίλαθαο 8. Γξακκηθέο εμηζψζεηο εμέιημεο βάξνπο θαη ζπληειεζηέο ζπζρέηηζεο ησλ πεηξακαηηθψλ νκάδσλ ησλ κηθξψλ αηφκσλ κεηά ηε δηαινγή. Οιάδα Δλίζςζδ r 2 Γι Τ = -0, ,9494 SS Γι Τ = -0, ,8366 Πίλαθαο 9. Γξακκηθέο εμηζψζεηο εμέιημεο παξαιιαθηηθφηεηαο κήθνπο θαη ζπληειεζηέο ζπζρέηηζεο ησλ πεηξακαηηθψλ νκάδσλ ησλ κηθξψλ αηφκσλ κεηά ηε δηαινγή. Οιάδα Δλίζςζδ r 2 Γι Τ = -1, ,9146 SΝS Γι Τ = -1, ,7439 Πίλαθαο 10. Γξακκηθέο εμηζψζεηο εμέιημεο παξαιιαθηηθφηεηαο βάξνπο θαη ζπληειεζηέο ζπζρέηηζεο ησλ πεηξακαηηθψλ νκάδσλ ησλ κηθξψλ αηφκσλ κεηά ηε δηαινγή. Οιάδα Δλίζςζδ r 2 Γι Γι Τ = -0, ,0025Υ Τ = -0, ,0018Υ 0,9124 0,8167 SΝS 4. πδήηεζε Έςξ ηδ δζαθμβή ηα ράνζα ηδξ μιάδαξ Ο αολήεδηακ ηαπφηενα, ιε ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ, ζε ζπέζδ ιε ηα ράνζα ηδξ μιάδαξ Ο Οιμίςξ ηα ιεβάθα άημια ηδξ μιάδαξ Ο αολήεδηακ ηαπφηενα ζε ζπέζδ ιε ηα ακηίζημζπα άημια ηδξ μιάδαξ Ο , ιε ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ. Σα ιζηνά άημια ηςκ μιάδςκ αολήεδηακ ιε πανυιμζμοξ νοειμφξ αφλδζδξ. Δκδεπμιέκςξ, δ ζδιακηζηή δζαθμνά ζηδκ αφλδζδ ηδξ μιάδαξ Ο μθείθεηαζ ζηα ιεβάθα άημια ηδξ μιάδαξ Ο ηαζ ζημ πθεμκέηηδια πμο είπακ θυβς ηδξ πμνήβδζδξ ηαζ ιεβαθφηενμο ηυηημο ηνμθήξ ζε ζπέζδ ιε ηδκ άθθδ μιάδα Ο

48 Οζ Helland et al. (1997) ηαηέθδλακ ζημ ζοιπέναζια υηζ μ ζοκδοαζιυξ ηνζχκ ιεβεεχκ ηνμθήξ εοκμεί ηδκ ηαθφηενδ ακάπηολδ ζηδκ ζππυβθςζζα (Hippoglossus hippoglossus L.). Βζαθζμβναθζηέξ ακαθμνέξ οπμζηδνίγμοκ υηζ δ εκένβεζα πμο επεκδφεηαζ βζα ηδ ζφθθδρδ ηδξ ηνμθήξ δεκ είκαζ ακάθμβδ ημο ιεβέεμοξ ηδξ ηνμθήξ. Χξ εη ημφημο, ημ ηαεανυ ηένδμξ εκένβεζαξ ιπμνεί κα είκαζ πμθφ παιδθυ βζα ηα ιζηνά ζςιαηίδζα ηνμθήξ, ιε απμηέθεζια ηδ παιδθή απμδμηζηυηδηα ηδξ ιεηαηνερζιυηδηαξ ηδξ ηνμθήξ ηαζ ηδξ ανβήξ ακάπηολδξ (Jobling & Wandsvik 1983, Dos Santos et al. 1993). Ακηίεεηα, μζ Goldan et al. (1997) ηαζ Bailey et al. (2003) δζαπίζηςζακ υηζ δζαθμνεηζηά ιεβέεδ ηνμθήξ δεκ επδνεάγμοκ ηδκ ακάπηολδ ιε ημκ ηεθεοηαίμ κα ζοιπεναίκεζ υηζ ηα ράνζα ιπμνμφκ κα πνμζανιμζημφκ ζε θμβζηέξ απμηθίζεζξ απυ ημ αέθηζζημ ιέβεεμξ ηδξ ηνμθήξ πςνίξ κα οπάνπμοκ ανκδηζηέξ επζπηχζεζξ ζηδκ ακάπηολδ ημοξ. Χζηυζμ, πνέπεζ κα επζζδιακεεί υηζ μζ ιεβαθφηενεξ ζε ιέβεεμξ ηνμθέξ είκαζ πενζζζυηενμ εθηοζηζηέξ μπηζηά βζα ηα ράνζα (Stradmeyer et al. 1988, Smith et al. 1995) ηαζ υηζ ημ πνμηζιχιεκμ ή αέθηζζημ ιέβεεμξ ηδξ ηνμθήξ ελανηάηαζ ηαζ απυ ηδ ζηθδνυηδηα ηδξ (Fessehaye et al. 2006). Ζ παναθθαηηζηυηδηα ζηδκ μιάδα Ο ακ ηαζ ήηακ ιεβαθφηενδ δεκ είπε ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ ζε ζπέζδ ιε ηδκ μιάδα Ο Χζηυζμ, δ επί ημζξ % δζαθμνά ηςκ ιέζςκ νοειχκ παναθθαηηζηυηδηαξ ιήημοξ ακένπεηαζ ζημ 14,5 %, βεβμκυξ πμο εκζζπφεζ ηδκ άπμρδ υηζ μ ηαπφηενμξ νοειυξ ακάπηολδξ εκζζπφεζ ηδ δζαζπμνά ηςκ ιεβεεχκ βφνς απυ ημ ιέζμ υνμ (Panagiotaki, 1992). ε ακάθμβεξ ιεθέηεξ ηςκ Tabachek (1988) ηαζ Azaza et al. (2010), δζαπζζηχεδηε πςξ δ δζαζπμνά ημο ιεβέεμοξ αολάκεηαζ πενζζζυηενμ ζε πθδεοζιμφξ πμο ηνέθμκηαζ ιε ιεβάθμ ηυηημ ηνμθήξ. Αοηυ ελδβήεδηε ιε δομ ηνυπμοξ: μζ ιεβαθφηενμζ ηυηημζ ηνμθήξ, εκδεπμιέκςξ κα ήηακ πζμ ημκηά ζημ «αέθηζζημ» ηυηημ ηνμθήξ ηαζ δεφηενμκ μζ ιεβαθφηενμζ ηυηημζ ηνμθήξ είκαζ ζπακζυηενμζ, ακεεηηζηυηενμζ ηαζ δ ηαηακάθςζδ ημοξ δζεοημθφκεζ ηδ δδιζμονβία ή ηδ ζοκέπζζδ «ζενανπζχκ», απυ ηζξ μπμίεξ ζοκήεςξ επςθεθμφκηαζ ηα ιεβαθφηενα άημια (Goldan et al.1997, Kestemont et al. 2003). Σέθμξ, μζ Nakamura & Kasahara (1956) ηαζ μζ Wankowski & Thorpe (1979) οπμζηήνζλακ υηζ μ ακηαβςκζζιυξ βζα ημοξ ιεβαθφηενμοξ ηυηημοξ ηνμθήξ είκαζ εκημκυηενμξ θυβς ηςκ θζβυηενςκ ηυηηςκ πμο πενζέπμκηαζ ζηδκ ίδζα αζμιάγα ηνμθήξ ηαζ εκδεπμιέκςξ μδδβεί ζε αφλδζδ ηδξ παναθθαηηζηυηδηαξ. Μεηά ηδ δζαθμβή ηα άημια ηδξ μιάδαξ ΓΜ ακαπηφπεδηακ βνδβμνυηενα ηαζ ζε ιήημξ ηαζ ζε αάνμξ ζε ζπέζδ ιε ηα άημια ηδξ μιάδαξ ΓΜ , ιε ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ. Πανυιμζα εζηυκα πανμοζζάγμοκ ηαζ ηα άημια ηδξ μιάδαξ ΓΜΜ ηα μπμία αολάκμκηαζ ηαπφηενα ζε ιήημξ ηαζ ζε αάνμξ ζε ζπέζδ ιε ηα άημια ηδξ μιάδαξ ΓΜΜ Ζ δζαθμνά ζηδκ ακάπηολδ ημο ιήημοξ ήηακ ζηαηζζηζηά ζδιακηζηή εκχ ζημ αάνμξ ιδ ζηαηζζηζηά ζδιακηζηή. Ζ δζαπίζηςζδ αοηή ένπεηαζ ζε ζοιθςκία ιε αζαθζμβναθζηέξ ακαθμνέξ (Jobling & Reinsnes 1987, Barki et al. 2000), πμο οπμζηδνίγμοκ υηζ μ δζαπςνζζιυξ ηςκ ιζηνχκ εοκμεί ηδκ ακάπηολδ ημοξ. Τπάνπμοκ υιςξ ηαζ ακαθμνέξ βζα νοειμφξ ακάπηολδξ ιεβαθφηενμοξ, ηυζμ ημο ιήημοξ υζμ ηαζ ημο αάνμοξ, ζε μιάδεξ πθδεοζιχκ υπμο πενζείπακ άημια ηαζ ηςκ δομ ιεβεεχκ (Imsland et al. 2008), ζοιπεναίκμκηαξ πςξ μζ αθθδθεπζδνάζεζξ πμο επδνεάγμοκ ηδ ζοιπενζθμνά ιεηαλφ ηςκ ρανζχκ, παίγμοκ ζδιακηζηυ νυθμ. Σέθμξ μ Kamstra (1993) παναηήνδζε υηζ δ δζαθμβή ιεβεεχκ δεκ πνμηάθεζε ζδιακηζηέξ ιεηααμθέξ ζηδκ ακάπηολδ ηαζ ηδκ επζαίςζδ ηςκ αηυιςκ. Ζ παναθθαηηζηυηδηα ζηζξ μιάδεξ ΓΜ ηαζ ΓΜΜ είκαζ ιεβαθφηενδ ζε ζπέζδ ιε ηζξ μιάδεξ ΓΜ ηαζ ΓΜΜ ακηίζημζπα, πςνίξ ςζηυζμ κα επζαεααζχκεηαζ ιε ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ. Σμ πθεμκέηηδια πμο είπε ζηδκ ακάπηολδ δ μιάδα Ο είκαζ πζεακυκ κα απαθείθεηαζ θυβς ηδξ δζαθμβήξ δ μπμία άθθςζηε ςξ εθανιμγυιεκδ πναηηζηή εκκμεί ηδκ ακάπηολδ ηςκ ιζηνχκ (Jobling & Reinsnes 1987, De March 1997, Barki et al. 2000). Δκδεπμιέκςξ, δ επίδναζδ ημο ιεβαθφηενμο εφνμοξ ημηημιεηνίαξ δ μπμία παναηδνήεδηε ιέπνζ ηδκ διένα 47 κα απέδζδε πανυιμζα απμηεθέζιαηα ακ ιεηά ηδ δζαθμβή πανέπμκηακ ηνμθή ιε ιεβαθφηενμ εφνμξ ηυηημο. Βηβιηνγξαθία Azaza M., Dhraief M., Kraiem M., Baras E. (2010). Influences of food particle size on growth, size heterogeneity, food intake and gastric evacuation in juvenile Nile tilapia, Oreochromis niloticus, L., Aquaculture, 309, Bailey J., Alanärä A.,Crampton V. (2003). Do delivery rate and pellet size affect growth rate in Atlantic salmon (Salmo salar L.) raised under semi-commercial farming conditions? Aquaculture, 224, Barki A., Harpaz G., Karplus I. (2000). Effects of larger fish and size grading on growth and size variation in fingerling silver perch. Aquaculture International, 8, Brown M. (1946). The growth of brown trout (Salmo trutta L.).I. Factors affecting the growth of trout fry. J. Exp. Biol., 22, Dos Santos J., Burkow I., Jobling M. (1993). Patterns of growth and lipid deposition in cod (Gadus morhua L.) fed natural prey and fish based feeds. Aquaculture, 110,

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50 TRENDS AND TYPOLOGY OF WORK ACCIDENTS IN GREEK MARICULTURE: THE ROLE OF GENDER Tiligadas I. 1,2*, Moutopoulos D.K. 3, Chatziefstathiou M. 2,4, Tsoumani M.-M. 2,5, Anastasiou S. 6 1 Ministry of Labour, Labour Inspection Body, Piraeus and South Aegean Sea, Greece, tililias@otenet.gr 2 Panhellenic Society of Technologists Ichthyologists, Greek Scientific & Professional Society, Piraeus, Greece 3 Department of Fisheries-Aquaculture, Technological Educational Institute of Western Greece, Mesolonghi, Greece, dmoutopo@teimes.gr 4 Laboratory for Local & Insular Development, Department of Environment, University of the Aegean, Mytilene, Greece, mhatzi@env.aegean.gr 5 Hatchery of Ioannina, Ministry of Rural Development & Food, Hani Terovou, Ioannina, Greece, mirandatsoumani@gmail.com 6 Department of Logistics, Technological Educational Institute of Central Greece, Thiva, cosmasfax@yahoo.com. ABSTRACT Greek Mariculture has been rapidly expanded in the Eastern Mediterranean during the last 20 years leading the sector to an increase of both the number of fish farms and farmed fisheries production. The present study aims to: (a) investigate the trend of the work related accidents in the Mariculture Industry during the last five years ( ), (b) create a typology on the types of injuries and their seasonal distribution and (c) seek potential correlations between changes in the trends of the types of injuries with the production line. Data were derived from European statistics for accidents at work during and covered all fish farms in Greece. Results showed that fatal accidents represented an extremely low part of the total number of cases (3.6%) and the total number of accidents (fatal and injuries) was decreased through time. Work related injuries did not showed a seasonal pattern rather a high number of cases were marked at spotted periods during the year, whereas fatal accidents took place during spring. In contrast, there is daily pattern showing that a high number of accidents took place during 9am and 3pm. Time of accidents followed a stable pattern; more than 85% of the cases took place during 6 am and 3 pm. Description and determination for health and safety working conditions are serving as a reference base for further improvement of health and safety working conditions and provides a future tool for human resources and production managers for maximizing production and reducing work place hazards. Keywords: aquaculture, hazards, safety, health, Greece *Correspondence author: Tiligadas I., Safety and Health Inspector, Ministry of Labour, Labour Inspection Body, Piraeus and South Aegean Sea, and, President of the Panhellenic Society of Technologist Ichthyologists (PASTI), tililias@otenet.gr. ΣΑΔΗ ΚΑΗ ΠΡΟΣΤΠΑ ΔΡΓΑΣΗΚΧΝ ΑΣΤΥΖΜΑΣΧΝ ΣΗ ΘΑΛΑΗΔ ΤΓΑΣΟΚΑΛΛΗΔΡΓΔΗΔ: Ο ΡΟΛΟ ΣΟΤ ΦΤΛΟΤ Σπιηγάδαο Ζ. 1,2*, Μνπηφπνπινο Γ.Κ. 3, Υαηδεεπζηαζίνπ Μ. 2,4, Σζνπκάλε Μ.-Μ. 2,5, Αλαζηαζίνπ. 6 1 Τπμονβείμ Δνβαζίαξ, Δπζεεχνδζδ Αζθάθεζαξ Δνβαζίαξ, Τ.Δ.Κ.Α.Π.-.ΔΠ.Δ.-Κ.ΔΠ.Δ.Κ. Πεζναζά ηαζ Νμηίμο Αζβαίμο, Δθθάδα, tililias@otenet.gr 2 Πακεθθήκζμξ φθθμβμξ Σεπκμθυβςκ Ηπεομθυβςκ, Δπζζηδιμκζηυξ ηαζ Δπαββεθιαηζηυξ φθθμβμξ, Πεζναζάξ 50

51 3 Σιήια Σεπκμθυβςκ Αθζείαξ - Τδαημηαθθζενβεζχκ, ΣΔΗ Γοηζηήξ Δθθάδαξ, Μεζμθυββζ, dmoutopo@teimes.gr 4 Δνβαζηήνζμ Σμπζηήξ ηαζ Νδζζςηζηήξ Ακάπηολδξ (Δ.Σ.Ν.Α.), Σιήια Πενζαάθθμκημξ, Πακεπζζηήιζμ Αζβαίμο, Μοηζθήκδ, Δθθάδα, mhatzi@env.aegean.gr 5 Ηπεομβεκκδηζηυξ ηαειυξ Ηςακκίκςκ, Τπμονβείμ Αβνμηζηήξ Ακάπηολδξ & Σνμθίιςκ, Υάκζ-Σενυαμο, Ηςάκκζκα, mirandatsoumani@gmail.com 6 Σιήια Γζμίηδζδξ οζηδιάηςκ Δθμδζαζιμφ, ΣΔΗ ηενεάξ Δθθάδαξ, Θήαα, sanastasiou@teiste.gr Πεξίιεςε Οζ δναζηδνζυηδηεξ ηδξ Θαθάζζζαξ Τδαημηαθθζένβεζαξ (ΘΤ) έπμοκ επεηηαεεί ιε βνήβμνμοξ νοειμφξ ζηδκ Ακαημθζηή Μεζυβεζμ ηα ηεθεοηαία 20 πνυκζα μδδβχκηαξ ημκ ηθάδμ ζε αφλδζδ ηυζμ ημο ανζειμφ ηςκ ιμκάδςκ υζμ ηαζ ηδξ παναβςβήξ ηςκ εηηνεθυιεκςκ πνμσυκηςκ. Ζ πανμφζα ενβαζία έπεζ ςξ ζηυπμ κα: (α) δζενεοκήζεζ ηδκ ηάζδ ηςκ αηοπδιάηςκ ζηζξ ΘΤ ηαηά ηδ δζάνηεζα ηςκ ηεθεοηαίςκ πέκηε εηχκ ( ), (α) δδιζμονβήζεζ ιζα ηοπμθμβία ηςκ αηοπδιάηςκ ιε αάζδ ημκ ηφπμ ημο αηοπήιαημξ, ηδκ επμπζηυηδηά ημοξ, ηδ πςνζηή ημοξ ηαηακμιή ηαζ ηα ημζκςκζηά παναηηδνζζηζηά ηςκ ενβαγμιέκςκ ηαζ (β) δζενεοκήζεζ πζεακμφξ ζοζπεηζζιμφξ ηςκ αθθαβχκ ζηζξ ηάζεζξ ηςκ ηφπςκ αηοπδιάηςκ ιε ηδ βναιιή παναβςβήξ. Σα δεδμιέκα πνμήθεακ απυ ηδκ Δονςπασηή ηαηζζηζηή Τπδνεζία αηοπδιάηςκ ζημ πχνμ ενβαζίαξ ηαζ ηαθφπηεζ υθεξ ηζξ ιμκάδεξ ΘΤ ζηδκ Δθθάδα. Σα απμηεθέζιαηα έδεζλακ υηζ ηα εακαηδθυνα αηοπήιαηα ακηζπνμζςπεφμοκ έκα ζοκηνζπηζηά εθάπζζημ πμζμζηυ ηςκ αηοπδιάηςκ (3,2%) ηαζ δ ηάζδ ημο ζοκμθζημφ ανζειμφ ηςκ αηοπδιάηςκ ιεζχκμκηακ ζδιακηζηά ζημ πνυκμ. Ο ανζειυξ ηςκ αηοπδιάηςκ δεκ αημθμοεμφζε έκα επμπζηυ πνυηοπμ πανά εκημπίγμκηακ ζε ζοβηεηνζιέκμοξ ιήκεξ ηαηά ηδ δζάνηεζα ημο έημοξ, εκχ οπάνπεζ έκα δζάζηδια ιεηαλφ 9 ημ πνςί ηαζ 3 ημ ιεζδιένζ υπμο θαιαάκμοκ πχνα ηα πενζζζυηενα αηοπήιαηα. Ζ απμηφπςζδ ηςκ ηάζεςκ ηςκ αηοπδιάηςκ ζηζξ ΘΤ ηαζ μ ηαεμνζζιυξ ιζαξ ηοπμθμβίαξ ημοξ εα πνδζζιεφεζ ςξ αάζδ ακαθμνάξ βζα ηδκ πεναζηένς αεθηίςζδ ηςκ ζοκεδηχκ ενβαζίαξ, ηδκ οβεία ηαζ ηδκ αζθάθεζα ηαζ εα απμηεθέζεζ έκα ενβαθείμ βζα ηδ ιεβζζημπμίδζδ ηδξ παναβςβήξ ζε ζοκδοαζιυ ιε ηδ ιείςζδ ηςκ αηοπδιάηςκ ζημ πχνμ ενβαζίαξ. Λέλεζξ-ηθεζδζά: οδαημηαθθζένβεζα, ηίκδοκμζ, οβζεζκή, αζθάθεζα ζηδκ ενβαζία, Δθθάδα *οββναθέαξ επζημζκςκίαξ: Σοθζβάδαξ Ζ., Δπζεεςνδηήξ Δνβαζίαξ Αζθάθεζαξ ηαζ Τβείαξ Τ.Δ.Κ.Α.Π.-.ΔΠ.Δ.-Κ.ΔΠ.Δ.Κ. Πεζναζά ηαζ Νμηίμο Αζβαίμο, ηαζ, Πνυεδνμξ Γ.. Πακεθθήκζμο οθθυβμο Σεπκμθυβςκ Ηπεομθυβςκ (ΠΑ..Σ.Η.), tililias@otenet.gr. 1. Δηζαγσγή Ο ημιέαξ ηςκ εαθάζζζςκ οδαημηαθθζενβεζχκ (ΘΤ) ζηδκ Δθθάδα επέδεζλε ιζα ηαπφηαηδ ακάπηολδ ηαηά ηδκ ηεθεοηαία 25εηία ιε ηδκ παναβςβή κα θεάκεζ ζημοξ ηυκμοξ ημ 2011, εκχ ιζα ηνζπθάζζα αφλδζδ ακαιέκεηαζ ζηα επυιεκα πνυκζα. Πανάθθδθα, μζ έκημκμζ αοημί νοειμί ακάπηολδξ αολάκμοκ ημκ ανζειυ ηςκ ενβαζζχκ ζηζξ ιμκάδεξ πμο ζπεηίγμκηαζ ιε ηζξ επζπηχζεζξ ζημ εζςηενζηυ ηςκ ενβαγμιέκςκ απυ ηζξ βεςνβζηέξ αζμιδπακίεξ. ε πνμδβμφιεκδ ενβαζία (Σοθζβάδαξ ηαζ Μμοηυπμοθμξ 2013) επζπεζνήεδηε ιζα πνχηδ πενζβναθζηή ακάθοζδ ημο ανζειμφ ηςκ αηοπδιάηςκ βζα ηδκ πενίμδμ ηδκ πανμφζα ενβαζία έβζκε επζηαζνμπμίδζδ ηςκ δεδμιέκςκ ιε αοηά ηδξ πενζυδμο ηαζ ακαθφεδηακ μζ πανάιεηνμζ πμο μδδβμφκ ζημ κα ακαπηοπεεί ή/ηαζ κα εηδδθςεεί ιία επζηίκδοκδ ηαηάζηαζδ ζε αηφπδια. Δζδζηυηενα, βίκεηαζ ιζα: (α) δζενεφκδζδ ηδξ ηάζδξ ηςκ αηοπδιάηςκ ζηζξ ΘΤ ηαηά ηδ δζάνηεζα ηςκ ηεθεοηαίςκ πέκηε εηχκ ( ), (α) ακάπηολδ ηδξ ηοπμθμβίαξ ηςκ αηοπδιάηςκ ιε αάζδ ημκ ηφπμ ημο αηοπήιαημξ, ηδκ επμπζηυηδηά ημοξ, ηδ πςνζηή ημοξ ηαηακμιή ηαζ ηα ημζκςκζηά παναηηδνζζηζηά ηςκ ενβαγμιέκςκ ηαζ (β) ιζα ζοζπέηζζδ ηςκ αθθαβχκ ζηζξ ηάζεζξ ηςκ ηφπςκ αηοπδιάηςκ ιε ηδ βναιιή παναβςβήξ. Σα ζημζπεία ηςκ ενβαηζηχκ αηοπδιάηςκ ζηζξ ΘΤ βζα ηδκ πενίμδμ πνζκ ημ 2009 δεκ ήηακ δοκαηυ κα ακαθοεμφκ, ηαεχξ ηα παναπάκς δεδμιέκα ηαηαβνάθμοκ ιαγί ηζξ πενζπηχζεζξ αηοπδιάηςκ ζε ζοζηεοαζηήνζα ηαζ ιεηαπμζδηζηέξ ιμκάδεξ αβνμηζηχκ ηαζ εαθαζζίςκ πνμσυκηςκ. 2. Τιηθά θαη Μέζνδνη Σα δεδμιέκα πνμήθεακ απυ ηζξ εηήζζεξ εηεέζεζξ ημο χιαημξ Δπζεεχνδζδξ Δνβαζίαξ ημο Τπμονβείμο Δνβαζίαξ ηαζ δ ιεεμδμθμβία πμο αημθμοεήεδηε ζηδνίγεηαζ ζηα πνυηοπα πμο ηαεμνίγμκηαζ απυ ηδκ Eurostat (ESAW: Δονςπασηέξ ζηαηζζηζηέξ βζα ηα ενβαηζηά αηοπήιαηα 2001). Ζ ακάθοζδ ηςκ δεδμιέκςκ ηςκ ενβαηζηχκ αηοπδιάηςκ πενζεθάιαακε ηδ δζενεφκδζδ: (α) ηδξ φπανλδξ ηάζδξ, (α) επμπζημφ ηαζ ςνζαίμο 51

52 πνμηφπμο, (β) παναηηδνζζηζηχκ ηδξ επζπείνδζδξ (ανζειυξ ενβαγμιέκςκ), (δ) θφζδ ημο αηοπήιαημξ (θφζδ ηςκ ηαηχζεςκ ηαζ ιένμξ ημο ζχιαημξ) ηαζ (ε) ζοζπέηζζδξ ιε ημζκςκζηά παναηηδνζζηζηά ηςκ ενβαγμιέκςκ (θφθμ, εεκζηυηδηα, δθζηζαηή μιάδα). Γζα ηδκ ηςδζημπμίδζδ ηςκ παναιέηνςκ πμο ιεθεηήεδηακ αημθμοεήεδηε δ ηςδζημπμίδζδ πμο ακαθένεηαζ ζηδ ιεεμδμθμβία βζα ηα ενβαηζηά αηοπήιαηα απυ ηδκ Eurostat. Ζ ακάθοζδ ηςκ δεδμιέκςκ πενζεθάιαακε ηδκ εηηίιδζδ ζοπκμηήηςκ βζα ηάεε ιζα απυ ηζξ παναπάκς παναιέηνμοξ ζημ ζφκμθμ ημο δείβιαημξ εκχ έβζκε ηαζ έθεβπμξ ακελανηδζίαξ (Zar, 1999) ιε ηδ π 2 ηαηακμιή (Likelihood-ratio π 2 ), βζα ηζξ πενζπηχζεζξ ζοβηνίζεςκ ηςκ παναιέηνςκ πμο αθμνμφζακ ηα ενβαηζηά αηοπήιαηα ιε ηα ημζκςκζηά παναηηδνζζηζηά ηςκ ενβαγμιέκςκ. Ζ ζφβηνζζδ ηςκ ηθίζεςκ ηδξ ιεηααμθήξ ημο ανζειμφ ηςκ αηοπδιάηςκ ιε ημ θφθμ έβζκε ιε ηδκ ακάθοζδ ζοιιεηααθδηυηδηαξ (ANCOVA) (Zar, 1999). 3. Απνηειέζκαηα οκμθζηά 221 ενβαηζηά αηοπήιαηα έθααακ πχνα ζηζξ εθθδκζηέξ εαθάζζζεξ οδαημηαθθζένβεζεξ ηδκ πενίμδμ , ιε ημ ιέζμ εηήζζμ ανζειυ ηςκ αηοπδιάηςκ κα είκαζ 44,2 (ηοπζηή απυηθζζδ 5,5) ηαζ ιε ηα εακαηδθυνα αηοπήιαηα κα ακηζπνμζςπεφμοκ έκα ζοκηνζπηζηά εθάπζζημ πμζμζηυ ημο ζοκυθμο ηςκ αηοπδιάηςκ (7 αηοπήιαηα: 3,2%). Ζ ηάζδ ημο ζοκμθζημφ ανζειμφ ηςκ αηοπδιάηςκ ιεζχκμκηακ ζδιακηζηά (P>0,05) ιέζα ζημ πνυκμ (Δζηυκα 1α), ιε ηδκ ηάζδ κα είκαζ ζδιακηζηή ηαζ κα έπεζ ηδκ ίδζα έκηαζδ ιείςζδξ (ANCOVA, P>0,05) ηαζ ζηα δφμ θφθα. Ο ανζειυξ ηςκ αηοπδιάηςκ δεκ αημθμοεμφζε έκα επμπζηυ πνυηοπμ (Δζηυκα 1α) πανά εκημπίγμκηακ ζε ζοβηεηνζιέκμοξ ιήκεξ ηαηά ηδ δζάνηεζα ημο έημοξ (46% ηςκ αηοπδιάηςκ εκημπίγμκηακ ηαηά ημοξ ιήκεξ Ημφθζμ, επηέιανζμ, Οηηχανζμ ηαζ Γεηέιανζμ), εκχ ηα εθάπζζηα εακαηδθυνα αηοπήιαηα θάιαακακ πχνα ηονίςξ ηδκ άκμζλδ (Μάνηζμξ-Μάζμξ). Σμ ζφκμθμ ηςκ εακαηδθυνςκ αηοπδιάηςκ αθμνμφζε απμηθεζζηζηά άκδνεξ ενβαγμιέκμοξ δθζηίαξ απυ 18 έςξ 44 εηχκ, εκχ ζημοξ ηναοιαηζζιμφξ ημ 70,6% ηςκ πενζπηχζεςκ αθμνμφζε άκδνεξ ηαζ ημ οπυθμζπυ βοκαίηεξ ενβαγυιεκμοξ (Πίκαηαξ 1). Ζ δθζηζαηή μιάδα ιε ημ ιεβαθφηενμ πμζμζηυ ηναοιαηζζιχκ ήηακ ακάιεζα ζηα πνυκζα, ιε ημ ιεβαθφηενμ πμζμζηυ ηςκ ηναοιαηζζιχκ ηαζ ζηα δομ θφθα (>75%) κα αθμνμφκ ενβαγυιεκμοξ δθζηίαξ απυ 35 έςξ 54 εηχκ, εκχ ηα πμζμζηά αοηά δε δζέθενε ζδιακηζηά (P>0,05) ιε ημ θφθμ (Πίκαηαξ 1). Πενζζζυηενμ απυ ημ 80% ηςκ αηοπδιάηςκ έβζκακ ζε έθθδκεξ ενβαγυιεκμοξ (Πίκαηαξ 1) ηαζ ζε ιζηνυηενμ πμζμζηυ αημθμοεμφζακ μζ αθθμδαπμί ενβαγυιεκμζ πνμενπυιεκμζ εηηυξ ηδξ ΔΔ (13,6%). Ο ανζειυξ ηςκ ηναοιαηζζιχκ ακά εεκζηυηδηα δζέθενε ζδιακηζηά (P<0,05) ιε ημ θφθμ, ιε ημοξ άκδνεξ αθθμδαπμφξ ενβαγυιεκμοξ πνμενπυιεκμοξ εηηυξ ΔΔ κα ηναοιαηίγμκηαζ ζε ιεβαθφηενμ πμζμζηυ απυ ηζξ βοκαίηεξ (Πίκαηαξ 1). Ακαθμνζηά ιε ηδ εέζδ ενβαζίαξ, ημ ζφκμθμ ηςκ εακαηδθυνςκ αηοπδιάηςκ ηαζ ημ ζοκηνζπηζηυ πμζμζηυ ηςκ ηναοιαηζζιχκ ηαηαβνάθδηε ζε ενβαγυιεκμοξ ιε ζοκήεδ εέζδ ενβαζίαξ Ζ εέζδ ενβαζίαξ δζαθμνμπμζμφκηακ ζδιακηζηά (P<0.05) ιε ημ θφθμ, ιε ημοξ άκδνεξ ενβαγυιεκμοξ ζε πενζζηαζηζαηή ή ηζκδηή εέζδ ενβαζίαξ κα ηναοιαηίγμκηαζ ζε ιεβαθφηενμ πμζμζηυ απυ υηζ μζ βοκαίηεξ ενβαγυιεκεξ. Πενζζζυηενμ απυ ηζξ ιζζέξ πενζπηχζεζξ ηςκ εακαηδθυνςκ αηοπδιάηςκ έθααακ πχνα ζε επζπεζνήζεζξ ιε ζοκμθζηυ ανζειυ αηυιςκ απυ 10 έςξ 49 άημια, ιε ημοξ άκδνεξ ενβαγυιεκμοξ κα επζδεζηκφμοκ ιεβαθφηενα πμζμζηά ηναοιαηζζιχκ ζηζξ επζπεζνήζεζξ ιε ανζειυ αηυιςκ απυ 10 έςξ 49 ηαζ ηζξ βοκαίηεξ ζηζξ επζπεζνήζεζξ ιε 1 έςξ 9 ενβαγυιεκμοξ (Πίκαηαξ 1). Καηά ηδκ πνςζκή αάνδζα ενβαζίαξ (6 π.ι. έςξ 2 ι.ι.) θάιαακε πχνα πενζζζυηενμ απυ ημ 85% ηςκ εακαηδθυνςκ αηοπδιάηςκ ηαζ ημ 75% ηςκ ηναοιαηζζιχκ (Δζηυκα 1β), ιε ημ θφθμ κα ιδ δζαθμνμπμζεί ζδιακηζηά (P<0,05) ημκ ανζειυ ηςκ ηναοιαηζζιχκ ακά χνα αηοπήιαημξ (Πίκαηαξ 1). ημ 71% ηςκ εακαηδθυνςκ πενζπηχζεςκ ήηακ άβκςζηδ δ θφζδ ηδξ ηάηςζδξ, εκχ ζηζξ πενζπηχζεζξ ηςκ ηναοιαηζζιχκ ημ ιεβαθφηενμ πμζμζηυ ηαζ ζηα δφμ θφθα ηαηαβνάθμκηακ βζα επζθακεζαηέξ ηαηχζεζξ ηαζ ζε ιζηνυηενα πμζμζηά ζε ακμζπηά ηναφιαηα ηαζ απθά ηαηάβιαηα. Ζ ζφβηνζζδ ημο ανζειμφ ηςκ ηναοιαηζζιχκ ακά θφζδ ηάηςζδξ ζε ζοκάνηδζδ ιε ημ θφθμ έδεζλε υηζ δεκ οπήνπε ζδιακηζηή (P>0,05) δζαθμνά ιε ημ θφθμ (Πίκαηαξ 1). Απυ ηζξ πενζπηχζεζξ πμο είπε πνμζδζμνζζηεί δ θφζδ ηδξ ηάηςζδξ, ημ ιεβαθφηενμ πμζμζηυ (11,9 ηαζ 12,7%) ηαηαβνάθδηε βζα ηαηχζεζξ ζηα δάπηοθα ηςκ πενζχκ, εκχ ηα πμζμζηά δζαθμνμπμζμφκηακ ζδιακηζηά 52

53 (P<0,05) ιε ημ θφθμ. Έηζζ, μζ βοκαίηεξ ενβαγυιεκεξ ειθάκζζακ ζδιακηζηά ιεβαθφηενα πμζμζηά ηναοιαηζζιχκ ζημ άηνμ ημο πενζμφ, ημοξ μθεαθιμφξ, ημ ζζπίμ ηαζ ηδκ ηεθαθή, εκχ μζ άκδνεξ ζημκ αζηνάβαθμ, ζηδκ ηκήιδ, ζημ εχναηα ηαζ ημ πνυζςπμ (Πίκαηαξ 1). 4. πδήηεζε ηδκ πανμφζα ενβαζία βίκεηαζ, βζα πνχηδ θμνά, ιζα απμηφπςζδ ηδξ ηοπμθμβίαξ ηςκ ενβαηζηχκ αηοπδιάηςκ πμο έθααακ πχνα ζηζξ εθθδκζηέξ εαθάζζζεξ οδαημηαθθζένβεζεξ ηδκ πενίμδμ , δ μπμία απμηεθεί ζοκέπεζα πνμδβμφιεκδξ ακαθμνάξ ζημ ίδζμ εέια (Σοθζβάδαξ ηαζ Μμοηυπμοθμξ. 2014). Σα απμηεθέζιαηα έδεζλακ ζε πνχημ επίπεδμ υηζ οπάνπεζ ιζα πηςηζηή ηάζδ ημο ανζειμφ ηςκ αηοπδιάηςκ ηαζ υηζ μ ανζειυξ ηςκ εακαηδθυνςκ πενζζηαηζηχκ είκαζ παιδθυξ. Οζ εηηζιήζεζξ ηςκ 44 αηοπδιάηςκ ηαηά ιέζμ υνμ ακά έημξ ηαζ ημο ανζειμφ ηςκ εακαηδθυνςκ αηοπδιάηςκ ακηζπνμζςπεφμοκ έκα ιζηνυ πμζμζηυ (< 3 ημζξ πζθίμζξ) ημο ζοκυθμο ηςκ αηοπδιάηςκ ζημοξ έθθδκεξ ενβαγυιεκμοξ, αθθά έκα ιεβάθμ πμζμζηυ ηςκ αηοπδιάηςκ ζημκ ημιέα ηδξ βεςνβίαξ (ιεβαθφηενμ απυ ημ 25%) (Σοθζβάδαξ ηαζ Μμοηυπμοθμξ, 2013). ηζξ πενζπηχζεζξ ηςκ παναιέηνςκ μζ μπμίεξ δζαθμνμπμζμφκηακ ςξ πνμξ ημ θφθμ πνέπεζ κα ακαθενεεί υηζ μζ άκδνεξ ενβαγυιεκμζ απμηεθμφκ ηδκ απυθοηδ πθεζμρδθία ηςκ ενβαγμιέκςκ ζηζξ πθςηέξ ιμκάδεξ παναβςβήξ, υπςξ απαζηείηαζ απυ ημοξ ελακηθδηζημφξ νοειμφξ ενβαζίαξ ζηζξ εαθάζζζεξ οδαημηαθθζένβεζεξ, εκχ μζ βοκαίηεξ θυβς ηδξ ζπμθαζηζηυηδηαξ πμο ηζξ δζαηνίκεζ απμηεθμφκ ηδκ πθεζμρδθία ζημοξ ζηαειμφξ παναβςβήξ ζηδκ λδνά ηαζ ηα ζοζηεοαζηήνζα κςπχκ ή ηαζ ιεηαπμζδιέκςκ εαθάζζζςκ πνμσυκηςκ, ακελάνηδηα ημο ιεβέεμοξ ηδξ εηαζνείαξ. Πανυθα αοηά, μζ άκδνεξ ενβαγυιεκμζ ζε ιζηνέξ επζπεζνήζεζξ ηάης 10 αηυιςκ ειθακίγμοκ ιζηνυηενα πμζμζηά ηναοιαηζζιχκ απυ ηζξ βοκαίηεξ, ιε ηδκ επζθφθαλδ ηδξ εεχνδζδξ ςξ λεπςνζζηχκ εβηαηαζηάζεςκ ηδξ ίδζαξ επζπείνδζδξ ημοξ πχνμοξ ζημοξ μπμίμοξ ηαηαβνάθδηακ ηα αηοπήιαηα. Απυ ηα απμηεθέζιαηα ηδξ πανμφζαξ ένεοκαξ βίκεηαζ θακενυ υηζ μζ άκδνεξ ενβαγυιεκμζ έπμοκ οπενδζπθάζζμ ανζειυ αηοπδιάηςκ ηαζ είκαζ ηα απμηθεζζηζηά εφιαηα ηςκ εακαηδθυνςκ ελ αοηχκ. Ακελάνηδηα ηδξ δθζηζαηήξ μιάδαξ ζηδκ μπμία ακήημοκ άκδνεξ ηαζ βοκαίηεξ, μζ ενβαγυιεκμζ δείπκμοκ εοάθςημζ ζηζξ δθζηίεξ έηδ ζοκδβμνχκηαξ ζηδκ οπυεεζδ υηζ δ ενβαζία ζηζξ οδαημηαθθζένβεζεξ είκαζ απαζηδηζηή ηαζ πνεζάγεηαζ ζοκεπήξ εηπαίδεοζδ ηαζ επίαθερδ ηαηά ηδκ εηηέθεζδ αοηήξ (Hatzakis 2005), αθμφ μζ πενζζζυηενμζ ηναοιαηζζιμί αθμνμφκ ενβαγυιεκμοξ μζ μπμίμζ δναζηδνζμπμζμφκηαζ ζε παναπάκς απυ ηδ ιζα εέζδ ενβαζίαξ (πενζζηαζζαηή ή ηζκδηή εέζδ ενβαζίαξ). Με ηδκ παναδμπή ηδξ 24ςνδξ θεζημονβίαξ ηδξ επζπείνδζδξ, θυβς ηδξ ζοκηήνδζδξ ηαζ δζάεεζδξ γςκηακχκ μνβακζζιχκ οπάνπεζ έκα δζάζηδια ιεηαλφ 9 ημ πνςί ηαζ 3 ημ ιεζδιένζ υπμο είκαζ ζφκδεεξ κα ζοιααίκμοκ αηοπήιαηα εκηυξ ημο ςνανίμο ενβαζίαξ ηςκ πενζζζυηενςκ ενβαγυιεκςκ. διεζχκεηαζ υηζ μζ αάνδζεξ, εηηυξ ηςκ πνςζκχκ, ζηζξ οδαημηαθθζένβεζεξ, απακηχκηαζ ηφνζα ηαηά ηδ δζαδζηαζία ηδξ ζοζηεοαζίαξ ή/ηαζ ηδξ ιεηαπμίδζδξ ημο πνμσυκημξ, ημ μπμίμ έπεζ αθζεοεεί κςνίηενα ηδκ ίδζα διένα. Δπίζδξ, αμδεδηζηέξ ενβαζίεξ, υπςξ μ εθμδζαζιυξ ιε ηνμθέξ ή άθθμ ελμπθζζιυ πμο ζοκήεςξ βίκεηαζ εηηυξ πνςζκήξ αάνδζαξ θαίκεηαζ κα ζοκδβμνμφκ ιε ηα αηοπήιαηα ηαηά ηζξ απμβεοιαηζκέξ χνεξ. Σμ επμπζηυ πνυηοπμ πμο πενζβνάθδηε ιπμνεί κα μθείθεηαζ ζηδκ εκηαηζημπμίδζδ ημο ηφηθμο παναβςβήξ ηςκ επζπεζνήζεςκ (εζζαβςβή ζε ηθςαμφξ - εηηνμθή - ελαθίεοζδ - ενβαζίεξ ζοκηήνδζδξ) ηαηά ημοξ ακηίζημζπμοξ ιήκεξ (ηαθμηαζνζκμφξ ιήκεξ: Dimitriou et al. 2007). Σμ είδμξ ημο ηναοιαηζζιμφ ηαζ ημ ιένμξ ημο ζχιαημξ πμο ζοκήεςξ επδνεάγεηαζ δείπκεζ κα ζοκδβμνεί ζηδ ζπεηζηά αανζά ζςιαηζηή ενβαζία ηυζμ βζα ημοξ άκηνεξ υζμ ηαζ βζα ηζξ βοκαίηεξ ενβαγυιεκμοξ (Zakia et al. 2012), υπμο μ δζαπςνζζιυξ ηςκ εέζεςκ ενβαζίαξ ιεηαλφ ημοξ, υπςξ ακαθένεδηε, μδδβεί ημοξ ιεκ άκδνεξ ζε πμθθαπθμφξ ηναοιαηζζιμφξ ηζξ δε βοκαίηεξ ζε ηαηχζεζξ (ηονίςξ 'ημρίιαηα') ηςκ άηνςκ ηαζ ζδζαίηενα ηςκ δαηηφθςκ ηςκ πενζχκ. Έηζζ μζ άκδνεξ ηναοιαηίγμκηαζ εκ δοκάιεζ ζε υθμ ημ ζχια μζ δε βοκαίηεξ ηφνζα ζηα άηνα ηαζ ηδκ ιέζδ. Σα πνμδβμφιεκα ζοκδβμνμφκ βζα ηδκ πνήζδ πμθθαπθχκ ελμπθζζιχκ ενβαζίαξ απυ ημοξ άκδνεξ ηαζ ζδζαίηενα ηαζ εζδζηυηενα απυ ηζξ βοκαίηεξ. 53

54 Αριθμός αηστημάηων HydroMedit 2014, November 13-15, Volos, Greece Βηβιηνγξαθία Dimitriou E., Katselis G., Moutopoulos D.K, Akovitiotis C., Koutsikopoulos C. (2007). Possible influence of reared gilthead sea bream (Sparus aurata, L.) on wild stocks in the area of the Messolonghi lagoon (Ionian Sea, Greece). Aquaculture Research 38(4): Δονςπασηή Δπζηνμπή (2001). Δονςπασηέξ ζηαηζζηζηέξ ζπεηζηά ιε ηα ενβαηζηά αηοπήιαηα. Hatzakis K.D., Kritsotakis E.I., Angelaki H.P., Tzanoudaki I.K., Androulaki Z.D. (2005). First aid knowledge among industry workers in Greece. Industrial Health, 43: Σοθζβάδαξ Ζ., Μμοηυπμοθμξ Γ.Κ. (2013). Δθθδκζηέξ Θαθαζζμηαθθζένβεζεξ: ηνέπμοζα ηαηάζηαζδ ενβαηζηχκ αηοπδιάηςκ. Τβζεζκή ηαζ Αζθάθεζα ηδξ Δνβαζίαξ. Έηδμζδ ημο Δθθδκζημφ Ηκζηζημφημο Τβζεζκήξ ηαζ Αζθάθεζαξ Δνβαζίαξ-ΔΛΗΝΤΑΔ, 53: Zakia A.M.Α, Dosiki M.I., Nasr S.A.A. (2012) Occupational Hazards in fish industry. World Journal of Fish and Marine Sciences, 4(2): Zar J. (1999): Biostatistical Analysis. 4 th Edition. Prentice Hall, New Jersey. 663 ζεθ. 60 (α) 30 Σύνολο Άνδρες Γσναίκες Έηος N=35,8-1,4t R² = 0,210 N=52,3-2,7t R² = 0,614 N=16,5-1,3t R² = 0, (β) Φεβροσάριος Μάρηιος Απρίλιος Μάιος Δηθφλα 1. Αξηζκφο εξγαηηθψλ αηπρεκάησλ ζηηο ειιεληθέο πδαηνθαιιηέξγεηεο ηελ πεξίνδν ζε ρξνληθή θιίκαθα: (α) εηψλ, (β) κελψλ θαη (γ) σξψλ εξγαζίαο. Ιούνιος Ιανοσάριος Ιούλιος Δεκέμβριος Αύγοσζηος Νοέμβριος Οκηώβριος Σεπηέμβριος (γ) Πίλαθαο 1. Αξηζκφο αηφκσλ ζαλαηεθφξσλ αηπρεκάησλ θαη ηξαπκαηηζκψλ αλά θαηεγνξία παξακέηξσλ γηα ην ζχλνιν ησλ εξγαηηθψλ αηπρεκάησλ ζηηο ειιεληθέο πδαηνθαιιηέξγεηεο ηελ πεξίνδν Οη ηηκέο ρ2-test αληηζηνηρνχλ ζην Likelihood-ratio ρ 2, φπνπ γηα ηηκέο P<0,05 ν έιεγρνο ππνδεηθλχεη ζηαηηζηηθά ζεκαληηθή δηαθνξνπνίεζε. Παξάκεηξνη Άλδξαο Γπλαίθα ρ2-test χλνιν Θακαηδθυνμ Σναοιαηζζιυξ Σναοιαηζζιυξ Ζιηθηαθή νκάδα π 2 =13, df= p=0,20 23 > Δζληθφηεηα π 2 =227,4 Eεκζηυηδηα ιδ ζαθςξ πνμζδζμνζγυιεκδ Αθθμδαπυξ, πνμενπυιεκμξ απυ ηδκ ΔΔ df=6 Αθθμδαπυξ, πνμενπυιεκμξ εηηυξ ηδξ ΔΔ Ζιεδαπυξ Θέζε εξγαζίαο π 2 p=0,00 =230,1 Άθθδ εέζδ ενβαζίαξ 1 1 Μδ πνμζδζμνζγυιεκδ df=8 Πενζζηαζζαηή ή ηζκδηή εέζδ ενβαζίαξ οκήεδξ εέζδ ενβαζίαξ πλνιηθφο αξηζκφο εξγαδνκέλσλ επηρείξεζεο π 2 p=0,00 =116, df= >500 2 p=0,00 2 Ώξα αηπρήκαηνο π 2 =21, df= p=0,

55 (ζπλερίδεηαη) Πίλαθαο 1 (ζπλέρεηα) Παξάκεηξνη Άλδξαο Γπλαίθα ρ2-test χλνιν Θακαηδθυνμ Σναοιαηζζιυξ Σναοιαηζζιυξ Φχζε θάθσζεο Αηνςηδνζαζιμί 3 3 Άθθα είδδ ελανενδιάηςκ, δζαζηνειιάηςκ ηαζ 1 1 Ακμζηηά ηναφιαηα Απθά ηαηάβιαηα Γζαζηνέιιαηα ηαζ ελανενχζεζξ 8 1 π 2 =15,3 9 Δβηαφιαηα ηαζ γειαηίζιαηα Δλανενήιαηα ηαζ αηεθείξ ελανενχζεζξ 1 1 Δλανενήιαηα, δζαζηνέιιαηα ηαζ ελανενχζεζξ 1 df=16 1 Δπζθακεζαηέξ ηαηχζεζξ Δζςηενζηέξ ηαηχζεζξ 3 3 p=0,50 6 Καηάβιαηα Πμθθαπθέξ ηαηχζεζξ 1 1 φκεεηα ηαηάβιαηα 3 3 Σναφιαηα ηαζ επζθακεζαηέξ ηαηχζεζξ Υδιζηά εβηαφιαηα Άθθεξ πνμζδζμνζγυιεκεξ ηαηχζεζξ 1 1 Άβκςζηδ θφζδ ηάηςζδξ ιδ πνμζδζμνζγυιεκδ Μέξνο ζψκαηνο θάθσζεο π 2 =45,7 Βναπίμκαξ ζοιπενζθαιαακμιέκμο ημο αβηχκα Ηζπίμ ηαζ ηαηά ζζπίμκ δζάνενςζδ 3 3 df=29 Κεθαθή, εβηέθαθμξ ηαζ ηνακζαηά κεφνα ηαζ αββεία Κεθαθή, ιδ ζαθέζηενα ηαεμνζγυιεκδ 1 1 Κκήιδ, ζοιπενζθαιαακμιέκμο ημο βυκαημξ 10 2 p=0,03 12 Κμνιυξ ηαζ υνβακα, ιδ ζαθέζηενα ηαεμνζγυιεκα 2 2 Λαζιυξ, ζπμκδοθζηήξ ζηήθδξ ηαζ αοπεκζηχκ ζπμκδφθςκ Πνυζςπμ Ράπδ, άθθα ιένδ 1 1 Ράπδ, ζπμκδοθζηήξ ζηήθδξ ηαζ ναπζαίςκ ζπμκδφθςκ Γάπηοθα πενζμφ Άκς άηνα, άθθα ιένδ 1 1 Αζηνάβαθμξ Θχναηαξ, πθεονέξ, ςιμπθάηδξ ηαζ δζάνενςζδξ χιμο 6 6 Κάηςζδ ζε πμθθά ζδιεία ημο ζχιαημξ Ώιμξ ηαζ δζανενχζεζξ ημο χιμο Κανπυξ Γάπηοθα πμδζμφ 3 3 Κάης άηνα, ηάηςζδ ζε πμθθά ζδιεία Άηνμ ημο πενζμφ Άηνμ ημο πμδζμφ 6 6 Κάης άηνα, άθθα ιένδ 1 1 Οθεαθιμί Άκς άηνα, ιδ ζαθέζηενα ηαεμνζγυιεκα 2 2 Κεθαθή, ηάηςζδ ζε πμθθά ζδιεία 2 2 Θςναηζηή ιμίνα, ζοιπενζθαιαακμιέκςκ ηςκ μνβάκςκ 1 1 Κάης άηνα, ιδ ζαθέζηενα ηαεμνζγυιεκα 1 1 Κεθαθή, άθθα ιένδ πμο δεκ ακαθένμκηαζ 1 1 Κμνιυξ, ηάηςζδ ζε πμθθά ζδιεία 1 1 Μδ πνμζδζμνζγυιεκμ ιένμξ ημο ζχιαημξ χλνιν

56 STUDY ON THE SEASONAL ENERGY INVESTMENT IN RED PORGY Pagrus pagrus (Linnaeus, 1758) Porlou D. 1*, Athanasiou D. 1, Vlachonikola E. 1, Nathanailides C. 2, Karayannakidis P. 3, Chatziantoniou S. 3, Karapanagiotidis I. 4, Michaelidis B. 1 1 Laboratory of Animal Physiology, Department of Zoology, School of Biology, Faculty of Science, Aristotle University of Thessaloniki, Thessaloniki, Greece 2 Department of Fisheries and Aquaculture Technology, Technological Educational Institute of West Greece, Messolonghi, Greece 3 Technology and Quality Control of Fish and Fish Products Laboratory, Department of Food Technology, Alexander Technological Educational Institute of Thessaloniki, P.O. Box 141, Thessaloniki, Greece 4* Department. of Agriculture, Ichthyology and Aquatic Environment, University of Thessaly, Volos, Greece ABSTRACT During this ongoing project we examined the seasonal energy investment in Pagrus pagrus (Linnaeus, 1758). Fish samplings (4) from an aquaculturestation in Evia Gulf, took place from November 2013 until June At each sampling 20 fish were collected, main biometric parameters (total weight, fork length, liver weight, gonad weight) were recorded and finally fish were dissected for the isolation of several tissues (heart, liver, spleen, gonads, white and red muscle). Tissues were immediately frozen in liquid nitrogen. Samples were kept at 80μC for further analysis. % Protein in liver, red and white muscle was quantified by the Kjeldahl method. Furthermore glycogen, total lipid levels and fatty acids profile were quantified. Fatty acids profile was prepared as described by Karayannakidis et al. (2008). Of the main energy sources, glycogen and lipids showed a seasonal pattern. Glycogen levels increased significantly at the end of the breeding period, while fatty acids levels decreased. Protein levels did not show significant differences in the seasonal pattern. Key words: Red porgy, Energy investment *Corresponding author: Porlou Despoina (dporlou@bio.auth.gr) ΜΔΛΔΣΖ ΣΖ ΔΠΟΥΗΑΚΖ ΔΝΔΡΓΔΗΑΚΖ ΔΠΔΝΓΤΖ ΣΟ ΦΑΓΓΡΗ PAGRUS PAGRUS (LINNAEUS, 1758) Ποπλού Γ. 1, Αθαναζίος Γ. 1, Βλασονικόλα Δ. 1, Ναθαναηλίδηρ K. 2, Καπαγιαννακίδηρ Π. 3, Χαηζηανηωνίος Σ. 3, Καπαπαναγιωηίδηρ Ι. 4, Μισαηλίδηρ Β. 1 1 Δνβαζηήνζμ Φοζζμθμβίαξ Εχςκ, Σιήια Βζμθμβίαξ, πμθή Θεηζηχκ Δπζζηδιχκ, Ανζζημηέθεζμ Πακεπζζηήιζμ Θεζζαθμκίηδξ, Πακεπζζηδιζμφπμθδ Θεζζαθμκίηδ, Δθθάδα 2 Σιήια Σεπκμθυβςκ Αθζείαξ ηαζ Τδαημηαθθζενβεζχκ, Σεπκμθμβζηυ Δηπαζδεοηζηυ Ίδνοια Γοηζηήξ Δθθάδαξ, Μεζμθυββζ, Δθθάδα 3 Σιήια Σεπκμθμβίαξ Σνμθίιςκ. Αθελάκδνεζμ Σεπκμθμβζηυ Δηπαζδεοηζηυ Ίδνοια Θεζζαθμκίηδξ. 141 Θεζζαθμκίηδ, Δθθάδα 4 Σιήια Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ, Πακεπζζηήιζμ Θεζζαθίαξ, Φοηυημο 38446, Νέα Ηςκία, Βυθμξ, Δθθάδα Πεξίιεςε ηδκ πανμφζα ενβαζία, πανμοζζάγμκηαζ απμηεθέζιαηα ζπεηζηά ιε ημ επμπζηυ πνυηοπμ ηδξ εκενβεζαηήξ επέκδοζδξ ηαζ ηδξ ιεηααμθήξ ηςκ θζπανχκ μλέςκ ζημ θαββνί Pagrus pagrus (Linnaeus, 1758). Οζ 4 δεζβιαημθδρίεξ έθααακ πχνα απυ ημκ Νμέιανζμ ημο 2013 ιέπνζ ημκ Ημφκζμ ημο 2014 ζε 56

57 ζπεομηαθθζένβεζα ζημκ Δοαμσηυ Κυθπμ. ε ηάεε δεζβιαημθδρία ζοθθέπεδηακ 20 άημια, βζα ηα μπμία ηαηαβνάθδηακ μζ ηονζυηενεξ αζμιεηνζηέξ πανάιεηνμζ (μθζηυ αάνμξ, ιεζμοναίμ ιήημξ, αάνμξ ήπαημξ, αάνμξ βμκάδςκ) ηαζ πναβιαημπμζήεδηε ακαημιία (ηανδζάξ, ήπαημξ, ζπθήκαξ, βμκάδςκ, θεοημφ ηαζ ενοενμφ ιο). Σα δείβιαηα δζαηδνήεδηακ ζημοξ - 80 μ C βζα ιεθθμκηζηή πνήζδ. ημοξ ζζημφξ ημο ήπαημξ, ημο ενοενμφ ηαζ ημο θεοημφ ιο πναβιαημπμζήεδηε μ πμζμηζηυξ πνμζδζμνζζιυξ ηςκ πνςηεσκχκ ιε ηδ ιέεμδμ Kjeldahl, μ πνμζδζμνζζιυξ ημο βθοημβυκμο, δ ιέηνδζδ ημο μθζημφ πμζμζημφ ηςκ θζπζδίςκ ηαεχξ ηαζ ημ πνμθίθ θζπανχκ μλέςκ. Σμ πνμθίθ θζπανχκ μλέςκ παναζηεοάζηδηε υπςξ πενζβνάθεηαζ απυ ημοξ Karayannakidis et al. (2008). ηδ ηανδζά έβζκε ιυκμ μ πμζμηζηυξ πνμζδζμνζζιυξ ηςκ πνςηεσκχκ. Απυ ηζξ ηφνζεξ πδβέξ εκένβεζαξ, ημ βθοημβυκμ ηαζ ηα θζπίδζα πανμοζίαζακ επμπζηυ πνυηοπμ. Σα επίπεδα ημο βθοημβυκμο αολήεδηακ ζδιακηζηά ζημ ηέθμξ ηδξ ακαπαναβςβζηήξ πενζυδμο, εκχ ακηίεεηα ηα επίπεδα ηςκ θζπανχκ μλέςκ ιεζχεδηακ. Οζ πνςηεΐκεξ δεκ έπμοκ δείλεζ ζδιακηζηέξ δζαθμνέξ ζημ επμπζηυ ημοξ πνυηοπμ. Λέμεηο θιεηδηά : Φαγγξί, Δλεξγεηαθή επέλδπζε οββναθέαξ επζημζκςκίαξ: Πμνθμφ Γέζπμζκα (dporlou@bio.auth.gr) 1. Δηζαγσγή Ζ επμπζαηή ακάπηολδ ηαζ μζ ηφηθμζ απμεήηεοζδξ εκένβεζαξ είκαζ ημζκέξ ιεηαλφ ηςκ ρανζχκ ηαζ ζπεηίγμκηαζ ζε ιεβάθμ ααειυ ιε ηδκ ακαπαναβςβζηή πενίμδμ. Ζ εκένβεζα πμο είκαζ δζαεέζζιδ ζηα ράνζα πνέπεζ κα ηαηακέιεηαζ επμπζηά ζηδκ αφλδζδ, ζηδκ ακάπηολδ ηδξ ζςιαηζηήξ ιάγαξ ηαζ ζηδκ ακαπαναβςβή (Aristizabal 2007). Ζ ακαπαναβςβή επζαάθεζ ζδιακηζηέξ ιεηααμθζηέξ απαζηήζεζξ ζηα ράνζα, ακελάνηδηα απυ ημ πνυηοπμ ακάπηολδξ ηςκ ςμεδηχκ ηαζ ηδκ ηαηακμιή ηςκ πυνςκ (Tyler & Sumpter 1996) Σμ θαββνί Pagrus pagrus (Linnaeus, 1758) ακήηεζ ζηδκ μζημβέκεζα ηςκ Sparidae ηαζ απμηεθεί ζδιακηζηυ είδμξ βζα άιεζδ ιαγζηή εηηνμθή ηαζ είκαζ πνςηυβοκμ ενιαθνυδζημ είδμξ (Froese & Pauly 2014). Ζ ακαπαναβςβζηή ημο πενίμδμξ λεηζκά απυ ημκ Απνίθζμ έςξ ημκ Ημφκζμ ηαζ δ ακαπαναβςβζηή ςνζιυηδηα εκημπίγεηαζ ηαηά ημ ηνίημ έημξ (Cotrina et al. 1994; Kokokiris et al 2001). ηδκ πανμφζα ενβαζία, δίκμκηαζ ζημζπεία ζπεηζηά ιε ημ επμπζηυ πνυηοπμ ηδξ εκενβεζαηήξ επέκδοζδξ ζημ θαββνί, ιε ζημπυ ηδκ δζεοηνίκδζδ ηςκ θοζζμθμβζηχκ ηαζ αζμπδιζηχκ ιδπακζζιχκ ημο είδμοξ ζε ζπέζδ ιε ηδκ επμπζαηή ιεηααμθή ηδξ εενιμηναζίαξ ημο κενμφ. 2. Τιηθά θαη Μέζνδνη Ζ ενβαζία πναβιαημπμζήεδηε ζε ιμκάδα ζπεομηαθθζένβεζαξ ζηδκ πενζμπή Λάνοικα ημο Δοαμσημφ Κυθπμο ηαζ μζ δεζβιαημθδρίεξ πναβιαημπμζμφκηακ ζε επμπζαηή αάζδ ιε έκανλδ ημ Νμέιανζμ ημο Ζ επζθμβή ηςκ διενμιδκζχκ βζα ηζξ δεζβιαημθδρίεξ έβζκε ιε ηνζηήνζμ ηζξ εθάπζζηεξ ηαζ ιέβζζηεξ εενιμηναζίεξ ηςκ οδάηςκ ηδξ πενζμπήξ (18 ιε 22 μ C ακηίζημζπα). ε ηάεε δεζβιαημθδρία απμιαηνφκμκηακ 20 άημια απυ ημοξ ηθςαμφξ, (ιε ιέζμ μθζηυ αάνμξ 400 gr) ηαζ ζηδκ ζοκέπεζα βζκυηακ ιέηνδζδ ημο μθζημφ αάνμοξ ηαζ ημο ιεζμοναίμο ιήημοξ, ηαεχξ ηαζ αζιμθδρία ζφιθςκα ιε ηδ ιέεμδμ Smith & Bell (1964). Αημθμοεμφζε ακαημιία ηςκ ζπεφςκ ηαζ θαιαάκμκηακ δ ηανδζά, ημ ήπαν ηαζ δείβιαηα θεοημφ ηαζ ενοενμφ ιο. Σα δείβιαηα ρφπμκηακ άιεζα ζε οβνυ άγςημ ηαζ ζηδ ζοκέπεζα απμεδηεφμκηακ ζημοξ - 80 μ C βζα πεναζηένς ακαθφζεζξ. Ο πμζμηζηυξ πνμζδζμνζζιυξ ηςκ πνςηεσκχκ πναβιαημπμζήεδηε ιε ηδ ιέεμδμ Kjeldahl πμο ααζίγεηαζ ζηδ ιεηαηνμπή υθςκ ηςκ ιμνθχκ ημο αγχημο ηδξ πνςηεΐκδξ ζε αιιςκζαηά άθαηα, εηηυξ απυ ηα κζηνζηά ζυκηα ηαζ ζηδ ζοκέπεζα βζκυηακ μ πνμζδζμνζζιυ ημοξ (AOAC 1995, Νήηαξ 2004). Ο πμζμηζηυξ πνμζδζμνζζιυξ ηςκ οδαηακενάηςκ έβζκε ιε ηδκ ιέεμδμ ηςκ Seifter et al. (1950) πνδζζιμπμζχκηαξ ακηζδναζηήνζμ ακενυκδξ. Ζ ιέεμδμξ πμο πνδζζιμπμζήεδηε βζα ημκ πνμζδζμνζζιυ ηςκ θζπζδίςκ ηαζ ηςκ θζπανχκ μλέςκ ήηακ αοηή ηςκ Bligh & Dyer (1959) υπςξ ηνμπμπμζήεδηε απυ ημοξ Hanson ηαζ Olley (1963). Ζ ακάθοζδ ηςκ θζπανχκ μλέςκ έβζκε ιε ηδ πνήζδ αένζμο πνςιαημβνάθμο ηαζ ημο θμβζζιζημφ ChromQuest. 3. Απνηειέζκαηα φιθςκα ιε ηα απμηεθέζιαηα πνμηφπηεζ υηζ μζ πνςηεΐκεξ (%) ζημ ήπαν ηοιαίκμκηαζ ζημ 45,7 ηαζ 42 % ιεηαλφ Νμειανίμο ηαζ Ημοκίμο. ημκ ενοενυ ιο πανμοζίαζακ ιία ιζηνή αφλδζδ ιέπνζ ημκ Ηακμοάνζμ (64%) ηαζ ζηδ ζοκέπεζα ιεζχεδηακ. ημκ θεοηυ ιο παναηδνήεδηε ιζα ζηαηζζηζηά 57

58 ζδιακηζηή αφλδζδ ηςκ πνςηεσκχκ ημκ Απνίθζμ ιε πμζμζηυ 92,3% ηαζ ζηδκ ζοκέπεζα ιεζχεδηακ ζηα ανπζηά επίπεδα ημο Νμειανίμο. Σμ ίδζμ πνυηοπμ αθθαβήξ ιε αοηυ ημο θεοημφ ιο παναηδνήεδηε ηαζ ζηδκ ηανδζά (πήια 1) Ήπαρ Λεςκόρ White Muscle μςρ * Πρωτείνες (%) Protein (%) Μήνας δειγματοληψίας Sampling dates 80 Ερσθρός μσς 100 Καπδιά Heart Πρωτείνες (%) Protein (%) Μήλαο Μήνας δεηγκαηνιεςίαο δειγματοληψίας Μήλαο δεηγκαηνιεςίαο Sampling dates ρήκα 1: Πνζνζηφ πξσηετλψλ ήπαηνο, ιεπθνχ, εξπζξνχ κπ θαη θαξδηάο (*P<0,05 ζε ζχγθξηζε κε ηελ πξψηε δεηγκαηνιεςία). Σα επίπεδα ημο βθοημβυκμο ζημ ήπαν έδεζλακ ζδιακηζηή ιείςζδ απυ ημκ Νμέιανζμ (69,2±5,45 ιg/g ζζημφ) έςξ ηδκ άκμζλδ (34±4,36 ιg/g ζζημφ) ηαζ ζηδκ ζοκέπεζα αολήεδηακ ζδιακηζηά έςξ ημκ Ημφκζμ (115,6±4,36 ιg/g ζζημφ). Σμ ίδζμ πνυηοπμ αημθμοεείηαζ ηαζ ζημ θεοηυ ιο, εκχ ζημκ ενοενυ ιο, δ πμζυηδηα βθοημβυκμο αολάκεηαζ ιέπνζ ημκ Ηακμοάνζμ (21,12±3,36 ιg/g ζζημφ), ημκ Απνίθζμ ιεζχκεηαζ (12±2,36 ιg/g ζζημφ), εκχ ημκ Ημφκζμ παναηδνείηαζ έκημκδ αφλδζδ 50,11±6,09 ιg/g ζζημφ ιg (πήια 2). μg Γλσκογόνο Ήπαρ * * * μg Γλσκογόνο Λεσκός μσς * Μήνας δειγματοληψίας Μήνας δειγματοληψίας 58

59 Red muscle μg Γλσκογόνο Ερσθρός μσς * Μήνας δειγματοληψίας ρήκα 2: Απνηειέζκαηα γιπθνγφλνπ ζην ήπαξ, ζην ιεπθφ θαη ηνλ εξπζξφ κπ (*P<0,05 ζε ζχγθξηζε κε ηελ πξψηε δεηγκαηνιεςία). Σα επίπεδα ηςκ θζπζδίςκ έδεζλακ αφλδζδ ζημ ήπαν ιέπνζ ημκ Απνίθζμ ιε πμζμζηυ 34% (αάνμξ θζπζδίςκ/gr ζζημφ), εκχ ημκ Ημφκζμ ιεζχεδηακ ζημ 22,3%. Σμ ίδζμ πνυηοπμ αημθμοεείηαζ ηαζ ζημ θεοηυ ιο ιε πμζμζηυ 27,2% ημκ Απνίθζμ ηαζ 19% ημκ Ημφκζμ. ημκ ενοενυ ιο παναηδνήεδηε αφλδζδ ηςκ θζπζδίςκ ιέπνζ ημκ Ηακμοάνζμ ιε πμζμζηυ 28,9%, εκχ έπεζηα ιεζχεδηακ ζηαδζαηά ζημ 21,5% ημκ Red muscle Red muscle Ημφκζμ (πήια 3) Ήπαρ Λεσκός μσς Λιπίδια (%) Λιπίδια (%) Red muscle Μήνας δειγματοληψίας 40 Ερσθρός μσς Μήνας δειγματοληψίας Λιπίδια (%) Μήνας δειγματοληψίας ρήκα 3: Απνηειέζκαηα ιηπηδίσλ ζην ήπαξ, ζην ιεπθφ θαη ηνλ εξπζξφ κπ (*P<0,05 ζε ζχγθξηζε κε ηελ πξψηε δεηγκαηνιεςία). Σα επίπεδα ηςκ θζπανχκ μλέςκ δίκμκηαζ ζημκ Πίκαηα 1. διακηζηέξ δζαθμνέξ παναηδνήεδηακ ηονίςξ ζημκ ενοενυ ιο ιε ηα MUFA κα πανμοζζάγμοκ αφλδζδ απυ ημκ Νμέιανζμ έςξ ηδκ άκμζλδ, εκχ ηα PUFA ακηίεεηα ιεζχεδηακ. 59

60 11/13 1/14 4/14 6/14 11/13 1/14 4/14 6/14 11/13 1/14 4/14 6/14 HydroMedit 2014, November 13-15, Volos, Greece Πίλαθαο 1: Σα επίπεδα ησλ ιηπαξσλ νμέσλ ζηνπο ηζηνχο ηνπ θαγθξί G fatty acid per 100 g fish oil (Mean) Ήπαν Λεοηυξ ιοξ Δνοενυξ ιοξ ς ς SFA MUFA PUFA διείςζδ: SFA: ημνεζιέκα θζπανά μλέα, MUFA: ιμκμαηυνεζηα θζπανά μλέα, PUFA: πμθοαηυνεζηα θζπανά μλέα. 4. πδήηεζε Απυ ηζξ ηφνζεξ πδβέξ εκένβεζαξ, ηονίςξ ημ βθοημβυκμ ηαζ ηα θζπίδζα πανμοζίαζακ επμπζηυ πνυηοπμ. Ζ ιείςζδ ημο βθοημβυκμο ζημοξ ιήκεξ ημο πεζιχκα ηαζ ηδξ άκμζλδξ δείπκεζ ιζα ελάνηδζδ ηςκ ζζηχκ ζε εκένβεζα απυ ηδκ μλείδςζδ ηςκ οδαηακενάηςκ. Έπεζ ακαθενεεί υηζ δ πανμοζία ημο βθοημβυκμο εεςνείηαζ ζδζαίηενα ζδιακηζηή, ηαζ ανίζηεηαζ ηονίςξ ζοζζςνεοιέκμ ζημ ήπαν ηςκ ζπεφςκ, ημ μπμίμ εκςιέκμ ιε βθμαμοθίκεξ απμηεθεί απμηαιζεοιέκδ ηαφζζιδ έκςζδ. Σμ πμζμζηυ ημο ζημοξ ιοξ είκαζ ηαηά πμθφ ιζηνυηενμ εηείκμο ημο ήπαημξ. Πνέπεζ κα ζδιεζςεεί υηζ ζημοξ πενζζζυηενμοξ απυ ημοξ ιεθεηδεέκηεξ ζπεφεξ δ ζοζζςνεοεείζα πμζυηδηα ημο δπαηζημφ βθοημβυκμο απμηεθεί ηδκ ηεθεοηαία δζαεέζζιδ πδβή εκένβεζαξ ηαζ δ απμοζία ημο ζοκήεςξ πνμδζαβνάθεζ ιδ ακηζζηνεπηέξ ζοκέπεζεξ αοημφ (Kieffer et al. 1998, Παπμοηζυβθμο 2008). Σα θζπίδζα απμηεθμφκ ιζα ζδζαίηενα εηενμβεκή μιάδα ιαηνμιμνίςκ ηαζ θεζημονβμφκ ςξ ζδιακηζηή πδβή ιεηααμθζηήξ εκένβεζαξ (Thorgaard & Disney 1990). Οζ ιεηνήζεζξ ηαηά ημ ιήκα Ηακμοάνζμ ηαζ ανπέξ Απνζθίμο, πνζκ ηδκ έκανλδ ηδξ ακαπαναβςβζηήξ πενζυδμο ζδιεζχκμοκ ιέβζζηδ ηζιή, ηυζμ ζημ θεοηυ υζμ ηαζ ζημκ ενοενυ ιο, εκχ ηαηά ημ ηέθμξ ηδξ ακαπαναβςβήξ ημ πμζμζηυ ειθακίγεζ πηςηζηή ηάζδ. Σα απμηεθέζιαηα αοηά ζοιθςκμφκ ιε ακάθμβεξ ιεθέηεξ πμο έπμοκ δζελαπεεί ηαζ οπμδδθχκμοκ ιζα δοκαιζηή ακαηαηακμιή ηδξ απμεδηεοιέκδξ ιεηααμθζηήξ εκένβεζαξ ηαηά ηδ δζάνηεζα ημο αζμθμβζημφ ηφηθμο ηςκ ζπεφςκ. Γεκζηά, ημ ήπαν θεζημονβεί ςξ αναπφπνμκδ απμεήηδ θζπζδίςκ ηαζ ζοκεπχξ εκένβεζαξ, βζα ημ ζχια ηςκ γχςκ. Σα απμεέιαηα αοηά αολάκμκηαζ ηαζ ζοζζςνεφμκηαζ ζημκ ζζηυ αοηυ, θίβμ δζάζηδια πνζκ ηδκ έκανλδ ηδξ ακαπαναβςβζηήξ πενζυδμο, απυ υπμο εα ηζκδημπμζδεμφκ ζηδ ζοκέπεζα πνμξ ηζξ βμκάδεξ (Alamansa 2001). Οζ πνςηεΐκεξ πανυθμ πμο εηπνμζςπμφκ ημ ορδθυηενμ πμζμζηυ ηςκ μνβακζηχκ εκχζεςκ ημο ζχιαημξ ηςκ ρανζχκ (Παπμοηζυβθμο 2008) ηαζ απακηχκηαζ ζε υθα ηα ηφηηανα ηαζ ζημ αίια ημοξ δεκ έπμοκ δείλεζ ζδιακηζηέξ δζαθμνέξ ζημ επμπζηυ ημοξ πνυηοπμ. 5. Βηβιηνγξαθία Νήηαξ (2004). Γζαηνμθή Αβνμηζηχκ Εχςκ Υδιζηέξ Ακαθφζεζξ, Σιήια Δηδυζεςκ ΣΔΗ Θεζζαθμκίηδξ. Παπμοηζυβθμο.Δ. (2008) Γζαηνμθή ζπεφςκ. ηαιμφθδ Α.Δ. Αεήκα ζεθ Almansa E. (2001). Lipid and fatty acid composition of female gilthead seabream during their reproductive cycle: effects of a diet lacking n-3 HUFA. J. Fish Biol. 59:

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62 COMPARISON OF TWO INJECTABLE BIVALENT COMMERCIAL VACCINES (ANTI-VIBRIO-PHOTOBACTERIUM) IN CULTURED SEA BASS (Dicentrarchus labrax, L. 1758) Spinos Δ. 1,2 *, Bakopoulos V. 1 1 Department of Marine Sciences, School of the Environment, University of Aegean, University Hill, Mytilene Lesvos, Greece. 2 Department of Fisheries, Directorate of Rural Economy and Veterinary, Regional Unit of Kefalonia, Residency, Argostoli Kefalonia, Greece. ABSTRACT In July 2013, a study comparing two injectable bivalent (anti-vibrio-photobacterium) commercial vaccines in field conditions in sea bass was launched, in collaboration with a farm in NE Kefalonia. This study aims to assess the efficacy in the field and after experimental infections of two injectable bivalent (anti-vibrio-photobacterium) vaccines commercially available in Greece, against the diseases caused by the pathogens Vibrio anguillarum O1 and Photobacterium damsela subsp. piscicida, in sea bass. From the results of the experimental infections that show % cumulative mortality and standard deviation, and the RPS value, seems that the oil-adjuvanted vaccine AlphaJect 2000 confers greater protection compared to the fish vaccinated with the aqueous vaccine AquaVac and to non-vaccinated fish (controls). Key words: Dicentrarchus labrax, Vibrio anguillarum O1, Photobacterium damsela subsp. piscicida. *Corresponding author: Spinos Efthimios (e.spinos@marine aegean.gr) ΤΓΚΡΗΖ ΓΤΟ ΔΝΔΗΜΧΝ ΓΗΓΤΝΑΜΧΝ ΔΜΠΟΡΗΚΧΝ ΔΜΒΟΛΗΧΝ (ANTI-VIBRIO-PHOTOBACTERIUM) Δ ΔΚΣΡΔΦΟΜΔΝΑ ΛΑΒΡΑΚΗΑ (Dicentrarchus labrax, L. 1758) πίλνο Δ. 1,2 *, Μπαθφπνπινο Β. 1 1 Σιήια Δπζζηδιχκ ηδξ Θάθαζζαξ, Πακεπζζηήιζμ Αζβαίμο, Λυθμξ Πακεπζζηδιίμο, Μοηζθήκδ Λέζαμξ, Δθθάδα. 2 Σιήια Αθζείαξ, Πενζθενεζαηή Δκυηδηα Κεθαθθδκίαξ, Γζμζηδηήνζμ, Ανβμζηυθζ Κεθαθμκζά, Δθθάδα. Πεξίιεςε Σμκ Ημφθζμ 2013 λεηίκδζε ιεθέηδ ζφβηνζζδξ δφμ εκέζζιςκ δζδφκαιςκ (anti-vibrio-photobacterium) ειπμνζηχκ ειαμθίςκ ζε ζοκεήηεξ εηηνμθήξ θααναηζμφ, ζε ζοκενβαζία ιε ιμκάδα ζπεομηαθθζένβεζαξ ζηδκ ΒΑ Κεθαθμκζά. Ζ πανμφζα ιεθέηδ έπεζ ζηυπμ κα αλζμθμβήζεζ ηδκ απμηεθεζιαηζηυηδηα, ζημ πεδίμ ηαζ ζημ ενβαζηήνζμ ιε πεζναιαηζηέξ ιμθφκζεζξ, δφμ εκέζζιςκ δζδφκαιςκ (anti-vibrio- Photobacterium) ειπμνζηά δζαεέζζιςκ ειαμθίςκ ζηδκ Δθθάδα, έκακηζ ηςκ αζεεκεζχκ πμο πνμηαθμφκηαζ, απυ ημοξ παεμβυκμοξ πανάβμκηεξ Vibrio anguillarum O1 ηαζ Photobacterium damsela subsp. piscicida, ζημ θαανάηζ. Απυ ηα απμηεθέζιαηα ηςκ πεζναιαηζηχκ ιμθφκζεςκ υπμο δίκμκηαζ δ % αενμζζηζηή εκδζζιυηδηα ηαζ δ ηοπζηή απυηθζζδ, ηαεχξ ηαζ δ ηζιή RPS, θαίκεηαζ υηζ ημ εθαζχδεξ ειαυθζμ ΑlphaJect 2000, πανέπεζ ιεβαθφηενδ πνμζηαζία ζηα ράνζα πμο ειαμθζάζεδηακ ιε αοηυ, ζε ζπέζδ ιε ηα ράνζα πμο ειαμθζάζηδηακ ιε ημ οδαημδζαθοηυ ειαυθζμ Αquavac ηαζ ζε ζπέζδ ιε ηα ακειαμθίαζηα ράνζα (ιάνηονεξ). Λέξειρ κλειδιά: Dicentrarchus labrax, Vibrio anguillarum O1, Photobacterium damsela subsp. piscicida. *οββναθέαξ επζημζκςκίαξ: πίκμξ Δοεφιζμξ (e.spinos@marine aegean.gr) 1. Δηζαγσγή Ζ εκηαηζημπμίδζδ ηδξ εηηνμθήξ οδνυαζςκ μνβακζζιχκ έπεζ μδδβήζεζ ζηδκ ειθάκζζδ ζμβεκχκ ααηηδνζαηχκ ηαζ παναζζηζηχκ αζεεκεζχκ ηςκ ρανζχκ (Athanassopoulou & Bitchava 2010). Οζ πζμ ζδιακηζηέξ ααηηδνζαηέξ αζεέκεζεξ είκαζ δ δμκαηίςζδ ηαζ δ θςημααηηδνζδίαζδ 62

63 (παζηενέθθςζδ) πμο πνμηαθείηαζ απυ ηα Gram ( - ) ααηηδνίδζα Vibrio anguillarum (ζοκχκοιμ: Listonella anguillarum) δζάθμνμζ μνυηοπμζ (Sorensen & Larsen 1986, Toranzo & Barja 1990) ηαζ Photobacterium damsela subsp. piscicida (Bakopoulos etal. 1995), ακηίζημζπα. Απυ ηζξ πνχηεξ πενζβναθέξ ηςκ δφμ αζεεκεζχκ, ηα δφμ αοηά ααηηήνζα έπμοκ βίκεζ εκδδιζηά ζημ εαθάζζζμ πενζαάθθμκ ηαζ επδνεάγμοκ ηυζμ άβνζα υζμ ηαζ εηηνεθυιεκα ράνζα, βεβμκυξ πμο ηαεζζηά αδφκαηδ ηδκ εθανιμβή μπμζμοδήπμηε πνμβνάιιαημξ ελάθεζρήξ ημοξ. Απυ ηα εηηνεθυιεκα ράνζα, ημ θαανάηζ ημ μπμίμ είκαζ πμθφ πζμ εοαίζεδημ απυ ηδκ ηζζπμφνα (Athanassopoulou & Bitchava 2010), πνμζηαηεφεηαζ ζε ηάπμζμ ααειυ απυ ημκ ειαμθζαζιυ ηαζ ηδ δζαηήνδζδ ηαθχκ ζοκεδηχκ εηηνμθήξ ηαζ δζαπείνζζδξ. Ο ειαμθζαζιυξ εηαημιιονίςκ ρανζχκ ζηζξ οδαημηαθθζένβεζεξ είκαζ ιζα πμθφπθμηδ δζαδζηαζία πμο πενζθαιαάκεζ ορδθυ ηυζημξ ενβαηζηχκ, ιεβάθδ δζάνηεζα εθανιμβήξ, ιε απχθεζεξ ρανζχκ πμο μθείθμκηαζ ζημ stress ηαζ ζημοξ ηναοιαηζζιμφξ, εζδζηά υηακ ηα ειαυθζα πμνδβμφκηαζ ζε ηάεε ράνζ εκδμπενζημκασηά (ip). οκήεςξ, μ πνχημξ ειαμθζαζιυξ πναβιαημπμζείηαζ ιε ειαάπηζζδ ζε εκαζχνδια πμο πενζέπεζ ημ ειαυθζμ υηακ ημ ιέβεεμξ ηςκ ρανζχκ είκαζ 1-2g ηαζ μ δεφηενμξ ειαμθζαζιυξ πναβιαημπμζείηαζ εκδμπενζημκασηά (ip) υηακ ηα ράνζα θεάζμοκ 20-25g. Σνμπμπμζήζεζξ αοημφ ημο ααζζημφ πνςημηυθθμο παναηδνμφκηαζ ιεηαλφ ηςκ εηαζνεζχκ ηαζ ζοκδέμκηαζ ιε ημ ζπέδζμ δζαπείνζζδξ πμο εθανιυγεηαζ. Ο ειαμθζαζιυξ ιε ειαάπηζζδ μδδβεί ηονίςξ ζηδκ ακάπηολδ ημπζηήξ ακμζίαξ ζηα επζεήθζα (Thorrnton etal. 1994, Kusuda & Hamaguchi 1987), ζε ακηίεεζδ ιε ημκ εκδμπενζημκασηυ ειαμθζαζιυ (ip) πμο μδδβεί ζηδκ ακάπηολδ ζοζηδιζηήξ ακμζίαξ (Hjeltneset etal. 1989, Bakopoulos etal. 2003). Διπμνζηά ειαυθζα (πμο απμηεθμφκηαζ απυ απεκενβμπμζδιέκα ζηεθέπδ ααηηδνίςκ) έκακηζ ηδξ δμκαηίςζδξ ή ηδξ θςημααηηδνζδίαζδξ (παζηενέθθςζδξ), είκαζ δζαεέζζια εδχ ηαζ ανηεηυ ηαζνυ ιε ηαθή πνμζηαζία ηαηά ηδξ δμκαηίςζδξ (Woo & Bruno, 1999) ηαζ πμζηίθα απμηεθέζιαηα ζπεηζηά ιε ηδκ θςημααηηδνζδίαζδ (παζηενέθθςζδ), (Nakai etal. 1992, Le Breton 1999). Γζδφκαια ειαυθζα είκαζ επίζδξ δζαεέζζια ζημ ειπυνζμ ηαζ είκαζ έκα ιίβια ηςκ ιμκμδφκαιςκ ειαμθίςκ ηαζ πνμζθένμοκ ημ πθεμκέηηδια ηδξ εθανιμβήξ εκυξ ειαμθζαζιμφ έκακηζ ηαζ ηςκ δφμ αζεεκεζχκ. Οζ πθδνμθμνίεξ ζπεηζηά ιε ηδκ απμηεθεζιαηζηυηδηα αοηχκ ηςκ ειαμθίςκ είκαζ ζπάκζεξ ή αζαθείξ. Ζ ιεθέηδ αοηή έπεζ ςξ ζηυπμ ηδ αλζμθυβδζδ ηςκ δφμ ειπμνζηά δζαεέζζιςκ δζδφκαιςκ ειαμθίςκ απυ ηδκ άπμρδ ηδξ πνμζηαζίαξ ηςκ ειαμθζαζιέκςκ ρανζχκ έκακηζ ηδξ δμκαηίςζδξ ηαζ ηδξ θςημααηηδνζδίαζδξ (παζηενέθθςζδξ), ζε ζοκεήηεξ πεδίμο ηαζ ζε πεζναιαηζηέξ ζοκεήηεξ. 2. Τιηθά θαη Μέζνδνη Ζ ιεθέηδ λεηίκδζε ημκ Ημφθζμ ημο 2013 ζε ιμκάδα ζπεομηαθθζένβεζαξ ζηδ ΒΑ Κεθαθμκζά ζε έλζ (6) ζπεομηθςαμφξ πμο πενζείπακ πενίπμο ράνζα (θαανάηζα) / ηθμοαί ιέζμο αάνμοξ 33g. Απυ ημ ζφκμθμ ημο οπυ ιεθέηδ πθδεοζιμφ ρανζχκ, ειαμθζάζεδηακ εκδμπενζημκασηά (ip) ράνζα δφμ ηθςαχκ ιε ημ κέμ εθαζχδεξ ειαυθζμ AlphaJect 2000, ράνζα δφμ ηθςαχκ ιε ημ οδαημδζαθοηυ ειαυθζμ AquaVac ηαζ ζε δφμ ηθςαμφξ ηα ράνζα πανέιεζκακ ακειαμθίαζηα έηζζ χζηε κα πνδζζιεφζμοκ ςξ ιάνηονεξ. Καζ ηα δφμ ειπμνζηά ειαυθζα ήηακ δζδφκαια [πενζέπμοκ πανυιμζεξ πμζυηδηεξ αδνακμπμζδιέκςκ ααηηδνζαηχκ ηφηηανςκ ηςκ παεμβυκςκ Vibrio anguillarum Ο1 (Vibrio anguillarum Ο2 ιυκμ ημ ειαυθζμ AquaVac) ηαζ Photobacterium damsela subsp. Piscicida]. Οζ ειαμθζαζιμί πναβιαημπμζδεήηακε εκδμπενζημκασηά (ip) αημθμοεχκηαξ ηζξ μδδβίεξ ηςκ παναζηεοαζηχκ ηςκ ειαμθίςκ. Γζα ηδκ οθμπμίδζδ ηδξ ιεθέηδξ ζε πεζναιαηζηέξ ζοκεήηεξ, ζε δζάθμνα πνμκζηά δζαζηήιαηα ιεηά ημκ ειαμθζαζιυ, ράνζα απυ ηάεε πεζναιαηζηή μιάδα ιεηαθένεδηακ απυ ηδκ οπυ ιεθέηδ ιμκάδα ζπεομηαθθζένβεζαξ ηαζ ημπμεεηήεδηακ ζε βοάθζκα εκοδνεία πςνδηζηυηδηαξ 250 L. Μεηά ημκ εβηθζιαηζζιυ ημοξ, ηα ράνζα ιμθφκεδηακ ιε έβποζδ (ip) ιε ααηηδνζαηά ηφηηανα είηε ημο Vibrio anguillarum Ο1 ή ημο Photobacterium damsela subsp. piscicida, ηα μπμία ηαθθζενβήεδηακ ζε ζοκήεδ ζηενεά οθζηά ηαθθζένβεζαξ. Ο ανζειυξ ηςκ παεμβυκςκ ααηηδνζαηχκ ηοηηάνςκ πνμζδζμνίζηδηε θςημιεηνζηά ηαζ βζα ηάεε πεζναιαηζηή ιυθοκζδ ηαεμνίζεδηε δ δμζμθμβία ακάθμβα ιε ημ ιέβεεμξ ηςκ ρανζχκ ηαζ ηδ εενιμηναζία ημο κενμφ. Μεηά ηδκ πεζναιαηζηή ιυθοκζδ ηα ράνζα ακά μιάδα ημπμεεηήεδηακ ηοπαία ζε ηνία εκοδνεία ηαζ παναημθμοεμφκηακ ηαεδιενζκά ηα ζοιπηχιαηα ηδξ αζεέκεζαξ, δ εκδζζιυηδηα ηαζ μζ θοζζημπδιζηέξ πανάιεηνμζ ημο κενμφ. Κάεε πείναια μθμηθδνςκυηακ υηακ δεκ ηαηαβναθυηακ εκδζζιυηδηα βζα δφμ ζοκεπυιεκεξ διένεξ. Σα 2/3 ημο κενμφ ακακεχκμκηακ ηάεε ιένα βζα κα απμθεοπεεί δ ζοζζχνεοζδ ημλζηχκ μοζζχκ ή δ ακάπηολδ ιζηνμαίςκ ζημ κενυ. Σα ράνζα πμο ζοιιεηείπακ ζηα πεζνάιαηα ηνέθμκηακ εθάπζζηα. Απυ ηα εημζιμεάκαηα ράνζα θαιαάκμκηακ δείβιαηα βζα ιζηνμαζμθμβζηή επζαεααίςζδ ηδξ αζηίαξ ηδξ κυζμο. Ζ ιεηαθμνά, μζ πεζνζζιμί ηαζ δ πεζναιαηζηή ιυθοκζδ ηςκ ρανζχκ βζκυηακ ηάης απυ κάνηςζδ ιε ηδ πνήζδ θαζκμλοαζεακυθδξ. Ζ πνμζηαζία πμο πανέπεηαζ απυ ηα ειπμνζηά ειαυθζα αλζμθμβήεδηε ιε ημκ οπμθμβζζιυ ημο πμζμζημφ ζπεηζηήξ επζαίςζδξ (Relative Percent Survival-RPS) ιε ηδκ αηυθμοεδ ελίζςζδ: 63

64 3. Απνηειέζκαηα ημκ Πίκαηα 1, πανμοζζάγμκηαζ μ ανζειυξ ηςκ ζπεφςκ ηαζ μζ μιάδεξ πμο ζοιιεηείπακ ζηζξ πεζναιαηζηέξ ιμθφκζεζξ, μ ανζειυξ ηςκ κεηνχκ ρανζχκ, δ % εκδζζιυηδηα ηαζ μζ ηζιέξ RPS ακά πείναια. ηζξ βναθζηέξ παναζηάζεζξ ζημ πήια 1 δίκεηαζ δ % αενμζζηζηή εκδζζιυηδηα ηαζ δ ηοπζηή απυηθζζδ ηςκ έλζ πεζναιάηςκ πμο δζελήπεδηακ. ε υθεξ ηζξ πενζπηχζεζξ, ημ ειαυθζμ AlphaJect 2000 θαίκεηαζ υηζ πανέπεζ ιεβαθφηενδ πνμζηαζία ακελάνηδηα απυ ημκ παεμβυκμ πανάβμκηα πμο πνδζζιμπμζείηαζ ηαζ ηδκ ααηηδνζαηή πίεζδ πμο εθανιυγεηαζ ζηα ράνζα ζε ζφβηνζζδ ιε ηα ράνζα πμο ειαμθζάζηδηακ ιε ημ ειαυθζμ AquaVac. Πίλαθαο 1. Πεηξακαηηθέο κνιχλζεηο, εκεξνκελία, παζνγφλνο νξγαληζκφο, αξηζκφο ςαξηψλ, απψιεηεο, % ζλεζηκφηεηα θαη πνζνζηφ ζρεηηθήο επηβίσζεο (RPS), αλά νκάδα ςαξηψλ. ΠΔΗΡΑΜΑ ΟΜΑΓΑ ΦΑΡΗΧΝ ΑΡΗΘΜΟ ΦΑΡΗΧΝ ΑΠΧΛΔΗΔ % ΘΝΖΗΜΟΣΖΣΑ ΣΗΜΖ RPS 23/9/2013 VIBRIO Control ΔΒΓΟΜΑΓΔ ΜΔΣΑ ΣΟΝ ΔΜΒΟΛΗΑΜΟ T 0 C=23,5±0,5 AlphaJect AquaVac /11/2013 VIBRIO Control ΔΒΓΟΜΑΓΔ ΜΔΣΑ ΣΟΝ ΔΜΒΟΛΗΑΜΟ T 0 C=19,0±0,8 AlphaJect ,9 AquaVac ,8 20/12/2013 PHOTOBACTERIUM 19 ΔΒΓΟΜΑΓΔ ΜΔΣΑ ΣΟΝ ΔΜΒΟΛΗΑΜΟ T 0 C=13,4±1,1 Control AlphaJect ,5 AquaVac ,5 10/1/2014 VIBRIO Control ΔΒΓΟΜΑΓΔ ΜΔΣΑ ΣΟΝ ΔΜΒΟΛΗΑΜΟ T 0 C=14,8±0,8 25/2/2014 PHOTOBACTERIUM 28 ΔΒΓΟΜΑΓΔ ΜΔΣΑ ΣΟΝ ΔΜΒΟΛΗΑΜΟ T 0 C=13,0±1,0 AlphaJect AquaVac Control AlphaJect AquaVac /3/2014 VIBRIO Control ΔΒΓΟΜΑΓΔ ΜΔΣΑ ΣΟΝ ΔΜΒΟΛΗΑΜΟ T 0 C=15,5±1,5 AlphaJect AquaVac ηα ράνζα πμο πέεακακ απυ ηδκ πεζναιαηζηή ιυθοκζδ, ηα ζοιπηχιαηα πμο παναηδνήεδηακ ήηακ ενοενυηδηα ημο ζηυιαημξ, έθηδ ζημ ζχια ηαζ ενοενυηδηα ηαζ πνμμδεοηζηή αθθμίςζδ ημο μοναίμο πηενοβίμο. Δζςηενζηά, ηα ράνζα πμο πέεακακ απυ δμκαηίςζδ είπακ δζυβηςζδ ηςκ μνβάκςκ ηαζ αζιμνναβίεξ εκχ πανυιμζα δζυβηςζδ ηαζ πενζζηαζζαηά οπυθεοηα μγίδζα παναηδνήεδηακ ζημκ ζπθήκα ηςκ ρανζχκ πμο πέεακακ απυ θςημααηηδνζδίαζδ (παζηενέθθςζδ). Σα ιδ ειαμθζαζιέκα ράνζα ήηακ ζε πμθφ πεζνυηενδ ηαηάζηαζδ (αθθμζχζεζξ ζηα πηενφβζα ηαζ ηονίςξ ζημ μοναίμ) απυ υ,ηζ ηα ειαμθζαζιέκα ζε υθεξ ηζξ πενζπηχζεζξ. Απυ ηδκ ανπή ιέπνζ ημ ηέθμξ ηδξ ιεθέηδξ δεκ παναηδνήεδηακ ζοιπηχιαηα δμκαηίςζδξ ή θςημααηηδνζδίαζδξ (παζηενέθθςζδξ) ζηα ράνζα ηδξ οπυ ιεθέηδ ιμκάδαξ ζπεομηαθθζένβεζαξ ζημ θοζζηυ πενζαάθθμκ. 64

65 ρήκα 1. Αζξνηζηηθή % ζλεζηκφηεηα θαη ηππηθή απφθιηζε γηα θάζε πεηξακαηηθή κφιπλζε. Έβζκε ζηαηζζηζηή επελενβαζία πνδζζιμπμζχκηαξ MANOVA (multivariate analysis of variance) ηαζ πνζκ ηδκ εθανιμβή ηδξ ηα δεδμιέκα ιεηαζπδιαηίζηδηακ (επεζδή αθμνμφκ ζε πμζμζηά) ζε asin (sqrt (M) (βζα ηδκ πνμζέββζζδ ηδξ ηακμκζημπμίδζήξ ημοξ). Οζ πανάβμκηεξ μζ μπμίμζ ιεθεηήεδηακ ήηακ μζ διένεξ, ηα ειαυθζα ηαζ ηα ράνζα ιάνηονεξ. Αημθμφεςξ πνδζζιμπμζήεδηε δ post hoc Fishers Least Significant Difference (LSD) δμηζιή βζα κα ανεεμφκ μζ ζηαηζζηζηέξ δζαθμνέξ ζε P<=0.05 ιεηαλφ ηςκ παναιέηνςκ ημο ηάεε πανάβμκηα. Γζα θυβμοξ μζημκμιίαξ, μ πανάβμκηαξ «διένεξ» έδεζλε ζε υθα ζηαηζζηζηή δζαθμνά (ακαιεκυιεκμ θυβς ημο υηζ πενζβνάθεζ ηδκ ηαιπφθδ) ζε υθα ηα πεζνάιαηα. Σα ζηαηζζηζηά ζημζπεία ηδξ ΜΑΝΟVA βζα ημκ πανάβμκηα ειαυθζα ακά πείναια δίκμκηαζ ζηδ ζοκέπεζα. ημ πείναια ζηζξ 23/9/13 βζα ημ AlphaJect δίκεηαζ ζηαηζζηζηά ιζηνυηενδ εκδζζιυηδηα απυ ημ AquaVac ηαζ ημ Control, ηαζ βζα ημ AquaVac απυ ημ Control. ημ πείναια ζηζξ 4/11/2013 βζα ημ AlphaJect δίκεηαζ ζηαηζζηζηά ιζηνυηενδ εκδζζιυηδηα απυ ημ AquaVac ηαζ ημ Control, ηαζ βζα ημ AquaVac απυ ημ Control. ημ πείναια ζηζξ 20/12/2013 παναηδνείηαζ ζηαηζζηζηά ίδζα εκδζζιυηδηα ηαζ βζα ηζξ ηνεζξ πανηίδεξ ρανζχκ. ηα πεζνάιαηα ζηζξ 10/1/2014, 25/2/2014, ηαζ 18/3/2014 βζα ημ AlphaJect δίκεηαζ ζηαηζζηζηά ιζηνυηενδ εκδζζιυηδηα απυ ημ AquaVac ηαζ ημ Control, ηαζ βζα ημ AquaVac απυ ημ Control. Σα παναπάκς είκαζ ειθακή ζηα ζπεδζαβνάιιαηα ιε ηδκ % αενμζζηζηή εκδζζιυηδηα (πήια 1). 4. πδήηεζε ηδ εαθαζζμηαθθζένβεζα ζηδκ Δθθάδα, πνμηεζιέκμο κα ιεζςεεί δ εκδζζιυηδηα ζε εηηνεθυιεκα ράνζα πμο πνμηαθείηαζ ηονίςξ απυ ηα παεμβυκα ααηηήνζα V. anguillarum ηαζ Ρ. damsela subsp. piscicida, εα πνέπεζ κα εθανιυγεηαζ ειαμθζαζιυξ ιε ειαάπηζζδ ηςκ ιζηνχκ ρανζχκ ηαζ εκδμπενζημκασηά (ip) ζε ιεβαθφηενα ράνζα. Ακ ηαζ οπάνπμοκ πνμδβμφιεκεξ ιεθέηεξ ζπεηζηά ιε ηδκ απμηεθεζιαηζηυηδηα ηδξ πνμζηαζίαξ πμο επζηοβπάκεηαζ ιεηά απυ ειαμθζαζιυ ιε ιμκμζεεκή ειαυθζα έκακηζ ημο V. anguillarum (Viale etal & Galeotti etal. 2013) ή έκακηζ ημο Ρ. damsela subsp. piscicida (Magarinos etal. 1994a & 1994b), οπάνπμοκ θίβεξ πθδνμθμνίεξ ζπεηζηά ιε ηδκ απμηεθεζιαηζηυηδηα ηδξ πνμζηαζίαξ, υηακ ηα ράνζα ειαμθζάγμκηαζ ιε δζδφκαια ειαυθζα ηαηά ηςκ δφμ παεμβυκςκ. Ζ πνμζηαζία ιεηά ημκ ειαμθζαζιυ ηαηά ημο V. anguillarum θένεηαζ κα είκαζ απμηεθεζιαηζηή (Αεακαζμπμφθμο & Bitchava 2010 & Galeotti etal. 2013). ε ακηίεεζδ, δ πνμζηαζία ιεηά ημκ ειαμθζαζιυ έκακηζ ημο Ρ. damsela subsp. piscicida είκαζ αιθίαμθδ (Nakai etal & Le Breton 1999). Πανμιμίςξ, δ πανμφζα ιεθέηδ έδεζλε υηζ δ πνμζηαζία πμο επζηοβπάκεηαζ απυ αοηά ηα δζδφκαια ειαυθζα έκακηζ ιμθφκζεςκ απυ ημ V. anguillarum O1 ήηακ ορδθή ηαζ ιαηνάξ δζάνηεζαξ (αηυιδ ηαζ 30 εαδμιάδεξ ιεηά ημκ ειαμθζαζιυ 7,5 ιήκεξ) ιε ημ ειαυθζμ AlphaJect 2000 (πμο πενζέπεζ εθαζχδεξ ακμζμεκζζποηζηυ) κα είκαζ πάκημηε ηαθφηενμ ζε ζφβηνζζδ ιε ημ ειαυθζμ AquaVac (οδαηζηυ, πςνίξ ακμζμεκζζποηζηυ). Σα πμζμζηά ζπεηζηήξ επζαίςζδξ πμο οπμθμβίζηδηακ βζα ημ ειαυθζμ AlphaJect 2000 ήηακ πάκημηε ορδθά εηηυξ ηςκ πενζπηχζεςκ υπμο εθανιυζηδηε οπεναμθζηή ααηηδνζαηή πίεζδ (εκδζζιυηδηα 100% ζημοξ ιάνηονεξ). ε υηζ αθμνά ηζξ ιμθφκζεζξ ιε ημ P. damsela subsp. piscicida, ηαζ πάθζ ημ ειαυθζμ AlphaJect 2000 οπήνλε πάκημηε ηαθφηενμ ζε ζφβηνζζδ ιε ημ ειαυθζμ AquaVac. Γεηαεκκζά (19) εαδμιάδεξ ιεηά ημκ ειαμθζαζιυ (πενίπμο 5 ιήκεξ) ηαζ ιε ιεζαίαξ έκηαζδξ ααηηδνζαηή πίεζδ (40% εκδζζιυηδηα ζημοξ ιάνηονεξ), οπμθμβίζηδηακ πμζμζηά ζπεηζηήξ επζαίςζδξ 62,5 ηαζ 37,5 βζα ημ ειαυθζμ AlphaJect 2000 ηαζ AquaVac, ακηίζημζπα. Πανυθα αοηά, 65

66 παναηδνήεδηε ιία ηάζδ ιείςζδξ ημο απμηεθέζιαημξ ημο ειαμθζαζιμφ ηαζ βζα ηα δφμ ειαυθζα ιε ηδ πάνμδμ ημο πνυκμο. Γοζηοπχξ, οπάνπεζ ιυκμ έκα επζζηδιμκζηυ άνενμ πμο δζενεφκδζε ημ ίδζμ δζδφκαιμ ειαυθζμ Vibrio-Pasteurella, ιε ακμζμεκζζποηζηυ ή πςνίξ (Gravingen etal. 1998). Ακ ηαζ δεκ ιπμνεί κα βίκεζ απεοεείαξ ζφβηνζζδ ιεηαλφ ηςκ δφμ ιεθεηχκ ελαζηίαξ ημο πνςημηυθθμο ηςκ ειαμθίςκ πμο πνδζζιμπμζήεδηακ, ημ ιαηνμπνυκζμ απμηέθεζια πάκς ζηδ πνμζηαζία ηςκ ρανζχκ έκακηζ ηδξ δμκαηίςζδξ είκαζ πανυιμζμ ηαζ ζηζξ δφμ ιεθέηεξ ιε ημ ειαυθζμ πμο πενζέπεζ ακμζμεκζζποηζηυ κα δνα ηαθφηενα. οιπεναζιαηζηά, θαίκεηαζ υηζ ημ δζδφκαιμ (anti-vibrio Pasteurella) ιε εθαζχδεξ ακμζμεκζζποηζηυ ειαυθζμ AlphaJect 2000 πανέπεζ ιεβαθφηενδ πνμζηαζία ζηα ράνζα πμο ειαμθζάζηδηακ ιε αοηυ, ζε ζπέζδ ιε ηα ράνζα πμο ειαμθζάζηδηακ ιε ημ δζδφκαιμ (anti-vibrio Pasteurella) οδαημδζαθοηυ ειαυθζμ AquaVac, ακελανηήηςξ ημο παεμβυκμο πμο πνδζζιμπμζείηαζ βζα ηδκ πεζναιαηζηή ιυθοκζδ ηαζ ηδ ααηηδνζαηή πίεζδ. Δπραξηζηίεο Θα εέθαιε κα εοπανζζηήζμοιε ημ Πακεπζζηήιζμ Αζβαίμο βζα ηδκ ακάεεζδ ηαζ ηδ πνδιαημδυηδζδ ηδξ ιεθέηδξ, ηζξ εηαζνείεξ Aquavet Α.Δ. ηαζ Pharmaq Α.Δ. βζα ηδ πνδιαημδυηδζδ ηδξ ιεθέηδξ, ηδ δζάεεζδ ηςκ ειαμθίςκ ηαζ ημοξ ειαμθζαζιμφξ, ηαεχξ ηαζ ηδκ εηαζνεία Ηπεομηαθθζενβδηζηή Δνφζζμο ΔΠΔ βζα ηδκ εθανιμβή ηςκ πεζναιάηςκ ζηδ ιμκάδα ηδξ ηαζ ηδκ πνμιήεεζα ηςκ ρανζχκ πμο πνεζάζηδηακ βζα ηα πεζνάιαηα. Βηβιηνγξαθία Athanassopoulou, F. & Bitchava, K. (2010). Main pathological conditions in Mediterranean marine finfish culture. In: Recent Advances in Aquaculture Research, ed. Koumoundouros G., pp , Transworld Research Network, Kerala, India. Bakopoulos, V., Adams, A. & Richards, R.H. (1995). Some biochemical properties and antibiotic sensitivities of Pasteurella piscicida isolated i n Greece and comparison with strains from Japan, France and Italy. Journal of Fish Diseases 18, 1-7. Bakopoulos, V., Volpatti, D., Gusmani, L., Galeotti, M., Adams, A. & Dimitriadis G.J. (2003). Vaccination trials of sea bass, Dicentrarchus labrax (L.), against Photobacterium damsela subsp. piscicida, using novel vaccine mixtures. Journal of Fish Diseases 26(2), Galeotti, M., Romano, N., Volpatti, D., Bulfona, C., Brunetti, A.,Tiscar, P. G., Mosca, F., Bertoni, F., Marchetti, M.G. & Abelli, L. (2013). Innovative vaccination protocol against vibriosis in Dicentrarchus labrax (L.) juveniles: Improvement of immune parameters and protection to challenge. Vaccine 31, Gravningen K, Thorarinsson R, Johansen LH, Nissen B, Rikardsen KS, Greger E, & Vigneulle M. (1998) Bivalent vaccines for sea bass (Dicentrarchus labrax) against vibriosis and pasteurellosis. Journal of Applied Ichthyology 14, Hjeltneset B., Andersen K. & Ellingsen H.M. (1989). Vaccination against Vibrio salmonicida; the effect of different routes of administration and of revaccination. Aquaculture 83, 1-6. Kusuda R. & Hmaguchi M. (1987). A comparative study on efficacy of immersion and a combination of immersion and oral vaccination methods against pseudotuberculosis in yellowtail. Nippon Suisan Gakkaishi 53(6), Le Breton, A.D. (1999). Mediterranean finfish pathologies: present status and new developments in prophylactic met hods.bulletin of the European Association of Fish Pathologists 19, Magarinos B., Noya M., Romalde J.L., Perez G. & Toranzo A.E. (1994a). Influence of fish size and vaccine formulation on the protection of gilthead seabream against Pasteurella piscicida. Bulletin of the European Association of Fish Pathologists 14, Magarinos B., Romalde J.L., Santos Y., Casal J.F., Barja J.L. & Toranzo A.E. (1994b). Vaccination trials on gilthead sea bream (Sparus aurata) against Pasteurella piscicida. Aquaculture 120, Nakai, T., Fujiie, N., Muroga, K., Arimoto, M., Mizuta, Y. & Matsuoka, S. (1992). Pasteurella piscicida infection in hatchery reared juvenile stripped jack. Gyobyo Kenkyu 27, Sorensen U.B. & Larsen J.L. (1986). Serotyping of Vibrio anguillarum. Applied & Environmental Microbiology 51(3), Thornton J.C., Garduno R.A. & Kay W.W. (1994). The development of live vaccines for furunculosis lacking the A-layer and O-antigen of Aeromonas salmonicida. Journal of Fish Diseases 17(3),

67 Toranzo, A. E. & Barja, J. L. (1990). A review of the taxonomy and seroepizootiology of Vibrio anguillarum, with special reference to aquaculture in the northwest of Spain. Disease of Aquatic Organisms 9, 73. Viale, I., Cubadda, C., Angelucci, G. & Salati F. (2006) Immunization of European Sea Bass, Dicentrarchus labrax L. 1758, Fingerlings with a Commercial Vaccine Against Vibriosis. Journal of Applied Aquaculture, 18(3), Woo, P.T.K. & Bruno, D.W. (1999). Fish Diseases and Disorders, Vol. 3, Viral, Bacterial and Fungal infections, CAB International, Wallingford, Oxon, p

68 LYMPHOCYSTIS DISEASE VIRUS (LCDV) DΔTECTION IN GILTHEAD SEABREAM EGGS AND LARVAE Arampatzi-Ziamou D., Golomazou E.*, Gkafas G., Malandrakis E.E., Panagiotaki P., Exadactylos A. Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly Fytoko str., 38446, N. Ionia, Volos, Greece, tel.: , fax: ABSTACT Lymphocystis disease virus is a member of Iridiviridae family and it has been reported in more than 125 fish species. It is a widely spread disease and its main sign is the appearance of small white to grey nodular lesions. The transmission of this virus has not been completely elucidated, while horizontal transmission is accepted. In the present study LCDV was detected in fertilized eggs and larvae from asymptomatic gilthead seabream hatchery broodstock, where disease was previously reported, by LAMP. Ten samplings were carried out in total; one egg sampling 2 days pre-hatching and nine larvae samplings 2, 6, 10, 14, 18, 22, 26, 30, 34 days post-hatching. Ten samples were examined in each sampling disinfecting them by dipping in active iodine 50mg/l for 10 min. LCDV was detected in eggs and larvae with prevalence of 70% and %, respectively, indicating its potential vertical transmission. Disinfection by dipping in active iodine did not alter prevalence possibly indicating intra-ovum transmission. Finally, feeding intake probably did not affect the virus transmission since prevalence remained at high levels before and after live food was provided. Keywords: Lymphocystis Disease Virus, gilthead seabream eggs and larvae, vertical transmission, Loop-mediated isothermal amplification (LAMP) *Corresponding author: Golomazou Eleni (egolom@uth.gr) Α ΑΝΗΥΝΔΤΖ ΣΟΤ ΗΟΤ ΣΖ ΛΔΜΦΟΚΤΣΖ Δ ΑΤΓΑ ΚΑΗ ΛΑΡΒΔ ΣΗΠΟΤΡΑ Αξακπαηδή-Εηάκνπ Γ., Γθνινκάδνπ Δ.*, Γθάθαο Γ., Μαιαλδξάθεο Δ.Δ., Παλαγησηάθε Π., Δμαδάθηπινο Α. Σιήια Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ, πμθή Γεςπμκζηχκ Δπζζηδιχκ, Πακεπζζηήιζμ Θεζζαθίαξ, Οδυξ Φοηυημο, Σ.Κ , Ν. Ηςκία Βυθμο, ηδθ.: , fax: Πεξίιεςε Ο ζυξ ηδξ θειθμηφζηδξ ακήηεζ ζηδκ μζημβέκεζα Iridoviridae ηαζ έπεζ ακζπκεοηεί ζε πενζζζυηενα απυ 125 είδδ ρανζχκ. Ζ αζεέκεζα έπεζ ιεβάθδ βεςβναθζηή ελάπθςζδ ηαζ παναηηδνίγεηαζ απυ ημ ζπδιαηζζιυ ιζηνχκ μγζδίςκ. Ο ηνυπμξ ιεηάδμζδξ ημο ζμφ δεκ έπεζ αηυια απμζαθζκζζηεί εκχ ιυκμ δ μνζγυκηζα ιεηάδμζδ ημο ζμφ ιέπνζ ζήιενα έπεζ επζαεααζςεεί. ημπυξ ηδξ πανμφζαξ ενβαζίαξ ήηακ δ ακίπκεοζδ ημο ζμφ ηδξ θειθμηφζηδξ ζε αοβά ηαζ θάναεξ ηζζπμφναξ πνμενπυιεκα απυ αζοιπηςιαηζημφξ βεκκήημνεξ. Γμκζιμπμζδιέκα αοβά ηαζ θάναεξ ηζζπμφναξ απυ ζπεομβεκκδηζηυ ζηαειυ ιε ζζημνζηυ ζημκ ζυ ηδξ θειθμηφζηδξ ελεηάζηδηακ ιε ζημπυ ηδκ ακίπκεοζδ ημο ζοβηεηνζιέκμο ζμφ ιε ηδκ ηεπκζηή LAMP. Πναβιαημπμζήεδηακ ζοκμθζηά δέηα δεζβιαημθδρίεξ. Μία δεζβιαημθδρία αοβχκ 2 διένεξ πνζκ ηδκ εηηυθαρδ ηαζ εκκζά δεζβιαημθδρίεξ θαναχκ 2, 6, 10, 14, 18, 22, 26, 30 ηαζ 34 διένεξ ιεηά ηδκ εηηυθαρδ. ε ηάεε δεζβιαημθδρία θαιαάκμκηακ 10 δείβιαηα, ζηα μπμία βζκυηακ απμθφιακζδ ιε δζάθοια ζςδίμο 50mg/l βζα 10. φιθςκα ιε ηα απμηεθέζιαηα μ ζυξ ακζπκεφηδηε ηυζμ ζηα αοβά υζμ ηαζ ζηζξ θάναεξ ζε πμζμζηά πνμζαμθήξ 70% ηαζ % ακηίζημζπα, εκζζπφμκηαξ ηδκ πζεακυηδηα ηδξ ηάεεηδξ ιεηάδμζδξ ημο ζμφ. Ζ απμθφιακζδ ιε δζάθοια ζςδίμο δεκ επδνέαζε ηδκ ιεηάδμζδ ημο ζμφ βεβμκυξ πμο οπμδεζηκφεζ υηζ έβζκε πζεακυκ ιέζς ημο ειανφμο. Σέθμξ, δ γςκηακή ηνμθή πζεακυκ δεκ επδνέαζε ηδ ιεηάδμζδ ημο ζμφ αθμφ ηα πμζμζηά πνμζαμθήξ πανέιεζκακ ορδθά πνζκ ηαζ ιεηά ηδ πμνήβδζδ ηδξ. 68

69 Λέμεηο θιεηδηά: ιεκθνθύζηε, απγά θαη ιάξβεο ηζηπνύξαο, θάζεηε κεηάδνζε, Loop-mediated isothermal amplification (LAMP) *οββναθέαξ επζημζκςκίαξ: Γημθμιάγμο Δθέκδ 1.Δηζαγσγή Ο ζυξ ηδξ θειθμηφζηδξ ακήηεζ ζηδκ μζημβέκεζα Iridoviridae ηαζ παναηηδνίγεηαζ απυ ημ ζπδιαηζζιυ ιζηνχκ μγζδίςκ (Alonso et al. 2005) ζηδκ ελςηενζηή επζθάκεζα ημο ζχιαημξ ηαζ ζπακζυηενα ζηα εζςηενζηά υνβακα (Cano et al. 2009). Έπεζ ακζπκεοηεί ζε πενζζζυηενα απυ 125 είδδ ρανζχκ (Noga 2010). Πμθθέξ θμνέξ, ηα ράνζα πμο έπμοκ πνμζαθδεεί απυ ημκ ζυ, ιπμνμφκ κα ακαννχζμοκ, ιε ιζηνή ζοκμθζηά εκδζζιυηδηα πνμηαθχκηαξ υιςξ ζδιακηζηή ηαεοζηένδζδ ζηδκ ακάπηολδ. Χζηυζμ δ φπανλδ ημο παεμβυκμο πανάβμκηα ζε ζοκδοαζιυ ιε ηδκ ηαηαπυκδζδ πμο οθίζηακηαζ ηα ράνζα ελαζηίαξ ηςκ εκηαηζηχκ ζοκεδηχκ εηηνμθήξ ιπμνεί κα αολήζμοκ ημ πμζμζηυ εκδζζιυηδηαξ (Roberts 2012). Ζ μνζγυκηζα ιεηάδμζδ ημο ζμφ έπεζ ιέπνζ ζήιενα επζαεααζςεεί (Bowser et al. 1999, Wolf 1988), εκχ ηάεεηδ ιεηάδμζδ ιέζς ηδξ επζθάκεζαξ ημο αοβμφ έπεζ ακαθενεεί ιυκμ ζε ιία πενίπηςζδ (Cano et al. 2013). Ζ ιμθοζιαηζηή ζηακυηδηα ημο ζμφ ζημ κενυ δζανηεί πενίπμο ιία εαδμιάδα (Noga 2010) ηαζ μ πνυκμξ επχαζδξ ιπμνεί κα δζανηέζεζ ιεβάθμ πνμκζηυ δζάζηδια ακάθμβα ιε ηδ εενιμηναζία ημο κενμφ (Roberts 2012). Ζ δζάβκςζδ βίκεηαζ ιε ανηεηέξ ηεπκζηέξ, υπςξ δ ηοηηανμηαθθζένβεζα, δ ακάπηολδ πμθφηθςκςκ ακηζζςιάηςκ ηαζ ακμζμαπμηφπςζδ, μ in situ οανζδζζιυξ ηαζ δ ιέεμδμξ ηδξ πμζμηζηήξ PCR (Wenbin et al. 2010). Δλαζηίαξ ηδξ ειπμνζηήξ αλίαξ ηςκ ρανζχκ πμο πνμζαάθθμκηαζ απυ ημκ ζυ, οπάνπεζ δ ακαβηαζυηδηα ηδξ έβηαζνδξ ηαζ αλζυπζζηδξ ακίπκεοζήξ ημο ζμφ πνμηεζιέκμο κα εθανιμζημφκ πνμθδπηζηέξ δζαπεζνζζηζηέξ πναηηζηέξ ιεζχκμκηαξ ηζξ δοζιεκείξ μζημκμιζηέξ επζπηχζεζξ ζηδκ εκηαηζηή εηηνμθή ηδξ ηζζπμφναξ. ημπυξ ηδξ πανμφζαξ ενβαζίαξ ήηακ δ ακίπκεοζδ ημο ζμφ ηδξ θειθμηφζηδξ ζε αοβά ηαζ θάναεξ ηζζπμφναξ πνμενπυιεκα απυ αζοιπηςιαηζημφξ βεκκήημνεξ. 2.Τιηθά θαη Μέζνδνη Γμκζιμπμζδιέκα αοβά ηαζ θάναεξ ηζζπμφναξ απυ αζοιπηςιαηζημφξ βεκκήημνεξ πνμενπυιεκα απυ ζπεομβεκκδηζηυ ζηαειυ ιε ζζημνζηυ ζημκ ζυ ηδξ θειθμηφζηδξ ελεηάζηδηακ ιε ζημπυ ηδκ ακίπκεοζδ ημο ζοβηεηνζιέκμο ζμφ ιε ηδκ ηεπκζηή LAMP (Li et al. 2010, Ren et al. 2010). Πναβιαημπμζήεδηακ ζοκμθζηά 10 δεζβιαημθδρίεξ. Μία δεζβιαημθδρία αοβχκ 2 διένεξ πνζκ ηδκ εηηυθαρδ ηαζ εκκζά δεζβιαημθδρίεξ θαναχκ 2, 6, 10, 14, 18, 22, 26, 30, 34 διένεξ ιεηά ηδκ εηηυθαρδ. ε ηάεε δεζβιαημθδρία θαιαάκμκηακ 10 δείβιαηα, ηα μπμία απμθοιαίκμκηακ ιε δζάθοια ζςδίμο 50mg/l βζα 10 (Moretti et al. 1999). Κάεε δείβια ημπμεεημφκηακ ζε απμζηεζνςιέκεξ ηοαέηηεξ ηαζ απμεδηεφμκηακ ζηδκ ηαηάρολδ (-80 C) ιέπνζ ηδκ επελενβαζία ημο. Ζ απμιυκςζδ ημο μθζημφ DNA έβζκε ιε ημ πνςηυημθθμ θαζκυθδξ/πθςνμθμνιίμο (Sambrook et al. 1989) ηαζ δζαηδνήεδηε ζε δζάθοια Tris-EDTA (TE). Γζα ηδκ ιμνζαηή ηεπκζηή LAMP πνδζζιμπμζήεδηακ ηέζζενζξ εηηζκδηέξ ζφιθςκα ιε ηδ ζπεηζηή αζαθζμβναθία (Li et al. 2010), μζ FIP (5 -ACCGAAAAAAAGGATTTTAATGGCA-TTTT-ACCTCTAACTATTCCAAGTCCTA- 3 ), BIP (5 -CCAGTTCTTCTCCTGTAATCTTT GA - TTTT-GATC AGCAGCAATACCCG -3 ), F3 (5 -ACAAACAGCACCTAAACATG-3 ) ηαζ B3 (5 -CGAGCACTATTTTCATAAACCAA-3 ). Γζα ηδκ ακηίδναζδ πνδζζιμπμζήεδηακ 1ιl DNA, 6ιl Thermopol Buffer, 0,8 ιl dntps, 2ιl Primer FIP ηαζ BIP, 1ιl Primer F3 ηαζ B3, 1ιl Bst Taq ηαζ ζοιπθδνχεδηε οπενηάεανμ κενυ έςξ ηα 25ιl. Ζ ακηίδναζδ επςάζηδηε βζα 1 χνα ζημοξ 60 C ηαζ εκ ζοκεπεία 2 θεπηά ζημοξ 80 C βζα ημκ ηενιαηζζιυ ηδξ. Γζα ηδκ επαθήεεοζδ ακίπκεοζδξ ημο ζμφ ηδξ θειθμηφζηδξ ηαζ ηδκ απμηεθεζιαηζηυηδηα ηδξ LAMP πνδζζιμπμζήεδηε μνζγυκηζα δθεηηνμθυνδζδ ζε πήηηςια αβανυγδξ νοειζζηζημφ δζαθφιαημξ TAE 1% ηαεχξ ηαζ SYBR-Green ςξ πνςζηζηή ακίπκεοζδξ. οκμθζηά ελεηάζηδηακ 100 δείβιαηα βζα ηδκ ακίπκεοζδ ημο ζμφ ηδξ θειθμηφζηδξ. Πανάθθδθα, ράνζα ημο είδμοξ Dentex macrophthalmus Bloch1791, ηα μπμία δεκ έπμοκ ηαηαβναθεί ςξ θμνείξ ημο ζμφ ηαζ δεκ ειθάκζγακ ηθζκζηά ζοιπηχιαηα, πνδζζιμπμζήεδηακ ςξ ιδ ιμθοζιέκα δείβιαηα ηαζ ηζζπμφνεξ ιμθοζιέκεξ ιε ημκ ζυ ηδξ θειθμηφζηδξ πνδζζιμπμζήεδηακ ςξ εεηζηά δείβιαηα. Ζ ζηαηζζηζηή επελενβαζία ηςκ απμηεθεζιάηςκ έβζκε ιε ημ ηνζηήνζμ Υ 2 βζα επίπεδμ ζδιακηζηυηδηαξ 95%. 3.Απνηειέζκαηα ημ βνάθδια 1 πανμοζζάγεηαζ ημ πμζμζηυ πνμζαμθήξ απυ ημκ ζυ ηδξ θειθμηφζηδξ υπςξ οπμθμβίζηδηε απυ ηα 100 δείβιαηα πμο ελεηάζηδηακ. πςξ πνμηφπηεζ, μ ζυξ ακζπκεφηδηε ηυζμ ζηα αοβά υζμ ηαζ ζηζξ θάναεξ ζε πμζμζηά πνμζαμθήξ 70% ηαζ % ακηίζημζπα. ηα πμζμζηά πνμζαμθήξ πμο οπμθμβίζηδηακ δεκ παναηδνήεδηακ ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ. Δπίζδξ, ζηα ιμθοζιέκα δείβιαηα ηζζπμφναξ επζαεααζχεδηε δ φπανλδ ημο ζμφ εκχ ζηα δείβιαηα ημο είδμοξ D. macrophthalmus δεκ ακζπκεφηδηε μ ζυξ. 69

70 ποςοςτό προςβολήσ HydroMedit 2014, November 13-15, Volos, Greece 120% 100% 80% 60% 40% 20% 0% ημζρεσ μετά την εκκόλαψη Δηθφλα 1. Πνζνζηφ πξνζβνιήο απφ ηνλ ηφ ηεο ιεκθνθχζηεο γηα φιεο ηηο δεηγκαηνιεςίεο, 2 εκέξεο πξηλ ηελ εθθφιαςε θαη 2, 6, 10, 14, 18, 22, 26, 30, 34 εκέξεο κεηά ηελ εθθφιαςε. 4.πδήηεζε Ζ θειθμηφζηδ είκαζ ιία απυ ηζξ πζμ ζοπκά παναηδνμφιεκεξ ζμβεκείξ αζεέκεζεξ πνμηαθχκηαξ ζδιακηζηέξ εκδζζιυηδηεξ ζηδκ εκηαηζηή εηηνμθή ηδξ ηζζπμφναξ. Ο ηνυπμξ ιεηάδμζδξ ημο ζμφ δεκ έπεζ αηυια απμζαθζκζζηεί. Ζ ιεηάδμζδ ημο ιέζς ημο δένιαημξ ηςκ αναβπίςκ ηαζ ημο πεπηζημφ ζςθήκα είκαζ επζαεααζςιέκδ (Wolf 1988, Bowser et al. 1999) πςνίξ υιςξ κα έπεζ δζενεοκδεεί ζοζηδιαηζηά ημ εκδεπυιεκμ ηδξ ηάεεηδξ ιεηάδμζδξ ημο ζμφ. φιθςκα ιε ημοξ Cano et al. (2013) μ ζυξ ηδξ θειθμηφζηδξ ιπμνεί κα ιεηαδμεεί απυ ηθζκζηά οβζείξ βεκκήημνεξ μζ μπμίμζ είκαζ αζοιπηςιαηζημί θμνείξ ηαζ δ ιεηάδμζδ βίκεηαζ ιυκμ ιέζς ηδξ επζθάκεζαξ ημο αοβμφ υπςξ ηαζ ζηζξ πενζπηχζεζξ άθθςκ ζχκ (Brock & Bullis 2001). Ζ ηάεεηδ ιεηάδμζδ έπεζ επζαεααζςεεί ζε ζμβεκείξ αζεέκεζεξ ρανζχκ (Bootland et al. 1991, Breuil et al. 2002, Georgiadis et al. 2001, MacAllister et al. 1993, Mulcahy & Pascho 1985, Mushiake et al. 1994, Nylund et al. 2007). ηζξ πενζπηχζεζξ αοηέξ μ ιμθοζιαηζηυξ πανάβμκηαξ ιπμνεί κα εκημπίγεηαζ ιέζα ή έλς απυ ημοξ βαιέηεξ ή ημ έιανομ. Δπίζδξ, μ νυθμξ ηςκ εδθοηχκ ηαζ ηςκ ανζεκζηχκ δεκ έπεζ δζεοηνζκζζηεί ηαζ δ ιεηάδμζδ ζε πμθθέξ πενζπηχζεζξ είκαζ πζεακυ κα βίκεηαζ ηυζμ ιέζς ημο ςανίμο υζμ ηαζ ιέζς ημο ζπενιαημγςανίμο (Brock & Bullis 2001). Απυ ηα απμηεθέζιαηα ηδξ πανμφζαξ ένεοκαξ πνμέηορε υηζ μ ζυξ ηδξ θειθμηφζηδξ ακζπκεφηδηε ηυζμ ζηα αοβά υζμ ηαζ ζηζξ θάναεξ πμο ελεηάζηδηακ. Αοηυ ζε ζοκδοαζιυ ιε ημ βεβμκυξ υηζ ηα δείβιαηα πνμένπμκηακ απυ αζοιπηςιαηζημφξ βεκκήημνεξ ηαζ ιε ημ υηζ δεκ οπήνπε εκενβή θμίιςλδ ηάηα ηδκ πενίμδμ δεζβιαημθδρίαξ πζεακμθμβμφκ ηδκ ηάεεηδ ιεηάδμζδ ημο ζμφ. Ζ απμθφιακζδ ιε δζάθοια ζςδίμο δεκ πενζυνζζε ηδ ιεηάδμζδ ημο ζμφ, βεβμκυξ πμο οπμδεζηκφεζ υηζ έβζκε πζεακυκ ιέζς ημο ειανφμο, ζε ακηίεεζδ ιε ημοξ Cano et al. (2013), ζφιθςκα ιε ημοξ μπμίμο δ ιεηάδμζδ ημο ζμφ βίκεηαζ ιέζς ηδξ επζθάκεζαξ ημο αοβμφ. Δπίζδξ ημ ζηάδζμ πμνήβδζδξ ηδξ γςκηακήξ ηνμθήξ ηνίκεηαζ ζδζαίηενα ζδιακηζηυ αθμφ ιέζς αοηήξ είκαζ πζεακυ κα ιεηαδμεεί μ ζυξ. ηδκ πανμφζα ένεοκα ηα πμζμζηά πνμζαμθήξ πανέιεζκα ορδθά πνζκ ηαζ ιεηά ηδ πμνήβδζδ γςκηακήξ ηνμθήξ, βεβμκυξ πμο οπμδεζηκφεζ υηζ δ γςκηακή ηνμθή πζεακυκ δεκ επδνέαζε ηδ ιεηάδμζδ ημο ζμφ. Ο έθεβπμξ ηδξ αζεέκεζαξ πμο μθείθεηαζ ζημκ ζυ ηδξ θειθμηφζηδξ ααζίγεηαζ ζε πνμθδπηζηέξ δζαπεζνζζηζηέξ πναηηζηέξ πμο ζπεηίγμκηαζ ιε ηδκ επζθμβή ηαζ ηδκ εηηνμθή ηςκ βεκκδηυνςκ, ηδ ζοθθμβή ηαζ δζαηήνδζδ ηςκ βαιεηχκ, ηδκ εηηυθαρδ ηςκ αοβχκ ηαζ ηδ δζαπείνζζδ ηςκ θαναχκ 70

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72 VOLATILE METABOLITES AS POTENTIAL CHEMICAL SPOILAGE INDICES OF GREEK AQUACULTURED FISH SPECIES Boziaris I.S.*, Parlapani F.F. Dept. of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Fitokou street, 38446, N. Ionia, Volos, Greece ABSTRACT The aim of this work was to carry out a preliminary investigation of Volatile Organic Compounds (VOCs) produced during aerobic storage of gutted sea bream and sea bass at 2 o C, using SPME- GC/MS, in order to reveal any potential Chemical Spoilage Indices (CSIs) of Greek aquacultured fish spoilage/freshness. TVB-N (Total Volatile Base Nitrogen) was also determined. The fish products and fish juice model systems inoculated with spoilage microbiota isolated from sea bream were also used for the study. VOCs such as 3-methylbutanal, 2-methyl-1-butanol, 2-ethyl-1-hexanol, ethyl acetate, ethyl propionate and ethyl isobutyrate were attributed to microbial origin according to the results of the model system substrates experiment and also exhibited desirable profiles at both products. Therefore from this study, those VOCs can be considered as potential CSIs of gutted sea bream and sea bass. This study can be the first step for designing bio-sensors for on-pack freshness assessment and shelf life determination. Keywords: volatiles, sea bream, sea bass, spoilage, SPME- GC/MS * Corresponding author. Ioannis S. Boziaris (boziaris@uth.gr) ΓΤΝΑΜΗΚΖ ΣΖ ΥΡΖΖ ΣΧΝ ΠΣΖΣΗΚΧΝ ΜΔΣΑΒΟΛΗΣΧΝ Χ ΓΔΗΚΣΔ ΠΟΗΟΣΖΣΑ ΣΧΝ ΗΥΘΤΧΝ ΔΛΛΖΝΗΚΖ ΤΓΑΣΟΚΑΛΛΗΔΡΓΔΗΑ Μπνδηάξεο Η..*, Παξιαπάλε Φ.Φ. Σιήια Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ, πμθή Γεςπμκζηχκ Δπζζηδιχκ, Πακεπζζηήιζμ Θεζζαθίαξ, Φοηυημ,38446 Ν. Ηςκία, Βυθμξ, Δθθάδα Πεξίιεςε ημπυξ ηδξ ιεθέηδξ ήηακ δ δζενεφκδζδ ηδξ πνήζδξ ηςκ πηδηζηχκ ιεηααμθζηχκ ιζηνμαζαηήξ πνμέθεοζδξ πμο πανάβμκηαζ ηαηά ηδ δζάνηεζα ηδξ ζοκηήνδζδξ απεκηενςιέκδξ ηζζπμφναξ ηαζ θααναηζμφ ζοζηεοαζιέκςκ ζε ζοκεήηεξ αένα ζημοξ 2 μ C, ζακ πδιζημί δείηηεξ αθθμίςζδξ/κςπυηδηαξ. Οζ πηδηζημί ιεηααμθίηεξ αθμνμφζακ ηθαζζζημφξ δείηηεξ υπςξ ημ Οθζηυ Πηδηζηυ Βαζζηυ Άγςημ (ΟΠΒΑ), ηαεχξ ηαζ πηδηζηχκ μοζζχκ πμο πνμζδζμνίζηδηακ ιε SPME (Solid Phase MicroExtraction) ζε ζοκδοαζιυ ιε αένζα πνςιαημβναθία-θαζιαημζημπία ιάγαξ (GC/MS). Ζ ιεθέηδ πναβιαημπμζήεδηε ζε πναβιαηζηά πνμσυκηα αθθά ηαζ ζε ιμκηέθα οπμζηνχιαηα ηα μπμία πνμζμιμζάγμοκ ημ αθίεοια εκμθεαθιζζιέκα ιε ημοξ αθθμζςβυκμοξ ιζηνμμνβακζζιμφξ. Απυ ηδκ ιεθέηδ πνμέηορε υηζ δ μ ηθαζζζηυξ δείηηδξ ΟΠΒΑ είκαζ ακεπανηήξ ηαζ ιπμνεί κα πνδζζιμπμζδεεί ιυκμ ςξ ηνζηήνζμ απμδμπήξ/απυννζρδξ ηςκ πνμσυκηςκ ηαζ υπζ ςξ δείηηδξ κςπυηδηαξ. Ζ 3-ιεεοθαμοηακάθδ, 2-ιεεοθ-1-αμοηακυθδ, 2-αζεοθ-1-ελακυθδ, μλζηυξ αζεοθεζηέναξ, πνμπζμκζηυξ αζεοθεζηέναξ ηαζ μ ζζμαμοηονζηυξ αζεοθεζηέναξ απμηεθμφκ πζεακμφξ πδιζημφξ δείηηεξ κςπυηδηαξ ηαζ βζα ηα δφμ πνμσυκηα. Πνάβιαηζ, μζ ακςηένς ιεηααμθίηεξ απμηεθμφκ απμηθεζζηζηά ιεηααμθζηά πνμσυκηα ηςκ αθθμζςβυκςκ ιζηνμμνβακζζιχκ υπςξ έδεζλακ ηαζ μζ ιεηνήζεζξ ζηα ιμκηέθα οπμζηνχιαηα. Ζ ιεθέηδ αοηή ιπμνεί κα έπεζ ζδιακηζηή πναηηζηή εθανιμβή ζηδ αζμιδπακία ηνμθίιςκ δζυηζ απμηεθεί ηδ αάζδ βζα ηδκ ακάπηολδ αζμαζζεδηήνςκ μζ μπμίμζ εα ακζπκεφμοκ ημοξ ιζηνμαζαημφξ ιεηααμθίηεξ ζημ εζςηενζηυ ηδξ ζοζηεοαζίαξ ηαζ εα ημοξ ζοζπεηίγμοκ ιε ηδκ πμζυηδηα ημο πνμσυκημξ ηαζ ημκ εκαπμιείκακηα ειπμνζηυ πνυκμ γςήξ. Λέξειρ κλειδιά: πηεηηθνί κεηαβνιίηεο, ηζηπνύξα, ιαβξάθη, αιινίσζε, SPME- GC/MS *πγγξαθέαο επηθνηλσλίαο: Μπμγζάνδξ Ηςάκκδξ. (boziaris@uth.gr) 72

73 log cfu/g log cfu/g HydroMedit 2014, November 13-15, Volos, Greece 1. Δηζαγσγή Ζ ιζηνμαζαηή αθθμίςζδ απμηεθεί ημκ ηονζυηενμ ιδπακζζιυ οπμαάειζζδξ ηδξ πμζυηδηαξ ζημοξ κςπμφξ ζπεφεξ (Gram & Huss 1996). Έκαξ εκαθθαηηζηυξ ηνυπμξ πνμζδζμνζζιμφ ηδξ αθθμίςζδξ είκαζ δ εηηίιδζδ ηδξ αθθμζςβυκμο δοκαιζηήξ ηςκ ιζηνμμνβακζζιχκ ιέζς ημο πνμζδζμνζζιμφ ηςκ ιεηααμθζηχκ ημοξ πνμσυκηςκ πμο πνμηαθμφκ ηδκ αθθμίςζδ ηαζ ηδκ μνβακμθδπηζηή απυννζρδ. Οζ ιζηνμμνβακζζιμί αοημί (Δζδζημί Αθθμζςβυκμζ Μζηνμμνβακζζιμί-ΔΑΜ) πανάβμοκ μοζίεξ (πδιζημί δείηηεξ αθθμίςζδξ/κςπυηδηαξ) μζ μπμίεξ είκαζ οπεφεοκεξ βζα ηδ δδιζμονβία δοζάνεζηςκ μζιχκ ιε ζοκέπεζα ηδκ μνβακμθδπηζηή απυννζρδ ηςκ αθζεοηζηχκ πνμσυκηςκ υηακ μ πθδεοζιυξ ημοξ θεάζεζ ζε ορδθά επίπεδα ηδξ ηάλδξ ηςκ 7-9 log cfu/g (Gram & Huss 1996). Γζάθμνεξ μοζίεξ υπςξ αθημυθεξ, αθδεΰδεξ, ηεηυκεξ, εεζχδδ ζοζηαηζηά, αιιςκία, εζηένεξ ηαζ μνβακζηά μλέα είκαζ μζ ηονζυηενεξ μιάδεξ ιζηνμαζαηχκ ιεηααμθζηχκ πμο πανάβμκηαζ απυ ηδ δνάζδ ηςκ αθθμζςβυκςκ ιζηνμμνβακζζιχκ ζηα ζπεοδνά. Οζ ιεηααμθίηεξ αοημί είκαζ ζοκήεςξ οπεφεοκμζ βζα ηζξ παναηηδνζζηζηέξ δοζάνεζηεξ μζιέξ υπςξ αοηή ηδξ αιιςκίαξ απυ ηνζιεεοθαιίκδ ηαζ αιιςκία, ημο εεζαθζμφ απυ εεζμφπεξ πηδηζηέξ εκχζεζξ, ηδξ αφκδξ απυ ιζηνμφ ιμνζαημφ αάνμοξ αθημυθεξ, αθδεΰδεξ ηαζ ηεηυκεξ (Dalgaard 2003). Οζ πηδηζηέξ μοζίεξ είκαζ δοκαηυ κα ιεηααάθθμκηαζ ζδιακηζηά ιεηαλφ ηδξ πνχηδξ διέναξ ηαζ ηδξ διέναξ απυννζρδξ ηαηά ηδ δζάνηεζα ζοκηήνδζδξ ηςκ αθζεοιάηςκ. Γζα ημ θυβμ αοηυ, μ πνμζδζμνζζιυξ ημοξ ηαηά ηδ δζάνηεζα ηδξ ζοκηήνδζδξ εκυξ αθζεοηζημφ πνμσυκημξ ηαζ δ πεναζηένς πνήζδ ημοξ ςξ δείηηεξ αθθμίςζδξ απμηεθεί ηδ κέα ηάζδ βζα ιεθέηδ (Parlapani et al. 2014a). ημπυξ ηδξ πανμφζαξ ιεθέηδξ ήηακ δ δζενεφκδζδ ηδξ πνήζδξ ηςκ πηδηζηχκ ιεηααμθζηχκ ιζηνμαζαηήξ πνμέθεοζδξ πμο πανάβμκηαζ ηαηά ηδ δζάνηεζα ζοκηήνδζδξ απεκηενςιέκδξ ηζζπμφναξ ηαζ θααναηζμφ ζημοξ 2 μ C ςξ πδιζημί δείηηεξ αθθμίςζδξ/κςπυηδηαξ. 2. Τιηθά θαη Μέζνδνη ηδκ πανμφζα ιεθέηδ δζενεοκήεδηε δ παναβςβή πηδηζηχκ ιεηααμθζηχκ ηαηά ηδ δζάνηεζα ηδξ ζοκηήνδζδξ απεκηενςιέκςκ ζπεφςκ ηζζπμφναξ ηαζ θααναηζμφ ζε ζοκεήηεξ αένα ζημοξ 2 μ C. Δπζπθέμκ, ιε ηδ πνήζδ ζηενεχκ ιμκηέθςκ οπμζηνςιάηςκ απυ ζπεομγςιυ ιεθεηήεδηε δ παναβςβή πηδηζηχκ ιεηααμθζηχκ, απυ ηάεε ηαηδβμνία αθθμζςβυκςκ ιζηνμμνβακζζιχκ, ιε ζημπυ κα δζενεοκδεεί δ ζοκεζζθμνά ημο ηαεεκυξ ζηδκ παναβςβή πζεακχκ πδιζηχκ δεζηηχκ ιζηνμαζαηήξ αθθμίςζδξ. Οζ ιζηνμμνβακζζιμί πμο πνδζζιμπμζήεδηακ βζα ειαμθζαζιυ (ειαυθζμ ηδξ ηάλδξ ημο 5*10 3 cfu/g) ήηακ Pseudomonas, Shewanella ηαζ μλοβαθαηηζηά ααηηήνζα (Carnobacterium, Lactobacillus) μζ μπμίμζ απμιμκχεδηακ ηαζ ηαοημπμζήεδηακ ιε ιμνζαηέξ ηεπκζηέξ ζε πνμδβμφιεκδ ιεθέηδ (Parlapani et al. 2014b). Ο πνμζδζμνζζιυξ ηςκ πηδηζηχκ μοζζχκ ιε SPME-GC/MS ηαζ δ ιζηνμαζμθμβζηή ακάθοζδ πναβιαημπμζήεδηακ ζφιθςκα ιε ημοξ Parlapani et al. (2014a). Οζ πηδηζηέξ πμζμηζημπμζήεδηακ ςξ ιέζμ ειααδυ ηςκ ημνοθχκ ηδξ GC δφμ ιεηνήζεςκ. 3. Απνηειέζκαηα Ο ειπμνζηυξ πνυκμξ γςήξ ηςκ δφμ πνμσυκηςκ ήηακ 9 διένεξ. Σα Pseudomonas spp. απμηέθεζακ ημκ ηονίανπμ αθθμζςβυκμ ιζηνμμνβακζζιυ (ΔΑΜ) ηαζ ζηζξ δφμ πενζπηχζεζξ (Δζηυκα 1). Οζ ηζιέξ ημο ΟΠΒΑ άνπζζακ ακ αολάκμκηαζ απυ ημ ιέζμ ηαζ πνμξ ημ ηέθμξ ημο ειπμνζημφ πνυκμο γςήξ ηαζ ήηακ πανυιμζεξ ηαζ βζα ηα δφμ πνμσυκηα (Δζηυκα 2) τσιπούρα λαβράκι Χπόνορ ζςνηήπηζηρ (ημέπερ) Χπόνορ ζςνηήπηζηρ (ημέπερ) Δηθφλα 1. Μεηαβνιέο ησλ πιεζπζκψλ TVC ( ), Pseudomonas spp. ( ), H 2 S producing bacteria ( ), Enterobacteriaceae ( ), Brochothrix thermosphacta ( ) and LAB ( ) θαηά ηε δηάξθεηα ζπληήξεζεο απεληεξσκέλεο ηζηπνχξαο θαη ιαβξαθηνχ ζηνπο 2 o C. Ζ θάζεηε δηαθεθνκκέλε γξακκή αληηζηνηρεί ζηελ νξγαλνιεπηηθή απφξξηςε ησλ πξντφλησλ. 73

74 TVB-N (mg N/100g) TVB-N (mg N/100g) HydroMedit 2014, November 13-15, Volos, Greece ηζιπούπα λαβπάκι Ημέρες Ημέρες Δηθφλα 2. Μεηαβνιέο ΟΠΒΑ θαηά ηε δηάξθεηα ηεο ζπληήξεζεο απεληεξσκέλεο ηζηπνχξαο θαη ιαβξαθηνχ ζηνπο 2 o C. Ζ θάζεηε δηαθεθνκκέλε γξακκή αληηζηνηρεί ζηελ νξγαλνιεπηηθή απφξξηςε ησλ πξντφλησλ. Πηζαλνί ρεκηθνί δείθηεο κηθξνβηαθήο πξνέιεπζεο ζηνπο ηρζύεο Οζ πηδηζηέξ μοζίεξ 3-ιεεοθ-αμοηακάθδ, 2-ιεεοθ-αμοηακυθδ, 2-αζεοθ-1-ελακυθδ, μλζηυξ ηαζ πνμπζμκζηυξ αζεοθεζηέναξ ανέεδηακ κα αολάκμκηαζ ηαηά ηδ δζάνηεζα ζοκηήνδζδξ ηαζ ηςκ δφμ πνμσυκηςκ ζε αενυαζεξ ζοκεήηεξ ζημοξ 2 μ C (Δζηυκεξ 1-3). area x μεθςλ-βοςηανάλη, ηζιπούπα ημέπερ area x μεθςλ-βοςηανάλη, λαβπάκι ημέπερ Δηθφλα 1. ρεηηθέο κεηαβνιέο ηεο ζπγθέληξσζεο ηεο 3-κεζπι-βνπηαλάιεο θαηά ηε δηάξθεηα ζπληήξεζεο απεληεξσκέλεο ηζηπνχξαο θαη ιαβξαθηνχ ζηνπο 2 o C. area x μεθςλ-1-βοςηανόλη, ηζιπούπα ημέπερ area x μεθςλ-1-βοςηανόλη, λαβπάκι ημέπερ 74

75 area x αιθςλ-1-εξανόλη, ηζιπούπα ημέπερ 40 2-αιθςλ-1-εξανόλη, λαβπάκι area x ημέπερ Δηθφλα 2. ρεηηθέο κεηαβνιέο ηεο ζπγθέληξσζεο ησλ αιθννιψλ 2-κεζπι-1-βνπηαλφιεο θαη 2- αηζπι-1-εμαλφιε θαηά ηε δηάξθεηα ζπληήξεζεο απεληεξσκέλεο ηζηπνχξαο θαη ιαβξαθηνχ ζηνπο 2 o C. area x οξικόρ αιθςλεζηέπαρ, ηζιπούπα ημέπερ area x οξικόρ αιθςλεζηέπαρ, λαβπάκι ημέπερ area x πποπιονικόρ αιθςλεζηέπαρ, ηζιπούπα ημέπερ ημέπερ Δηθφλα 3. ρεηηθέο κεηαβνιέο ηεο ζπγθέληξσζεο εζηέξσλ θαηά ηε δηάξθεηα ζπληήξεζεο απεληεξσκέλεο ηζηπνχξαο θαη ιαβξαθηνχ ζηνπο 2 o C. Πηεηηθέο νπζίεο πνπ παξήρζεζαλ από κηθξνβηαθή δξαζηεξηόηεηα ζε κνληέια ηρζύνο Σα Pseudomonas spp. ηαζ ηα Shewanella spp. ανέεδηε κα πανάβμοκ πανυιμζμοξ ιεηααμθίηεξ. Πανυθα αοηά μζ αζεοθεζηένεξ ηαζ ημ 2-αμοηεκμσηυ μλφ πανήπεδζακ απμηθεζζηζηά απυ ηα Pseudomonas spp. (Πίκαηαξ 1). Δπζπθέμκ, δ 2-ιεεοθ-αμοηακάθδ, δ 3-ιεεοθ-αμοηακάθδ ηαζ 3- φδνμλο-2-αμοηακυκδ πανήπεδζακ απμηθεζζηζηά απυ ηα μλοβαθαηηζηά ααηηήνζα (Πίκαηαξ 1). area x πποπιονικόρ αιθςλεζηέπαρ, λαβπάκι 75

76 Πίλαθαο 1. Πηεηηθνί κεηαβνιίηεο απφ ηε δξάζε ησλ Pseudomonas spp., Shewanella spp. θαη νμπγαιαθηηθψλ βαθηεξίσλ ζε ζηείξα κνληέια ππνζηξψκαηα απφ ηρζπνδσκφ θαηά ηε ζπληήξεζή ηνπο ππφ αεξφβηεο ζπλζήθεο ζε ρακειέο ζεξκνθξαζίεο (ςχμεο). Μεηαβνιίηεο Pseudomonas Shewanella Ομπγαιαθηηθά Αιθνφιεο 2-ιεεοθ-1-αμοηακυθδ X X 3-ιεεοθ-1-αμοηακυθδ X X X αζεακυθδ X X X Αιδευδεο 2-ιεεοθ-αμοηακάθδ X 3-ιεεοθ-αμοηακάθδ X Κεηφλεο 2-πεκηακυκδ X X 2-επηακυκδ X X 2-εκκεακυκδ X X 2-εκδεηακυκδ X X 3-φδνμλο-2-αμοηακυκδ X Δζηέξεο 2-ιεεφθ-αμοηονζηυξ αζεοθεζηέναξ X ζζμααθενζηυξ αζεοθεζηέναξ X ηνακξ-2-ιεεφθ-2-αμοηεκζηυξ αζεοθεζηέναξ X πνμπζμκζηυξ αζεοθεζηέναξ X Οξγαληθά νμέα μλζηυ μλφ X X 2-αμοηεκμσηυ μλφ Υ νπιθίδηα δζιεεοθμζμοθθίδζμ Υ Υ 4. πδήηεζε Ζ αθθμίςζδ βίκεηαζ ακηζθδπηή ελαζηίαξ ηςκ αθθαβχκ ζηα μνβακμθδπηζηά παναηηδνζζηζηά ηςκ αθζεοηζηχκ πνμσυκηςκ. Οοζίεξ μζ μπμίεξ πανάβμκηαζ ηονίςξ απυ ιζηνμαζαηή δναζηδνζυηδηα υπςξ είκαζ ημ ΟΠΒΑ, ηνζιεεοθαιίιδ, μζ αζμβεκείξ αιίκεξ η.ά. έπμοκ πνμηαεεί ςξ δείηηεξ αθθμίςζδξ. Πανυθα αοηά μζ μοζίεξ αοηέξ έπμοκ απμδεζπεεί ιδ ζηακμπμζδηζηέξ βζα ηδ πνήζδ ημοξ ςξ πδιζημί δείηηεξ αθθμίςζδξ ζηδκ ηζζπμφνα (Parlapani et al. 2014a). Δπζπθέμκ, ημ ΟΠΒΑ απμδείπεδηε ιδ ζηακμπμζδηζηυξ δείηηδξ αθθμίςζδξ ζηδκ απεκηενςιέκδ ηζζπμφνα ηαζ ζημ απεκηενςιέκμ θαανάηζ. Ζ ακαγήηδζδ πζμ αλζυπζζηςκ δεζηηχκ απυ δζάθμνμοξ ενεοκδηέξ αθθά ηαζ απυ ηδκ πανμφζα ιεθέηδ ακέδεζλε ανηεηέξ μοζίεξ μζ μπμίεξ εα ιπμνμφζακ κα πνδζζιμπμζδεμφκ ςξ πδιζημί δείηηεξ αθθμίςζδξ ιζηνμαζαηήξ πνμέθεοζδξ ζηα αθζεοηζηά πνμσυκηα. Γζάθμνεξ μοζίεξ έπμοκ ακαθενεεί ςξ πζεακμί πνήζζιμζ πδιζημί δείηηεξ ηαηά ηδκ αθθμίςζδ ηςκ αθζεοιάηςκ ζηδ αζαθζμβναθία. Χζηυζμ, δ πανμφζα ιεθέηδ ηαεχξ ηαζ δ ζπεηζηή δδιμζίεοζδ πμο αθμνά θζθέηα ζπεφμξ ηζζπμφναξ (Parlapani et al. 2014a) είκαζ μζ πνχηεξ ιεθέηεξ πνμζδζμνζζιμφ πηδηζηχκ ιεηααμθζηχκ βζα πνήζδ ςξ πδιζημί δείηηεξ αθθμίςζδξ/κςπυηδηαξ ζε αθζεοηζηά πνμσυκηα ηδξ εθθδκζηήξ οδαημηαθθζένβεζαξ. Ζ 3-ιεεοθαμοηακάθδ ανέεδηε κα απμηεθεί πζεακυ πδιζηυ δείηηδ κςπυηδηαξ/αθθμίςζδξ ιζηνμαζαηήξ πνμέθεοζδξ ηαζ ζηα θζθέηα ηζζπμφναξ (Parlapani et al. 2014a). Ζ μοζία αοηή ηαεχξ ηαζ δ 2-ιεεοθαμοηακάθδ ανέεδηακ ςξ πνμσυκηα ιεηααμθζζιμφ ηςκ μλοβαθαηηζηχκ ααηηδνίςκ ζηδκ πανμφζα ιεθέηδ. Πνάβιαηζ, μζ Joffraud et al. (2001) ακαθένμοκ ηζξ δφμ μοζίεξ ςξ πνμσυκηα ιεηααμθζζιμφ ηςκ Carnobacterium ηαηά ηδκ αθθμίςζδ αθζεοηζηχκ πνμσυκηςκ. Δπζπθέμκ, δ παναβςβή ηδξ 2-αζεοθ-1- ελακυθδ έπεζ ζοκδεεεί ηονίςξ ιε ιζηνμαζαηή δναζηδνζυηδηα. Πνάβιαηζ, δ μοζία αοηή ακζπκεφεδηε ζηα ιμκηέθα ιε ηα μλοβαθαηηζηά ααηηήνζα. Δπζπθέμκ, δ παναβςβή ηςκ αζεοθεζηένςκ ζπεηίγεηαζ ιε ηδ ιεηααμθζηή δναζηδνζυηδηα ηςκ Pseudomonas spp, υπςξ πνμέηορε απυ ηδκ πανμφζα αθθά ηαζ απυ άθθεξ ακαθμνέξ (Casaburi et al. 2014). θεξ μζ παναπάκς μοζίεξ αοηέξ ανέεδηε κα πανάβμκηαζ θυβς ιζηνμαζαηήξ δναζηδνζυηδηαξ ηαζ κα πανμοζζάγμοκ αφλδζδ ηαζ ζηα δφμ πνμσυκηα ηαζ ζηα ιμκηέθα ηαηά ηδ δζάνηεζα ηδξ ζοκηήνδζδξ. Ζ ιεθέηδ αοηή εα έπεζ ζδιακηζηή πναηηζηή εθανιμβή ζηδ αζμιδπακία ηνμθίιςκ δζυηζ απμηεθεί ηδ αάζδ βζα ηδκ ακάπηολδ αζμαζζεδηήνςκ μζ μπμίμζ εα ακζπκεφμοκ ημοξ ιζηνμαζαημφξ ιεηααμθίηεξ ζημ εζςηενζηυ ηδξ ζοζηεοαζίαξ ηαζ εα ημοξ ζοζπεηίγμοκ ιε ηδκ πμζυηδηα ημο πνμσυκημξ ηαζ ημκ εκαπμιείκακηα ειπμνζηυ πνυκμ γςήξ. 76

77 Βηβιηνγξαθία Casaburi A., Piombino P., Nychas G.-J., Villani F., Ercolini D. (2014). Bacterial populations and the volatilome associated to meat spoilage. Food Microbiology, DOI: /j.fm Dalgaard P. (2003). Spoilage of seafood. In: Encyclopedia of food science and nutrition, Caballero B., Trugo L., Finglas P. (eds). London: Academic Press., pp Gram L., Huss H.H. (1996). Microbiological spoilage of fish and fish products. International Journal of Food Microbiology 33, Joffraud J.J., Leroi F., Roy C., Berdague J.L. (2001). Characterisation of volatile compounds produced by bacteria isolated from the spoilage flora of cold-smoked salmon. International Journal of Food Microbiology 66, Parlapani F.F., Mallouchos A., Haroutounian S.A., Boziaris I.S. (2014a). Microbiological spoilage and investigation of volatiles profile during storage of sea bream fillets under various conditions. International Journal of Food Microbiology 189, Parlapani F.F., Kormas Ar.K., Boziaris I.S. (2014b). Microbiological changes, shelf life and identification of initial and spoilage microbiota of sea bream fillets stored under various conditions using 16S rrna gene analysis. Journal of the Science of Food and Agriculture (accepted). 77

78 RESEARCH OF THE COOLING EFFECT WITH EVAPORATION IN THE MICROCLIMATE OF NET-COVERED GREENHOUSE AND IN THE GROWTH OF FARMED SNAILS Apostolou K. 1 *, Neofytou C. 1, Aifanti S. 1, Katsoulas N. 2, Kittas C. 2, Hatziioannou M. 1 1 Department of Ichthyology & Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Fytoko Street, , Nea Ionia Magnesia, Greece 2 Agriculture Crop Production and Rural Environment, School of Agricultural Sciences, University of Thessaly, Fytoko Street, , Nea Ionia Magnesia, Greece ABSTRACT This paper presents the results that arise from the operation of the experimental snail farming station of the Department of Ichthyology & Aquatic Environment of the University of Thessaly. A netcovered greenhouse of 300 m 2 was established in the yard of the School of Agricultural Sciences (Volos, Greece). The maintenance of the appropriate humidity is assured via a mist propagation system with watering, of high and low pressure. The aim of this experiment was twofold: to determine whether the appropriate climatic conditions for snail rearing can be maintained within the net house in two different seasons, and to estimate certain technical characteristics, like the electric wire fence as well as the substrate of the establishment. New born snails Cornu aspersum which came from wild breeders were used for the experiment. The first experiment took place during the summer and lasted for a month (9/8/2011 until 6/9/2011). The Temperature inside the net house ranged from 15 C 25 C and the Relative Humidity was in a very good level (82,95 ± 17.2). During the second experimental period which took place in October, for a month as well (7/10/11 until 11/11/11), the Relative Humidity inside the net-covered greenhouse was high, while the average air temperature was lower inside (12,62 C) compared to the surrounding environment (14,8 C). The summer was associated with a high mortality rate for snails (58,2%), mainly due to the snails' escapes owing to technical problems. However, the mortality rate decreased significantly in the fall (18%) and the increase in snails' biomass was higher in the fall (28,96%) compared to the summer (16,5%). Key words: snail farming, climatic conditions, net covered greenhouse. *Corresponding author: Apostolou Konstantinos ( apostolou@uth.gr ) ΜΔΛΔΣΖ ΣΖ ΔΠΗΓΡΑΖ ΓΡΟΗΜΟΤ ΜΔ ΔΞΑΣΜΗΖ ΣΟ ΜΗΚΡΟΚΛΗΜΑ ΣΟΤ ΓΗΥΣΤΟΚΖΠΗΟΤ ΚΑΗ ΣΖΝ ΑΤΞΖΖ ΣΧΝ ΔΚΣΡΔΦΟΜΔΝΧΝ ΑΛΗΓΚΑΡΗΧΝ Απνζηφινπ Κ. 1 *, Νενθχηνπ Υ. 1, Αυθαληή. 1, Καηζνχιαο Ν. 2, Κίηηαο Κ. 2 Υαηδεησάλλνπ Μ. 1 1 Σιήια Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ, πμθή Γεςπμκζηχκ Δπζζηδιχκ, Πακεπζζηήιζμ Θεζζαθίαξ, μδυξ Φοηυημο, , Νέα Ηςκία, Δθθάδα 2 Σιήια Γεςπμκίαξ Φοηζηήξ Παναβςβήξ ηαζ Αβνμηζημφ Πενζαάθθμκημξ, πμθή Γεςπμκζηχκ Δπζζηδιχκ, Πακεπζζηήιζμ Θεζζαθίαξ,, μδυξ Φοηυημο, , Νέα Ηςκία, Δθθάδα Πεξίιεςε ηδκ ενβαζία πανμοζζάγμκηαζ ηα απμηεθέζιαηα απυ ηδκ θεζημονβία ημο πεζναιαηζημφ ζηαειμφ εηηνμθήξ ζαθζβηανζχκ ημο Σιήιαημξ Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ ημο Πακεπζζηδιίμο Θεζζαθίαξ. Πνυηεζηαζ βζα έκα δζπηομηήπζμ, επζθάκεζαξ 300 m 2, πμο είκαζ εβηαηεζηδιέκμ ζημκ πνμαφθζμ πχνμ ηδξ πμθή Γεςπμκζηχκ Δπζζηδιχκ (Βυθμξ, Δθθάδα). Ζ δζαηήνδζδ ηδξ απαζημφιεκδξ οβναζίαξ επζηοβπάκεηαζ ιε ζφζηδια οδνμκέθςζδξ, ορδθήξ ηαζ παιδθήξ πίεζδξ ιε ρεηαζιυ κενμφ. ηυπμξ ημο πεζνάιαημξ ήηακ κα δζαπζζηςεεί ακ ζημ δζπηομηήπζμ είκαζ δοκαηυκ κα δζαηδνδεμφκ ηθζιαηζηέξ ζοκεήηεξ ηαηάθθδθεξ βζα ηδκ πάποκζδ ηςκ ζαθζβηανζχκ ζε δφμ δζαθμνεηζηέξ επμπέξ ηαεχξ ηαζ κα αλζμθμβδεμφκ μνζζιέκα ηεπκζηά παναηηδνζζηζηά ηδξ εβηαηάζηαζδξ υπςξ δ διεηηνμθυνα πενίθναλδ ηαζ ημ οπυζηνςια. Γζα ηζξ ακάβηεξ ημο πεζνάιαημξ πνδζζιμπμζδεήηακ κεμβέκκδηα ζαθζβηάνζα (βυκμξ) ημο είδμοξ Cornu aspersum πμο πνμήθεακ απυ αβνίμοξ βεκκήημνεξ. Ζ πνχηδ πεζναιαηζηή εηηνμθή πναβιαημπμζήεδηε ημ Καθμηαίνζ ηαζ δζήνηδζε 78

79 έκα ιήκα (9/8/2011 έςξ 6 /9/2011). Ζ εενιμηναζία ζημ εζςηενζηυ ηδξ εβηαηάζηαζδξ ηοιάκεδηε ιεηαλφ 15 C - 25 C ηαζ δ ζπεηζηή οβναζία ημο αένα ηοιάκεδηε ζε πμθφ ηαθά επίπεδα (82,95 ± 17.2). Καηά ηδ δεφηενδ πεζναιαηζηή πενίμδζμ, πμο πναβιαημπμζήεδηε ημκ Οηηχανζμ ηαζ δζήνηδζε επίζδξ έκακ ιήκα (7/10/11 έςξ 11/11/11) δ ζπεηζηή οβναζία ημο αένα εκηυξ ημο δζπηομηδπίμο ήηακ ορδθή εκχ δ ιέζδ εενιμηναζία ημο αένα ήηακ παιδθυηενδ ζημ εζςηενζηυ (12,62 C) ζε ζπέζδ ιε ημκ πενζαάθθμκηα πχνμ (14,8 C). Σμ Καθμηαίνζ ηαηαβνάθδηε ορδθυ πμζμζηυ εκδζζιυηδηαξ ηςκ ζαθζβηανζχκ (58,2%) ηονίςξ ελαζηίαξ ηδξ δζαθοβήξ ημοξ θυβς ηεπκζηχκ πνμαθδιάηςκ. Σμ Φεζκυπςνμ ιεζχεδηε ζδιακηζηά δ εκδζζιυηδηα (18%). Ζ αφλδζδ ηδξ αζμιάγαξ ηςκ ζαθζβηανζχκ ήηακ ιεβαθφηενδ ημ Φεζκυπςνμ (28,96%), ζε ζπέζδ ιε ημ ηαθμηαίνζ (16,5%). Λέξειρ κλειδιά: αιηγθαξνηξνθία, θιηκαηνινγηθέο ζπλζήθεο, δηρηπνθήπην. *οββναθέαξ επζημζκςκίαξ: Απμζηυθμο Κςκζηακηίκμξ (apostolou@uth.gr ) 1. ΔΗΑΓΧΓΖ Σα ζαθζβηάνζα απμηεθμφκ ηνυθζιμ ημ μπμίμ ηαηακαθχκεηαζ απυ εηαημιιφνζα ακενχπμοξ ζε μθυηθδνμ ημκ ηυζιμ (Jess & Marks 1998, Milinsk et al. 2006). Ζ εηηνμθή ημοξ πανμοζζάγεζ πμθθά πθεμκεηηήιαηα, ηαεχξ ηα ζαθζβηάνζα απμηεθμφκ απμδμηζημφξ παναβςβμφξ ηνέαημξ, ηαζ άθθςκ πνμσυκηςκ ιε πνμζηζεέιεκδ αλία (Boyd et al. 1986, Pivoravov et al. 1995). Ζ ηαηακάθςζδ ηςκ ζαθζβηανζχκ ζηδκ αβμνά ηδξ Δονςπασηήξ Έκςζδξ ηοιαίκεηαζ ζε ζδζαίηενα ορδθά επίπεδα ηαεχξ μζ εζζαβςβέξ αολήεδηακ απυ ημ 1995, ζε ημ 2010 (Οζημκυιμο 2013). Ζ εηηνμθή ζαθζβηανζχκ (αθζβηανμηνμθία, Heliciculture) πναβιαημπμζείηαζ ζε ακμζπηυ πχνμ (πςνάθζ), ζε πθήνςξ εθεβπυιεκεξ ζοκεήηεξ ή ζε δζπηομηήπζα. Γζα ηδκ πάποκζδ ηςκ ζαθζβηανζχκ απαζηείηαζ έκα ήπζμ ηθίια ιε ιέηνζα εενιμηναζία (20-25 μ C) ζε ζοκδοαζιυ ιε ορδθή οβναζία (75-95%) ακ ηαζ ηα πενζζζυηενα είδδ ιπμνμφκ κα δζααζχζμοκ ζε έκα εονφηενμ θάζια εενιμηναζζχκ (5-30ºC) (Bailey 1981, Iglesias et al. 1996, Murphy 2001). Ζ πανμφζα ιεθέηδ απμηεθεί ηδκ πνχηδ ιεθέηδ επίδναζδξ ημο δνμζζζιμφ ιε ελάηιζζδ ζημ ιζηνμηθίια ημο δζπηομηδπίμο ηαζ ζηδκ αφλδζδ ηςκ εηηνεθυιεκςκ ζαθζβηανζχκ, ηαεχξ πανυιμζεξ ένεοκεξ έπμοκ βίκεζ ιυκμ ζε γχα πμο ιεβαθχκμοκ ζε πθήνςξ εθεβπυιεκεξ ζοκεήηεξ ζημ ενβαζηήνζμ (Lazaridou - Dimitriadou et al. 1998, Dupont-Nivet et al. 2000). ηδκ ενβαζία ηςκ Καηζμφθα ηαζ ζοκ. (2013), έβζκε έθεβπμξ ηδξ εενιμηναζίαξ ηαζ ζπεηζηήξ οβναζίαξ ημο αένα ηςκ δζπηομηδπίμο ηαζ δμηζιή ημο ζε πναβιαηζηέξ ζοκεήηεξ ηαηά ηδ δζάνηεζα ημο ηαθμηαζνζμφ. ηυπμξ ημο πεζνάιαημξ αοημφ ήηακ κα δζαπζζηςεεί ακ ζημ δζπηομηήπζμ είκαζ δοκαηυκ κα δζαηδνδεμφκ ηθζιαηζηέξ ζοκεήηεξ ηαηάθθδθεξ βζα ηδκ πάποκζδ ηςκ ζαθζβηανζχκ ημο είδμοξ Cornu aspersum ηαζ κα ζοβηνζεμφκ δφμ πενζυδμζ εηηνμθήξ (Καθμηαίνζ - Φεζκυπςνμ). Πανάθθδθα αλζμθμβήεδηακ μνζζιέκα ηεπκζηά παναηηδνζζηζηά ηδξ εβηαηάζηαζδξ, υπςξ δ θεζημονβία ηςκ δθεηηνμθυνςκ ηαζ δ απμηεθεζιαηζηυηδηα ημο ελμπθζζιμφ (οπυζηνςια, ηαηαθφβζα, ηαΐζηνεξ). 2. ΤΛΗΚΑ ΚΑΗ ΜΔΘΟΓΟΗ Ο πεζναιαηζηυξ ζηαειυξ εηηνμθήξ ζαθζβηανζχκ ημο Δνβαζηδνίμο Ηπεομθμβίαξ Τδνμαζμθμβίαξ ημο Σιήιαημξ Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ ημο Πακεπζζηδιίμο Θεζζαθίαξ είκαζ έκα δζηηομηήπζμ 300 m 2, πμο απμηεθεί έκα ηφπμ ηνμπμπμζδιέκμο ημλςημφ εενιμηδπίμο. Σμ δζπηομηήπζμ ηαηαζηεοάζηδηε απυ ιεηαθθζηυ ζηεθεηυ (7 m πθάημξ, 2,5 m φρμξ), πμο ηαθφπηεηαζ ιε δίπηο ζηίαζδξ, ιε ηάθορδ 90%. Πενζιεηνζηά, οπάνπεζ ηάθορδ ιε θαιανίκα, φρμοξ 80 cm, ζε αάεμξ 20 cm, δ μπμία απμηνέπεζ ηδκ είζμδμ ηνςηηζηχκ ηαζ ενπεηχκ. Ζ δζαηήνδζδ ηδξ απαζημφιεκδξ οβναζίαξ επζηοβπάκεηαζ ιε ζφζηδια οδνμκέθςζδξ, ορδθήξ ηαζ παιδθήξ πίεζδξ ιε ρεηαζιυ κενμφ. Σμ ζφζηδια ορδθήξ πίεζδξ (εηαηξίαο AIR PETRI) ρεηάγεζ ζηαβμκίδζα κενμφ (ιεβέεμοξ ιενζηχκ δεηάδςκ ιm ηαζ πίεζδξ 60 bar) επζηνέπμκηαξ έηζζ ηδ δδιζμονβία μιίπθδξ, ιέπνζ ηδκ πθήνδ ελάηιζζή ημοξ. ηδ δζάνηεζα ημο πεζνάιαημξ ημ ζφζηδια θεζημονβμφζε ιε αάζδ δθεηηνμκζηυ αζζεδηήνα ηαζ εκενβμπμζμφκηακ ηαηά ηδ δζάνηεζα ηδξ διέναξ (απυ ηζξ 9:00 π.ι. έςξ ηζξ 21:00 ι.ι.) βζα 55 sec/min, υηακ δ ζπεηζηή οβναζία ημο αένα ήηακ ιζηνυηενδ απυ 90%. Σμ ζφζηδια παιδθήξ πίεζδξ (εηαηξίαο NETAFIM), ρεηάγεζ ζηαβμκίδζα κενμφ (ιεβέεμοξ 200 ιm ηαζ πίεζδξ 3 bar), ηα μπμία ηαηά ηφνζμ θυβμ πέθημοκ ζημ έδαθμξ ηαζ απυ εηεί ελαηιίγμκηαζ ακάθμβα ιε ηζξ ζοκεήηεξ ημο πενζαάθθμκημξ. Σμ 79

80 ζφζηδια θεζημονβμφζε ζε διενήζζα αάζδ (απυ ηζξ 10:00 π. ι. έςξ ηζξ 19:00 ι. ι.) βζα 2 sec/min. Γζα ηδκ ηαηαβναθή ηςκ ααζμηζηχκ ζοκεδηχκ πνδζζιμπμζήεδηακ: αζζεδηήναξ εενιμηναζίαξ ηαζ οβναζίαξ ημο αένα (Δ+Δ Ακεξηθήο), οδαημζηεβέξ ηαηαβναθζηυ εενιμηναζίαξ ηαζ ζπεηζηήξ οβναζίαξ (ONSET, Ακεξηθήο) ιε πενζμπή ιέηνδζδξ απυ 0,5 m/s έςξ 40 m/s, αζζεδηήναξ δθζαηήξ αηηζκμαμθίαξ (DECAGON, Ακεξηθήο) ηαζ αζζεδηήναξ ηαπφηδηαξ ακέιμο (THIES CLIMA Γεξκαλίαο). Ζ πενζμπή ιέηνδζδξ ηδξ εενιμηναζίαξ ήηακ απυ -40 C έςξ 70 C ιε αηνίαεζα ιέηνδζδξ 0,2 C. Ζ πενζμπή ιέηνδζδξ ηδξ ζπεηζηήξ οβναζίαξ ηοιαίκμκηακ απυ 0 100% ιε αηνίαεζα ιέηνδζδξ 2,5%. Οζ ιεηνήζεζξ παίνκμκηακ ηάεε 10 min απυ αζζεδηήνεξ πμο οπήνπακ ιέζα ηαζ έλς απυ ημ δζπηομηήπζμ, εκχ βζα ηδκ επελενβαζία πνδζζιμπμζήεδηε θμβζζιζηυ, ζοιααηυ ιε ημοξ ιεηεςνμθμβζημφξ ζηαειμφξ HOBO Warre BHW-PC. Ζ πνχηδ πενίμδμξ εηηνμθήξ ζαθζβηανζχκ δζήνηδζε έκα ιήκα (9/8/2011 έςξ 6 /9/2011). ημ εζςηενζηυ ημο δζπηομηδπίμο ηαηαζηεοάζηδηακ ιζηνυηενα δζαιενίζιαηα, δζαζηάζεςκ 2,5 m x 2,5 m, ζηδκ πενίιεηνμ ηςκ μπμίςκ ημπμεεηήεδηε δθεηηνμθυνμξ πενίθναλδ παιδθήξ ηάζδξ (14V ηδηνθαηαζθεπή) ηαζ ανίζηεηαζ ζημ πάκς ιένμξ ηδξ ζήηαξ πμο πνδζζιμπμζήεδηε βζα ηδκ ηαηαζηεοή ηςκ δζαιενζζιάηςκ. Ζ δεφηενδ πενίμδμξ εηηνμθήξ δζήνηδζε επίζδξ έκακ ιήκα (7/10/11 έςξ 11/11/11). Γζα αοηήκ ηδκ πενίμδμ ηαηαζηεοάζηδηακ δφμ κέα δζαιενίζιαηα δζαζηάζεςκ 2,9m 2,9m, ιε ζήηα φρμοξ 0,55m, πμο δζέεεηε εκζςιαηςιέκα ακμλείδςηα δθεηηνμθυνα ζφνιαηα (DIATEX Γαιιίαο). Ο βυκμξ ηαζ ζηζξ δφμ πενζυδμοξ εηηνμθήξ πνμήθεε απυ άβνζμοξ βεκκήημνεξ ημο είδμοξ Cornu aspersum (ζοκ. Helix aspersa) πμο ζοθθέπεδηακ απυ ηδκ Κνήηδ ηδκ άκμζλδ, εβηθζιαηζζηήηακ ηαζ ακαπανάπεδηακ ζημ ενβαζηήνζμ ζε εθεβπυιεκεξ ζοκεήηεξ (εενιμηναζία 20 C ηαζ θςημπενίμδμξ 12 h θςξ / 12 h ζημηάδζ). Ζ ηνμθή πμο πνδζζιμπμζήεδηε ήηακ ειπμνζηυ ζζηδνέζζμ (μνκζεμηνμθή πνχηδξ δθζηίαξ), ακαιειζβιέκδ ιε ακεναηζηυ αζαέζηζμ. Καεδιενζκά βζκυηακ δ ηαηαιέηνδζδ ηαζ απμιάηνοκζδ ηςκ κεηνχκ ζαθζβηανζχκ, ηάεε δφμ διένεξ βζκυηακ πνμζεήηδ ζζηδνεζίμο ηαζ ιία θμνά ηδκ εαδμιάδα γοβίγμκηακ δ ζοκμθζηή αζμιάγα ηςκ ζαθζβηανζχκ. 3. ΑΠΟΣΔΛΔΜΑΣΑ ΤΕΖΣΖΖ Ζ πνχηδ πενίμδμξ εηηνμθήξ πναβιαημπμζήεδηε ημκ Αφβμοζημ ιε ορδθέξ εενιμηναζίεξ ζηδ Μαβκδζία (δ ιέζδ ελςηενζηή ήηακ 28 C ± 4 C) αθθά ιε παιδθή ζπεηζηή οβναζία (δ ιέζδ ελςηενζηή ήηακ 54%) (Πίκαηαξ 1). Ζ δζαηήνδζδ ηδξ εενιμηναζίαξ ζημ εζςηενζηυ ηδξ εβηαηάζηαζδξ ηοιάκεδηε ιεηαλφ 15 C - 25 C ηαζ δ ζπεηζηή οβναζία ημο αένα ηοιάκεδηε ζε πμθφ ηαθά επίπεδα (δ ιέζδ εζςηενζηή ήηακ 82,95 ± 17.2) (Πίκαηαξ 1). Καηά ηδ δεφηενδ πενίμδμ εηηνμθήξ, πμο πναβιαημπμζήεδηε ημκ Οηηχανζμ δ ζπεηζηή οβναζία ημο αένα ζημκ πενζαάθθμκηα πχνμ ήηακ ακά πενζυδμοξ ζδακζηή ηαζ πάνδ ζημ ζφζηδια δνμζζζιμφ επεηεφπεδ δ δζαηήνδζδ ηδξ οβναζίαξ εκηυξ δζπηομηδπίμο ζε πμζμζηά άκς ημο 90% (Πίκαηαξ 1). Ζ εενιμηναζία ημο αένα ηδκ ίδζα πενίμδμ ήηακ πμθφ παιδθή (3,59 C εθάπζζηδ, ιέζδ: 14,8 C), ηαζ ιέζα ζημκ πχνμ ημο πεζνάιαημξ έπεθηε αηυια πενζζζυηενμ (3,25 C εθάπζζηδ, ιέζδ: 12,62 C). Πίκαηαξ 3. Καηαβεβναιιέκεξ πενζααθθμκηζηέξ ζοκεήηεξ (Μέζμξ υνμξ ηαζ ηοπζηή απυηθζζδ) εκηυξ ηαζ εηηυξ δζπηομηδπίμο. Δζςηενζηά Δζςηενζηά Δλςηενζηά Δλςηενζηά οκεήηεξ Αφβμοζημξ Οηηχανζμξ Αφβμοζημξ Οηηχανζμξ Θενιμηναζία ( C) 22,38 ±3.6 12,62 C ± 3,6 27,74 ± 4 14,8 C ± 4,6 πεηζηή οβναζία (%) 82,95 ± ,45% ± 6,2% 54 ± 12 68,53 ± 16,2 Ζθζαηή (W/m 2 ) αηηζκμαμθία 21, ,

81 ηδκ πνχηδ πενίμδμ ημο πεζνάιαημξ (Αφβμοζημξ) παναηδνήεδηε ορδθυ πμζμζηυ εκδζζιυηδηαξ ημο βυκμο ηςκ ζαθζβηανζχκ, πμο έθηαζε ζημ 58,17%. Απυ ηα γχα πμο ζοκμθζηά εεςνήεδηακ κεηνά, έκα ιεβάθμ πμζμζηυ (50%) δζέθοβε θυβς ηαημηεπκζχκ ζηδκ ηαηαζηεοή ηςκ δζαπςνζζηζηχκ ηςκ δζαιενζζιάηςκ, ή θυβς πνμαθήιαημξ ζηδκ ηάζδ ηςκ δθεηηνμθυνςκ ζονιάηςκ. Ο νοειυξ αφλδζδξ ηςκ ζαθζβηανζχκ (ζοκμθζηή αζμιάγα) ήηακ παιδθυξ (16,5% ζε έκα ιήκα). ηδ δεφηενδ πενίμδμ εηηνμθήξ (Οηηχανζμξ) δ αφλδζδ ημο βυκμο ηοιάκεδηε ζε ηαθφηενα επίπεδα (28,96%), ηαζ αοηυ μθείθεηαζ ζηζξ ηαθφηενεξ ζοκεήηεξ πμο επζηναημφζακ ηζξ 10 πνχηεξ διένεξ ημο πεζνάιαημξ ηαζ μζ απχθεζεξ ηςκ ζαθζβηανζχκ ιεζχεδηακ ηαηά πμθφ ζε ζπέζδ ιε ηδκ πνχηδ πενίμδμ (18%) (Πίκαηαξ 2). ε αοηυ ζοκέααθε δ αεθηζςιέκδ ηαηαζηεοή ηςκ δζαιενζζιάηςκ ηαζ δ πενίθναλδ πενζιεηνζηά, δ μπμία εηιδδέκζζε ηδ δζαθοβή ηςκ γχςκ. οβηνίκμκηαξ ηα απμηεθέζιαηα ηδξ πανμφζαξ ενβαζίαξ ιε παθαζυηενςκ ιεθεηχκ (Γεζπμημπμφθμο 2008, Lazaridou - Dimitriadou et al 1998, Begg & Mcinness 2003), ακαιεκυηακ έκαξ ιεβαθφηενμξ νοειυξ αφλδζδ ηςκ γχςκ. ζμκ αθμνά ηδκ δναζηδνζυηδηα ηςκ εηηνεθυιεκςκ ζαθζβηανζχκ ηοιάκεδηε ζε ζηακμπμζδηζηά επίπεδα ζηδ δζάνηεζα ημο ηαθμηαζνζμφ, εκχ ημ θεζκυπςνμ παναηδνήεδηε ζηαδζαηή ιείςζδ ηδξ ηζκδηζηυηδηαξ ηςκ γχςκ πμο ακάβεηαζ ζηδκ πηχζδ ηδξ εενιμηναζίαξ. Πίκαηαξ 2. Ποηκυηδηα ηαζ αζμιάγα ηςκ ζαθζβηανζχκ Πενίμδμζ Ανπζηή Ποηκυηδηα (ανζειυξ γχςκ/ m 2 ) Μέζμ αημιζηυ αάνμξ (gr) ) Αφλδζδ Βάνμοξ (%) Θκδζζιυηδηα (%) 1 δ Αφβμοζημξ 2 δ Οηηχανζμξ 100 1,15 16,50 58, ,99 28,96 18,02 Ο πεζναιαηζηυξ ζηαειυξ εηηνμθήξ ζαθζβηανζχκ ζηδ δμηζιαζηζηή πενίμδμ (πνχηδ πενίμδμ θεζημονβίαξ) ήηακ απμηεθεζιαηζηυξ υζμκ αθμνά ζηδκ πνμζηαζία ημο γςζημφ ηεθαθαίμο απυ επενμφξ ηαζ ζημκ ηζκδηυ ελμπθζζιυ (ηαΐζηνεξ ηαζ ηαηαθφβζα). Πνμαθήιαηα ειθακίζηδηακ ζηδκ δθεηηνμθυνα πενίθναλδ ηςκ εζςηενζηχκ δζαιενζζιάηςκ πμο απμηεθμφζε ζδζμηαηαζηεοή, υιςξ ιε ηδκ πνμιήεεζα ηδξ κέαξ ζήηαξ αοηά ελμοδεηενχεδηακ. Πεναζηένς ένεοκαξ πνήγεζ ηαζ ημ οπυζηνςια ηςκ εζςηενζηχκ δζαιενζζιάηςκ (ζήηα). Σα ηεπκζηά παναηηδνζζηζηά ημο δζπηομηδπίμο ηαζ ημ ζφζηδια δνμζζζιμφ ιε ελάηιζζδ πμο εθανιυζηδηε βζα πνχηδ θμνά ζηδκ πανμφζα ιεθέηδ, ιε ζηυπμ ηδ νφειζζδ ημο ιζηνμηθίιαημξ ημο δζπηομηδπίμο, ήηακ απμηεθεζιαηζηά βζα ηζξ ακάβηεξ ηδξ εκηαηζηήξ εηηνμθήξ ζαθζβηανζχκ ημο είδμοξ Cornu aspersum. ΒΗBΛΗΟΓΡΑΦΗΑ Γεζπμημπμφθμο Α. (2008) Καηαβναθή ημο ζηαδίμο ημο βεκκδηζημφ ζοζηήιαημξ ηςκ ζαθζβηανζχκ Helix aspersa (Cornu aspersum) (F1 βεκζά) πμο πνμένπμκηαζ απυ ιμκάδα εηηνμθήξ. Μεηαπηοπζαηή Γζαηνζαή, Π.Θ. ζεθ Καηζμφθαξ Ν., Απμζηυθμο Κ., Υαηγδσςάκκμο Μ., Ατθακηή., Νεμθφημο Υ., Κίηηαξ Κ. (2013) Μεθέηδ ζοζηήιαημξ δνμζζζιμφ ιε ηεπκίηδ μιίπθδ ζε δζπηομηήπζμ πάποκζδξ ζαθζβηανζχκ. Πναηηζηά 8 μο Δεκζημφ οκεδνίμο Γεςνβζηήξ Μδπακζηήξ, ζεθ Οζημκυιμο. (2013) Γζενεφκδζδ Σςκ Πνμμπηζηχκ Σςκ Δθθδκζηχκ αθζβηανζχκ ηδκ Αβμνά Σδξ Δονςπασηήξ Έκςζδξ, Πηοπζαηή ενβαζία, Π.Θ. Bailey S.E.R. (1981) Circannual and Circadian Rhythms in the Snail Helix aspersa Miiller and the Photoperiodic Control of Annual Activity and Reproduction. Journal of Comparative Physiology, 142: Begg S., Mcinness P. (2003) Farming Edible Snails - Lessons from Italy. Publication No. 03/137, Printed by Union Offset Printing, Canberra, Australia:

82 Boynd P.J, Osborne N.N., Walker R.J. (1986) Localization of a substance P-like material in the central and peripheral nervous system of the snail Helix aspersa. Hystochemistry and cell biology, 84: Dupont-Nivet M., Coste V., Coinon P., Bonnet J.C.and Blanc J.M. (2000). Rearing density effect on the production performance of the edible snail Helix aspersa Müller in indoor rearing. INRA, EDP Sciences,Ann. Zootech., 49: Jess S., Marks R.J. (1998) Effect of temperature and photoperiod on growth and reproduction of Helix aspersa var. maxima. The Journal of Agricultural Science, 130: Iglesias J., Santos M., Castillejo J. (1996). Annual Activity Cycles of the Land Snail Helix aspersa (Muller) in Natural Populations in North-Western Spain. Journal of Molluscan studies, 62: Lazaridou-Dimitriadou M, Alpoyanni E., Baka M., Brouziotis T., Kifonidis N., Mihaloudi E., Sioula D. and Vellis G. (1998). Gowth, mortality and fecundity in successive generations of Helix aspersa Muller cultured indoors and crowding effects on fast-, medium-and slow-gowing snails of the same clutch. Journal of Molluscan Studies, 64: Milinsk M.C, Padrea R.G., Hayashib C., Oliveiraa C.C., Visentainera J.V., Evela zio de Souzaa N., Matsushita M. (2006) Effects of feed protein and lipid contents on fatty acid profile of snail (Helix aspersa maxima) meat. Journal of Food Composition and Analysis, 19: Murphy B. (2001) Breeding and Growing Snails Commercially in Australia. A report for the Rural Industries Research and Development Corporation. RIRDC Publication No Pivovarov A.S, Sharma R., Walker R.J. (1995) Inhibitory action of SKPYMR Famide on acetylcholine receptors of Helix aspersa neurons: role of second messengers. General Pharmacology, 26:

83 ORAL PRESENTATIONS IN ENGLISH HOW GREEN CAN AQUACULTURE BE? Klaoudatos D.S. 1*, Nathanailides C. 2, Conides A. 1, Klaoudatos S.D. 3 1 Institute of Marine Biological Resources and Inland Waters, Hellenic Centre for Marine Research, Athens, Greece 2 Department of Fisheries and Aquaculture Technology, Technological Educational Institute of West Greece, 30200, Messolonghi, Greece 3 Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Fytokou Street, 38445, Nea Ionia Magnesia, Volos, Greece ABSTRACT With global food security becoming an ever increasing concern, sustainable aquaculture sets to become the most rapidly increasing food production system worldwide. However the sustainability of the aquaculture sector is under heated discussion. The argument is whether aquaculture could potentially provide a sufficient - in terms of quality and quantity - alternative source of protein in a sustainable way. The adoption of environmentally friendly production strategies like Integrated Multitrophic Aquaculture (IMTA), Recirculating aquaculture systems (RAS) and fish-polyculture methods and through the combination of extensive and intensive aquaculture the sector exhibits a promising potential of an environmentally friendly and sustainable direction. Key words: Sustainability, global, fish, food, environment. *Corresponding author: Klaoudatos Dimitris (dklaoudatos@hcmr.gr) Introduction Sustainability of the aquaculture sector has recently been brought into question for 2 reasons: (a) the interaction of aquaculture with the coastal environment and (b) the use of fish meal and fish oil for feeds, using as raw material wild fish. Fish meal is a component of most aquaculture feeds used as a diet for cultured aquatic species and its use to feed aquatic animals of higher market value has prompted the question of whether aquaculture is actually reducing pressure on wild stocks or just transferring one biomass into another. It is generally recognised that the world s oceans are being overfished and for a number of species, aquaculture is perhaps the only way of supplying increasing demand to take the pressure off the fishing of wild stocks. The last 15 years, global capture fisheries production show stable trends while aquaculture productions shows still positive trends (Fig. 1). 83

84 Figure 1. Recent trends of global capture fisheries and aquaculture production (source: FAO Yearbooks) With global food security becoming an increasing concern, sustainable aquaculture will probably remain the most rapidly increasing food production system worldwide (Butterworth, 2009). At the same time, however,the increasing demand for aquaculture feeds can no longer be based on capture fisheries landings. It makes no sense economically as depleted fish stocks result in higher prices. Furthermore carnivorous fish which are grown with a fisheries-based diet may contain high levels of pollutants which can reach the consumer through the food chain (for example polychlorinated biphenyl's and organochlorine pesticides; Hites et al., 2004). Currently plant protein supplements are used to some extent in all aquaculture feeds. Soybean meal is subjected to rigorous research for its suitability in aquaculture feeds (Krogdahl et al., 2003; Robinson et al., 2000; Sugiura et al., 2001; Day & Gonzalez, 2003). In addition the culture of seaweed as an on-site feed source for marine grazers has the potential to decrease feed costs. Many types of seaweed have the potential to be incorporated into artificial feeds for all aquatic animals including finfish (Pereira et al., 2010) as partial replacement for fish meal, as well as a significant source of protein, carbohydrates, vitamins and trace elements. Interaction of Environment and Aquaculture Fish farming offers a solution to the problem of food scarcity, offering animal protein employing a method with small environmental footprint. The current trend is to increase the use of plant protein in aquaculture feed, but this practice needs to be accompanied by extensive research on nutrition (Purchase & Brown, 2000) in order to achieve food conversion rates similar to the standard feeds as well as the reduction of feed wastes (Hardy, 2000). Aquaculture has an impact on the surrounding environment and ecosystem in various ways. Aquaculture generates significant amounts of waste, composed of uneaten feed, faeces, and both organic and inorganic elements such as nitrogen molecules (NH X, NOx), and phosphorus (Wallace, 1993; Karakassis et al., 2005; Klaoudatos et al., 2006). It has been documented that in several cases, pollution from aquaculture may result in oxygen deficiency, generation of hydrogen sulphides and harmful plankton blooms especially at strata close to the sea bottom below the aquaculture farms. Waste solids can form sediments, for example below the cages, which can alter the benthic ecosystem with consequences to the ecology of the aquatic body (Karakassis et al., 1999; Pusceddu et al., 2007; Russell et al., 2011). In turn, this increase in nutrients 84

85 entering the water body can result in eutrophication (Mpeza et al., 2013), a condition characterised by massive growth of algae and aquatic plants, leading to oxygen reduction in the surrounding waters. At the same time, however, research results have shown that the sea bottom disturbance does not extend more than m from the outer boundaries of the cages. Fish communities cannot thrive in low oxygen concentration, and algal blooms have a significant impact on the recreational value associated with reduced water clarity, foul odours and toxicity (Turner et al., 1999; Pillay, 2004). The use of pesticides, antifoulants, antibiotics and disinfectants has adverse consequences to aquatic life in the water body. The end result of aquaculture development with little concern for sustainability leads to poor economic returns. In that sense, fish farming needs to maintain a wealthy relationship with the aquatic ecosystem and, as an agricultural activity, is a typical example illustrating the relationship between the well-being of fish and human communities and the environment (Naylor et al., 2003). The possible accidental escape of farmed animals can have detrimental consequences for the thriving of the local fish populations. Transmission of pathogens, alteration of the local fish fauna species composition, competition of the introduced fish for food and spawning grounds as well as possible genetic pollution of the local stock with genetic material not relevant to the particular local ecosystem, are among the well-constituted negative impacts of accidentally or even intentionally released farmed fish (Naylor et al., 2001a; Kelso & Mangel, 2005; Krkosek et al., 2007). Sustainable aquaculture development According to several researchers, aquaculturists, and governmental instances sustainable aquaculture is possible, depending on the management of the activity (Stickney & Mcvey, 2002). Sustainable aquaculture development requires the identification of potential environmental problems associated with aquaculture activities, especially the effect on the ecosystem and carrying capacity. The combination of intensive aquaculture, where feed is based on the supply of artificial feed and extensive aquaculture, where feed is provided by the natural ecosystem, is a promising approach for dealing with aquaculture wastes (Diab et al., 1992) and constitutes a green aquaculture methodological approach. Aquaculture development in the industrialised world is market driven, and the demand for particular species that are usually carnivorous is leading the way to the farming of certain species such as salmon and tuna. In the past, fish feeds for carnivorous species contained animal protein, a practice recently abolished. Currently fisheries products constitute the single source of meat protein used in the manufacturing of fish feed. The feeding of carnivorous species in North European (e.g. salmon) and Mediterranean (e.g. sea bream) fish farms is based on feed manufactured with fish oil and fish meal, derived from fish landings (anchovies, sand-eel capelin, herring, blue whiting) from the North Sea and the South American coasts (Serrano et al., 2008). The use of wild fish for the feed manufacture for carnivorous farmed fish leads to a reduction of food resources available to be utilised by wild fish and other marine life, and certainly does not constitute a sustainable form of aquaculture (Naylor et al., 2001b). Interestingly, a smart way towards sustainable fish farming is the utilisation of other species by-products (Kotzamanis et al., 2001; Gunasekera et al., 2002) or of domestic waste (Staudenmann & Junge-Berberovic, 2003). Recent technological developments in aquaculture methods aim to divert pollution away from the coastal zone (Stokstad, 2007). A common practice in Asian countries is polyculture and integrated multitrophic aquaculture (IMTA). In typical polyculture ponds, different carp species are grown together, each consuming different food items in a pond. Polyculture practices have the potential to diminish the environmental impact caused by the organic effluents (Chopin et al., 2001; Marttinez-Cordova et al., 2011; Martinez- Porchas et al., 2010). Integrated Multi-trophic Aquaculture (IMTA; Fig. 2)) is a production strategy, which, through the combined culture of different commercial species, has sufficient potential to achieve total respect for the environment where waste is converted into usable assets, while consumables are kept to a minimum, thus contributing to sustain the activity in the best possible manner. It is set to head the socalled Turquoise Revolution as it involves integrating the ideas of the green revolution (the increased world agricultural production, particularly in food, from 1940 and 1970) with that of the 85

86 blue revolution (the growth of aquaculture experienced since the nineties). In some countries with a highly developed aquaculture, IMTA generates an added value to marine culture since its products have access to labelling that certifies to consumers that the fish, crustacean, mollusc or alga has been reared with systems that have a low, zero or even a positive impact on the environment (Guerrero & Cremades, 2012). Figure 2. Integrated Multi-trophic Aquaculture concept Unlike polyculture which includes species that all share the same biological and chemical processes which could potentially lead to significant shifts in the ecosystem, the multi-trophic approach combines cultured organisms that extract either dissolved inorganic nutrients (seaweeds) or particulate organic matter (shellfish) and, hence, the biological and chemical processes at work are balancing each other. Moreover, the different types of aquaculture are integrated, i.e. operating in proximity to each other, but not necessarily right at the same location (Chopin, 2006). The dual objective of sustainable aquaculture, i.e., to produce food while sustaining natural resources, is achieved only when production systems with a minimum ecological impact are used. Recirculating aquaculture systems (RAS) provide the opportunity to reduce water usage and to improve waste management and nutrient recycling. RAS are closed-loop facilities that retain, treat and reuse the water within the system making intensive fish production compatible with environmental sustainability. In addition, RAS systems allow aquaculture activities to be installed and operate in remote areas not connected to the shoreline, thus eliminating conflicts for the use of space.. However the potential accumulation of substances in the water as a consequence of reduced water refreshment rates may pose new challenges requiring a deeper understanding of the interaction between the fish and the system (Martins et al., 2010). With increasing farm size and potentially higher nutrient 86

87 release, an understanding of the carrying capacity and ecosystem processes are important. In the last 10 years there has been a shift toward viewing waste nutrients as a resource that can be recycled through plants in a range of aquaculture situations from land-based freshwater to open-ocean culture. Although world aquaculture is an obvious potential solution for providing the needed precious protein for an increasing human population, and despite the availability of scientific knowledge to support a sustainable expansion of the aquaculture production, the future steps of the aquaculture sector towards an environmentally friendly and sustainable direction remain to be seen. References Butterworth, A. (2009). Integrated Multi-Trophic Aquaculture systems incorporating abalone and seaweeds. Nuffield Australia Project No Chopin, T. (2006). Integrated Multi-Trophic Aquaculture. What it is, and why you should care.. and don t confuse it with polyculture. Northern Aquaculture Page 4. Chopin, T., Buschmann A.H., Halling C. (2001). Integrating seaweeds into marine aquaculture systems: a key toward sustainability. Journal of Phycology, 37 (6): Day, O., González P. ( 2003). Soybean protein concentrate as a protein source for turbot Scophthalmus maximus L. Aquaculture Nutrition, 6: Diab, S., Cochaba M., Mires D., Avnimelech Y. (1992). Combined intensive extensive (CIE) pond system, A: inorganic nitrogen transformations. Aquaculture, 101: Guerrero, S., Cremades J. (2012). Integrated multi-trophic aquaculture a sustainable, pioneering alternative for marine cultures in Galicia. Regional Government of Galicia Regional Council of the Rural and Regional Maritime Environment Marine Research Centre. Vilanova de Arousa (Pontevedra). 58p. Gunasekera, R.M. Turoczy N.J., De Silva S.S., Gavine F., Gooley G.J. (2002). An evaluation of the suitability of selected waste products in feeds for three fish species. Journal of Aquatic Food Product Technology, 11: Hites, R.A., Foran J.A., Carpenter D.O., Hamilton M.C., Knuth B.A., Schwager S.J. (2004). Global assessment of organic contaminants in farmed salmon. Science, 303: Karakassis, I., Hatziyanni E., Tsapakis M., Plaiti W. (1999). Benthic recovery following cessation of fish farming: a series of successes and catastrophes. Marine Ecology Progress Series, 184: Karakassis, I., Pitta P., Krom M.D. (2005). Contribution of fish farming to the nutrient loading of the Mediterranean. Scientia Marina, 69: Kelso, D., Mangel M. (2005). Fugitive Salmon: Assessing the Risks of Escaped Fish from Net-Pen Aquaculture. Bioscience, 55(5): Klaoudatos, S.D., Klaoudatos D.S., Smith J., Bogdanos K., Papageorgiou E Assessment of site specific benthic impact of floating cage farming in the eastern Hios Island, Eastern Aegean Sea, Greece. Journal of Experimental Marine Biology and Ecology, 338: Kotzamanis, Y., Alexis M., Andriopoulou A., Castritsi-Cathariou I., Fotis F. (2001). Utilization of waste material resulting from trout processing in gilthead bream (Sparus aurata L.) diets. Aquaculture Research, 32 (1): Krkosek, M., Ford J.S., Morton A., Lele S., Myers R.A., Mark A.L. (2007). Declining Wild Salmon Populations in Relation to Parasites from Farm Salmon. Science, 318: Krogdahl, A., Bakke-McKellep A., Baeverfjord G. (2003). Effects of graded levels of standard soybean meal on intestinal structure, mucosal enzyme activities, and pancreatic response in Atlantic salmon (Salmo salar L.). Aquaculture Nutrition, 9: Marttinez-Cordova, L.R., Lopez-Elias J.A., Leyva-Miranda G., Armenta-Ayon L., Martinez-Porchas M. (2001). Bioremediation and reuse of shrimp aquaculture effluents to farm whiteleg shrimp, Litopenaeus vannamei: a first approach. Aquaculture Research, 42 (10): Martinez-Porchas, M., Martinez-Cordova L.R., Porchas-Cornejo M.A., Lopez-Elias J.A. (2010). Shrimp polyculture: a potentially profitable, sustainable, but uncommon aquacultural practice. Reviews in Aquaculture, 2(2): Martins, C.I.M., Edinga E.H., Verdegema M.C.J., Heinsbroeka L.T.N., Schneiderc O., Blanchetond 87

88 J.P., Roque d Orbcasteld E., Verretha J.A.J. (2010). New developments in recirculating aquaculture systems in Europe: A perspective on environmental sustainability. Aquacultural Engineering, 43:(3) Mpeza, P., Mavraganis T., Nathanailides C. (2013). Dispersal and Variability of Chemical and Biological Indices of Aquaculture Pollution in Igoumenitsa Bay (NW Greece). Annual Review & Research in Biology, 3(4): Naylor, R.L., Williams S.L., Strong D.R. (2001)a. Aquaculture: A Gateway for Exotic Species. Science, 294(5547): Naylor, R.L., Goldburg R.J., Primavera J., Kautsky N., Beveridge M.C.M., Clay J., Folke C., Lubchenco J., Mooney H., Troell M. (2001)b. Effects of Aquaculture on World Fish Supplies. Ecology, 8: 14. Naylor, R.L., Eagle J., Smith W. (2003). Salmon Aquaculture in the Pacific Northwest: a global industry with local impacts. Environment, 45: Pereira, R., Abreu M.H., Valente L., Rema P., Sousa-Pinto I. (2010). Production of seaweeds in integrated multi-trophic aquaculture for application as ingredients in fish feed. 20th Seaweed Symposium, Ensenada, Mexico, p. 86. Pillay, T.V.R. (2004). Aquaculture and the environment 2 nd ed. Fishing New Books, Oxford. 212pp. Purchase, C.F., Brown J.A. (2000). Inter-population differences in growth rates and food conversion efficiencies of young Grand Banks and Gulf of Maine Atlantic cod (Gadus morhua L.). Canadian Journal of Fisheries and Aquatic Sciences, 57: Pusceddu, A., Fraschetti S., Mirto S., Holmer M., Danovaro R. (2007). Effects of intensive mariculture on sediment biochemistry. Ecological Applications, 17(5): Robinson, E.H., Li M.H., Manning B.B. (2000). Evaluation of various concentrations of dietary protein and animal protein for pond-raised channel catfish (Ictalurus punctatus) fed to satiation or at a restricted rate. Journal of the World Aquaculture Society, 31: Russell, M., Robinson C.D., Walsham P., Webster L., Moffat C.F. (2011). Persistent organic pollutants and trace metals in sediments close to Scottish marine fish farms. Aquaculture, 319(1-2): Serrano, M., Barreda M., Blanes M.A. (2008). Investigating the presence of organochlorine pesticides and polychlorinated biphenyls in wild and farmed gilthead sea bream (Sparus aurata) from the Western Mediterranean sea. Marine Pollution Bulletin, 56: Staudenmann J., Junge-Berberovic R. (2003). The Otelfingen Aquaculture Project: Recycling of Nutrients from Waste Water in a Temperate Climate. Journal of Applied Aquaculture, 13(1/2): Stickney, R.R., Mcvey J.P. (2002). Responsible Marine Aquaculture. CABI Publishing, New York. Stokstad, E. (2007). Panel Urges Environmental Controls on Offshore Aquaculture. Science, 315: 175. Sugiura, S. H., Gabaudan J., Dong F.M., Hardy R.W. (2001). Dietary microbial phytase supplementation and the utilization of phosphorus, trace minerals and protein by rainbow trout (Oncorhynchus mykiss (Walbaum) fed soybean meal-based diets. Aquaculture Research, 32(7): Turner, R.K., Georgiou S., Gren I., Wulff I.F., Barrett S., Söderqvist T., Bateman I.J., Folke C., Langaas S., Zylicz T., Mäler K., Markowska A. (1999). Managing nutrient fluxes and pollution in the baltic: An interdisciplinary simulation study. Ecological Economics, 30(2): Wallace, J. (1993). Environmental considerations. pp In: Heen, K., Monahan, R.L., Utter, F. (eds), Salmon aquaculture. Fishing News, Oxford, UK. 88

89 FROM RISK ANALYSIS TO GREEK CRISIS MANAGEMENT IN AQUACULTURE: THE CASE OF THE MEDITERRANEAN MUSSEL FARMING IN GREECE. Theodorou J.A., 1, 4* Tzovenis I., 2 Sorgeloos P., 3 Viaene J. 4 1 Deptartment of Fisheries & Aquaculture Technology, Technological Educational Institution (T.E.I.) of Western Greece, Nea Ktiria Gr 30200, Mesolonghi, Greece. 2 Laboratory of Ecology & Systematics, Biology Dept., University of Athens, Panepistimioupolis, Zografou 15784, Greece 3 Laboratory of Aquaculture & ARC, University of Gent, Rozier 44, B-9000 Gent, Belgium 4 Department of Agricultural Economics, Faculty of Bioscience Engineering, University of Gent, Coupure Links 653, B-9000 Gent, Belgium ABSTRACT Mussel farming as an aquaculture activity based on the natural primary productivity, faces risks similar to those of the agriculture sector. Consequently, much theoretical risk research has been applied to aquaculture as in agriculture, livestock, forestry, conservation and its management. Mussel farming, as a niche and vulnerable primary production sector, seems to be a high risk activity so it does not appear very promising for bankers. Because of this fact, financial viability of the venture depends heavily on EU funding schemes for assets in order to share the investment risk. In addition, farmers use personal deposits and resort to alternative activities to complement their cash flow when in need. For the time being, no insurance policy exists for this sector. As a consequence, there is no support to compensate for losses, rendering the business vulnerable to operational risks. A thorough mussel farming risk assessment was carried out to delineate all aspects needed by private companies, banks, or the government to formulate a valid plan for operational risk management of the sector Keywords: Risk analysis, mussel farming, Greek crisis management *Corresponding author: Theodorou John A. (jtheo@teimes.gr) 1. Introduction Modern Mediterranean aquaculture developed considerably during the last 30 years passing from early pilot stages to maturation at the beginning of the new century. Marine farming in Greece has been based mainly on Mediterranean mussels (Mytilus galloprovincialis) regarding marine shellfish, and on seabream (Spaurus aurata) and seabass (Dicentrarchus labrax) regarding marine fish species (Theodorou 2002; Theodrou et al. 2011). However successful the industry has been so far on research and development issues, little or no effort has been attributed yet to the risk assessment and moreover to the risk management of the sector. Bivalve shellfish farming as an activity based on the natural primary productivity, faces risks similar to those of the agriculture sector. Consequently, much theoretical risk research has been applied to aquaculture as in agriculture (Huirne et al. 2000; 2007), livestock (Meuwissen et al. 2001), forestry (Stordal et al. 2007), conservation and its management (Greiner et al. 2009). Nevertheless, limited studies have so far focused on risk perceptions strategies of the aquaculturists (Theodorou & Tzovenis 2004; Bergfjord 2009; 2013, Le Grel & Le Bihan 2009, Le & Cheong 2010, Ahsan & Roth 2010, Ahsan 2011, Le Bihan & Padro 2009, Le Bihan et al. 2010;2013, Zagmutt et al. 2013). For this purpose a study was conducted to explore the mussel farmers perceptions of risk and risk management, to examine relationships between farm and farmer characteristics, and highlight the prevailing risk perceptions and strategies (Theodorou et al., 2010b). The present study to fill up this knowledge gap was structured as an exploratory research on risk source priorities and their management options associated with the mussel farming business. In this context, a conceptual framework for the marine shellfish aquaculture industry of Greece was developed to be used as a tool by the sector s decision makers (Theodorou et al., 2010a). 89

90 2. Materials and Methods The work was based on the Joint Australian and New Zealand Risk Management Standard AS/NZS ISO 31000: 2009 (Figure 1) that incorporates as a model process the earlier AS/NZS 4360: 2004 version (Standards Australia and New Zealand, 2004; 2009). As the initial principles of this risk management standard method are generic (Crawford 2003; Cooper et al., 2005), it was successfully adapted to the specific national characteristics of all levels of the business activities and the industry function of the sector under study. The working steps have been to (1) establish the context; (2) identify the risks; (3) analyse the risks; (4) evaluate the risks; (5) treat the risks; (6) monitor and review the whole process; and (7) communicate and consult the outcomes. The framework was based on data sets regarding development, production, profits and losses, retrieved by surveys through distributed questionnaires or interviews during site-visits, as well as by collecting data from national and international authorities. Data input covered technology, farm size, farmer risk-attitude, risk-management strategies, risk-perceptions and socioeconomic profiles (Theodorou et al., 2010b). Major risks and risk management options were identified with descriptive statistics and ranked by principal component analysis. The production and marketing trends of the Mediterranean mussel farming in Greece were also taken in account to establish the context of this effort (Theodorou et al., 2011). The industry survey was carried out during late 2008 before the Greek crisis culminated (2010), providing valuable background data to evaluate the sectors adaptations under the new business environment in Greece. Since there are limited data from inside sources during the crisis period, we tried to compare our results with facts and figures referred to the vision for the Greek economy as the new national growth model and strategy developmental model presented by McKinsey & Company (2012) to cover the Greek government demand for setting up the current and future developmental priorities to surpass the crisis. 3. Results and Discussion Results show that the ex-farm prices of the mussels were perceived to be the major source of risk while the financial/credit reserves were the most preferred risk management strategy. Farmers seem to resort to such practices as the activity is characterized by negligible banking support, due to the production unpredictability and the marginal profitability. Finally, the farmers attitudes and comments on loss compensations bring up the need to develop a more effective and versatile insurance system (Theodorou et al., 2010b,c). The profitability of the Mediterranean mussel farming depends on a combination of factors including natural productivity, technical practices, production costs and product pricing. In an effort to analyse the financial risks of the mussel farming in Greece, we examined the profitability of the different farm sizes (1 to 6 ha) under the present situation of the local market and the modern production practices. Assuming that the farms use the widely accepted long-line technique, it was demonstrated that small farm sizes less than 3 ha are not viable financially. Moreover, the cost of new establishments or the modernization of the existing ones was affordable only if larger enterprise structures could be adopted. Consequently, the past EU and/or public support (up to 45% of the total cost of the fixed assets) has been critical for the development of the industry. The initial investments were a high risk opportunity as the variability of the production due to the extensive nature of the business increased the financial risk and consequently there was a limited interest from the banking sector to support these type of operations (Theodorou et al. 2014). 90

91 Figure 1. A generalized overview of the adapted AS/NZS ISO 31000:2009 Risk Management Standard showing the relations between the added principles (a) for the effective and mandatory risk management framework development (b) to the existing process (c) of the earlier version of AS/NSZ 2431:2004. Taking in account that the majority of the Greek mussel farms are rather small (1-3 ha), we concluded that for financial sustainability the sector needs to be restructured. A suggested cluster management of small scale mussel farms might enable the producers to work together, improving production, develop sufficient economy of scale and knowledge to participate in modern chains, increase ability to join certification schemes, and improve reliability of production and reduce risks. The future of the industry in organizing the producers in larger schemes, hinges on the industrialization of the production methods and the scale-up of production units in order to reduce average production costs and enhance the marketability of the product. 91

92 This is in accordance with the guidelines of the proposed new national growth model and strategy developmental model by McKinsey & Company (2012) which suggested that the scaling up of the Greek enterprises is necessity to solve the competitive disharmony of the country. The severity and consequences of site closures to shellfish commercial harvesting, a protection measure for public health against toxicity inflicted by harmful algal blooms, has been evaluated for the Mediterranean mussel farming in Greece. Estimations were carried out in a semi-quantitative manner at the farm level. Results showed that financial losses depended on the season and duration of the harvest ban. Since the product becomes marketable from late spring to early autumn, site-closures longer than 6 weeks within that period could be catastrophic for a farm. Consequences include yield losses due to extended stocking of ready to harvest mussels in the farm, and ex-farm price reduction due to oversupply after the harvest ban (Theodorou et al., 2012). Moreover, mussel seed collection and placement within the farm is delayed due to lack of space as the bulk of mussels remain unharvested putting in danger next season s production. Proposed strategies to minimise losses consisting of differential handling of the marketable mussels and of extraordinary spatial extension of farm facilities due to harvest bans caused by HABs were discussed (Theodorou et al., 2012; 2015). At the the time that research carried out, no insurance policy existed for this sector rendering the business vulnerable to operational risks (Theodorou et al., 2011). Recently (2012) limited compensation was available through the European Fisheries Fund only in cases of mussel harvesting losses due to human health protection. The situation seems to be significantly improved as the article 57 of the EU Regulation 508/2014 through the European Maritime & Fisheries Fund takes into account the insurance compensation of the animal stock losses due to natural disasters, weather impacts, water quality and diseases. The present exploratory effort was carried out to delineate the major indicative aspects needed by private companies, banks, or the government to formulate a valid plan for operational risk management of the sector. Meanwhile, special programs, providing training in labor and environmental safety procedures, may improve the risk management of the farms and thus decrease losses. References Ahsan D.A., Roth E. (2010). Farmers perceived risks and risk management strategies in an emerging mussel aquaculture industry in Denmark. Marine Resource Economics 25, Ahsan D.A. (2011). 'Farmers' motivations, risk perceptions and risk management strategies in a developing economy: Bangladesh experience'. Journal Risk Research 14 (3), Bergfjord J.O. (2009). Risk perception and risk management in Norwegian aquaculture. Journal Risk Research 12 (1), Bergfjord O. J. (2013). Farming and risk attitude. Emirates Journal Food & Agriculture. 25 (7), Crawford C. (2003). Qualitative risk assessment of the effects of shellfish farming on the environment in Tasmania, Australia. Ocean & Coastal Management 46, Greiner R., Patterson L., Miller O. (2009). Motivations, risk perceptions and adoption of conservation practices by farmers. Agricultural Systems 99, EU Regulation No 508/2014 (2014). Regulation of the European Parliament and the Council of 15 May 2014 on the European Maritime and Fisheries Fund and repealing Council Regulations (EC) No 2328/2003, (EC) No 861/2006, (EC) No 1198/2006 and (EC) No 791/2007 and Regulation (EU) No 1255/2011 of the European Parliament and of the Council. Official Journal of the European Union , L 140/66. Huirne R.B.M., Meuwissen M.P.M., Hardaker J.B., Anderson J.R. (2000). Risk and risk management in agriculture: an overview and empirical results. International. Journal. Risk Assessment & Management 1 (1/2), Huirne R.B.M., Meuwissen M.P.M., Van Asseldonk M.A.P.M. (2007). Importance of whole-farm risk management in agriculture. In: Handbook of Operations Research in Natural Resources, Springer Publ. p Le T.C., Cheong F. (2010). Perceptions of risk and risk management in Vietnamese catfish farming: an empirical study. Aquaculture. Economics & Management 14, Le Grel L., Le Bihan V. (2009). Oyster farming and externalities: The experience of the Bay of Bourgneuf. Aquaculture. Economics & Management 13:

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94 Theodorou J.A., Tzovenis I., Sorgeloos P., Viaene J. (2015). Semi-Quantitative Risk Assessment of the effects of HAB closures on the shellfish farming in Greece. Journal of Shellfish Research (Submitted). Theodorou J.A., Le Bihan V., Pardo S., Tzovenis I., Sorgeloos P., Viaene J. (2011). Risk Perceptions and Risk Management Strategies of the European Bivalve Producers. In: Aquaculture Europe Mediterranean Aquaculture 2020, Organized by the European Aquaculture Society, October 18-21, Rhodes, Greece. Zagmutt F.J., Sempier S.H., Hanson T.R. (2013). Disease Spread Models to Estimate Highly Uncertain Emerging Diseases Losses for Animal Agriculture Insurance Policies: An Application to the U.S. Farm-Raised Catfish Industry. Risk Analysis 33(10),

95 CAN WE OPTIMIZE OXYGENATION IN AQUACULTURE IN THE MEDITERRANEAN REGION BY USING A NOVEL AIR DIFFUSION SYSTEM? Nikouli E. 1*,Mente E. 1, Makridis P. 2, Kormas, A.K. 1, Koufostathi, E 1., Grundvig H. 3, Ribeiro L. 4, Pousão-Ferreira P. 4, Hugo Quental-Ferreira, H. 4, Araújo, R. 4,Gausen M. 5, Hovden N. 5, Colt J. 6, Bergheim A. 7 1 Department of Ichthyology & Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Fytoko Street, , Nea Ionia Magnesia, Greece 2Department of Biology, School of Natural Sciences, University of Patras, University campus, 26504, Rio, Greece 3TeknologiskInstitutt as, P.O.Box 141 Økern, NO-0509 Oslo, Norway 4InstitutoPortugues do Mare da Atmosfera (IPMA), Av. 5 de Outubro, s/n Olhao, Portugal 5Oxsea Vision AS, Oslo,Norway 6National Marine Fisheries Service, 2725 Montlake Blvd East, Seattle, WA 98112, USA 7International Research Institute of Stavanger,Stavanger, Norway ABSTRACT Low levels of dissolved oxygen can be influenced by numerous factors such as temperature, salinity, water exchange rate and can create additional problems in fish rearing in aquaculture. The effects of reduced dissolved oxygen levels on reared fish vary from reduced appetite, reduced feed utilization, to decreased immune system and to high fish mortalities. Aeration can be utilized both as an emergency tool as well as on more regular basis especially in critical periods when it is known by experience that related problems commonly occur. The type of aeration, dimensioning of the devices, avoidance of total gas super-saturation and economic issues are important factors that have to be taken under consideration. The AirX project developsand tests a new technology, a new air diffuser based system for control of dissolved oxygen levels in aquaculture. The aeration concept, patented by OxseaVision (OSV), is designed for use in large rearing units, including earth ponds, sea cages, tanks and raceways. The majority of the technical development and lab-scale tests took place in Norway while verification and field trials were performed in the Mediterranean region, more specifically in Portugal and Greece. Keywords: air diffusion system, aquaculture. * Corresponding author: Eleni Nikouli (elnikoul@uth.gr) 1. Introduction Oxygen deficiency can constitute a challenge in aquaculture, especially when water temperatures are high. This challenge manifests itself in decreased appetites, low-level feed utilisation, slow growth rates, increased stress among the farmed stock, and higher production costs. The factors resulting in oxygen deficiency typically coincide during summer and early autumn at a time when the stocking densities are normally quite high. This can result in prolonged periods with low oxygen levels, making it necessary for the farmer to alter husbandry practices in order to reduce the need for oxygen. For cultured red sea bream (Pagrus major) it has been shown that a minimum of dissolved oxygen required is 5.7 mg/l and decrease below this level may cause increased mortalities. In cages for coldwater fish species, such as Atlantic salmon, long-term DO concentrations below 70 80% of saturation (< 7mg/L) will significantly reduce the growth and feed utilization even at low temperature (Bergheim et al., 2002).Sea bass generally tolerates O 2 deficit rather well; acute hypoxia is found to be 1.9 mg/l for 4 hrs while chronic hypoxia is stated 4.3 mg/l lasting for 15 days (Terova et al., 2008). Both acute and chronic hypoxia caused significantly increased number of HIF-1a mrna (HIF: hypoxia-inducible factor) in liver tissue.thetmeyer et al. (1999) observed less appetite/growth rate but unaffected feed utilization of sea bass with initial weight of g at constant 40% O 2 saturation lasting for 1 month (22 C, 37 ppt) but no effects of oscillating O 2 concentration between 40 and 86%. As growth was correlated with feed intake, the reduced growth under moderate hypoxic or oscillating oxygen conditions is primarily due to reduced appetite and not a consequence of a decrease in feed conversion efficiency. Sea bream is more sensitive to low oxygen than sea bass (Ökte, 2002), but no exact figures describing hypoxia in sea bream are available in the literature.in an experiment with aeration in four fish cages with red seabream, where micro-bubble generators were placed at 7 m 95

96 depth for more than five months, no negative effects were reported for the fish (Endo et al., 2008). Use of micro-bubble aeration has been shown to improve the environment in aquaculture farms not only in area over the diffuser but 5 m below the aerator as well (Endo et al., 2008; Maeda et al., 2002). EU s AirX project develops and tests a new technology that provides small bubbles and uses air to control dissolved oxygen levels in earth ponds and sea cages in aquaculture. 2. Material and methods There are two main methods utilized for aeration: air can be supplied into a flow of water ( air-inwater ), or water can be supplied into a flow of air ( water-in-air ). The first one is hydraulic type and the second one air diffusion type (gravity aerators, subsurface aerators and surface aerators).in the case of ponds, there is a considerable amount of studies which took into account the problem of oxygenation, the technology present at the time (most studies done before year 2000) and focused on the use of paddle-wheels which appeared as the most economically feasible solution. As an alternative approach to avoid problems with oxygenation possibly increasing the self-pollution of the farm low stocking density has been suggested. In the case of fish cages, the problem of low oxygen levels has been generally overlooked and very few studies are available. There is a general trend in the industry to believe that such problem can only be detected in bad locations for cages. Further research is needed especially in the case of cages, where the problem of reduced oxygen has been underestimated. Aeration in cages seems as a solid alternative, better than addition of oxygen, as the transport of oxygen containers is always feasible and can be economically difficult to justify.there might be a risk of critical super-saturation of gases and development of gas bubble disease in cages and ponds aerated by submerged diffusers. The risk of harmful gas conditions is dependent on type of aerator, aeration depth, depth layer of the fish stock, and several other factors. However, the chance of harmful gas levels is low under normal operation of aerators in fish ponds and cages. Compared with existing aeration devices the AirX diffuser has the ability to efficiently distribute gas over a large volume. The completed AirX system will consist of a diffuse hose grid system that releases gas at an equal pressure, thus results in an homogenous distribution of gas, a compressor that provides air under pressure to the system and an automatic system that ensures that the desired amount of air is dosed according to the needs of the system. The system provides small bubbles that efficiently transfer oxygen into the water in a homogeneous way and can provide direct diffusion towards areas where extra oxygen addition is most needed (Figures 1 and 2). Figure 1 - AirX system working in earth ponds. 96

97 Figure 2 AirX system working in sea cages. 3. Results and Discussion The purpose of aeration or oxygenation in aquaculture systems is either to remove gases, such as carbon dioxide (CO 2 ) and nitrogen (N 2 ), or to increase the concentration of dissolved oxygen in the water.tests have shown that AirX is able to add oxygen in an efficient and homogenous manner throughout the water volume. The diffusers system is also designed to direct diffusion towards areas in the rearing unit where oxygenation is mostly needed. Dissolved oxygen is the most important parameter of water treatment in aquaculture facilities and the supply requirements approach the mass rate of elimination addition to feed per day (Colt et al,. 1991). In open sea fish cage the major source of dissolved oxygen is water flowing through the cage as a result of external currents and the movements of the cage (Beveridge, 1987). In many cases have been reported at both marine and fresh water facilities problems by reducing the oxygen availability (Inoue, 1972; Kils, 1979). Low concentrations of dissolved oxygen have also indicated problems in Mediterranean aquacultures producing sea bass and sea bream (Bergheim et al., 2006).Dallavia et al. (1998) has concluded that when dissolved oxygen decreased due to increased temperatures and the metabolic rate increases, the farmer can only respond by increasing oxygenation/water exchange rate or by decreasing fish stock density.airx system contributes to possible benefits for both the fish and the environment. Acknowledgments The present study was funded by the EU 7th Framework Programme, (project number FP ). References Colt, J., K. Orwicz, & G. Bouck Water quality considerations and criteria for high density fish culture with supplemental oxygen. American Fisheries Society Symposium 10, Bergheim, A., Gausen, M., Næss, A., Fjermedal, A.B., Hølland, P.M. & Å. Molversmyr Effects of oxygen deficit in post-smolt salmon. Trial I. Report RF Rogaland Research, 2002/ pp. Bergheim, A., Gausen, M., Næss, A., Hølland, Per M., Krogedal, P. & V. Crampton A newly developed oxygen injection system for cage farms. Aquacultural Engineering, 34, Beveridge, M.C.M Problems. In: Beveridge M. (Ed.), Cage Aquaculture. Fishing News Books, London, pp Dalla Via, G.J., Villani, P., Gasteiger, E. & H. Niederstätter Oxygen consumption in sea bass fingerling Dicentrarchuslabrax exposed to acute salinity and temperature changes: metabolic basis for maximum stocking density estimations. Aquaculture, 169: Endo, A., Srithongouthai, S., Naskiki, H., Teshiba, I., Iwasaki, T., Hama, D. & H. Tsutsumi DO-increasing effects of a microscopic bubble generating system in a fish farm. Marine Pollution Bulletin 57,

98 Inoue, H On water exchange in a net cage stocked with the fish, Hamachi. Bulletin of the Japanese Society for the Science of Fish, 38, Maeda, K., Matsuo, K., Yamahara, Y., Onari, H., Watanabe, K., Ishikawa, N. &Shimose, T The hydraulic effect of microbubble generator at oyster farm.proceedings of Annual Conference of the Japan Society of Civil Engineers, JSCE 2(56), Kils U Oxygen regime and artificial aeration of net cages.meeresforsch. 27, Ökte, E Grow-out of Sea bream Sparusaurata in Turkey, particularly in a land-based farm with recirculation system in Canakkale: better use of water, nutrients and space. Turkish Journal of Fisheries and Aquatic Sciences, 2, Terova, G., Rimoldi, S., Corá, S., Bernardini, G., Gornati, R. & M. Saroglia Acute and chronic hypoxia affects HIF-1a mrna levels in sea bass (Dicentrarchuslabrax). Aquaculture, 279 (1-2), Thetmeyer, H., Waller, U., Black, K.D., Inselmann, S. & H. Rosenthal Growth of European sea bass (Dicentrarchuslabrax) under hypoxic and oscillating oxygen conditions. Aquaculture, 174 (3-4),

99 CONTENTS OF As, Cd, Hg AND Pb IN TWO CULTURED FISH SPECIES FROM TURKEY Aksan S., Ergül H. A. * Department of Biology, Science and Arts Faculty, Kocaeli University, 41380, Kocaeli, Turkey ABSTRACT: Fish farms are able to produce high amount of quality food for human consumption. On the other hand, heavy metal pollution in aquatic ecosystems can be a serious problem in this study the contents of As, Cd, Hg and Pb in the edible tissue of culture breed Dicentrarchus labrax (Seabass) and Sparus aurata (Seabream) that are commercially available in the Turkey s fish markets were analyzed using ICP-MS. None of the heavy metal contents in the fish muscle tissue exceeded the threshold levels which were suggested by Food and Agriculture Organization and by the Turkish Food Codex and based on calculated element intake rates, there were no risk for humans to consume these farm fishes. Key words: Aquaculture, heavy metal seabass, seabream * Corresponding author: Halim Aytekin Ergül (halim.ergul@gmail.com) 1. Introduction Aquaculture currently provides a considerable proportion of edible fish which is expected to increase in future decades in order to meet the needs of the growing human population (Duarte et al., 2009). Seafood consumption by humans is important because of its high nutritional quality, valuable proteins, vitamins and mineral content. However, marine environments can be contaminated with toxins, particularly in coastal waters that receive industrial and domestic discharges. Through atmospheric deposition, sewage outfalls, urban storm water, agricultural and industrial runoff, heavy metals may enter marine and pond fish culture areas and subsequently pose a human health risk. Thus, in this study the contents of As, Cd, Hg and Pb in edible tissue of culture breed Dicentrarchus labrax (Seabass) and Sparus aurata (Seabream) that are commercially available in the Turkey s fish markets were analysed. The aims of this study are to determine and compare the contents of some toxic elements in the edible tissue of culture breed fish over a year. 2. Material and Methods D. labrax and S. aurata which are produced in fish farms were purchased from the primary fish markets of Kocaeli Province two times over a year. Samples which are fed in Aegean Sea on offshore of Aydın Province were put into polyethylene containers and kept cool for immediate transportation to the laboratory. Before dissection, length and weight measurements of samples were done (Table 1). Table 1: Sampling dates, muscle tissue dry weight ratios and total lengths of cultured fish that purchased from the primary fish markets in Kocaeli Province Species Common Name Sampling Date Total Lenght (cm) Muscle Dry Weight Ratio (%) Dicentrarchus labrax Sparus aurata Seabass Seabream Dec ± Jan ± Dec ± Jan ± Ten individuals per fish species were filleted using porcelain knives to avoid any metal contamination. Dissected muscle tissues were homogenized; fifty grams of samples were freeze dried until constant dry weight and homogenized. 0.5 g dried samples were digested for 30 minutes with 99

100 mixture of HNO 3, HCl and H 2 O 2 in a microwave digestion system. Digested samples and analytical blanks that were prepared in the same acid matrix were analyzed with ICP-MS which equipped with auto sampler and diluter. In order to validate the method for accuracy and precision, standard reference material (SRM-NIST 2977 Mussel Tissue) was analyzed for the corresponding elements. 3. Results and Discussion Contents of As, Cd, Hg, and Pb in the muscle tissue of D. labrax and S. aurata which were harvested in December 2011 and January 2013 are given in Table 2. Measured element contents in all samples were below recommended threshold levels for human consumption which were indicated by FAO (1983) and Turkish Food Codex (TFC, 2011) (i.e. 1 mg kg -1 for As, 0.5 mg kg -1 for Cd, 1 mg kg - 1 for Hg, and 0.3 mg kg -1 for Pb). Table 2. Element contents (dry weight ± standart deviation) in cultured fish species harvested from Aegean Sea. D. labrax S. aurata Elements Dec Jan Dec Jan As (mg kg -1 ) 2.53 ± ± ± ± 0.18 Cd (mg kg -1 ) 0.01 ± ± ± ± 0.01 Hg (mg kg -1 ) 0.25 ± ± ± ± 0.01 Pb (mg kg -1 ) 0.03 ± ± 0.02 BDL 0.03± 0.04 BDL: Below detection limit Although below recommended values it is noteworthy that these fish species include nonessential elements. The highest As content was determined in D. labrax (i.e., 2.53 mg kg -1 ) in December 2011 in the present study. In a previous study As was found in lower content (i.e., average 0.37 mg kg -1 - wet weight) in cultured D. labrax (Ersoy et al., 2006) from Mediterranean Sea. On the other hand, higher As contents (i.e., average 4.9 mg kg -1 ) was reported in cultured S. aurata (Minganti et al., 2010) from Mediterranean Sea. Fish, those analyzed in the present study, contains an average of 0.07 mg kg -1 inorganic As and could be consumed without restriction according to EPA (2000). Because approximately 80% of As in fish muscle is estimated to be in the form of arsenobetaine (Larsen and Francesconi, 2003), while inorganic As remain below the recommended level by Turkish Food Codeks (2011) and FAO (1983). Cadmium contents in the present study were less then 0.01 mg kg -1 for both species. In a previous study slightly higher Cd content was determined (i.e., mg kg -1 ) in S. aurata in a fish farm from Adriatic Sea (Creti et al., 2010). While the highest Hg levels were determined in D. labrax (i.e mg kg -1 ) the lowest were determined in S. aurata (i.e 0.05 mg kg -1 ). In a previous study, while average Hg content was as 0.04 mg kg-1 in D. labrax in a fish farm from Canary Island (Hardisson et al., 2012). In another study 0.12 mg kg -1 average total Hg content was reported in S. aurata in a fish farm from Mediterranean Sea (Minganti et al., 2010). All Hg contents reported from other studies were lower than the results in the present study. Pb values varied between BDL and 0.03 mg kg -1 in the present study. In previous studies higher Pb contents were determined (i.e mg kg -1 ) in S. aurata in a fish farm from Adriatic Sea (Cretì et al. 2010) and in cultured D. labrax (i.e mg kg -1 - wet weight) (Ersoy et al. 2006) from Mediterranean Sea (Table 2). Beside of atmospheric and riverine born inputs, food pellets, precipitated and/or resuspended sediment, and cage materials and equipment including sea vessels can be sources of these toxic elements in the muscle tissue of fish samples. On the other hand, because of lack of studies on metal contents of artificial food from fish farms, it is difficult to estimate sources of non-essential elements. Though there are some surface sediment studies below the fish farms in the region (Basaran et al., 2010; Kalantzi et al., 2013) it is also difficult to say presence of toxic elements in the muscle tissue of farm fishes, originated from sediments. 100

101 Generally, none of measured elements exceed threshold levels or recommended values for consumption in fish. However, some toxic elements (i.e. As, Cd, Hg, and Pb) were determined in all samples and it is suggested that monitoring of these elements can be useful for studies in the future. Also in the future studies element measurements in food pellets and nearby surface sediments can be supply valuable information for evaluate the results. Acknowledgements This study was funded by the Kocaeli University Scientific Research Projects Unit (Grant No: KOU-BAPB 2011/115). References Basaran A.K., Aksu, M., Egemen, O. (2010). Impacts of the fish farms on the water column nutrient concentrations and accumulation of heavy metals in the sediments in the eastern Aegean Sea (Turkey). Environmental Monitoring and Assessment 162, Creti, P. Trinchella, F., Scudiero, R. (2010). Heavy metal bioaccumulation and metallothionein content in tissues of the sea bream Sparus aurata from three different fish farming systems. Environmental Monitoring and Assessment 165, Duarte, C.M. Holmer, M., Olsen, Y., Soto, D., Marba, N., Guiu, J., Black, K., Karakassis, I. (2009). Will the Oceans Help Feed Humanity? Bioscience 59, EPA (2000). Guidance for Assessing Chemical Contaminant Data for Use in Fish Advisories Volume 2 Risk Assessment and Fish Consumption Limits Third Edition, in: Water, O.o.S.a.T.O.o. (Ed.), United States Environmental Protection Agency. United States Environmental Protection Agency, Washington, p Ersoy, B. Yanar, Y., Kucukgulmez, A., Celik, M. (2006). Effects of four cooking methods on the heavy metal concentrations of sea bass fillets (Dicentrarchus labrax Linne, 1785). Food Chemistry 99, FAO (1983). Compilation of legal limits for hazardous substances in fish and fishery products, Roma. Hardisson A., Rubio, C., Gutierrez, A., Jalili, A., Hernandez-Sanchez, C., Lozano, G., Revert, C., Hernandez-Armas, J., Total Mercury in Aquaculture Fish. Pol. J. Environ. Stud. 21, Kalantzi I., Shimmield, T.M., Pergantis, S.A., Papageorgiou, N., Black, K.D., Karakassis, I. (2013). Heavy metals, trace elements and sediment geochemistry at four Mediterranean fish farms. Science of The Total Environment 444, Larsen E.H., Francesconi, K.A. (2003). Arsenic concentrations correlate with salinity for fish taken from the North Sea and Baltic waters. Journal of the Marine Biological Association of the United Kingdom 83, Minganti V., Drava, G., De Pellegrini, R., Siccardi, C. (2010). Trace elements in farmed and wild gilthead seabream, Sparus aurata. Marine Pollution Bulletin 60, TFC (2011). Decleration on Maximum Limits of Contaminants in Food, ed. Turkish Republic Official Gazette, Ankara, Turkey. 101

102 EFFECT OF DIETARY SUPPLEMENTATION OF Spirulina platensis ON THE GROWTH AND HAEMATOLOGY OF THE STRESSED CATFISH Clarias gariepinus Alaa El-Din H. Sayed1, Mustafa A. Fawzy2 1 Zoology Department, Faculty of Science, Assiut University, Assiut, Egypt. 2 Botany and Microbiology Department, Faculty of Science, Assiut University, Assiut, Egypt. Corresponding author: Alaa El-Din Hamid Sayed, Telephone: Fax: alaa_h254@yahoo.com (A.H. Sayed) ABSTRACT The effect of feeding Spirulina platensis on the growth and haematological parameters of the Nile catfish; Clarias gariepinus exposed to food shortage stress were investigated. S. platensis was added to the basal diet at 0.0, 1.25, 2.5 and 5.0 g Spirulina /kg diet and fed for two months to the Nile catfish. Our results showed that the final fish weight, weight gain and specific growth rate of C. gariepinus fed on the experimental diets were not significantly different (p > 0.05). The fish fed on Spirulina diets exhibited higher RBCs counts, WBCs counts, haemoglobin and haematocrit levels as compared with stressed fish and control. The feeding dietary Spirulina resulted in significant decreases in mean cell volume, mean cell haemoglobin and neutrophils, while, the mean cell haemoglobin concentration was not affected. The platelets and monocytes were increased with Spirulina levels increase. A significant decrease in eosinophils and small lymphocytes were observed in the fish treated with Spirulina, however, the large lymphocytes were increased. The percentage of altered erythrocytes of fish treated with Spirulina was significantly decreased in comparison to stressed fish and control. We can conclude that Spirulina supplementation is promising for improving the hametological parameters in Clarias gariepinus, as immun-inducer and growth factor in food ingredients for fish feeding. Keywords: Spirulina platensis, Clarias gariepinus, growth performance, haematology. 1- INTRODUCTION Marine macro- and microalgae were receiving increasing attention as a possible protein source for fish diets, particularly in tropical developing countries, because of their high protein content and production rate (Venkataraman et al., 1980). Microalgal species are of great value because of their high bioactive materials content, including polyunsaturated fatty acids, α- carotene and other pigments (antioxidants) (Bhat and Madyastha, 2000). The use of algae as a feed additive might help in effective utilization of artificial diets in cultured fish (Mustafa and Nakagawa, 1995). Spirulina is a freshwater blue-green filamentous alga, and has been one of the most widely used microalgal species in aquafeeds due to its high contents of proteins, vitamins, essential amino acids, minerals, essential fatty acids and antioxidant pigments such as carotenoids (Nakagawa and Montgomery, 2007). α-carotene in Spirulina firmly maintains the mucous membrane and thereby prevents the entry of toxic elements into the body (Henrikson, 1994). Chlorophyll in Spirulina acts as a cleaning and detoxifying factor against toxic substances (Henrikson, 1994). Growth studies with Spirulina, have confirmed that it improves carcass quality (Liao et al., 1990), encourages growth (Mustafa et al., 1994a). Therefore, it has been used as a nutrient for fish larvae (Lu 102

103 and Takeuchi, 2004; Lu et al., 2002) and as an ingredient in fish diet for juveniles and adults common carp (Palmegiano et al., 2008). Tilapia fed solely on raw Spirulina could maintain normal reproduction from parents to progeny throughout three generations (Lu and Takeuchi, 2004). It has been verified that larval tilapia fed solely on raw Spirulina cultivated in photo-bioreactors can grow normally from the onset of exogenous feeding without any nutrient supplements (Lu et al., 2002). The addition of small amounts of algae to fish feed exerted pronounced effects on growth, lipid metabolism, body composition and disease resistance (Mustafa et al., 1994b). As well as, haematological studies in fish have diagnostic as well as economic significance. In recent years fish haematology has become an increasingly important tool of fisheries biologists and research ichthyologists (Mekkawy et al., 2011; Sayed et al., 2013; Sayed et al., 2007). Hence, S. platensis may have potential to be used as a natural feed supplement for increasing fish growth. Therefore, the main objective of the present study is to investigate the effect of diets containing S. platensis on the growth and some haematological parameters of Clarias gariepinus. 2- MATERIALS AND METHODS 2.1. Algal Culture The culture of Spirulina platensis (Gomont) was isolated from agriculture faculty farm in Assiut University (Egypt) and identified according to (Prescott, 1978). S. platensis was grown in Zarrouk's medium (Zarrouk, 1966) at ph 9 and incubated at 30 o C under continuous illumination fluorescent light of 48.4 ιmole.m-2.s-1. The alga was cultivated in 50 L photobioreactors using a unialgal semi-continuous culture (Morist et al., 2001). To determine the algal biomass, a 100 ml aliquot of the algae suspension was filtered through Whatman (GF/A) glass fiber (0.45 m), and the obtained pellet was then oven-dried at 85oC for 4h and weighed. Chlorophyll-a and carotenoids were extracted in methanol (80 %) and determined according to (Marker, 1972). Phycobiliproteins contents of S. platensis were determined according to the method described by (Bennet and Bogorad, 1973). Total proteins in S. platensis were determined according to (Lowry et al., 1951). For the determination of total carbohydrates, the anthrone sulfuric acid method was used (Badour, 1959). Total lipids in S. platensis were determined by the sulfophosphovanilin method (SPV) (Drevon and Schmitt, 1964) (Table 2) Fish sample collection and pre-experimental adaptation Nightly six healthy fishes of the Nile catfish; Clarias gariepinus (490 ± 17.8 g) in weight were caught from the fish farm of Faculty of Agriculture, Assiut University, Egypt in April Fishes immediately transported to the Fish Biology laboratory in the Department of Zoology, Faculty of Science, Assiut University. The experimental fishes were reared in aerated glass tanks (100 L capacity) and acclimatized for two weeks before being used in the experimental study. The experimental fish fed commercial pellets at a rate of 5 % of wet weight twice daily to help the fish adapt to their new environment before the experiment. Feces and residual food were aspirated regularly. The water temperature, ph, dissolved oxygen (DO) concentrations and electrical conductivity (EC) were measured daily (25.2 ± 0.08 ºC, ph: 6.8 ±11, DO: 6.5± 0.89 mg L-1 and EC: 260 ± 0.2 ιmho.cm-1) Experimental setup The adapted fishes were exposed to food shortage stress (feed at 2% of body wet weight daily) for two months (May and June 2013). This experiment was done under the same conditions of the adaption period. After that, fishes were weighed and classified randomly into 4 groups according to the concentrations of Spirulina. Each group was contained three replicates (8 fish/ 100 L tank). Then, fishes were exposed to different concentrations of Spirulina within food (0.0 (control), 1.25, 2.5 or 5.0 g Spirulina /kg diet). The exposure was 103

104 for two months and experimental fish were fed on commercial pellets (5 % of wet weight twice daily) with changing all the tap water every day Diet preparation Isolated Spirulina culture was added to the basal diet which represented in Table (1) to represent various concentrations as 0.0 (control), 1.25, 2.5 or 5.0 g Spirulina/kg diet. The nutritional composition of Spirulina platensis was shown in Table (2). Each concentration of Spirulina was suspended in 100 ml distilled water and added to the ingredients of the experimental diet, and blended for 40 min at least to make a paste of each diet. The pastes were separately passed through a grinder, and pelleted (1 mm diameter) in a paste extruder. The diets were air-dried and stored in plastic bags in a refrigerator (-2 o C) for further use. Water quality such as temperature, dissolved oxygen ph and electrical conductivity were measured every 20 day during the experiment Growth parameters Fishes were weighed at the beginning and end of the experiment. Growth was calculated as the difference between the wet weights at the beginning of the experiment and on the day of calculation. Percentage weight gain PWG (%) was calculated as (Final mean body weight/ Initial mean body weight) x 100 (Tacon, 1990). Specific growth rate (SGR) was calculated as (Wt1 Wto)/t1 x 100, where Wto and Wt1 are the weights of the fish at the beginning and end of each sampling period and t1 is the period between samplings in days (Hevrory et al., 2005). The survival rate was calculated as (No of fishes remaining at the end of the experiment/ No of fishes at the beginning of the experiment) x 100 (Ai et al., 2006) Hematological parameters Blood samples were taken from the caudal vein into heparinzed tubes. The concentration of Hb and blood cells count was immediately estimated. Other samples of blood were centrifuged at 5000 rpm for 10 min and serum samples were stored in polyethylene Eppendorf test tubes at -20 C until serum analysis. The RBC s, WBC s, blood Platelets, Haematocrit (HCT), Hemoglobin (Hb) were determined by using automated technical analyzer (Mindray Bc-2800). Mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC) were calculated using the formulae mentioned by (Dacie and Lewis, 1991). MCHC (g/dl) = Hb/ HCT x 100, MCH (pg ( = Hb/ RBC's x 10, MCV (ιm³) = HCT/ RBC's x 10. Differential WBC's were counted using blood smears stained with Giemsa satin according to (Tavares- Dias and Moraes, 2003) 2.7. Erythrocytes alterations Blood smears were obtained by the caudal incision on clean grease free microscopic slides after exposure. The smears were fixed in absolute methanol for 10 min after drying at room temperature. Slides were stained with haematoxylin and eosin. It was followed by dehydration in ascending grades of alcohol (30, 50, 70, and 90%, absolute). Finally the slides were cleared in xylene and permanently mounted by DPX (Pascoe and Gatehouse, 1986). Many slides were selected on the basis of staining quality, then coded, randomized and scored blindly. In each group 10,000 cells (a minimum of 1000 per slide) were examined (Al-Sabti and Metcalfe, 1995) at 40 objective and 10 eyepiece for morphologically altered erythrocytes in separate studies. The morphologically altered erythrocytes were described according to (Mekkawy et al., 2011) Statistical analysis Statistical analyses were performed on the data obtained from completely randomized design with three replications after two months of the experimental period. One-way ANOVA was used to test the effect of the dietary treatment. Duncan Multiple Range test was also applied 104

105 to compare the means when a significant difference (p < 0.05) was detected by ANOVA. All the statistical analyses were done using SPSS program version 10 (SPSS, Richmond, VA, USA). Ethical statement All experiments were carried out in accordance with the Egyptian laws and University guidelines for the care of experimental animals. All procedures of the current experiment have been approved by the Committee of the Faculty of Science of Assiut University, Egypt. 3- RESULTS 3.1. The physico-chemical characteristics of the water The water quality was measured every 20 day during the experiment (Table 3). Water temperature ranged between 28.6 and 29.1o C at twenty day and first day of the experiment, respectively. With respect to the dissolved oxygen and electrical conductivity, the maximum value was recorded at the forty day. The ph value was tented to weakly alkaline Nutritional composition of Spirulina platensis and Growth performance Nutritional composition of Spirulina platensis was shown in Table (2). Spirulina platensis were contained high percentage of total proteins (43.4 %), total carbohydrates (28.1 %), total lipids (5.02 %), chlorophyll-a (0.68 %), carotenoids (0.65 %) and phycobiliproteins (18.43 %). The effects of Spirulina diets on the growth parameters for Clarias gariepinus throughout the experimental periods are given in Table (4). The final fish weight ranged from 471 g to 535 g for the fishes exposed to food shortage stress (after stress) and 2.5 g Spirulina/kg diet, respectively; and was not significantly lower in fish fed after stress than all Spirulina diets (p > 0.05). Also, the weight gain and specific growth rate of Clarias gariepinus fed on the experimental diets was not significantly different (p > 0.05). Furthermore, fish survival was not statistically different among dietary treatments, and its range was % (Table 4) Hematological parameters Fishes were fed on Spirulina diets exhibited significant increasing in RBCs counts and their ranges were /ιL for the fishes fed after stress and 5 g Spirulina/kg diet, respectively (p < 0.05; Table 5). The high counts of WBCs were obtained at 5g/kg diet ( /ιL). Dietary Spirulina significantly affected the haemoglobin of fishes and varied from 7.51 to 9.83 mg/dl for the fishes fed after stress and 1.25 g Spirulina/kg diet, respectively. Haematocrit tended to increase with increasing dietary Spirulina levels than the control fish (p < 0.05). Mean cell volume ranged between and ιm³ for the fishes fed 5 g Spirulina/kg diet and the control fish, respectively. The highest level of mean cell haemoglobin was found in control diet; however, there were no differences in mean cell haemoglobin concentration of the fishes fed Spirulina diets. Platelets were significantly increased than the control fish with increasing Spirulina levels in fish diet (p < 0.05) and the high value was recorded at 5 g Spirulina/kg diet. The number of neutrophils was decreased with the Spirulina levels while monocytes increased in comparison with control fish (Table 5). The highest number of neutrophils and monocytes were recorded in fish fed after stress. The fish were fed 1.25 g Spirulina/kg diet displayed high number of basophils. Generally eosinophils were significantly decreased with Spirulina levels (p < 0.05). The control diet produced the highest percentage of small lymphocytes, which decreased with the increase of Spirulina levels in fish diet (p < 0.05). Fish fed 5 g Spirulina/kg diet had a significantly (p < 0.05) higher number of large lymphocytes compared to the control fish (Table 4). 105

106 3.4. Altered erythrocytes As shown in Fig.1 the percentage of altered erythrocytes of control fish was 3.14 ± 0.26% and this percentage increased significantly in group exposed to feeding shortage stress. With increasing the concentration of Spirulina levels the percentage of altered erythrocytes significantly decreased as 3.00 ± 0.44 %, 2.29 ± 0.52 % and 1.00 ± 0.31 % for 1.25, 2.5 and 5.0 g/kg fish diet, respectively. Fig. 2 shows the important variations in erythrocytes such as acanthocytes, tear drop like cells, sickle cells, and enucleated erythrocytes (arrows). DISCUSSION The current investigation was performed to test the feasibility of including dietary Spirulina meal in practical diets for Clarias gariepinus. The water quality in the present study was within an acceptable range for catfish culture (Bhujel, 2000). The data in this study showed that, the growth performance of Clarias gariepinus fed on Spirulina diets was not significantly different. These results are in accordance with (Ungsethaphand et al., 2010) who recorded that the final weight gain and specific growth rate of hybrid red tilapia were not affected by S. platensis supplementation. Also, (Teimouri et al., 2013) found that, S. platensis supplemented diets did not change growth related parameters in rainbow trout. (Olvera-Novoa et al., 1998) and (Dernekbasi et al., 2010) observed that replacing fishmeal with S. platensis up to 40% did not change growth rate in tilapia and guppy. On the contrary, (James et al., 2006) reported that dietary inclusion of 8 % Spirulina significantly elevated growth performance of the ornamental red swordtail Xiphophorus helleri. Because Spirulina is rich in proteins, vitamins, minerals, essential amino acids and fatty acids (Nakagawa and Montgomery, 2007), it has been identified as a potential feed ingredient for cichlids and ornamental fish and appears to be a promising dietary ingredient. In the current study, fish fed on Spirulina diets exhibited higher RBC's and WBC's counts as well as, the haemoglobin value as compared with fish fed after stress and the control diet. This increase could be due to the presence of C-phycocyanin in the Spirulina alga, which can help build the immunity capacity (Vonshak, 1997). These results proved the improvement of fish health when fed Spirulina-supplemented diets because Spirulina contains carotenoids, which increase the ability to fight off infections through the reduction of stress levels (Nakono et al., 2003). The major functions of WBCs are to fight infection; defend the body against foreign organisms and in immune response. Decreased in WBCs counts in control fish after food shortage stress in this study was similar to the observation of (Sunmonu and Oloyede, 2008) in catfish exposed to increased crude oil concentration. Feeding dietary Spirulina had a significant (P < 0.05) increase in the levels of haematocrit. (Moe, 2011) recorded that haematocrit value in treated fish was lower than that of control fish. On the other hand, the obtained results revealed that feeding dietary Spirulina resulted in significant decreases in mean cell volume as well as mean cell haemoglobin but mean cell haemoglobin concentration were not affected by S. platensis supplementation. These results are disagreeing with (Moe, 2011) who reported that the values of MCH were significantly higher (p < 0.05) than that of control fish. The platelets and monocytes in this study were increased while neutrophils were decreased with Spirulina levels. (Abd El-Ghany and Abd Alla, 2008) observed increasing in plasma levels of cortisol, eosinophils and monocytes in the fish treated with Fucus. The results of the present investigation exhibit that, the highest number of basophils was recorded in the fish fed 1.25g Spirulina/kg diet. Basophils play an important role in body immune responses (Miller, 1993). Generally, the fish treated with Spirulina exhibited a significant decrease in eosinophils and small lymphocytes, however, the large lymphocytes were increased. (Abd El-Ghany and Abd Alla, 2008) revealed that, the fish treated with Fucus exhibited a significant increase in the total leucocytic count and 106

107 lymphocytes. Our study indicated that, the percentage of altered erythrocytes of fish treated with Spirulina was significantly decreased in comparison to fish fed after stress and the control diet. The improvement of the erythrocytes alterations was recorded after treatment with quince leaf extract in the same species after UV radiation (Sayed et al., 2013). In the present study the increase in altered cell frequencies appeared more clearly in fishes exposed to food shortage stress. The alterations in fish erythrocytes were observed in hypoxic condition (Sawhney and Johal, 2000), factors that induce apoptosis of blood cells like radiations, 4-nonylphenol (Mekkawy et al., 2011), and UVA (Sayed et al., 2013). In conclusion, the present study showed hematology profile for the Clarias gariepinus species after two months of food shortage stress in comparison with control and Spirulina diets. Also, the Spirulina feeding improved the hametological parameters in all exposed groups compared with stressed and control groups. Finally we recommend with using Spirulina as immun-inducer and growth factor in food ingredients for fish feeding in fish culture. REFERENCES Abd El-Ghany, N.A., Abd Alla, H.M.L., A trial for treatment of ichthyophonosis in cultured Oreochromis niloticus using Fucus and neem plants, 8th International Symposium on Tilapia in Aquaculture, Cairo, Egypt. Ai, Q., Mai, K., Tan, B., Xu, W., Duan, Q., Ma, H., Zhang, L., Replacement of fish meal by meat and bone meal in diets for large yellow croaker, Pseudosciaena crocea. Aquaculture 260, Al-Sabti, K., Metcalfe, C.D., Fish micronuclei for assessing genotoxicity in water. Mutation Resarch, Badour, S.S.A., AnalytischoChemische unter suchung des kalimangels bei Chlorella in vergleich mit anderen manget zamstanden, Goettingen, Germany. Bennet, A., Bogorad, L., Complementary chromatic adaptation in filamentous bluegreen algae. Cell Biology 58, Bhat, V.B., Madyastha, K.M., C-phycocyanin: a potent peroxyl radical scavenger in vivo and in vitro. Biochemical and Biophysical Research Communications 275, Bhujel, R.C., A rewiew of strategies for the management of Nile tilapia (Oreochromis niloticus) broodfish in seed production systems, especially hapa-based systems. Aquaculture 181, Dacie, S., Lewis, S., Practical Haematology, Seventh ed, London. 13 Dernekbasi, S., H., Una, I., Karayucel, A.I., Aral, O., Effect of dietary supplementation of differentrates of Spirulina (Spirulina platensis) on growth and feed conversion in guppy (Poecilia reticulata Peters, 1860). Journal of Animal and Veterinary Advances 9, Drevon, B., Schmitt, J.M., La reaction sulfophosphovanillique dans l ét.ude des lipides seriques. Bulletin Trau. Society Pharmaceuticals Lyon 8, Henrikson, R., Microalga Spirulina Super Alimento del Futuro Ronore Enterprises, Urano, Barcelona, Spain. Hevrory, E.M., Espe, M., Waagbo, R., Sandnes, K., Ruud, M., Hemre, G., Nutrition utilization in Atlantic salmon (Salmo salar) fed increased level of fish rotein hydrolyses during a period of fast growth. Aquaculture Nutrition 11, James, R., Sampath, K., Thangarathinam, R., Vasudevan, I., Effect of dietary Spirulina level on growth, fertility, coloration and leucocyte count in red swordtail, Xiphophorus helleri. Israeli Journal of Aquaculture Bamidgeh 58,

108 Liao, W.L., Takeuchi, T., Watanabe, T., Yamaguchi, K., Effect of dietary Spirulina supplementation on extractive nitrogenous constituents and sensory test of cultured striped jack flesh. Journal of Tokyo University of Fisheries 77, Lowry, D.H., Rosebrough, N.J., Farr, A.L., Randall, R.J., Protein measurement with the folin phenol reagent. Journal of Biological Chemistry 193, Lu, J., Takeuchi, T., Spawning and egg quality of tilapia Oreochromis niloticus fed solely on raw Spirulina throughout three generations. Aquaculture 234, Lu, J., Yoshizaki, G., Sakai, K., Takeuchi, T., Acceptability of raw Spirulina platensis by larval tilapia Oreochromis niloticus. Fisheries Science 68, Marker, A.F.H., The use of acetone and methanol in the estimation of chlorophyll in the presence of Phaeophytin. Freshwater Biology 2, Mekkawy, I.A., Mahmoud, U.M., Sayed, A.H., Effects of 4-nonylphenol on blood cells of the African catfish Clarias gariepinus (Burchell, 1822). Tissue and Cell 43, Miller, O., Laboratory for clinical. Rio de Janeiro, Atheneu. Moe, P.P., Effect of Diet Containing Spirulina platensis on the Growth and Haematology of Nile Tilapia, Oreochromis niloticus (Linnaeus, 1758). Universities Research Journal 4, Morist, A., Montesinos, J.L., Cusido, J.A., Godia, F., Recovery and treatment of Spirulina platensis cells cultured in a continuous photobioreactor to be used as food. Process Biochemistry 37, Mustafa, M.G., Nakagawa, H., A review: dietary benefits of algae as an additive in fish feed. Israeli Journal of Aquaculture Bamidgeh 47, Mustafa, M.G., Takeda, T., Umino, T., Wakamatsuand, S., Nakagawa, H., 1994b. Effects of Ascophyllum and Spirulina meal as feed additives on growth performance and feed utilization of red sea bream, Pagrus major. Journal of the Faculty of Applied Biological Science 33, Mustafa, M.G., Umino, T., Nakagawa, H., 1994a... 10, 1994a. The effect of Spirulina feeding on muscle protein deposition in red sea bream, Pagrus major. Journal of Applied Ichthyology 10, Nakagawa, H., Montgomery, W.L., Algae. In: Dietary supplements for the health and quality of cultured fish. CABI North American Office Cambridge, USA. Nakono, T., Yamaguchi, T., Sato, M., Iwama, G.K., Biological Effects of Carotenoids in Fish, Effective Utilization of Marine Food Resource, Songkhla, Thailand, pp Olvera-Novoa, M., Domnguez-Cen, L., Olivera-Castillo, L., Martnez-Palacios, C.A., Effect ofthe use of the microalga Spirulina maxima as fish meal replacement in diets for tilapia, Oreochromis mossambicus (Peters), fry. Aquaculture Research 29, Palmegiano, G.B., Gai, F., Dapra, F., Gasco, L., Pazzaglia, M., G., P.P., Effects of Spirulina and plant oil on the growth and lipid traits of white sturgeon (Acipenser transmontanus) fingerlings. Aquaculture Research 39, Pascoe, S., Gatehouse, D., The use of a simple haematoxylin and eosin staining procedure to demonstrate micronuclei within rodent bone marrow. Mutation Resarch 164, Prescott, G.W., How to Know Freshwater Algae. WM.C. Brown Company, Dubuque, Iowa, USA. Sawhney, A.K., Johal, M.S., Erythrocyte alterations induced by malathion in Channa punctatus (Bloch). Bulletin of Environmental Contamination and Toxicology 64,

109 Sayed, A.H., Abdel-Tawab, H.S., Abdel Hakeem, S.S., Mekkawy, I.A., The protective role of quince leaf extract against the adverse impacts of ultraviolet-a radiation on some tissues of Clarias gariepinus (Burchell, 1822). Journal of Photochemistry and Photobiology B: Biology 119, Sayed, A.H., Ibrahim, A.T., Mekkawy, I.A.A., Mahmoud, U.M., Acute effects of Ultraviolet-A radiation on African Catfish Clarias gariepinus (Burchell, 1822). Journal of Photochemistry and Photobiology B: Biology 89, Sunmonu, T.O., Oloyede, O.B., Haematological response of African Catfish (Clarias gariepinus) and rat to Crude oil exposure. The Internet Journal of Haematology 4, 3-6. Tacon, A.G.J., Standard methods for the nutrition and feeding of farmed fish and shrimp. Argent laboratories press, Washington DC., USA. Tavares-Dias, M., Moraes, F.R., Hematological evaluation of Tilapia rendalli Boulenger, 1896 (Osteichthyes: Cichlidae) captured in a fee fishing farm from Franca, S?o Paulo, Brasil (in Portuguese). Biosc J. 19, Teimouri, M., Amirkolaie, A.K., Yeganeh, S., Effect of Spirulina platensis Meal as a Feed Supplement on Growth Performance and Pigmentation of Rainbow Trout (Oncorhynchus mykiss). World Journal of Fish and Marine Sciences 5, Ungsethaphand, T., Peerapornpisal, Y., Whangchai, N., Sardsud, U., Effect of feeding Spirulina platensis on growth and carcass composition of hybrid red tilapia (Oreochromis mossambicus O. niloticus). Maejo international journal of science and technology 4, Venkataraman, L.V., Nigam, B.P., Ramanatham, P.K., Rural oriented fresh water cultivation and production of algae in India, in: Shelef, G., Soede, C.J. (Eds.), Algae Biomass. Elsevier, Amsterdam, pp Vonshak, A., Spirulina platensis (Arthospira): Physiology, Cell Biology and Biotechnology. Taylor and Francis, London. Zarrouk, C., Contribution à l étude d une cyanophycée. Influence de divers facteurs physiques et chimiques sur la croissance et la photosynthè se de Spirulina maxima Geilter. Universite de Paris, Paris, France. Table 1. Nutrient composition of Percentage experimental diets (%) Ingredient Soybean meal (48%) a 30.1 Cotton meal (41%) 10.0 Menhaden meal (61%) 4.0 Corn grain 33.6 Wheat middlings 20.0 Dicalcium phosphate 0.6 Catfish vitamin and mineral 0.2 mix b Fat/oil

110 SUBSTITUTION OF FISHMEAL BY FLY Hermetia illucens PREPUPAE MEAL IN THE DIET OF GILTHEAD SEABREAM (Sparus aurata) Karapanagiotidis I.T. 1 *, Daskalopoulou E. 1, Vogiatzis I. 1, Rumbos C. 1,2, Mente E. 1, Athanassiou C.G. 2 1 Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Fytoko Street, 38446, Volos, Greece. 2 Laboratory of Entomology and Agricultural Zoology, Department of Agriculture, Crop Production and Rural Environment, School of Agricultural Sciences, University of Thessaly, Fytoko Street, 38446, Volos, Greece. ABSTRACT One of the most critical issues that threatens the sustainability and further growth of aquaculture production is its dependency on fishmeal that is included in industrially compounded aquafeeds. Global annual production is being static for the last 15 years, with its price being steadily increased, and many sustainability issues have arisen. Insects could be an alternative solution to partially satisfy the nutritional needs of the cultured fish, provided that their growth and the quality of their edible flesh would not be negatively affected. Many insect species are rich sources of animal proteins, with a good profile of amino acids, while they are also rich in lipids-energy. The aim of the present study was to assess the suitability of prepupae of the black soldier fly Hermetia illucens as a feedstuff of the diet of gilthead seabream (Sparus aurata) partially replacing fishmeal (FM). A total number of 240 juveniles of 1.47 ± 0.22g initial mean weight were transferred to 12 saltwater aquaria within a closed recirculation system. They were divided into 4 dietary treatments that were fed twice a day for 10 weeks four isoenergetic (20.3 Mj/Kg) and isonitrogenous (46%) diets differing in the inclusion level of a meal produced by dried prepupae of H. illucens: FM diet contained only fishmeal and used as a control diet, while in diets FPM10, FPM20 and FPM30 the fishmeal protein level was substituted by fly prepupae meal at 10%, 20% and 30%, respectively. Fly prepupae meal resulted in similar values of FCR, protein efficiency ratio and protein retention with the fish feeding on fishmeal. Fish fed the FM diet had the significantly higher feed consumption than the rest groups that led to a significantly higher weight gain. Fish fed the FM diet had also the highest SGR, but not significantly higher than the rest fish groups. The partial replacement of FM up to 30% by H. illucens prepupae meal in the diet of seabream does not significantly reduces fish growth rate. Key words: seabream, Sparus aurata, fishmeal, insects, Hermetia illucens, nutrition. *Corresponding author: Karapanagiotidis Ioannis T. (ikarapan@uth.gr). Introduction One of the most critical issues that threatens the sustainability and further growth of aquaculture production is its dependency on fishmeal (FM) that is included in industrially compounded aquafeeds. Particularly, the intensive production of carnivorous species such as gilthead seabream is heavily dependent on continuing supplies of high quality FM. FM global annual production is around 6 million tonnes being static for the last 15 years, with its price being steadily increased since 2000 (Tacon & Metian 2008). Over the last two decades, research findings revealed that significant reductions of the inclusions levels of FM in feeds for most carnivorous species can be achieved by partially replacing it with plant proteins without leading to detrimental effects on fish growth (Bell & Wagboo 2008). However, FM cannot be fully replaced by plant proteins in aquafeeds of most cultured European farmed fish species because this results in loss of fish growth performance due to reduced levels of essential amino acids, the presence of several anti-nutritional factors and reduced palatability of plant feedstuffs (reviewed by Bell & Wagboo 2008). Moreover, plant feedstuffs can also reduce nutrient bioavailability in fish body resulting in nutrient loss to the aquatic environment, which in turn produces an undesirable disturbance to the balance of organisms present in the aquatic environment (Gatlin et al. 2007). FM will continue to make an important contribution to aquaculture production as its high protein value makes it a key material in aquafeeds. In the future, this marine resource will be 110

111 used as sparingly as possible and will become a strategic ingredient in special diets targeting at the critical stages of the life cycle of farmed fish, especially the carnivorous ones (Tacon & Metian 2008). If the production of farmed fish is to contribute in global fish availability it is essential for the sector to continue searching for suitable raw alternatives to FM that are both economically viable and environmentally friendly for aquafeed production. An ideal viable alternative feedstuff to FM in aquafeeds should possess certain characteristics including wide availability, competitive price, plus ease of handling, shipping, storage and use in feed production. Furthermore, it should possess certain nutritional characteristics, such as low levels of fibre, starch, especially non-soluble carbohydrates and antinutrients, a relatively high protein content, favorable amino acid profile, high nutrient digestibility and reasonable palatability. Insects could be an alternative solution to partially satisfy the nutritional needs of the cultured fish, assuming that their growth and the quality of their edible flesh would not be negatively affected. They are rich sources of animal proteins, with a good profile of amino acids, and consist a rich source of lipids-energy (Sánchez-Muros et al. 2014). Insects are also considered as a natural diet of fish (Hill & Watson 2007). Apparently, the availability of insects in adequate quantities as well as suitable manufacture technology for mass production is currently a threshold (Monentcham et al. 2010). Studies up to date using insect meals in fish diets have shown equivocal results as regards the fish growth rate and nutrient utilization among the several insect and fish species used (Sánchez-Muros et al. 2014). The larvae of black soldier (Hermetia illucens) have also been evaluated as feed in various fish species, including channel catfish and tilapia (Oreochromis sp.) without exerting any significant effect on fish growth though (Bondari and Sheppard 1981). In rainbow trout (Oncorhynchus mykiss) it has been shown that the growth of fish fed enriched H. illucens diets was not significantly different from fish fed a fishmeal-based control diet (Sealey et al. 2011). The aim of the current study was to assess the suitability of incorporating meal from prepupae of the fly H. illucens in the diet of gilthead seabream (Sparus aurata) substituting fishmeal. Materials and Methods A total number of 240 Sparus aurata juveniles with 1.47±0.22g initial mean weight were taken from a nearby commercial fish hatchery, transferred to the Department of Ichthyology and Aquatic Environment aquaculture station and stocked at 12 saltwater aquariums (60L) within a closed recirculation system. Juveniles were divided into four dietary treatments in triplicates (60 fish per treatment) and were fed four isoenergetic (20.3 Mj/Kg) and isonitrogenous (46%) diets differing in the inclusion level of a meal produced by dried prepupae of the H. illucens: FM diet contained only fishmeal and used as a control diet, while in diets FPM10, FPM20 and FPM30 the fishmeal protein level was substituted by fly prepupae meal at 10%, 20% and 30%, respectively. A H. illucens colony has been maintained in the Laboratory of Entomology and Agricultural Zoology of the Department of Agriculture, Crop Production and Rural Environment. The fly colony was originated from a wild population, originally collected from the south region of mountain Pelion (Central Greece). Larvae were reared under greenhouse conditions and fed mainly on vegetal organic wastes. Prepupae were collected with a ramp and gutter system as they migrated away from the manure to pupate and then stored at -20 C until used. All prepupae were dried at 40 C for 5 h and then for another 24 h under vacuum, milled and sieved to less than 1 mm particle size prior to the inclusion to the diet. The proximate composition of the dried black soldier meal was 12.1%, moisture, 31.6% crude protein, 27.2% crude lipid and 15.4% ash. Fish were being fed twice a day at and by hand to saturation. The feeding trial lasted 10 weeks. Water temperature was maintained at 21 C, ph was 8.0±0.4, salinity at 34±0.5 and dissolved oxygen was >6.5 mg/l. At the end of the trial, fish were killed by anesthesia and three fish, randomly selected from each tank, were taken and stored at -20 C for body proximate composition analysis. This was performed according to AOAC (1995) methods. Specifically, the determination of the moisture held by drying the samples at 105 C for 20h, the crude protein by the method Kjeldahl, the total fat with the Soxhlet method and total ash by burning the samples at 600 C for 3h. The following growth performance and feed utilization indices were measured: weight gain (%) = (W F W I ) 100 W I -1, mean daily weight gain (g day -1 ) = (W F W I ) (days) -1, specific growth rate (SGR, % day -1 ) = 100 [lnw F lnw I ] (days) -1, feed efficiency (FE) = wet weight gain (g) feed given (g) -1, protein efficiency ratio (PER) = weight gain (g) protein given -1 (g), nutrient retention (%) = 100 nutrient gain (g) nutrient given -1 (g), where, W I and W F are the initial and the final fish mean weights, TL the total length. In order to determine any significant differences between dietary treatments, data were subjected to one-way ANOVA, followed by Tukey s post-hoc test to rank the groups. Differences were regarded 111

112 as significant at P < ANOVA was performed using SPSS 18.0 (2009; SPSS, Inc., Chicago, IL, USA). Results and discussion All diets containing the fly prepupae meal were readily accepted by fish. However, fish feeding on the FM diet had significantly higher (P<0.05) feed consumption than the rest of the groups, indicating a poorer palatability of prepupae meal for gilthead seabream. Survival was similar (P>0.05) among groups (Table 2) indicating that prepupae meal does not exert any negative effect on fish health. On the other hand, Bondari & Sheppard (1987) found reduced survival rate in the channel catfish (Ictalurus punctatus) and blue tilapia (Oreochromis aureus) feeding on diets with H. illucens prepupae meal replacing fishmeal at 10% and 100%. All groups of fish feeding on prepupae meal based diets had significantly lower (P<0.05) final weight and weight gain compared to the FM diet. Fish fed the FM diet had also the highest SGR, but not significantly different than the values found at the rest groups. Thus, the partial replacement of FM at 10% to 30% by H. illucens prepupae meal in the diet of seabream does not significantly reduces its growth rate. As far as FCR is concerned, the values coming from the groups of fish feeding on the prepupae meal remained at low levels and were not significantly different (P>0.05) than that of the control group indicating a remarkable metabolic conversion of the prepupae meal. Protein efficiency ratio (PER) and protein retention (%) were also insignificant among the different dietary groups, although slightly higher in FM group, indicating a similar high protein utilization (digestion, absorption and synthesis) of prepupae meal to that of fishmeal by gilthead seabream. The body nutrient composition (Table 2) of fish was also unaffected (P>0.05) by the use of H. illucens prepupae meal in the diet. Table 1. Formulation and proximate composition of the experimental diets. FM FPM10 FPM20 FPM30 Ingredients (%) Fishmeal Fly meal Corn gluten Wheat, meal Fish oil Vitamins & minerals, premix MCP Choline Methionine Lysine Vitamin Δ Vitamin C Anti-moulting agent Chemical composition (%) Dry matter Crude proteins Crude lipids Crude carbohydrates Ash Crude fibre Gross energy(mj/kg) Protein/Energy (g/mj) Crude carbohydrate calculated by difference (100% - (crude protein (%) + total lipid (%) + ash (%)). 2 The content of crude fibre was estimated from known concentrations of the individual components (NRC 1993). 3 Energy calculated from nutrients assuming an energy content of 23.6 KJ/g for protein, 38.9 KJ/g for lipid and 16,7 kj/g for carbohydrate (Atienza et al. 2004). Studies with insects as feedstuffs for cultured fish are limited, though an increased research interest came out recently (Sánchez-Muros et al. 2014). St-Hilaire et al. (2007) tested the H. illucens prepupae meal as well as prepupae of the house fly (Musca domestica) in the diet of rainbow trout (Oncorhynchus mykiss) and reported that a 25% replacement of FM can be achieved, while higher inclusion levels resulted in fish growth reduction and deterioration of feed utilization. Bondari & Sheppard (1987) working with two freshwater fish species, catfish (I. punctatus) and blue tilapia (O. 112

113 aureus) reported that H. illucens can successfully replace 100% the fishmeal in diets with low fishmeal inclusion (10%). To our knowledge, the present study is the first trial of assessing the suitability of H. illucens prepupae meal in the diet of gilthead seabream. Our results suggest that an up to 30% replacement of fishmeal by H. illucens can be achieved without exerting significantly negative effects on fish growth and feed utilization by fish. The significantly higher weight gain by fish fed the FM diet is mainly due to the higher feed consumption, which is probably due to the higher palatability of FM compared to H. illucens prepupae meal. Additional experimental work is required is required so to enlighten the suitability of H. illucens as well as of other insect species as feedstuffs for cultured fish. The nutritional value of insects makes them a promising and valuable feed alternative that could replace, at least in part, fishmeal in aquafeeds. However, apart from the effect of these diets on fish growth and feed utilisation, future studies should also focus on the economic sustainability of insectbased diets, in comparison with the currently used FM. Acknowledgments The authors express their thanks to DIAS Aquaculture for provision of fingerlings, to Biomar Hellenic for provision of feedstuffs as well as to Mr. L. Papadimitropoulos for his assistance with fish culture. Table 2. Growth performance, feed utilization and body nutrient composition of S. aurata feeding on the fishmeal and fly prepupae meal based diets. FM FPM10 FPM20 FPM30 Survival (%) 80.0 ± ± ± ± 7.6 Final weight (g) ± 1.96 a ± 1.52 b ± 2.82 b ± 1.38 b Weight gain (g) ± 1.96 a ± 1.52 b 8.88 ± 2.83 b 9.53 ± 1.39 b Total consumption (g) ± 1.51 a ± 0.75 b ± 1.72 b ± 1.25 b SGR (%/δι.) 3.54 ± ± ± ± 0.18 FCR 1.12 ± ± ± ± 0.04 PER 1.98 ± ± ± ± 0.09 Protein retention (%) ± ± ± ± 2.18 Body nutrient composition Moisture ± ± ± ± 1.85 Protein ± ± ± ± 0.72 Lipid 7.34 ± ± ± ± 1.11 Values represent means ± SD (n=3 groups of all alive fish at the end of the trial). For body nutrient composition values represent means ± SD (n=9 fish). Means within a row not sharing a common superscript letter are significantly different (P<0.05). Rrows with no letters indicate that there were no significant differences. References AOAC (1995) Association of Official Analytical Chemists. Official methods of analysis of the Association of Official Analytical Chemists International, (16th edition) AOAC, Arlington, VA, USA. Bell J.G., Wagboo R. (2008). Safe and Nutritious Aquaculture Produce: Benefits and Risks of Alternative Sustainable Aquafeeds. In: Aquaculture in the Ecosystem, Holmer M., Black K., Duarte C.M., Marba N. and Karakassis I. (eds.), Springer Science + Business Media B.V., pp Bondari K., Sheppard D.C. (1987). Soldier fly Hermetia illucens L., as feed for channel catfish, Ictalurus punctatus (Rafinesque), and blue tilapia, Oreochromis aureus (Steindachner). Aquaculture and Fisheries Management 18, FAO (2014). The State of World Fisheries and Aquaculture Food and Agriculture Organization of the United Nations, Rome, 223 pp. Gatlin D.M., Barrows F.T., Brown P., Dabrowski K., Gaylord T.G., Hardy R.W., Herman E., Hu G., Krogdahl A., Nelson R., Overturf K., Rust M., Sealey W., Skonberg D., Souza E.J., Stone D., Wilson R., Wurtele E. (2007). Expanding the utilization of sustainable plant products in aquafeeds: a review. Aquaculture Research 38, Monentcham S.E, Pouomogne V., Kestemont P. (2010) Influence of dietary protein levels on growth performance and body composition of African fingerlings, Heterotis niloticus (Cuvier, 1829). Aquaculture Nutrition 16,

114 St-Hilaire S., Sheppard C., Tomberlin J.K., Irving S., Newton L., McGuire M.A., Mosley E.E., Hardy R., Sealey W. (2007). Fly prepupae as a feedstuff for rainbow trout (Oncorhynchus mykiss). Journal of the World Aquaculture Society 38, Tacon A.G.J., Metian M. (2008). Global overview on the use of fish meal and fish oil in industrially compounded aquafeeds: Trends and future prospects. Aquaculture 285, Sánchez-Muros S.M., Barroso F.G., Manzano-Agugliaro F. (2014). Insect meal as renewable source of food for animal feeding: a review. Journal of Cleaner Production 65, Bondari K., Sheppard D.C. (1981). Soldier fly larvae as feed in commercial fish production. Aquaculture 24, Sealey W.M., Gaylord T.G., Barrows F.T., Tomberlin J.K., McGuire M.A., Ross C., St-Hilaire S. (2011). Sensory analysis of rainbow trout, Oncorhynchus mykiss, fed enriched black soldier fly prepupae, Hermetia illucens. J. World Aquaculture Society 42,

115 HIGH-THROUGHPUT SEQUENCING IN AQUACULTURE: THE COMPLEXITIES OF SEX DETERMINATION IN FARMED FISH WITH SEXUAL DIMORPHISM Palaiokostas C *1, Bekaert M 1, Taggart J.B 1, Gharbi K 2, Davie A 1, Migaud H 1, Vandeputte M 3, McAndrew B.J 1, Penman D.J 1 1. Institute of Aquaculture, School of Natural Sciences, University of Stirling, Stirling FK9 4LA, Scotland, UK 2. The GenePool, University of Edinburgh, Edinburgh 3. Ifremer, Laboratoire de Recherche Piscicole en Méditerranée, Station Expérimentale d Aquaculture, Palavas Les Flots, France ABSTRACT The current study provides a review on the application of High-Throughput sequencing technologies in aquaculture, focusing on the complexities of sex determination in farmed fish with sexual dimorphism. Sex-associated Single Nucleotide Polymorphisms (SNPs) in three important farmed species, the Nile tilapia (Oreochromis niloticus), the Atlantic halibut (Hippoglossus hippoglossus) and the European sea bass (Dicentrarchus labrax) have been identified by applying Restriction-site Associated DNA sequencing (RAD-seq) and double digest Restriction-site Associated DNA sequencing (ddrad-seq). The above platforms can be used for rapid discovery of thousands of SNPs by sequencing flanking regions of restriction enzymes cleavage sites at high depth. The first SNP-based linkage maps for the above species were constructed (> 3,000 SNPs). Evidence for the location of QTLs involved in sex determination is provided. Key words: High-Throughput sequencing, QTL mapping, linkage analysis, genomic selection * Corresponding author: Christos Palaiokostas (christos.palaiokostas@stir.ac.uk) 1. Introduction High-Throughput sequencing has significantly lowered the cost of whole genome sequencing, making possible its application to a wide range of aquaculture species (Sundquist et al., 2007). Currently sequencing the human genome at 30X coverage costs approximately UK 5,000 (Davey et al., 2011). In RAD-seq the resulting reads create a reduced representation of the genome, allowing over-sequencing of the nucleotides next to restriction sites and detection of SNPs. By using a restriction enzyme of choice the number of markers can be increased multi-fold (Baird et al., 2008; Hohenhole et al., 2010). Peterson et al. (2012) elaborated on the RAD-seq platform by using a double digest (dd) with two restriction enzymes and eliminating the shearing step (ddrad-seq). This, combined with the usage of a combinatorial multiplex indexing (primers with different coding), allowed several hundred individuals to be pooled in a single sequencing lane. The aim of the current study was the analysis of the genetics of sex determination of farmed fish with sexual dimorphism, using RAD and ddrad sequencing. Three different species of farmed fish with sex-determining systems of varying complexity were studied. Both full-sibs and more distantly related specimens of Atlantic halibut (Hippoglossus hippoglossus), Nile tilapia (Oreochromis niloticus) and European sea bass (Dicentrarchus labrax) were used for this study. Males are preferred in Nile tilapia (faster growth; monosex culture prevents reproduction during ongrowing), while in Atlantic halibut and European sea bass the females are preferred due to superior growth and later maturation. 115

116 2. Materials and Methods The RAD - ddrad library preparation protocol followed essentially the methodology originally described in Baird et al. (2008) and Peterson et al. (2012). The RAD specific P1 and P2 paired-end adapters and library amplification PCR primer sequences used in this study are detailed in Baxter et al. (2011). Single Nucleotide Polymorphisms were identified from the resulting Illumina reads (Firuge 1). Three different species of farmed fish with sex-determining systems of varying complexity were studied. Both full-sibs and more distantly related specimens of Atlantic halibut (Hippoglossus hippoglossus), Nile tilapia (Oreochromis niloticus) and European sea bass (Dicentrarchus labrax) were used. Figure 1. SNP discovery from Illumina reads. 3. Results Atlantic halibut (Hippoglossus hippoglossus) A linkage map was constructed based on 5,703 Single Nucleotide Polymorphism (SNP) markers consisting of 24 linkage groups, which corresponds to the expected number of chromosomal pairs. The first evidence concerning the location of the sex-determining region of Atlantic halibut is provided in this study (linkage group 13; Palaiokostas et al. 2013a). 116

117 Nile tilapia (Oreochromis niloticus) In the case of Nile tilapia both novel sex-determining regions and fine mapping of the major sex-determining region are presented. We constructed a linkage map with 3,802 polymorphic SNP markers, which corresponded to 1,646 discrete map positions, and identified a major sex-determining region on linkage group 1 explaining nearly 96% of the phenotypic variance. This sex-determining region was mapped in a 2 cm interval, corresponding to approximately 1.2 Mb in the O. niloticus draft genome (Palaiokostas et al. 2013b). Additional QTL mapping on families with skewed sex provided evidence for a QTL in LG 20 (LOD = 4.87) being implicated in sex reversal of genotypic females (Palaiokostas et al., submitted). European sea bass (Dicentrarchus labrax) The first SNP-based linkage map for European sea bass was constructed, consisting of 5,097 SNPs grouped into 24 linkage groups. Indications for putative sex-determining QTL, significant at the genome-wide threshold, are provided in linkage groups 13, 19 and 21. Evidence concerning the absence of major sex-determining genes was provided. 4. Discussion The current study has attempted to elaborate and provide new insight into the complexities of the genetics of sex determination in three farmed fish species by using High-Throughput Sequencing. RAD-seq and ddrad-seq by combining control over the fragments that result from the digestion(s) with deep sequencing, allow the detection of reproducible SNPs in the magnitude of thousands (McCormack et al 2012). The above techniques have been successfully used in this study to map sex-determining regions in three farmed fish species. In addition the results of the current study have practical applications as well, towards the production of mono-sex stocks of those species for the aquaculture industry through MAS (Marker-Assisted Selection). Especially in farmed species with limited genomic resources, RAD-seq and ddrad-seq offer an excellent and economic way for conducting large-scale QTL studies (for sex determination or other traits) that would have been unrealistic in terms of cost for most research groups in the recent past. Acknowledgements The authors acknowledge the support of the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland), a University of Stirling PhD scholarship and a KTN BioSciences SPARK award (04054). The sea bass project was funded by INRA-IFREMER. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions. References Baird, N.A., Etter, P.D., Atwood, T.S., Currey, M.C., Shiver, A.L., Lewis, Z.A., Selker, E.U., Cresko, W.A., Johnson, E.A Rapid SNP discovery and genetic mapping using sequenced RAD markers. PloS ONE 3:e3376. Baxter SW, Davey JW, Johnston JS, Shelton AM, Heckel DG, Jiggins CD, Blaxter ML Linkage mapping and comparative genomics using next-generation RAD sequencing of a nonmodel organism. PLoS One 6: e

118 Davey, J.W., Hohenlohe, P.A., Etter, P.D., Boone, J.Q., Catchen, J.M., Blaxter, M.L Genomewide genetic marker discovery and genotyping using next-generation sequencing. Nat Rev Genet 17;12(7): McCormack JE, Hird SM, Zellmer AJ, Carstens BC, Brumfield RT Applications of nextgeneration sequencing to phylogeography and phylogenetics. Mol Phylogenet Evol 66(2): Hohenhohe, P.A., Bassham, S., Etter, P.D., Stiffler, N., Johnson, E.A., Cresko, W.A Population genomics of parallel adaptation in threespine stickleback using sequenced RAD tags. PLoS One 6:e Palaiokostas, C., Bekaert, M., Khan, M.G.Q., Taggart, J.B., Gharbi, K., MacAndrew, B.J., Penman, D.J. A novel sex-determining QTL in Nile tilapia (Oreochromis niloticus). Submitted Palaiokostas, C., Bekaert, M., Davie, A., Cowan, M.E., Oral, M., Taggart, J.B., Gharbi, K., McAndrew, B.J., Penman, D.J., Migaud, H. 2013a. Mapping the sex-determination locus in the Atlantic halibut (Hippoglossus hippoglossus) using RAD sequencing. BMC Genomics 14:556. Palaiokostas C, Bekaert M, Khan MGQ, Taggart JB, Gharbi K, et al. 2013b. Mapping and validation of the major sex-determining region in Nile tilapia (Oreochromis niloticus L.) using RAD sequencing. PLoS One 8(7): e doi: /journal.pone Peterson, B.K., Weber, J.N., Kay, E.H., Fisher, H.S., Hoekstra, H.E Double Digest RADseq: An inexpensive method for de novo SNP discovery and genotyping in model and non-model species. PloS One 7(5): e doi: /journal.pone Sundquist, A., Ronaghi, M., Tang, H., Pevzner, P., Batzoglou, S Whole-genome sequencing and assembly with high-throughput, short-read technologies. PLos One 2(5): e484. doi: /journal.pone

119 THEMATIC FIELD: ENVIRONMENTAL MANAGEMENT 119

120 ORAL PRESENTATIONS IN ENGLISH METHODOLOGICAL CONTRIBUTION TO THE FORMATION OF MARITIME SPATIAL PLANS AS A MANAGEMENT TOOL TO MINIMISE CONFLICTS BETWEEN AQUACULTURE AND OTHER COASTAL ACTIVITIES Chatziefstathiou M. 1*, Spilanis I. 1 1 Laboratory for Local & Insular Development, Department of Environment, School of the Environment, University of the Aegean, "Xenia" Building, University Hill, 81100, Mytilene, Lesvos island, Greece ABSTRACT A new EU Directive, entering into force in August 2014, establishes a framework for maritime spatial planning, aimed at promoting the sustainable growth of maritime economies, the sustainable development of marine areas and the sustainable use of marine resources, using an ecosystem based approach. To implement this EU policy and use MSPs as management tools there is a need for practically applicable models and frameworks that can help decision makers and administration to design robust plans for coastal activities, especially in islands, and direct limited financial resources towards these activities where expected returns are the greatest. The method described here allows the estimation of sustainability level in an area and the footprint of the activities (driving forces) in this area, especially for marine fish farming in islands. For the purposes of the method developed (based on UNEP s DPSR), the evaluation of the activities examines the performance per production unit, that relates to the added value, the employment created at the area, water use, energy use, waste production, and, the scale of the examined human activity compared to the carrying capacity of the host area. Then a priority-setting method gives as results analytically rigorous and well-structured decisions. With the assessment of the contribution of each human activity we can propose appropriate policies for the sustainable development of an area and discover the best sites to establish an activity and to minimise any possible conflicts between them (marine aquaculture here), and existing and future users of the area. Keywords: sustainable development, maritime spatial planning, blue growth, conflicts, marine aquaculture * Corresponding author: Chatziefstathiou Michael (mhatzi@env.aegean.gr) 1. Introduction The high and rapidly increasing demand for maritime space for different purposes, as well as the multiple pressures on coastal resources, require an integrated planning and management approach. Such an approach has been developed in the Integrated Maritime Policy for the European Union (IMP). The objective of the IMP is to support the sustainable development of seas and oceans and to develop coordinated, coherent and transparent decision making in relation to the Union's sectoral policies affecting the oceans, seas, islands, coastal and outermost regions and maritime sectors, including through sea basin strategies or macro-regional strategies, whilst achieving good environmental status as set out in Directive 2008/56/EC. 120

121 Blue Growth is the contribution of the EU s Integrated Maritime Policy to achieving the goals of the Europe 2020 strategy for smart, sustainable and inclusive growth, and has identified five (5) specific areas with a particular potential for growth where targeted action could provide an additional stimulus: maritime, coastal and cruise tourism, blue energy, marine mineral resources, aquaculture, and, blue biotechnology. The IMP identifies maritime spatial planning as a crosscutting policy tool enabling public authorities and stakeholders to apply a coordinated, integrated and transboundary approach. The application of an ecosystem-based approach will contribute to promoting the sustainable development and growth of the maritime and coastal economies and the sustainable use of marine and coastal resources (Chatziefstathiou & Spilanis, 2013). Maritime spatial planning, which remains a prerogative of individual EU countries, is about planning and regulating all human uses of the sea, while protecting marine ecosystems. The relevant EU Directive after a discussion that lasted more than one year was agreed at COREPER of 15th of July 2014 and then adopted by the Council of Ministers for General Affairs at 23rd of July 2014, and establishes a framework aimed to balance frequently competing sector-based interests so that i) Marine space and resources are used efficiently and sustainable, ii) Decisions can be taken based on sound data and in-depth knowledge of the sea, iii) Investors have greater legal certainty, encouraging economic development. There is fierce competition for marine space and the interests of different users need to be taken into account. For example, an offshore wind farm could hamper navigation or fishing, unless its location is well planned. This approach will also allow an adaptive management, which ensures refinement and further development as experience and knowledge increase, taking into account the availability of data and information at sea basin level to implement that approach. However, plans for shared seas should be compatible to avoid conflicts and support crossborder cooperation and investments. Common principles agreed at EU level can ensure that national, regional and local maritime spatial plans are coherent. An effective spatial planning is an essential condition in order to guarantee a long-lasting development without depleting the sea and therefore ensuring a sustainable use of marine resources for future generations. The issue is particularly important today, because the European Commission is launching the Action Plan for the Adriatic and Ionian macro-region (EUSAIR), which will contribute to the definition of the development strategies of the region and to the destination of resources and projects. The Council Conclusions at the end of the Greek Presidency of the Council of the EU (January June 2014) on the Integrated Maritime Policy and its achievements and future developments of the Maritime Agenda for Growth and Jobs stressed that an innovative and dynamic agenda for maritime affairs can unlock the sustainable growth and job-creating potential of the blue economy and contribute to Europe s economic recovery, while Blue Growth and the integrated approach to maritime affairs can maximise the sustainable use of seas and coasts, ensuring at the same time the health of their ecosystems. The agreement of the co-legislators on a Directive for Maritime Spatial Planning, will provide legal certainty for maritime investments and help manage the cumulative impacts of maritime activities on the environment, activities that can be an essential source of innovation, sustainable growth and employment for European regions. The sustainable growth of coastal and maritime tourism, Europe s largest maritime activity, is essential to the wealth and well-being of coastal and insular regions and Europe s economy, as well as the role of sustainable aquaculture in meeting the EU demand for seafood while reducing pressure on wild fish stocks. Usually not all the desired or available activities can assigned in a given area and a spatial plan must prioritise them and assign these that have the maximum contribution to the sustainable development of this area. Priority-setting task always involves trade-offs due to political, social, cultural, financial, legal & technological constraints. In multi-stakeholder and multi-objective settings the decision-making process is complex. The task is often made harder by incomplete or inaccurate 121

122 datasets. Decision makers will aim to adopt a procedure that is analytically robust, auditable, transparent and understandable (Chatziefstathiou & Spilanis, 2006). This method, developed by the Laboratory for Local & Insular Development (University of the Aegean, Department of Environment), allows the estimation of sustainability level in a given region (the islands) and the footprint of the activities (driving forces) in this area. The method has been adapted to measure the contribution of marine fish farming to sustainable development of a region (Aegean sea islands), letting us to proceed to faster implementation of Blue Growth initiative in Greece. The sustainability analysis calls for consensual setting of a "band of equilibrium" for a list of indicators making possible to evaluate the sustainability of present situation in the target region and to determine what is desirable and what is unacceptable (Spilanis et al., 2005). 2. Materials and Methods For the purposes of the method developed (based on UNEP s DPSR), evaluation of activities is based on two (2) steps: i) performance per production unit, relating to added value, employment created at the area, water use, energy use, waste production, etc, and, ii) scale of the examined human activity compared to carrying capacity of the host area. In this method, the sustainable development (SD) considered a continuous process leading simultaneously to improvement of economic, social, and environmental goals adopted by each local society (this approach is shown graphically beside). To measure the performance, and, locate and record factors & parameters that affect performance (economic, social, environmental) of the marine fish farms that operates on the Aegean sea islands, and the role of each one of these to their sustainability, research has been made with structured questionnaires at the total number of fish farms of Aegean sea that use floating cages (Chatziefstathiou et al, 2006). The questionnaire had a set of questions about the value of the proposed indicators and also on the factors that affect the performance and the sustainability of each installation separately - and not the company or group of companies in total - so, if the company had more fish farms in the study area (islands of Aegean sea) they had to complete one questionnaire for each one site. Totally, 31 questionnaires were sent by fax and to farms and finally 20 from them were answered. These 20 questionnaires relate to 80% of the fish farms at Aegean Sea and cover more than 90% of production. Performance measured for all 3 dimensions of sustainable development: Economic, where the annual turnover per tonne of product (or per fry) is the critical index, Social, which takes into account the employment created (quantitative, number of employees, duration, wages) and qualitative characteristics (education level, gender, ethnicity), Environmental, where the per tonne (or per fry) resource consumption and waste generation, and the permanent change (deterioration) of the environment caused by infrastructure and facilities, are the parameters to be considered. The measurement uses in total 33 indicators for the 3 dimensions of sustainable development, spilt to 6 indicators for the economic (F1 - F6), to 9 indicators for the social (S1 - S9) and to 18 indicators for the environmental (E1 - E18) dimension of sustainability (Chatziefstathiou et al, 2006, 2012). 122

123 3. Results and Discussion The quantitative and qualitative analysis of the answers gave us meaningful results, which are briefly presented here by the following two (2) graphs (Graph of the Performance of Each Assessed Aegean Fish Farm, and, Graph of the Total Performance of the Aegean Fish Farms), showing that we have two different group of farms, the one with relatively worst socio-economic status, but their total performance considered satisfactory. (Chatziefstathiou et al, 2012). Having these data as a starting point we can repeat the survey after a period of time and estimate if their development drives them to a more sustainable status. Our initial research determined that 14 factors should be measured when the Status (State) of an island region is estimated. These measured with different indicators, from which 9 indicators give the state of economy, 11 indicators state of society, and 19 indicators the state of the environment. These indicators were supplemented with a more specialised series of indicators for use to productive aquatic ecosystems. According to the applied theory, the evaluation of any human activity (Pressure) can be based on two criteria: 1) Performance per unit of production, linked to economic performance (value added), employment generated per unit, and the environmental burden (e.g. water consumption, energy, waste generation per unit), 2) Scale of activity compared with the carrying capacity of the area. Marine aquaculture as a competitor for the same limited resources should be judged on the basis of the efficiency of resource utilize, as well as the environmental compatibility, as it has today an important role to play in rural development and in reversing decline in fishing communities (Burbridge et al., 2001). Common criteria should be used for evaluating all economic activities, and to include socioeconomic and environmental costs & benefits is a must. Our research concluded with the selection of indicators for better measurement of the impact of marine fish farms, supplementing and adjusting the existing ETNA s methodology (Spilanis et al, 2005; Chatziefstathiou et al, 2006). The 2 additional environmental indicators cover the case in which at the study area there is activities that are taking place in marine environment: a) Π20 - Recording appearance of alien species, cultivation or farming of alien species, helps to estimate the pressure on marine ecosystems (e.g. from lessepsian immigrants), and the threat that consists human activities for the biodiversity, by type of ecosystem, and for the different ecosystems of the island, and, b) Π21 - quality of marine waters (marine environment), helps to estimate the quality of marine waters, which is particularly important in the case of marine fish farming, since it is the environment in which the production takes place, and is highly influenced by them, while at the same time the farms influence them back. According to the MSP Directive Member States shall take into consideration relevant interactions of activities and uses. Possible activities and uses and interests may include aquaculture areas, fishing areas, installations and infrastructures for the exploration-exploitation-extraction of oil, of gas and other energy resources, of minerals and aggregates, and for the production of energy from renewable sources, maritime transport routes and traffic flows, military training areas, nature and species 123

124 conservation sites and protected areas, raw material extraction areas, scientific research, submarine cable & pipeline routes, tourism, and, underwater cultural heritage. Also, mentioned that: <<(19) The main purpose of maritime spatial planning is to promote sustainable development and to identify the utilisation of maritime space for different sea uses as well as to manage spatial uses and conflicts in marine areas. Maritime spatial planning also aims at identifying and encouraging multipurpose uses, in accordance with the relevant national policies and legislation. In order to achieve that purpose, Member States need at least to ensure that the planning process or processes result in a comprehensive planning identifying the different uses of maritime space and taking into consideration long-term changes due to climate change.>>, and for that reason states: <<(24) With a view to ensuring that maritime spatial plans are based on reliable data and to avoid additional administrative burdens, it is essential that Member States make use of the best available data and information by encouraging the relevant stakeholders to share information and by making use of existing instruments and tools for data collection, such as those developed in the context of Marine Knowledge 2020 initiative and Directive 2007/2/EC of the European Parliament and of the Council.>>. With our research a simple system is proposed that can monitor the progress of each local society by calculating a number of indicators that can measure the state (S) and its change over time as pressure (P) comes from mariculture (DF). This approach reflects the fact that SD has a different content for different societies and comparisons can be misleading (Katranidis et al., 2003). Advantage of this approach is that compares similar states of sustainability for the same society and yields meaningful results (Chatziefstathiou et al., 2006). Resources constraint is one of the major causes for conflicts between existing and future users of an area, especially in the island regions, where the eligible areas for new development are limited. For that reasons it is need to introduce a requirement for priority setting, which can be defined as the task of selecting a subset of issues, policies or projects towards which limited resources will be directed. The priority-setting task always involves trade-offs due to political, social, cultural, financial, legal and technological constraints. The outcome of a priority-setting task can be the ranking or scoring of each option s performance, or it can be the allocation of a fixed resource, often money, amongst the alternative options. The ATS model (Hajkowicz & McDonald, 2006) emerged from the need to ensure environmental priority-setting decisions were analytically rigorous and well structured. Its primarily role is to guide the selection and weighting of evaluative criteria. Under the ATS model, shown graphically below, environmental problems related to highly valued assets (asset value) causing a large amount of damage (threat) but easily fixed (solvability) would be considered high priority. Investment in these problems is likely to deliver greater public benefit and have the minimum conflicts. Conversely, problem acting on low value asset, with low severity and hard or expensive to solve would be low priority. In our work we enhance ATS model (e-ats) to include economic and social issues (Chatziefstathiou & Spilanis, 2006). Adopting its principles involves a rational approach to decisionmaking as opposed to an informal, unstructured or an intuitive approach. The main contribution of this enhanced ATS model is to provide a robust analytical structure for decision-making. This structure sets a solid foundation for handling intangible issues requiring human judgement, which arise in the majority of significant priority-setting decisions. Major advantage of this model is the structure of the methodology introduced to the debate. Using ATS people could debate threat and asset issues and 124

125 provide insights. Group clarification about the nature of different threats can lead to revisions. ATS model adopted because shares much in common with the pressure state response (PSR) framework, which is near to our method for measuring the sustainability, based to the DPSR framework. When faced with a complex assemblage of data, managers can apply the model we develop to help them select criteria for priority setting in a structured manner. Quality of judgements on which projects or locations receive investment, and therefore which do not, will partly dictate the success or failure of policy. Another key factor determining success is the ability to implement the projects once selected. There is a need for practically applicable models and guidelines that can help decision makers resolve trade-offs and direct limited resources towards projects or regions where the expected returns are greatest. Priorities are dependent on people s preferences. Feedback from decision makers can provide some insights but invariably carries bias. The decision procedure may have worked well, but if it did not select a decision maker s un-stated preferences it may be evaluated poorly. Different concepts of decision procedure apply to different fields of decision-making, e.g. financial, environmental, and social. Hereafter we can identify some basic principles (Hajkowicz & McDonald, 2006). A sound decision procedure should be: a) Transparent. The reasons behind a particular decision should be clear to all interested parties. This will require explicit statement of assumptions, data and value preferences. b) Repeatable. With the same assumptions, input data and value preferences the decision procedure should always yield an identical, or at least similar, result regardless of who applies it and when. c) Involve comprehensive use of information. It should not be possible to identify additional information that could have been used at low cost and within reasonable time frames. d) Consistent with the decision maker s preferences. The decision maker will invariably have preferences for some decision objectives over others. The procedure should reflect these preferences in its final selection of options. e) Consistent with social, moral and legal obligations. Decisions are never made in a policy, legal or social vacuum. There will generally exist social norms, standards and legal obligations that set additional constraints around the selection of actions (Hajkowicz & McDonald, 2006; Chatziefstathiou & Spilanis, 2006). Meeting these requirements does not necessarily guarantee a good decision outcome. However, there would be an expectation that decisions performing well on these criteria will typically lead to better outcomes than others. Analysts developing decision procedures can use the requirements of procedural rationality to design appropriate policy frameworks and tools and to minimise conflicts and negative local reactions. The initial ATS model has been developed with this purpose - it aims to improve procedural rationality. If applied appropriately, the structured approach to setting priorities in e-ats model will improve the procedural rationality of decisions. The system of measurement is relatively simple, relying mainly on published or easily accessible data, and this method could be used as tool capable in determining also the inappropriate sites for projects in areas that initially had been considered suitable for development. Monitoring practices will ensure that the established activities will not lead in dew time to deviation from the sustainability s targets, and at the end of each policy period evaluation practices will determine whether the overall state of the Sustainable Development of the area had been improved (Chatziefstathiou & Spilanis, 2012). To diversify the activities we can proper assess the contribution of each activity and select the most desirables. In the case that this is aquaculture, we can propose the policy on which we must continue examine the possibility of establishing new or expanding existing farms, in a way that will support the sustainable development of the given area (Chatziefstathiou & Spilanis, 2013). References Burbridge P., Hendrick V., Roth E., Rosenthal H. (2001): Social and economic policy issues relevant to marine aquaculture. Journal of Applied Ichthyology, 17 (2001),

126 Chatziefstathiou M., Spilanis I. (2006). Combining a Method for Evaluating the Contribution of Human Activities to the Sustainable Development of Islands and a Priority-setting Method to Examine If and Where can Aquaculture Established in a Given Island. AquaMedit 2006, 3rd International Congress on Aquaculture, Fisheries Technology & Environmental Management, November 2006, GR. Chatziefstathiou M., Spilanis I. (2013). Towards the Implementation of European Union's new Integrated Maritime Policy in Greece: Blue Growth through Marine Aquaculture for the Sustainable Development of the Islands. 6th "Water & Fish" International Conference, June, University of Belgrade, Faculty of Agriculture, Belgrade, Serbia. Chatziefstathiou M., Spilanis I., Koutsoubas D., Klaoudatos S. (2012). Assessment of the Contribution of Marine Aquaculture to the Sustainable Development of Island Regions. AQUA Securing Our Future. 1-5 September, Prague, Czech Republic. Chatziefstathiou M., Spilanis I., Vayanni H. (2006): Developing a Method to Evaluate the Contribution of Different Human Activities to the Sustainable Development of Islands: Case Study on Marine Aquaculture. Sustainable Management and Development of Mountainous & Island Areas. International Conference. 29/9/2006-1/10/2006, Naxos Hajkowicz S., McDonald G. (2006). The Assets, Threats & Solvability (ATS) Model for Setting Environmental Priorities. Journal of Environmental Policy & Planning, Vol. 8, No. 1, March 2006, Katranidis S., Nitsi E., Vakrou A. (2003): Social Acceptability of Aquaculture Development in Coastal Areas: The Case of two Greek Islands. Coastal Management, 31: Spilanis I., Kizos T., Kondili J., Koulouri M., Vakoufaris H. (2005): Sustainability measurement in islands: The case of South Aegean islands, Greece. International Conference on Biodiversity Conservation & Sustainable Development in Mountain Areas of Europe, Ioannina, 20-24/9/05 126

127 ASSESSMENT OF CONSECUTIVE PLANKTON BLOOMS ON MARCH AND APRIL 2014 IN IZMIT BAY (THE MARMARA SEA) Ergül, H. A. 1*,Aksan, S. 1,Ipsiroglu, M. 1, Baysal, A. 2 1 Department of Biology, Science and Arts Faculty, Kocaeli University, 41380, Kocaeli, Turkey 2 Department of Biology, Science and Arts Faculty, Kafkas University, 36100, Kars, Turkey ABSTRACT: Results of the field experiments regarding to the consecutive plankton blooms which were observed through end of March to middle of April, 2014 in Izmit Bay (the Marmara Sea) are presented. The first sampling carried out on March 31, 2014 while the second one was realized on 14 April, Water samples were taken from a station on the North coast of the bay. Nitrite (NO 2 ), Nitrate (NO 3 ), Ammonia (NH 3 ), Silica (SiO 2 ) and Orthophosphate (o-po 4 ) analysis were done via spectrophotometrical methods. Plankton quantifying were done via Nageotte counting chamber using inverted and light microscopes. In the first bloom Prorcentrum micans was the unique species (i.e., 10,770,000 individual/l) while in the second one, Noctiluca scintillans was dominant (i.e., 55.6%, 620,000 individual/l) among 7 different species. Based on the results it is thought that nitrogen and phosphorus increasing triggered excessive plankton abundance while sufficient amount silica already presented. Plankton abundance generally increased from West to East direction on the Northern coast of the bay. Untreated wastewater inputs and current regime can be responsible for the blooms of plankton and their distributions in Izmit Bay. Key words: Red-tide, Plankton bloom, Izmit Bay, Marmara Sea, Nutrient * Corresponding author: Halim Aytekin Ergül (halim.ergul@kocaeli.edu.tr, halim.ergul@gmail.com) 1. Introduction Izmit Bay is a semi-enclosed coastal ecosystem located in the most industrialized area of the Marmara region. There are 1.5 million inhabitants living in Kocaeli Province surrounding Izmit Bay. Industrial activities have been increasing rapidly since the 1980s around the bay and it receives a considerable amount of domestic and industrial discharge from its drainage basin. It is reported that Izmit Bay which is a part of the Marmara Sea, seriously affected by eutrophication (Morkoç et al., 2001; Okay et al., 2001) and recently a plankton bloom occurred in the region (Ergül et al., 2010). In this study, it was aimed to report two consecutive plankton blooms accompanied with mucilage formation in March and April 2014 from Izmit Bay. Figure 1. Map of Izmit Bay and sampling station 2. Material and Methods Water samples were taken from 50 cm below the surface of Northern-East coast of Izmit Bay on March 31, 2014 and April 14, 2014 (Figure 1). Samples were put into amber glass bottles and kept cool for immediate transportation to the laboratory. Half of the sample was filtered and used for Nitrite (NO 2 ), Nitrate (NO 3 ), Ammonia (NH 3 ), Silica (SiO 2 ) and Orthophosphate (o-po 4 ) analysis via spectrophotometrical methods while other half was used for plankton identification. 10 ml Hydrobios 127

128 plankton chamber were used for pre-identification under an inverted microscope while plankton were alive. Then samples were fixed using 4% formaldehyde solution for better identification and quantifying. Before counting procedure, the samples were centrifuged at 800 rpm for 15 minutes, supernatant were removed and residues were used for quantifying via Nageotte counting chamber under a light microscope. Results were given as individual per liter. 3. Results and Discussion At the end of March 2014 Izmit Bay suffered from algal bloom. Brownish-red appearance was observed in the surface water of the bay during a week from March 31. Algal bloom formation was concentrated on the Northern-East coast of the bay. Almost a week later, strong winds and heavy rain dissipated algal bloom formation. On April 14 a second algal bloom with its pale red appearance, formed in the same area. Prorocentrum micans (i.e., 10,778,000 individual/l) was the unique responsible species of the red-tide on March 31, 2014 in Izmit Bay. In this bloom mucilage formation which covers the surface water of the bay somewhere, was observed. However, low density second algal bloom on April 14 was formed by 7 different dominant species. The most abundant species of this bloom was Noctiluca scintillans (i.e., 55.6 %; 620,000 individual/l). Plankton abundances and their distributions among species were given for both blooms in Table 1 and Figure 2. Table 1. Plankton species distributions and abundance in the surface water of Izmit Bay on March 31 and April 14, 2004 Species 31/03/ /04/2014 (Individual/L) Noctiluca scintillans - 620,000 Prorocentrum micans 10,778, ,000 Prorocentrum scutellum - 80,000 Dictyoctha speculum - 100,000 Licmophora abbreviata - 2,000 Rhizosolenia setigera - 1,000 Rhizosolenia hebetata - 3,000 NO 2 -N, NO 3 -N, NH 3 -N, SiO 2 and o-po 4 -P concentrations of the samples were given in Table 2 and Figure 3. Measured values represent relatively increased nitrite, ammonia and reactive phosphate concentrations in the second bloom. It should be noted that plankton diversity was higher in second bloom than the first one. Figure 2. Interpolated maps of plankton distributions a) in the first (March 31, 2014) and b) in the second bloom (April 14, 2014) in Izmit Bay. In the first bloom Prorcentrum micans was the unique species, while in the second one, Noctiluca scintillans was dominant. These maps were plotted based on surface water observations throughout the bay. 128

129 Table 2. NO 2 -N, NO 3 -N, NH 3 -N, SiO 2 and o-po 4 -P concentrations and standard deviations in surface water samples from Northern-East coast of Izmit Bay on March 31 and April 14, 2004 Parameter (mg/l) NO 2 -N 0.03 ± ± NO 3 -N 0.03 ± ± NH 3 -N 4.76 ± ± o-po 4 -P 5.60 ± ± 2,010 Silica 0.83 ± ± Si/N NO 3 /DIN In terms of Si/N ratio, diatom growth is limited by dissolved silica when the ratio is less than 1 in marine waters (Redfield et al., 1963). Although, much lower Si/N values (i.e., 0.17 on March 31 and 0.10 on April 14, 2014) were determined in both blooms, relatively higher SiO 2 concentrations were also measured (Table 2). Based on these results it is thought that increase in both nitrogen and phosphorus, triggered excessive plankton abundance while sufficient amount silica has already presented in the bay. Since NH 3 concentrations were relatively high, low NO 3 /DIN (dissolved inorganic nitrogen) ratios were calculated. Comparison with a previous study (Aktan et al., 2005) showed that total nitrogen and o-po 4 concentrations significantly increased in the present study (i.e., 15 and 1018 folds respectively). In another study (Ergül et al., 2010), which reported red-tide in the Izmit Bay, lower o-po 4 concentrations were determined (i.e., 0.6 mg/l). On the other hand, in the same study, 55 x 10 8 individual/l P. micans was reported from the surface water of Izmit Bay. 129

130 individual/l 14x a 6 mg/l 0.09 b mg/l c d 12x x x x x x Total plankton 0 NO 2 -N NO 3 -N 0.00 PO 4 -P SiO 2 NH 3 -N NO 3/DIN NO3/DIN Figure 3. a: Total plankton abundance b: Nitrite and nitrate concentrations c: Orthophosphate, silica and ammonia concentrations and standard deviations d: NO 3 /DIN ratio in the water from Northern-East coast of Izmit Bay on March 31 and April 14, 2004 Plankton abundance generally increased from West to East direction on the Northern coast of the bay (Figure 2). It is known that current velocities in Izmit Bay decreases from West to East (Balkis, 2003) and treated or untreated wastewaters were mainly discharged from North coast of the bay (Ergül et al., 2013). Thus, it is thought that untreated wastewater inputs and current regime can be responsible for the plankton blooms and their distributions in Izmit Bay. Acknowledgements This study was funded by the Kocaeli University Scientific Research Projects Unit (Grant No: KOU- BAPB 2009/040). The authors wish thank to Mr. Burhan Özkara for his help during sampling. 130

131 References Aktan, Y., Tüfekçi, V., Tüfekçi, H., Aykulu, G., Distribution patterns, biomass estimates and diversity of phytoplankton in İzmit Bay (Turkey). Estuarine, Coastal and Shelf Science 64, Balkis, N., The effect of Marmara (Izmit) Earthquake on the chemical oceanography of Izmit Bay, Turkey. Marine Pollution Bulletin 46, Ergül, H.A., Belivermiş, M., Kılıç, Ö., Topcuoğlu, S., Çotuk, Y., Natural and artificial radionuclide activity concentrations in surface sediments of Izmit Bay, Turkey. J. Environ. Radioact. 126, Ergül, H.A., Küçük, A., Terzi, M., A Study on the Red Tide of Izmit Bay-June 2010, in: Ozturk, B. (Ed.), Marmara Denizi 2010, Istanbul, pp Morkoç, E., Okay, O.S., Tolun, L., Tüfekçi, V., Tüfekçi, H., Legoviç, T., Towards a clean İzmit Bay. Environment International 26, Okay, O.S., Tolun, L., Telli-Karakoc, F., Tufekci, V., Tufekci, H., Morkoc, E., Izmit Bay (Turkey) ecosystem after Marmara earthquake and subseqnent refinery fire: the long-term data. Marine Pollution Bulletin 42, Redfield, A.C., Ketchum, B.H., Richards, F.A., The influence of organisms on the composition of seawater, in: Hill, M.N. (Ed.), The Sea, 2. John Wiley & Sons, New York, pp

132 THE COMPREHENSIVE CHARACTERISTIC OF POPULATION PARAMETERS OF HIGH BODY PICKAREL Spicara flexuosa FROM DIFFERENT BAYS IN COASTAL AREA OF SEVASTOPOL (BLACK SEA) Kuzminova N. S. Department of ichthyology, Institute of Biology of the Southern Seas, , Nakhimov av. 2, Sevastopol, Russia ABSTRACT The complex state of mass specie of Black Sea fish, high body pickarel Spicara flexuosa catched in bays with different level and character of pollution was studied. Population (size and weight) and morphophysiological (hepatosomatic, gonadosomatic indexes) characteristics of fish were higher in cleaner waters Karantinnaya and Balaklavskaya bays. Key words: pollution, Black Sea fish, high body pickarel *Corresponding author: Kuzminova Natalya 1. Introduction In the past decade, scientific information on the status of the Black Sea waters and their inhabitants is very contradictory. In this regard, it is interesting and necessary to investigate the state of one of the last links of the food chain fish- for a long period. The main part of fish in the Black Sea coastal catches is presented by red mullet, horse mackerel, scorpion fish and high body pickerel (Oven et al., 2008; data of Sevastopol inspection of protection and reproduction of fish stocks and the fishing regulation). The first two species are commercial. High body pickerel is secondary food-fish which means that it contributes little to natural resources depletion; it is caught together with herring, anchovy (Probatov & Moskvin, 1940). Recently horse mackerel, red mullet and high body pickarel accounts 9 to 15%, 27 to 42% and 6,9 to 16,7% respectively of all the species in catches in the bottom snares installed by Institute of Biology of the Southern Seas. High body pickarel - mass specie of coastal areas of the Black and Mediterranean Seas, eastern site of the Atlantic Ocean, desalted waters of the lower reaches of rivers are not frequented by this specie. It matures at a young age, but spawning as a whole is typical for 3-4 years old creatures. Spawning takes place in the coastal zones of the Black Sea: coast of the Crimea, the Caucasus, Bulgaria and Romania. Eggs are spawned on the algae and bottom. Fecundity of fish of 8-16 cm long is from 6075 to eggs. Distinctive characteristics of S. flexuosa are protoginia and sexual dimorphism. High body pickarel in the Black Sea mainly feeds on small coastal planktonic and benthic invertebrates (polychaetes, molluscs), algae, some small fish and fish eggs. In the Mediterranean Sea it feeds mainly crustaceans and their larvae, sometimes sponges, shellfish larvae, rarely foraminifera. The longevity of females is much shorter than that of males (Probatov & Moskvin, 1940; Svetovidov, 1964; Salekhova, 1979; Oven et al., 2000). The aim of this paper is to monitor the modern state of high body pickarel Spicara flexuosa Rafinesque caught in Sevastopol bays with different levels of pollution; hence two purposes of research we have put: to analyze the size-mass and morphophysiological parameters of fish in the period Materials and methods The object of study high body pickarel Spicara flexuosa Rafinesque, caught from 2008 to 2012 by means of gillnets installed in bays of Sevastopol: Balaclavskaya bay (N=209), Karantinnaya bay (N=654), Alexandrovskaya bay (N=270) (Figure 1). Such parameters as size of fish (total length, the fork length and standard length SL), the mass of fish and the weight of the fish without viscera, liver, gonads, spleen were measured and analysed. Sex and stage of maturity were also registered. Age was determined using scales structure. The index of the liver (hepatosomatic index HSI), the spleen index (SI), gonadosomatic index (GSI) and the condition factor were calculated based on the weight of the fish without viscera. 132

133 Results of investigation were calculated statistically and presented as M±SEM; significant differences were determined using t-criteria of Stʹ-udent. Data mentioned above point to the improvement of the state of the environment as well as Black Sea biota. Nevertheless, differences in the level of contamination of some bays in the coastal area of Sevastopol are still observed. On the basis of research data (Alemov, 2010; Boltachev & Karpova, 2012; Eremeev et al., 2008; Kopitov et al., 2010; Kovrigina & Popov, 2006; Kuftarkova, 2006; Lomakin & Popov, 2011; Makarov et al., 2010; Popov et al., 2010; Revkov et al., 2000; Timofeev et al., 2009) it can be concluded that Alexandrovskaya bay is the most polluted, Karantinnaya bay - less polluted area and the place in Balaklavskaya bay where the fishing gear were installed - the cleanest point investigated taking into account the temporary spreading of different chemicals in this zone. 3. Results and discussion It was showed that in most cases there were not significant differences in the values of the size and weight of the females from three bays. Males caught in Balaklavskaya bay were larger (especially in weight) in years old (Table 1). Earlier, on the basis of the results of the analysis of the size-weight characteristics of high body pickarel from Karantinnaya, Alexandrovskaya, Strelezkaya and Kazachya bays the differences between these parameters of fish from different zones were not found (Kuzminova et al., 2010). The explanation for this fact lies in high moving activity and migration of S. flexuosa (Salekhova, 1979). HSI for females in age from 0+ to 4 years old was lower for individuals from Alexandrovskaya bay. HSI of males of older age groups had the maximum value for fish from Balaklavskaya bay and the minimum - for fish from Karantinnaya bay. During the annual cycle the values of GSI of males and females, on the contrary, in most cases, were high for high body pickarel from Karantinnaya and Balaklavskaya bays. The values of condition factor were similar for same age individuals from three bays. Our recent research into changes of many years in the basic population parameters of horse mackerel, high body pickarel, red mullet and peacock wrasse showed improvement in their condition (Oven et al., 2009, 2010; Kuzminova, 2011a, b; Kuzminova et al., 2011). This tendency is clearly observed for young Black Sea fish, in particular, horse mackerel and red mullet (Kuzminova, 2012). However, differences for demersal fish and benthic group are still registered in size and weight, age and sex composition of the fish that live in the coves with different levels of pollution. Reduction in size and weight, the proportion of males and individuals of older age groups noted for shore rockling, scorpion fish in recent years (Kuzminova & Skuratovskaya, 2008, 2011). By comparing length and weight of high body pickarel in it was found that the average values of these parameters were in most cases much lower than those for fish inhabiting in the Black Sea during the last century (Salekhova, 1979; Oven et al., 2000), which is indicative of a negative lasting anthropogenic effect on the coastal waters of the Black Sea and its inhabitants. Only weight of males of S. flexuosa in the modern period has been close to or even higher than values obtained in 1971 and , 1998 (Salekhova, 1979; Oven et al., 2000). In most cases HSI was higher for females from Karantinnaya bay, which, in addition to the information we received about the high values of the index of spleen for fish from this bay (Kuzminova, 2012 b), is indicative of more favorable conditions for fish in their habitat. For males, this parameter was low for fish aged years from different bays, but for older individuals was high for fish from the Balaclavskaya bay (Table 1). It is interesting to note, that exactly SI of the older age groups of the bay was also high (Kuzminova, 2012b). This can be explained not only by the best habitat conditions, but also by a high adaptive capacity of this species to pollution. The latter increases with age and maybe related to the sex changes, which is characteristic of the species. The reaction of bottom Black Sea fish, which is also indicative of adaptation processes, is always of a certain type: HSI increases and SI decreases, and the differences for fish inhabiting bays with different level of pollution are more clearly noticeable with age (Kuzminova & Skuratovskaya, 2008, 2011). The greatest values of GSI of females and males were for S.flexuosa from Balaklavskaya and Karantinnaya bays (Table 1), that together with other ichthyological parameters of population shows better conditions of putting on flesh. We have previously shown that there were not changes of GSI values for high body pickarel (both females and males) in the spawing-free period in the years between 2002 to Moreover, the values of GSI of this fish which is on the II stage of maturity in the modern period are close to those for fish captured in the Black Sea in (Kuzminova, 2011). This can be partly due to the fact that the gonads are detoxification products of oxidative stress 133

134 also: the values of the most of antioxidant enzymes activity in the sexual organs of Black Sea fish in the 2000s were more than 2 times as high as those indices in 1990s. This is the result of adaptation to the existence conditions in the contaminated environment for a long period, which makes normal development of sexual products and the ability of reproduction possible (Rudneva & Kuzʹ-minova, 2011). 4. Conclusion On the basis of complex data obtained it can be concluded that the main population and morphophysiological characteristics of high body pickarel were higher in more cleaner waters Karantinnaya and Balaklavskaya bays. References Alemov S.V. (2010). Long-term changes of macrozoobenthos of Balaklavskaya bay. Scientific notes of Ternopol national unіversity of V. Gnatiuk name. Serіes of Biology. Special issue: Hydroecology 3 (44), 6 9 [in Russian]. Boltachev A.R., Karpova E.P. (2012). The species composition of icthyofauna of the coastal area of Sevastopol. Marine ecological journal 2 (11), [in Russian]. Eremeev V.N., Mironov O.G., Alemov S.V., Burdiyan N.V., Shadrina T.V., Tikhonova E.A., Volkov N.G., Istomina M.I. (2008). Preliminary results of the assessment of oil pollution of the Kerch strait after the ships accident in 11 of November of Marine ecologіcal journal 3 (7), [in Russian]. Kovrigina N.P., Popov M.A. (2006). The dynamic of hydro-chemical indexes and thermohaline characteristics of the waters of Balaklavskaya bay. In: Abstracts of reports international of intern. conf., dedicated to 135th anniversary of the IBSS «Problems of biological oceanography of the XXI century». Sevastopol, Ukraine, рр. 97 [in Russian]. Kopitov Y.P., Minkina N.I., Samyshev E.Z. (2010). The level of contamination of water and sediments of Sevastopol Bay (the Black Sea). In: Control systems of environment: Scientific works. Sevastopol. National Academy of Sciences of Ukraine, Marine Hydrophysical Institute, pp [in Russian]. Kuzminova N.S., Lebed D.A., Zav'yalov A.V. (2010). Population, morphophysiological and biochemical parameters of high body pickerel Spicara flexuosa (Rafinesque) in the modern period. In: Materials of V Intern. scient.-pract. conf. «Man and Animals». Astrakhan. pp [in Russian]. Kuzminova N.S., Skuratovskaya E.N. (2008). Sex and age- features of stability of marine scorpion fish Scorpaena porcus L. in relation to anthropogenic factor. In: Control systems of environment. Tools, information technologies and monitoring: Scientific works. Sevastopol. National Academy of Sciences of Ukraine, Marine Hydrophysical Institute, pp [in Russian]. Kuzminova N.S. (2011 a). Population characteristics of Black Sea horse mackerel in the modern period. In: Scientific papers devoted 90th anniversary of the Novorossiysk Marine Biological Station of prof. V.M. Arnoldi name «The state of the shelf of Black and Azov seas ecosystem under anthropogenic influence». Krasnodar. pp [in Russian]. Kuzminova N.S. (2011 b). Population characteristics of high body pickarel Spicara flexuosa in the modern period. In: Scientific works «Actual problems of modern biology and human health». Nikolaev national university of V.O. Suhomlinskiy name. Nikolaev. 11, рр [in Russian]. Kuzminova N.S., Skuratovskaya E.N. (2011). State of shore rockling Gaidropsarus mediterraneus (L.) (Gadiidae), inhabiting Sevastopol bays with different levels of pollution. Ribne gospodarstvo of Ukraine 1 (72), 3 9 [in Russian]. Kuzminova N., Rudneva I., Salekhova L., Shevchenko N., Oven L. (2011). State of Black Scorpion fish (Scorpaena porcus L., 1758) inhabited coastal area of Sevastopol region (Black Sea) in Turkish J. of Fisheries and Aquatic Sciences 11(1), Kuzminova N.S. (2012 a). The current state of young mass commercial species of fish in the coastal zone of the Black Sea. Vestnik of Zaporozskogo national university. Bіologіcal sciences 3, [in Russian]. Kuzminova N.S. (2012 b). The index of spleen of mass species of fish from the Black Sea bays with different levels of pollution. In: Materials of Russian conf. of young scientists and international experts, dedicated 90th anniversary of the construction of the first scientific ship 134

135 of Polar Scientific Institute of Fisheries and Oceanography "Perseus". Murmansk, pp [in Russian]. Kuftarkova E.A. (2006). Evaluation of hydrochemical conditions in the area of functioning of experimental aqua farming. In: Abstract of reports of Intern. conf. dedicated 135th anniversary of the IBSS «Problems of Biological Oceanography of the XXI century». Sevastopol, рр. 99 [in Russian]. Lomakin P.D., Popov M.A. (2011). Oceanographic characterization and assessment of pollution of Balaklavskaya bay. Marine Hydrophysical Institute of NASU, Institute of Biology of the Southern Seas NAS of Ukraine, Ukraine. Sevastopol, 191 pp. [in Russian]. Makarov M.V., Bondarenko L.V., Kopiy V.G., Zinkovskaya N.G. (2010). Macrozoobenthos of natural solid substrates of Karantinnaya Bay (Crimea, Ukraine). Scientific notes of Ternopol national unіversity of V. Gnatiuk name. Serіes of Biology. Special issue: Hydroecology 3 (44), [in Russian]. Oven L.S., Rudneva I.I., Shevchenko N.F. (2000). The use of biomarkers for analyse of the state of the Black Sea high body pickarel Spicara flexuosa (Centracanthidae). Journal of ichthyology 40 (6), [in Russian]. Oven L.S., Salekhova L.P., Kuzminova N.S. (2008). Long-term dynamics of species composition and quantity of Black Sea fish near Sevastopol. Ribne gospodarstvo of Ukraine 4 (57), [in Russian]. Oven L.S., Salekhova L.P., Kuzminova N.S. (2009). Modern state of the blunt-snouted mullet Mullus barbatus ponticus population dwelling in the coastal zone near Sevastopol. Journal of Ichthyology 49 (2), Oven L.S., Salekhova L.P., Kuzminova N.S. (2010). New data on the size-mass composition of peacock wrasse Crenilabrus tinca (Linnaeus, 1758) (Pisces, Labridae) in the coastal area of Sevastopol (Black Sea). Ribne gospodarstvo of Ukraine 2 (67), [in Russian]. Popov M.A., Kovrigina N.P., Machkevskiy V.K., Lozovskiy V.L., Kozintsev A.F. (2010). The influence of anthropogenic factor on the hydrochemical conditions, the mussel Mytilus galloprovincialis Lam. and its endosymbionts in Balaklavskaya bay. Scientific notes of Ternopol national unіversity of V. Gnatiuk name. Serіes of Biology. Special issue: Hydroecology 3 (44), [in Russian]. Probatov A.N., Moskvin B.S. (1940). Materials for the taxonomy and biology of high body pickarel (Smaris S. spicara chryselis Cuvier et Valenciennes) from north-east of the Black Sea. Works of Novorossiysk Biological Station of prof. V.M. Arnoldi name. 2 (3), pp [in Russian]. Revkov N.K., Kolesnikova E.A., Valovaya N.A., Mikhailova T.V., Mazlumyan S.A., Shaliapin V.K. (2000). Benthos of the coastal zone of the southern coast of Crimea (Balaklava cape Aya): composition and state. Hidrobiol J 36 (4), 3 10 [in Russian]. Rudneva I.I., Kuzʹ-minova N.S. (2011). Changing of biomarkers of gonads of some Black Sea fish living in conditions of chronic pollution. Ecological systems and equipment 2, 8 12 [in Russian]. Salekhova L.P.(1979). Centracanthidae fish of the Mediterranean basin. K.: Scien. Dumka. [in Russian]. 169 pp. Svetovidov A.I. (1964). Fish of the Black Sea. Leningrad: Science. 550 pp. [in Russian]. Timofeev V.A., Kopitov U.P., Samyshev E.Z. (2009). The morphology of the gill apparatus of bivalves due to contamination of bottom sediments. Marine Ecol. Journal 8 (3), [in Russian]. 135

136 Figure 1. Sampling sites of high body pickarel Spicara flexuosa in Sevastopol bays (Sevastopol, Ukraine, Black Sea). Table 1. Size, weight and morphophysiological indices of high body pickarel from different Sevastopol bays in Karantinnaya bay Alexandrovskaya bay Balaklavskaya bay Age Parameter female male female male female male SL, sm 9.8± ±.016* 9.4± ±0.14 weight, g 16.16± ±0.7* 14.36± ± HSI, 15.8±0.8* 14.67± ± ±2.1 GSI, % 2.94±0.3* 2.31± ± ±0.3 CF, % 1.47± ±0.03* 1.50± ±0.05 SL, sm 9.67± ± ± ± ±0.1" 12.0 weight, g 15.4± ± ± ± ±0.43" HSI, 14.9±0.5* 12.60± ±0.05** 12.59± ± GSI, % 2.72±.02* 1.85± ±0.2** 1.34± ±0.44" 0.68 CF, % 1.5±0.01* 1.58± ±0.01** 1.65± ±0.001" SL, sm 10.6±0.1* 11.73± ± ±0.3** 10.4±0.3" 12.98±0.3" weight, g 21.8±0.9* 29.29± ± ±2.4** 17.7± ±3.4" HSI, 18.7±0.7* 12.94± ± ± ± ±

137 GSI, % 5.08±0.4* 1.78±0.25* 2.01±0.3** 0.88±0.2** 5.4± ±0.059 CF, % 1.5±0.01* 1.56± ±0.02** 1.59± ±0.04" 1.52±0.03 SL, sm 9.8±0.18* 12.53±0.1* 10.7± ± ± ±0.2" weight, g 17.48± ±0.9* 20.18± ± ± ±1.9" HSI, 16.9±0.5* 13.64± ± ±0.6** 14.9± ±0.64" GSI, % 1.21± ± ± ±0.16** 4.45± ±0.02" CF, % 1.59± ± ± ±0.02** 1.38± ±0.02" SL, sm 9.7± ±0.2* ± ± ±0.2 weight, g 19.5± ±2.5* ± ± ± HSI, 20.6± ± ± ± ±0.7" GSI, % 1.33± ± ±0.4** 7.03± ±0.25 CF, % 1.79± ± ± ± ±0.02 Note: * - the significant differences for fish of the same sex from Karantinnaya and Alexandrovskaya bays, ** - from Alexandrovskaya and Balaklavskaya bays, "- from Balaklavskaya and Karantinnaya bays 137

138 UNDERWATER TRAILS: INNOVATIVE ACTIVITY IN SITHONIA (CHALKIDIKI, GREECE) Skoufas G. 1*, Tsirika A Department of Fisheries Technology and Aquacultures, Α.Σ.Δ.Η.Th., N. Miltiadi 1, 63200, Nea Moudania, Greece 2. School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, A.U.Th., University Campus, 54124, Thessaloniki, Greece ABSTRACT Underwater trails constitute an innovative approach in the field of recreational diving (SCUBA diving and snorkeling). Their establishment, although it has taken place both in the tropics and in temperate regions, is the first implementation of such an action in Greece and especially in the Municipality of Sithonia (Chalkidiki). The development of the underwater trails was based on the selection of a route accessible to all levels of diving training. Across each trail, ten sites of biological interest are marked. The creation of underwater trails aims at the enhancement of diving tourism, providing diving safety and contributing to environmental awareness. Keywords: Underwater trails, diving tourism * Corresponding author: Skoufas George (skoufas@aqua.teithe.gr) ΚΑΣΑΓΤΣΗΚΔ ΓΗΑΓΡΟΜΔ: ΚΑΗΝΟΣΟΜΟ ΓΡΑΖ ΣΟΝ ΓΖΜΟ ΗΘΧΝΗΑ (ΥΑΛΚΗΓΗΚΖ, ΔΛΛΑΓΑ) ημφθαξ Γ. 1*, Σζζνίηα Α Σιήια Σεπκμθμβίαξ Αθζείαξ ηαζ Τδαημηαθθζενβεζχκ, Α.Σ.Δ.Η.Θ., Ν. Μζθηζάδδ 1, 63200, Νέα Μμοδακζά, Δθθάδα 2. Σιήια Γεςπμκίαξ, πμθή Γεςπμκίαξ, Γαζμθμβίαξ ηαζ Φοζζημφ Πενζαάθθμκημξ, Α.Π.Θ., Πακεπζζηδιζμφπμθδ, 54124, Θεζζαθμκίηδ, Δθθάδα Πενίθδρδ Σα ηαηαδοηζηά ιμκμπάηζα απμηεθμφκ ιία ηαζκμηυιμ πνμζέββζζδ ζημκ πχνμ ηδξ ηαηάδοζδξ ακαροπήξ (SCUBA diving ηαζ snorkeling). Ζ εθανιμβή ημοξ, ακ ηαζ έπεζ θάαεζ πχνα ηυζμ ζε ηνμπζηέξ εάθαζζεξ υζμ ηαζ ζε εφηναηεξ πενζμπέξ, είκαζ πνςημπυνα βζα ηδκ Δθθάδα ηαζ εζδζηυηενα βζα ημκ Γήιμ ζεςκίαξ (Υαθηζδζηή). Ζ δδιζμονβία ημο ηαηαδοηζημφ ιμκμπαηζμφ ααζίζηδηε ζηδκ επζθμβή ιίαξ δζαδνμιήξ, πνμζζηήξ ζε υθα ηα ηαηαδοηζηά επίπεδα εηπαίδεοζδξ, ηαηά ιήημξ ηδξ μπμίαξ επζθέβμκηαζ δέηα ζδιεία αζμθμβζημφ εκδζαθένμκημξ ζηα μπμία έβζκε ζήιακζδ. Ζ δδιζμονβία ηςκ ηαηαδοηζηχκ ιμκμπαηζχκ απμζημπεί ζηδκ ακάπηολδ ημο ηαηαδοηζημφ ημονζζιμφ, πανέπμκηαξ ηαηαδοηζηή αζθάθεζα ηαζ ζοιαάθθμκηαξ ζηδκ πενζααθθμκηζηή εοαζζεδημπμίδζδ. Λέλεζξ ηθεζδζά: Καηαδοηζηά ιμκμπάηζα, ηαηαδοηζηυξ ημονζζιυξ * οββναθέαξ επζημζκςκίαξ: ημφθαξ Γεχνβζμξ (skoufas@aqua.teithe.gr) 1. Δζζαβςβή Οζ οδάηζκμζ πυνμζ πμο δφκακηαζ κα πνμζθένμοκ ηα εαθάζζζα μζημζοζηήιαηα αθμνμφκ ζε ιεβάθα ιεβέεδ ηαζ ηαθφπημοκ έκα εονφηαημ θάζια. Δηηυξ υιςξ απυ ημοξ αζμθμβζημφξ οδάηζκμοξ πυνμοξ (π.π. αθζεία, οδαημηαθθζένβεζεξ) ηαζ ημκ εαθάζζζμ μνοηηυ πθμφημ, ζδζαίηενα ζδιακηζηυ μζημκμιζηυ νυθμ παίγεζ δ ακάπηολδ ημο πανάηηζμο ημονζζιμφ. Ο πανάηηζμξ ημονζζιυξ εα ιπμνμφζε κα παναηηδνζζηεί ςξ ιία ζδζαίηενα ακαπηοζζυιεκδ ημονζζηζηή αζμιδπακία (Mola et al. 2012), δ μπμία 138

139 πνμζθένεζ πμθθέξ ηαζ δζαθμνεηζηέξ δοκαηυηδηεξ πμο απεοεφκμκηαζ ζε πθδεοζιμφξ ιε δζαθμνεηζηά παναηηδνζζηζηά (Leeworthy et al. 2010). Έκαξ εκαθθαηηζηυξ ηθάδμξ ημο πανάηηζμο ημονζζιμφ είκαζ μ ηαηαδοηζηυξ ημονζζιυξ. Ο ηαηαδοηζηυξ ημονζζιυξ δίκεζ ιζα δοκαηυηδηα in situ πνμζέββζζδξ ημο θοζζημφ πενζαάθθμκημξ, ηδξ οπμανφπζαξ αζμπμζηζθυηδηαξ αθθά ηαζ ηδξ πμθζηζζηζηήξ ηθδνμκμιίαξ ηςκ οπμεαθάζζζςκ ικδιείςκ, υπςξ είκαζ ηα καοάβζα, μζ αοεζζιέκεξ πυθεζξ απυ ηεηημκζηή δνάζδ, η.ά. Τπάνπμοκ πμθθέξ πνμηάζεζξ ηαζ ζπέδζα ζπεηζηά ιε ημκ ηνυπμ αλζμπμίδζδξ ηδξ πανάηηζαξ γχκδξ ζε ζοκάνηδζδ ιε ημκ ηαηαδοηζηυ ημονζζιυ. Ο ηαηαδοηζηυξ ημονζζιυξ εα πνέπεζ κα είκαζ ιζα ηαεμδδβμφιεκδ δνάζδ, ηυζμ βζα ηδκ απμθοβή αηοπδιάηςκ ηςκ πνδζηχκ, υζμ ηαζ βζα ηδκ απμθοβή ηοπυκ ηαηαζηνμθχκ ημο θοζζημφ οπμεαθάζζζμο πθμφημο ηαζ ηδξ πμθζηζζηζηήξ ηθδνμκμιζάξ. Ζ πνήζδ ηςκ ηαηαδοηζηχκ δζαδνμιχκ ή ηαηαδοηζηχκ ιμκμπαηζχκ ιπμνεί κα έπεζ ςξ πνήζηεξ ηυζμ ημοξ δφηεξ πμο ηάκμοκ αοηυκμιδ ηαηάδοζδ (SCUBA diving) υζμ ηαζ αοημφξ πμο πναβιαημπμζμφκ εθεφεενδ ηαηάδοζδ (snorkelers) (Plathong et al. 2000). Ζ εθανιμβή ηδξ παναπάκς δνάζδξ ζηδκ αοηυκμιδ ηαηάδοζδ ηαζ ημκ ηαηαδοηζηυ ημονζζιυ έπεζ ςξ απμηέθεζια ηδκ μνεμθμβζηή ηαζ αεζθυνμ δζαπείνζζδ ηδξ αζμπμζηζθυηδηαξ ηαζ ημο οπμεαθάζζζμο πθμφημο (Delgado 2011). Πανάθθδθα, δ ηαεμδδβμφιεκδ ηαηάδοζδ ιέζς ηςκ ηαηαδοηζηχκ δζαδνμιχκ πανμοζζάγεζ έκα δζηηυ υθεθμξ: πενζμνίγεζ ηοπυκ ηαηαζηνμθέξ ζημ θοζζηυ πενζαάθθμκ απυ ημοξ δφηεξ, εκχ πανέπεζ βκχζεζξ ημο οπμεαθάζζζμο πενζαάθθμκημξ ηαηεοεφκμκηαξ ηδκ πνμζμπή ηςκ οπμανφπζςκ επζζηεπηχκ ζε ζοβηεηνζιέκα αζμθμβζηά ή πμθζηζζιζηά ζημζπεία (Rangel et al. 2014). Ακ παναθθδθζζημφκ ηα ηαηαδοηζηά ιμκμπάηζα ιε ηζξ πενζαίεξ δζαδνμιέξ (π.π. ιμκμπάηζα ζημ αμοκυ ή ζημ δάζμξ), ιπμνεί ηακείξ κα δζαπζζηχζεζ υηζ πθέμκ υθμ ηαζ ιεβαθφηενμ πμζμζηυ ηςκ επζζηεπηχκ επζθέβεζ ηζξ ηαεμνζζιέκεξ δζαδνμιέξ ζηζξ πενζαίεξ επζζηέρεζξ ημο. Σα ηίκδηνα ηδξ επζθμβήξ ηςκ πνμηαεμνζζιέκςκ δζαδνμιχκ απυ ημοξ επζζηέπηεξ ιπμνεί κα είκαζ πμθοπμίηζθα, υπςξ βζα πανάδεζβια: μζ επζζηέπηεξ ζε έκα πχνμ παναιέκμοκ ζοβηεκηνςιέκμζ, είκαζ ζπεηζηά εφημθα κα δζαπεζνζζηεί ηακείξ ηδ θένμοζα ζηακυηδηαξ ιζαξ πενζμπήξ, μ επζζηέπηδξ κμζχεεζ αζθάθεζα ηαζ πμθθά άθθα. Δπζπθέμκ, μζ πνμηαεμνζζιέκεξ γχκεξ επίζηερδξ είκαζ πνςηανπζηήξ ζδιαζίαξ, εζδζηά ζε δζαπεζνζζηζηά πνμβνάιιαηα πνμζηαηεουιεκςκ πενζμπχκ (Davis & Tisdell 1996). Έκα απυ ηα ζδιακηζηυηενα ζημζπεία ζηδκ αοηυκμιδ ηαηάδοζδ (SCUBA diving), αθθά ηαζ ζηδκ εθεφεενδ (snorkeling) είκαζ δ πνμηαηαδοηζηή εκδιένςζδ (briefing). Ζ πνμηαηαδοηζηή εκδιένςζδ απμηεθεί έκα πμθφηζιμ ενβαθείμ ηυζμ ζηδ δζελαβςβή αζθαθχκ ηαηαδφζεςκ, υζμ ηαζ ζηδκ αθθαβή ηδξ ζοιπενζθμνάξ ηςκ δοηχκ, έκακηζ ηδξ οπμεαθάζζζαξ αζμπμζηζθυηδηαξ (Barker & Roberts 2004; Krieger & Cladwick 2013). Σα ηαηαδοηζηά ιμκμπάηζα ή αοημηαεμδδβμφιεκεξ δζαδνμιέξ έπμοκ εθανιμζηεί πθέμκ ηυζμ ζε ηνμπζηά εαθάζζζα μζημζοζηήιαηα (Plathong et al. 2000), υζμ ηαζ ζε εφηναηεξ γχκεξ (Rangel et al. 2014). ημπυξ ηδξ πανμφζαξ ιεθέηδξ είκαζ δ εθανιμβή βζα πνχηδ θμνά ζηδκ Δθθάδα εκυξ πζθμηζημφ ζπεδίμο ηαηαδοηζηχκ ιμκμπαηζχκ. Σμ εκδζαθένμκ πμο πανμοζζάγεζ δ παναπάκς ιεθέηδ έβηεζηαζ ζημ βεβμκυξ υηζ δζενεοκάηε πανάθθδθα δ εθανιμζιέκδ πνήζδ ηςκ ηαηαδοηζηχκ ιμκμπαηζχκ ηυζμ ζηδκ αοημηαεμδδβμφιεκδ οπμανφπζα πενζήβδζδ, υζμ ηαζ ζηδκ πνμηαηαδοηζηή εκδιένςζδ (briefing). 2. Τθζηά ηαζ Μέεμδμζ Ζ ακάβηδ οθμπμίδζδξ ημο ζοβηεηνζιέκμο ένβμο ζημκ δήιμ ζεςκίαξ (Υαθηζδζηή, Δθθάδα) πνμέηορε απυ ηδκ ζδζαίηενα ακαπηοζζυιεκδ δναζηδνζυηδηα ζηδκ πενζμπή ηδξ ηαηάδοζδξ ακαροπήξ. Δκδεζηηζηά ακαθένεηαζ υηζ, ζηδκ εονφηενδ πενζμπή δζηαζμδμζίαξ ημο δήιμο ζεςκίαξ, δναζηδνζμπμζμφκηαζ πενζζζυηενα απυ 5 ηαηαδοηζηά ηέκηνα. Γζα ηδκ οθμπμίδζδ ημο ζοβηεηνζιέκμο ένβμο επζθέπεδηακ ηέζζενζξ (4) ηαηαδοηζηέξ δζαδνμιέξ: ιία δοηζηά ηδξ πενζμκήζμο, ζημκ Σμνςκαίμ Κυθπμ, ζηδ κήζμ Κέθοθμ (Μανιανάξ), ιία ζηδκ ακαημθζηή πθεονά, ζημκ ζββζηζηυ Κυθπμ, ζηδκ πενζμπή ημο Αβίμο Νζημθάμο, ηαζ δφμ ζημ κυηζμ άηνμ, ζηζξ πενζμπέξ Ένζηα ηαζ Νέιεζδ, μζ μπμίεξ βεςβναθζηά ανίζημκηαζ ακάιεζα ζημ Πυνημ Κμοθυ ηαζ ζημ Καθαιίηζζ. 139

140 Σα παναηηδνζζηζηά ηςκ επζθεβιέκςκ πενζμπχκ πανμοζζάγμκηαζ ζημκ αηυθμοεμ πίκαηα (Πίκαηαξ 1). Πίκαηαξ 1. Γεκζηά παναηηδνζζηζηά ηςκ επζθεβιέκςκ ηαηαδοηζηχκ δζαδνμιχκ. ΔΡΗΚΑ ΝΔΜΔΖ ΚΔΛΤΦΟ ΑΓΗΟ ΝΗΚΟΛΑΟ Μδ πενζμπή ηαημζηδιέκδ Πνυζααζδ ιε πθςηυ ιέζμ Ήπζα δνάζδ Μέηνζμξ δοζημθίαξ οδνμδοκαιζηή ααειυξ Μδ πενζμπή ηαημζηδιέκδ Πνυζααζδ ιυκμ ιε πθςηυ ιέζμ Έηεεζδ ζηδκ οδνμδοκαιζηή δνάζδ Τρδθυξ δοζημθίαξ ααειυξ Μδ ηαημζηδιέκδ πενζμπή, αθθά πμθφ ημκηά ζημ αζηζηυ ηέκηνμ ημο Νέμο Μανιανά ηαζ ζηδκ λεκμδμπεζαηή ιμκάδα Πυνημ Καννά Πνυζααζδ ιε πθςηυ ιέζμ Ήπζα δνάζδ ημονζζηζηή Κμκηά ζε θζιάκζ (νιμξ Πακαβίαξ) Πνυζααζδ απυ λδνάξ Μζηνυ αάεμξ ηαζ δοκαηυηδηα επίζηερδξ ιε εθεφεενδ ηαηάδοζδ Γναζηδνζμπμζμφκηαζ ηαηαδοηζηά ηέκηνα Γναζηδνζμπμζμφκηαζ ηαηαδοηζηά ηέκηνα Ήπζα δνάζδ οδνμδοκαιζηή Γναζηδνζμπμζμφκηαζ ηαηαδοηζηά ηέκηνα Γναζηδνζμπμζμφκηαζ ηαηαδοηζηά ηέκηνα Γζα ηδκ επζθμβή ηςκ ηαηαδοηζηχκ δζαδνμιχκ δζελήπεδζακ ιία ζεζνά απυ δζενεοκδηζηέξ ηαηαδφζεζξ. ημ πθαίζζμ ηδξ πνχηδξ πζθμηζηήξ εθανιμβήξ ηςκ ηαηαδοηζηχκ δζαδνμιχκ, επζθέπεδηακ πενζμπέξ μζ μπμίεξ πανμοζζάγμοκ δζαθμνεηζηά παναηηδνζζηζηά (Πίκαηαξ 1). ε ηάεε ηαηαδοηζηή δζαδνμιή επζθέπεδηακ δέηα επζιένμοξ ζδιεία αζμθμβζημφ εκδζαθένμκημξ, ηα μπμία ηαζ ζδιάκεδηακ ζε πνχηδ θάζδ, εκχ ζε δεφηενδ θάζδ πνμαθέπεηαζ δ ημπμεέηδζδ ηςκ ηαηαδοηζηχκ πζκαηίδςκ (ηα ζδιεία ηδξ ηάεε ηαηαδοηζηήξ δζαδνμιήξ πανμοζζάγμκηαζ ζημκ Πίκαηα 2). Συζμ ηαηά ηδ δζάνηεζα ηδξ οθμπμίδζδξ, υζμ ηαζ ζηδκ ηεθζηή θάζδ ηδξ οθμπμίδζδξ, πνμαθέπεηαζ δ θςημβνάθδζδ ηαζ δ αζκηεμζηυπδζδ ηυζμ ηδξ ζοκμθζηήξ δζαδνμιήξ, υζμ ηαζ ηςκ επζιένμοξ ζημζπείςκ ηδξ αζμπμζηζθυηδηαξ. 3. Απμηεθέζιαηα Ζ οθμπμίδζδ εκυξ ηαηαδοηζημφ ιμκμπαηζμφ ή ιζαξ ηαηαδοηζηήξ δζαδνμιήξ πνμτπμεέηεζ ηδ ζοκεηηίιδζδ ααζμηζηχκ ηαζ αζμηζηχκ παναιέηνςκ ζηα επζθεβιέκα ζδιεία. Γεκζηυηενα, ηα ααζμηζηά ζημζπεία ζηα μπμία δυεδηε αανφηδηα αθμνμφζακ ζηδκ αζθάθεζα ηςκ ηαηαδφζεςκ, εκχ δ επζθμβή ηςκ αζμηζηχκ παναηηδνζζηζηχκ απμζημπεί ζηδκ πενζααθθμκηζηή εοαζζεδημπμίδζδ. Με βκχιμκα ηα ααζμηζηά ηαζ ηα αζμηζηά ζημζπεία έβζκε δ επζθμβή 4 ηαηαδοηζηχκ δζαδνμιχκ ζηδ ζεςκία Υαθηζδζηήξ, δοηζηά ηαζ ακαημθζηά ηδξ πενζμκήζμο. Γζα ηάεε ιία απυ ηζξ ηαηαδοηζηέξ δζαδνμιέξ επζθέπεδηακ δέηα (10) ζδιεία, ηα μπμία πανμοζζάγμοκ αζμθμβζηυ εκδζαθένμκ ηαζ ηα μπμία πανμοζζάγμκηαζ ζημκ Πίκαηα 2. Σμ ηνίημ ζηέθμξ ηδξ οθμπμίδζδξ ηδξ δνάζδξ πενζθαιαάκεζ ηδκ πνμηαηαδοηζηή εκδιένςζδ (briefing). Ζ πνμηαηαδοηζηή εκδιένςζδ ιπμνεί κα πενζθαιαάκεζ δφμ ζημζπεία, ηα μπμία ιε ηδ ζεζνά ημοξ κα απεοεφκμκηαζ ζε δφμ μιάδεξ πνδζηχκ. Ζ πνχηδ αθμνά ζηα ηαηαδοηζηά ηέκηνα, ηαζ ζηδκ πνμηεζιέκδ πενίπηςζδ ζηυπζιδ είκαζ δ πανμοζίαζδ κα είκαζ ζε δθεηηνμκζηή ιμνθή αθμφ εα θαιαάκεζ πχνα ζηζξ εβηαηαζηάζεζξ ημο ηαηαδοηζημφ ηέκηνμο ηαζ εα οπάνπεζ έκα εηηεκέζηενμ ηείιεκμ. Πανάθθδθα υιςξ, εα πνέπεζ κα θδθεεί οπυρδ ηαζ δ πενίπηςζδ ηςκ δοηχκ πμο εα επζζηεθεμφκ ηδκ ηαηαδοηζηή πενζμπή ιε ζδζςηζηή πνςημαμοθία. Θα έπεζ βίκεζ πνυαθερδ κα οπάνπμοκ πθαζηζημπμζδιέκα θφθθα (slates), ηα 140

141 μπμία εα δίκμοκ πθδνμθμνίεξ ζημκ οπμανφπζμ πενζδβδηή βζα ηάεε ζδιείμ ηδξ πνμηεζκυιεκδξ ηαηαδοηζηήξ δζαδνμιήξ. Πίκαηαξ 2. ημζπεία αζμθμβζημφ εκδζαθένμκημξ ζηζξ 4 επζθεβιέκεξ ηαηαδοηζηέξ δζαδνμιέξ ζηδ ζεςκία (Υαθηζδζηή, Δθθάδα). α/α ΔΡΗΚΑ ΝΔΜΔΖ ΚΔΛΤΦΟ ΑΓΗΟ ΝΗΚΟΛΑΟ I Αsparagopsis armata Crambe crambe Aplysina aerophoba Arbacia lixulla & Paracentrotus lividus Ii Codium bursa Posidonia oceanica Chondrosia reniformis Posidonia oceanica Iii Coris julis ηζυθζθδ αζμημζκυηδηα Caulerpa racemosa Anemonia viridis Vi Halocynthia papillosa Asparagopsis armata Posidonia oceanica Crambe crambe V Udotea petiolata Coris julis Peltaster placenta Posidonia oceanica (κέηνςζδ θεζιχκα) Vi ηζυθζθδ αζμημζκυηδηα Hermodice carinculata Leptosammia pruvoti Νέηνςζδ ζπυββςκ vii Anthias anthias Codium bursa Parazoanthus axinellae Βνουγςα viii Crambe crambe Dictyota spp. Chromis chromis ηζυθζθδ αζμημζκυηδηα Ix Sphaerechinus granularis Chondrosia reniformis Spondylus gaederopus Balanophylia europea X Chromis chromis Halocynthia papillosa Pinna nobilis Dictyota spp. 4. ογήηδζδ Ζ αοηυκμιδ ηαηάδοζδ είκαζ έκαξ ζδζαίηενα ακαπηοζζυιεκμξ ημιέαξ ημο πανάηηζμο ημονζζιμφ, ηαζ πθέμκ βζα πμθθέξ πχνεξ μ ηαηαδοηζηυξ ημονζζιυξ απμηεθεί έκα ζδιακηζηυ πμζμζηυ ημο αηαεάνζζημο εεκζημφ εζζμδήιαημξ (Musa & Dimmock 2012). Ζ εκίζποζδ ημο ηαηαδοηζημφ ημονζζιμφ, πνμτπμεέηεζ δφμ ααζζηά ζημζπεία: ημ πνχημ ζημζπείμ αθμνά ζηδ δδιζμονβία εκυξ εεζιμεεηδιέκμο πθαζζίμο θεζημονβίαξ, ζημ μπμίμ εα δίκεηαζ ζδζαίηενδ έιθαζδ ζηδκ αζθάθεζα, ηαζ ημ δεφηενμ ζδιακηζηυ ζημζπείμ αθμνά ζηδκ πνμαμθή ημο ηαηαδοηζημφ πνμσυκημξ, ημ μπμίμ ιπμνεί κα πανμοζζάγεζ ζημζπεία αζμθμβζημφ, πμθζηζζηζημφ ή άθθμο εκδζαθένμκημξ (ππ. βεςθμβζημφ). ηδκ οθμπμίδζδ ηαζ δζάεεζδ εκυξ ηαηαδοηζημφ πνμσυκημξ, ζδζαίηενμ εκδζαθένμκ πανμοζζάγεζ ημ δδιμβναθζηυ πνμθίθ ηδξ μιάδαξ ζηδκ μπμία απεοεφκεηαζ ημ ένβμ (Davis & Tisdell, 1996; Musa et al. 2010). Γεκζηά, ημ ηαηαδοηζηυ πνμσυκ εα πνέπεζ κα απεοεφκεηαζ ζε υζμ ημ δοκαηυ πενζζζυηενμοξ πνήζηεξ ηαζ εονφηενμ αβμναζηζηυ ημζκυ. Μέζα ζε αοηυ ημ πθαίζζμ ζδεχκ, βζα ηδκ οθμπμίδζδ ημο ζοβηεηνζιέκμο ένβμο πνμηάεδηε ημ ιέβζζημ αάεμξ ηςκ 18 ιέηνςκ, ημ μπμίμ ακηζζημζπεί ζημ πνχημ επίπεδμ εηπαίδεοζδξ δοηχκ ακαροπήξ (Open Water SCUBA Diver, PADI). ηδκ πανμφζα ιεθέηδ δυεδηε επίζδξ έιθαζδ ζηδκ πνμαμθή ηςκ βκςζηχκ αβκχζηςκ, δδθαδή ζε ιμνθέξ οπμεαθάζζζςκ μνβακζζιχκ, μζ μπμίμζ ακ ηαζ είκαζ μζηείμζ ζημοξ δφηεξ, εκημφημζξ αοημί βκςνίγμοκ εθάπζζηα βζα ηδ αζμθμβία ημοξ ή βεκζηυηενα ηδ θοζζηή ημοξ ζζημνία. Χξ εκδεζηηζηυ πανάδεζβια ακαθένεηαζ δ 141

142 πενίπηςζδ ημο πθςνμθφημοξ Codium bursa, ημ μπμίμ πμθφ ζοπκά ακαθένεηαζ θακεαζιέκα απυ ημοξ δφηεξ ακαροπήξ ςξ ζπυββμξ. Σμ ζδιακηζηυηενμ ζημζπείμ, ημ μπμίμ ιπμνεί κα αμδεήζεζ ηαεμνζζηζηά ζηδκ πνμχεδζδ ημο ηαηαδοηζημφ πνμσυκημξ, είκαζ δ πνμηαηαδοηζηή εκδιένςζδ (briefing) (Barker & Roberts 2004; Krieger & Chadwick 2013). Δκδζαθένμκ πανμοζζάγεζ ημ βεβμκυξ υηζ δ ζςζηή πνμηαηαδοηζηή εκδιένςζδ ιπμνεί κα ηαηαζηήζεζ ημκ ιαγζηυ ηαηαδοηζηυ ημονζζιυ ακαροπήξ ςξ έκα πμθφηζιμ ενβαθείμ ζηδ δζαπείνζζδ ημο εαθάζζζμο πενζαάθθμκημξ, υπςξ ζοκέαδ βζα πανάδεζβια ζε ενεοκδηζηή ιεθέηδ βζα ηα ράνζα ημο βέκμοξ Hippocampus (Goffredo et al. 2004). Μία εκδζαθένμοζα πνμζέββζζδ ζημκ πχνμ ημο ηαηαδοηζημφ ημονζζιμφ είκαζ δ δδιζμονβία ηαηαδοηζηχκ ιμκμπαηζχκ ή δζαδνμιχκ, ηα μπμία εα είκαζ πνμζζηά είηε ιε αοηυκμιδ ηαηάδοζδ (SCUBA diving) είηε ιε εθεφεενδ ηαηάδοζδ (snorkeling) (Plathong et al. 2000; Wegner et al. 2006; Rangel et al. 2014). Σμ ζοβηεηνζιέκμ ζπέδζμ δδιζμονβίαξ ηαηαδοηζηχκ ιμκμπαηζχκ ζημκ Γήιμ ζεςκίαξ απμηεθεί ιία ηαζκμηυιμ δνάζδ πμο εθανιυγεηαζ βζα πνχηδ θμνά ζηδκ Δθθάδα. Σμ ένβμ, ακ ηαζ ζε πζθμηζηή θάζδ, είκαζ δοκαηυ κα ακαααειίζεζ ζδιακηζηά ηζξ πνμζθενυιεκεξ ηαηαδοηζηέξ οπδνεζίεξ ηαζ κα αμδεήζεζ ζηδκ ακάπηολδ ημο ηαηαδοηζημφ ημονζζιμφ. Πανάθθδθα, δ δδιζμονβία ηαηαδοηζηχκ ιμκμπαηζχκ απμηεθεί ιία ζδιακηζηή πνμζέββζζδ ζηδκ πενζααθθμκηζηή εηπαίδεοζδ ηαζ ζηδκ πενζααθθμκηζηή εοαζζεδημπμίδζδ. Αλίγεζ κα πνμηαεεί δ δδιζμονβία εκυξ δζηηφμο ηαηαδοηζηχκ ιμκμπαηζχκ ηα μπμία εα ακαδείλμοκ ηδκ οπμανφπζα αζμπμζηζθυηδηα. Μία άθθδ εκδζαθένμοζα πνμμπηζηή ηςκ ηαηαδοηζηχκ ιμκμπαηζχκ είκαζ πςξ εα ιπμνμφζακ κα απμηεθέζμοκ ηζξ πνυδνμιεξ ιμνθέξ ηςκ Πενζμπχκ Ονβακςιέκδξ Ακάπηολδξ Καηαδοηζηχκ Πάνηςκ (Π.Ο.Α.Κ.Π.), υπςξ αοηέξ μνίγμκηαζ ζημκ Νυιμ 3409 (Φ.Δ.Κ. 273/2005). Δοπανζζηίεξ Ζ οθμπμίδζδ ημο ένβμο πνδιαημδμηήεδηε απυ ημκ Γήιμ ζεςκίαξ (Υαθηζδζηή), ιε ακάδμπμ ημο ένβμο ηδκ ΑΜΒΗΟ Α.Δ. Οζ ζοββναθείξ εα ήεεθακ κα εοπανζζηήζμοκ ζδζαίηενα ημκ δήιανπμ η. Ηςάκκδ Σγίηγζμ βζα ημ αιένζζημ εκδζαθένμκ πμο επέδεζλε. Σμ ηεπκζηυ ηιήια ηδξ δνάζδξ οπμζηδνίπηδηε απυ ηδκ ηαηαδοηζηή μιάδα Northern Greece Underwater Explorers (NGUE). Βζαθζμβναθία Άνενμ ζε πενζμδζηυ: Barker N.H.L., Roberts C. M. (2004). Scuba diver behaviour and the management of diving impacts on coral reefs. Biological Conservation, 120, Davis D., Tisdell C. (1996) Economic Management of Recreational Scuba Diving and the Environment. Journal of Environmental Management, 48, Goffredo S., Picinetti C., Zaccanti F. (2004). Volunteers in Marine Conservation Monitoring: a study of the distribution of seahorse carried out in collaboration with recreational scuba divers. Conservation Biology, 18(6), Krieger J.R., Chadwick N.E. (2013) Recreational diving impacts and the use of pre-dive briefings as a management strategy on Florida coral reefs. Journal of Coastal Conservation 17, Mola F, Shafaei F, Mohamed B. (2012). Tourism and the environment: issues of concern and sustainability of southern part of the Caspian Sea Coastal Areas. Journal of Sustainable Development 5(3), 2-15 Musa G., Seng W. T., Thirumoorthi, Abessi M. (2010). The influence of SCUBA dives's personality, experience and demographic profile n their underwater behavior. Tourism in Marine Environments, 7(1), Musa G., Dimmock K. (2012). SCUBA Diving tourism introduction to special issue. Tourism in Marine Environments 8(1/2), 1-5. Plathong S., Inglis G.J., Huber M.E. (2000). Effects of self-guided snorkeling trails on corals in tropical marine park. Conservation Biology, 14,

143 Rangel M.O., Pita C.B., Concalves J.M.S., Oliveira F., Costa C., Erzini K. (2014) Deloping selfguided scuba dive routes in the Algarve (Portugal) analysing visitors' perceptions. Marine Policy 45, Wegner E. Tonioli F.C., Cabral D.Q. (2006). Underwater Trails: a new possibility of marine tourism. Journal of Coastal Research, Special issue 39, Leeworthy V.R, Bowker JM, Hospital J, Stone E. Projected participation in marine recreation: 2005 & National Survey on Recreation and the Environment. Coastal and Ocean Resource Economics. Maryland: NOAA National Ocean Service, Silver Spring; Πναηηζηά ζε ζοκέδνζα: Delgado J.P (2011).The impact on and opportunities arising from tourism to submerged sites. UNESCO Scientific Colloquium on Factors Impacting the Underwater Cultural Heritage Proceedings pp

144 IMPLEMENTING STANDRAD EU METHOD FOR SAMPLING FRESHWATER FISH WITH MULTI-MESH GILLNETS IN A LAKE'S SUB- BASINS (PRESPA LAKE, ALBANIA) Shumka, S 1*, Aleksi P 2 and Trajҫe, K 3 1 Agricultural University of Tirana, Faculty of Biotechnology and Food, Tirana, Albania 2 Institute of Veterinary Research and Food Security, Tirana, Albania 3 Fishery Management Organization Prespa, Prespa, Albania Abstract The European standards for fish sampling in lakes determined the sampling protocols and methodology developed in the course of fish and fishery monitoring for Prespa lakes. The sampling procedure was based on stratified random sampling. The sampled area has been divided in strata (3 strata for Greater Prespa Lake) and random sampling is performed within each depth stratum. The specially designed multi mesh size gillnets are 30 m long and 1, 5 m deep. The gillnets are composed of 12 different mesh size nets varying from 5-55 mm. Sampling was developed in period between 1 st 15 th September, when there are no fish to spawn and epilimnium temperature usually exceeds 15 o C. The requirements of the WFD in relation to fish communities were considered in relation to assessing status, surveillance monitoring and measuring sustainable reproductive successes and proposals are made on WFD assessments of species composition, abundance and age classes. Key words: fish sampling, European standards, monitoring, Nordic nets Corresponding author: Spase Shumka (sprespa@gmail.com) 1. Introduction The Prespa Lakes Basin is a high altitude system ( m) with a catchment area of over km 2 ; it covers parts of the territories of Albania, the Former Yugoslav Republic of Macedonia and Greece. The basin is home to nearly people with the majority residing in the Former Yugoslav Republic of Macedonia. The Region has little industry and the main source of income is agriculture which is estimated to employ about 75% of the work-force. The ecosystem and the biodiversity of the Region are worth special mention. The geography, soil types and climate coupled with the relatively low human population and impact in the basin has resulted in high species diversity with significant proportion of endemic species. The Region has been recognized as a European and Global Hotspot of Biodiversity, not only because of the sheer number of species and habitats present, but also due to their quality, such as rarity and conservation significance. The most striking feature of the Prespa Lake Watersheds Biodiversity is its enormous richness and heterogeneity. Twenty-three fish taxa have been identified in the Prespa Lakes. Thirteen of these are introduced, and 9 of the remaining 10 (native) are endemic to the Prespa Lakes. At first sight, the proportion of endemism in the fish populations of the Prespa Lakes seems remarkable. It should be mentioned however, that, according to Crivelli et al. (1997), the taxonomic position of a number of taxa occurring in the Prespa Lakes remains doubtful. At present, only the barbel Barbus prespensis would appear to be undoubtedly endemic to both lakes, Micro and Macro Prespa (Dupont & Lambert, 1986; Economidis, 1989; Catsadorakis et al., 1996; Crivelli et al., 1996). Prespa barbel presents species with some economic importance in the Prespa watershed, with medium interest for fisheries (Kapedani & Hartmann 2009). 144

145 Figure 1 Sub basins considered for fish sampling and Relative and absolute fish species composition represented in the total catch at the Albanian Part of Lake Prespa during the sampling campaign in October 2013 According to Economidis (1992) only two endemic species are classified as Endangered (Barbus prespensis and Salmo peristericus), which is an important criterion used for identification of priority species for conservation of animals in Prespa Region. Both species are listed as Vulnerable species on the IUCN Red List of Threatened Animals (Globally threatened species and Regional-European threatened species). Further, Prespa barbel is represented in Prespa Lakes in three countries (the Former Yugoslav Republic of Macedonia, Albania, Greece) which is important for transboundary collaboration, unlike the Pelister stream trout (Salmo peristericus) that can be only found in the adjacent rivers of Prespa basin (River Braychinska and its tributaries, Aghios Germanos stream, and others) (Crivelli et al., 2008). Out of determined 11 native and 12 introduced fish species. In this lake 9 fish species are endemics: A. prespensis Karaman, 1924, A. belvica Karaman, 1924, B. prespensis Karaman, 1924, C. prespensis Karaman, 1924, C. meridionalis Karaman, 1924, P. prespensis Karaman, 1924, R. prespensis Karaman, 1924, S. peristericus Karaman, 1938, and S. prespensis Fowler, The European standard for gillnet fishing (EN 14757) was developed primarily in shallow north European lakes (Appelberg et al. 1995) and further to that unification of the sampling protocols (CEN standards) was a very important step for the comparability of lake fish data (Achleinter, 2012). 2. Material and Methods Fish data were collected during the period of October 2013 using benthic gillnets following the Norden gillnet standardized protocol (CEN, 2005). Random samplings were performed in different 145

146 depth strata and respectively 0-3, 3-6 and 6-12 m during the period considered without reproducing species in the lakes area. The random sampling and the number of nets set in each stratum has been guided by the CEN, 2005 document and in relation to lakes depth and area, it was divided in two sub basins. In each sub basin there has been set 32 nets as it is shown in the Figure 1. In total there has been set 64 benthic gillnets. The set of gillnets was organized in evening, and along with that the water temperature, transparency and coordinates are measured. The benthic multi-mesh gillnets were 30 m long and 1.5 m high, and composed of 12 different panels with mesh sizes ranging between 5 and 55 mm knot to knot in a geometric row. The captured fish were identified to species level, counted and weighed in grams. Catch per unit effort (CPUE) was calculated for each net/night as a measure of relative abundance. CPUE was calculated by dividing the total number of species collected in each net by the number of hours of fishing. The CPUE for all nets in different strata site were averaged to compute the average CPUE for each site for each net. A literature review considered past studies with analytical approaches to the assessment of freshwater fish communities, particularly those relevant to the requirements of CSBL and the WFD 3. Results and discussions Out of determined 11 native and 12 introduced fish species, during our fish campaining were recorded the following fish species: A. prespensis, A. belvica, B. prespensis, C. prespensis, C. meridionalis,p. prespensis, R. prespensis, Salmo peristericus, Squalius prespensis C. carpio, C. gibelio, L. gibosus, R. amarus, P. parcva and T. tinca. Other species Anguilla Anguilla, Ctenopharyngodon idella, Gambusia holbrooki, Hypophthalmichthys militrix, Salmo letnica, Silurus glanis, Prabramis pekinensis, Onchorynchus mykiss listed in various sources were not part of recorded assemblage.. 146

147 Figure 3. CPUE expressed in biomass (g/m 2 ) in percentage per species of total catch per subbasin (BPUE) at Albanian Part of Lake Prespa during the sampling campaign in October In both sub basins, SB1 and SB2 bitterling is representing a dominant species in terms of number of individuals particularly at the depth strata 0-3 and 3-6 m with 51% of total number of individuals. The second most present species in terms of numbers from the alien s one is stone moroko that for entire sampled area represents 15%. Differences between two sampled sub-basins are only present in the biomass/m 2 where dominant species for SB1, bleak and bitterling are presented with almost the same biomass as bitterling in the SB2. As for the third dominant species native roach, both SB are showing similar values. Regarding the following figure which is expressing the catch per unit effort in numbers of individuals per square meter of net, the actual recorded differences are only in the values of Prespa spirlin and carp. 147

148 Figure 3. CPUE expressed in number of individuals/m 2 in percentage per species of total catch per sub-basin (NPUE) at Albanian Part of Lake Prespa during the sampling campaign in October 2013 Bleak is endemic to Prespa Lake. It is the most commercial one and shows stability in Lake Prespa. This species is major prey of fish eating birds and is also a target species of fishermen and local people. Thanks to its life-history strategy it can cope with such high predation mortality. On both sides of the lake it is the dominant economic resource in terms of fishery. Based on the data from this sampling campaign presence of bleak (from 4% at the depth strata 0-3 m and 13% at the depth strata 6-12 m) comparing with previous records (Crivelli et alt., 2006) reveals better species status in entire stock on Albanian side of the Lake. The most valuable commercial fish in Lake Prespa is carp. It s the most important commercial species at the transboundary area. Other sensitive species Prespa barbell and Prespa nase are also less distributed with hypotheses that it is indicative of a failure in the reproduction or development due to water quality and water oscillation with direct impact on species spawning grounds as riverine and gravel habitats. The Prespa sprilin shows a tendency of satisfied presence. In case of an accelerated eutrophication obviously this species will face unpredictable problems due to the fact that primary this species is generally a riverine species with adaptations to this standing water body where it spawns also. Bitterling and stone moroko are introduced species and there are with no commercial value. Both species have a negative impact on native species (e.g. Prespa spirlin), that need to be tested. This species is much more numerous in Micro Prespa than in Macro Prespa, especially from the beginning of this century. Following the increased presence of alien species in terms of number of individuals of bitterling, stone moroko, pumpkinseed etc, the role as aliens in relation to natives in Prespa Lakes is poorly understood. The WFD status class has been discussed with a number of people and it seems to be general agreement that the presence of one or more established alien species is certainly not natural and is likely to affect the WFD status class in a detrimental way. The pumpkinseed in the data is well present and based on experiences and personal communication with local fisherman it has increased in Prespa Lake. During this and previous MMGN surveys it was evident from the local fishermen that 148

149 caught specimens of this species were thrown back in to the lake and according to their endurance they survive almost all. Other recorded species like tench seems to not establish stable populations in Prespa Lake. During this sampling campaign this species was caught only at Albanian side. Being an intensive agricultural area Prespa Lakes watershed presence of additional nutrient load as well as other agrochemicals, combined with lake s habitats disruption and high fishing pressure are representing the main threats to the fish biodiversity. In addition presence of the high number of alien fish species and fish eating predatory birds leads towards intervention as in the local strategies for biodiversity protection as well in the legislative part in the countries shearing the lake. 4. Conclusions The present monitoring survey and data collected serve as a proof for the usefulness of applying standardized lake fish parameters to assess the ecological status of lakes and support the development of integrated monitoring of entire lake. Further to that following European experiences development and setting ecological quality based on different metrics. Based on very specific conditions of the Lakes Prespa with significant events of water level oscillations there are needed additional studies in order to determine the response of the fish fauna (particularity spawning) to the alteration of hydromorphology. The number of benthic gill nets used to sample all species, following the current delineation in two sub basins in the lakes was significantly relevant with lake area. For the future monitoring we propose use of 32 nets in three depth state that is in full line with EU standard. Use of both native endemic species Barbus prespensis and Chondrostoma prespensis as indicators for the water quality due to particular spawning requirements along with fishes as entire component is serving a very good indicator for assessment of water under the WFD. References Achleitner, D., Gassner, H., Luger, M ): Comparison of three standardised fish sampling methods in 14 alpine lakes in Austria. Fisheries Management and Ecology, Volume 19, Issue 4, pages Appelberg M., Berger H.-M., Hesthagen T., Kleiven E., Kurkilahti M., Raitaniemi J. (1995): Development and intercalibration of methods in Nordic freshwater fish monitoring. Water, Air and Soil Pollution 85, Catsadorakis, G., M. Malakou & A.J. Crivelli (1996). The Prespa barbel Barbus prespensis, Karaman 1924 in the Prespa lakes basin, north-western Greece. Tour du Valat, Arles, 79 pp. (also in Greek language) CEN (2003). Water Quality Sampling of fish with electricity. European standard. Ref. No. EN CEN 2005a Water quality guidance on the scope and selection of fish sampling methods. Brussels. CEN CEN 2005b Water quality sampling of fish with multi-mesh gill nets. Brussels. CEN. Dupont, F., Lambert, A., (1986). Etude des communaut es de monog`enes Dactylogyridae parasites de Cyprinidae du LacMikri Prespa (Nord de la Gr`ece). Description de trois nouvelles esp`eces chez un Barbus end emique: Barbus cyclolepis prespensis Karaman, Ann. Parasitol. Hum. Comp. 61: Economidis, P. S Distribution pattern of the genus Barbus (Pisces, Cyprinidae) in the freshwaters of Greece. Trav. Mus. Hist. nat. Grigore Antipa 30: EU Water Framework Directive, (2000). Directive of the European parliament and of the council 2000/60/EC establishing a framework for community action in the field of water policy. Official Journal of the European Communities L 327/1 Crivelli, A. (2010). Pilot Application of the Transboundary Monitoring System for the Prespa Park: Fish and Fisheries Monitoring, Final report, Society for the Protection of Prespa Tour du Valat, Agios Germanos Economidis, P. S. (2005). Barbatula pindus, a new species of stone loach from Greece (Teleostei: Balitoridae). Ichthyological Exploration of Freshwaters 16(1),

150 Freyhof, J. (2010). Threatened freshwater fishes and mollusks of the Balkans, Potential impacts of the hydropower projects. ECA Watch Austria & Euronatur, 81 pp. Kapedani, R., Hartmann, W "Aspects of Institutional Set-up for Transboundary Fisheries Management in the Prespa Lakes, and Livelihoods and Fisheries in the Prespa Lakes Basin". Consultant Report Kottelat, M. and Freyhof, J. (2007). Handbook of European Freshwater Fishes. Kottelat Cornol, Switzerland and Freyhof, Berlin. 150

151 Cu AND Zn CONTENT IN WILD SEA BREAM AND SEA BASS FROM THE PAGASITIKOS GULF (EASTERN MEDITERRANEAN) Nikolaou M.*, Neofitou N., Skordas K., Kosmidis D., Tziantziou L. Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Fytokou St, N. Ionia, 38446, Volos, Greece Abstract This study deals with the copper (Cu) and zinc (Zn) content in muscle tissue of Sparus aurata and Dicentrarchus labrax, fished in the Pagasitikos Gulf. The metal content in biological tissues (muscle, gills and liver) were determined using the USEPA Method Determinations of Cu were carried out using a graphite furnace atomic absorption spectrometer (GF AAS), while for Zn these were carried out with a flame atomic absorption spectrometer (Flame AAS). Statistical analysis revealed significant differences in metal content among tissues for both studied species. Heavy metal contents were found to be substantially higher in the liver of sea bream and sea bass. Furthermore, the estimated daily intake of Cu and Zn was calculated and an assessment of the health risk to consumers was made. The results showed that heavy metal contents in the edible part (muscle) of fish caught in the Pagasitikos Gulf did not exceed permissible limits and therefore their consumption should be considered safe for human health. Key words: Copper, Zinc, Sparus aurata, Dicentrarchus labrax, Eastern Mediterranean *Corresponding author: Nikolaou Marina (maze55@live.com) 1. Introduction Aquatic environmental quality, and how humans may be affecting this, is an area which has received increasing attention in recent years. Heavy metals pollution has begun to grow at an alarming rate and now constitutes a significant global problem (Malik et al. 2010). Heavy metals cannot degrade, and they are continuously deposited and incorporated into water, sediments, and aquatic organisms (Linnik & Zubenko 2000). Anthropogenic activities, such as increased population, urbanisation, industrialisation and agricultural practices, have further aggravated this problem (Gupta et al. 2009).Various metals are naturally present in the aquatic environment via geochemical processes and anthropogenic industrial sources, where these can be accumulated along the food chain (Castritsi- Catharios et al. 2014). Accumulation of trace elements in aquatic organisms is one of the most striking effects of pollution in aquatic system. Fish are widely used as bio-indicators of marine pollution by metals (Evans et al. 1993). According to the mechanisms of absorption, regulation, storage and excretion of trace metals, the various fish tissues used for analyses, present varying bioaccumulation rates and due to their different roles in the above processes, their analysis lead to results with special interest and interpretation (Catsiki & Strogyloudi 1999). The city of Volos, its port and industrial area, results in the Pagasitikos Gulf having toxicological significance of anthropogenic contaminants. Food production, packaging facilities, wood units, and metal processing plants, including a cement plant, are the area s predominant activities (Tsangaris et al. 2013, Giannakopoulou & Neofitou 2014). The metals that have been examined in this study are used in industrial activities and also exist in the background shale of the Gulf (Salomons & Förstner 1984). Although Cu and Zn are essential minerals for humans, overdosing on these beneficial elements can also cause health problems (Gale et al. 2004). The purpose of this study was to examine the content of Cu and Zn in different tissues of wild Sparus aurata and Dicentrarchus labrax collected from Pagasitikos Gulf and to assess whether the edible parts of these fish are acceptable for human consumption. 2. Materials and methods Sampling of S. aurata and D. labrax was carried out on catches by professional fishermen during September 2012 in the Pagasitikos Gulf. For this study, a total of 5 individuals of each species were selected (n=10). To avoid any possible variability due to the growth stage of the fish, the specimens chosen were of approximately the same age and size (commercial size). Immediately after collection the fish were killed on ice and then transferred to the laboratory in insulated boxes full of ice to avoid any contamination. After sample collection, total length (TL) 151

152 and fork length (FL), accurate to 0.1 cm, and total weight (TW) to the nearest 0.01 g were recorded (S. aurata: n = 5, TW = g, TL = cm & D. labrax: n = 5, TW = g, TL = cm). Metals content were determined using USEPA Method 3052 (1996) for microwave-assisted acid digestion of siliceous and organically based matrices. All samples of fish tissues were homogenised and stored in a dry environment until digestion. For total dissolution, 9 ml of concentrated HNO 3 were added to 0.5 g of biological tissue in acid-cleaned Teflon vessels. The vessels were sealed and placed in a closed, high-pressure microwave system (Multiwave 3000, Anton Paar, Austria). After digestion, the samples were diluted with ultra-pure water in 50 ml volumetric flasks and stored in polypropylene sample bottles at 4 ºC until further analysis. Quantitative determinations of Cu were carried out with a graphite furnace atomic absorption spectrometer (GF AAS), while for Zn they were carried out with a flame atomic absorption spectrometer (Flame AAS), using standard addition methods. The estimation of human health risk from consumption of wild fish from the Pagasitikos Gulf was assessed according to Onsanit et al. (2010). The human health risk was assessed and then comparisons of mean metal contents with internationally established food safety standards for edible fish tissues were made. One-way ANOVA was used to determine differences in metal contents among the tissues for both studied species. 3. Results Figure 1 shows the results for copper and zinc content in all tissues separately for each species. In all cases, the maximum contents of heavy metals appeared in the liver of both species. For sea bream, the maximum contents of Cu and Zn were and mg kg 1, respectively. For sea bass Figure 1. Mean±SD contents of Cu and Zn in muscle, liver and gills of sea bream and sea bass (mg kg -1 dry wt). these contents were and mg kg 1. Furthermore, the lowest mean contents of Cu and Zn was detected in the muscle of both species studied. The lowest mean contents of Cu and Zn in sea 152

153 bream were 3.04 and mg kg -1, respectively. For sea bass these contents were 7.46 mg kg -1 and mg kg -1. One-way ANOVA showed significant differences in heavy metals content among the tissues for both studied species (p<0.001). For an average consumer in Greece, the estimated daily intake of Cu and Zn from the consumption of wild sea bream and sea bass was lower than the Allowed Daily Intake (ADI) and the Reference Doses (RfD) of these metals (JECFA 2003, Ikem & Egilla 2008, Onsanit et al. 2010, USEPA 2012). In all cases, the hazard quotient (HQ) for both studied species was less than 1 (Table 1). Table 1: Daily intake of Cu and Zn (κg kg -1 bw d -1 ) by consumers through consumption of wild fish in the Pagasitikos Gulf. (EDI: Estimated Daily Intake, ADI: Allowed Daily Intake, (RfD) Reference Doses, HQ: Hazard Quotient). Species Copper Zinc EDI S. aurata D. labrax ADI ADI RfD HQ S. aurata D. labrax : Calculated from the provisional tolerance weekly intake set by the JECFA (2003) 2: Calculated from Ikem &Egilla (2008) 4. Disscussion Comparing the mean contents of Cu and Zn in the tissues of the two species fished in the same location, higher contents of the metals were observed in D. labrax. Levels of heavy metals in the environment, size (weight - length) of individuals and stage of development are all considered to be important factors affecting the content of metals in aquatic organisms. Type of fish also seems to be a very important factor for the accumulation of elements in fish tissues. This could be due to differences in physiology between the two species (Kalantzi et al. 2013). In all cases maximum contents of heavy metals were detected in liver tissue of sea bream and sea bass. The accumulation of elements in different fish tissues depends on the function of each tissue, the uptake route, the physiology of the fish species and behavioural factors such as habitat use and feeding habits, as well as the degree of contamination (Alam et al. 2002). Metals and trace elements chiefly accumulate in metabolically active tissues (Saha et al. 2006, Adhikari et al. 2009). The liver has been shown to be the main storage tissue for metals. It is well known that a great deal of metallothionein induction occurs in the liver tissue of fish (Alam et al. 2002, Cogun et al. 2006, Ferreira et al. 2008). The differences between metal contents in the different tissues may be a result of their differing capacity to induce metal-binding proteins such as metallothioneins (Canli & Atli 2003). In assessing health risks for human consumption of these fish, a comparison with limits for Cu and Zn in edible parts of fish which have been established by various national or international authorities showed that both species had lower contents than the values set for safety standards. Furthermore, a comparison of estimated daily intake (EDI) with allowed daily intake and reference doses (RfD) demonstrates that there is no obvious risk for human health from Cu and Zn through consumption of S. aurata and D. labrax caught in this area of Greece. In all cases the contents of the metals in the muscle tissue of both studied species were lower than the maximum limits allowed for food (Kalantzi et al. 2013). References Adhikari S., Ghosh L., Rai S.P., Ayyappan S. (2009). Metal concentrations in water, sediment, and fish from sewage fed aquaculture ponds of Kolkata, India. Environmental Monitoring and Assessment 159,

154 Alam M.G.M., Tanaka A., Allinson G., Laurenson L.J.B., Stagnitti F., Snow E.T. (2002). A comparison of trace element concentrations in cultured and wild carp (Cyprinus carpio) of Lake Kasumigaura, Japan. Ecotoxicological Environmental Safety 53, Canli M., Atli G. (2003). The relationships between heavy metal (Cd, Cr, Cu, Fe, Pb, Zn) levels and the size of six Mediterranean fish species. Environmental Pollution 121, Castritsi-Catharios J., Neofitou N., Vorloou A.A. (2014). Comparison of heavy metals concentrations in fish samples from three fish farms (Eastern Mediterranean) utilizing antifouling paints. Toxicological and Environmental Chemistry, DOI: / (in press). Catsiki V.A., Strogyloudi E. (1999). Survey of metal levels in common fish species from Greek waters. Science of the Total Environment 238, Cogun H.Y., Yuzereroglu T.A., Firat O., Gok G., Kargin F. (2006). Metal concentrations in fish species from the Northeast Mediterranean Sea. Environmental Monitoring and Assessment 121, Evans D.W., Dodoo D.K., Hanson P.J. (1993). Trace elements concentrations in fish livers. Implications of variations with fish size in pollution monitoring. Marine Pollution Bulletin 6, Ferreira M., Caetano M., Costa J., Pousão-Ferreira P., Vale C., Reis-Henriques M.A. (2008). Metal accumulation and oxidative stress responses in cultured and wild, white sea bream from Northwest Atlantic. Science of the Total Environment 407, Gale N.L., Adams C.D., Wixson B.G., Loftin K.A., Huang Y.W. (2004). Lead, zinc, copper, and cadmium in fish and sediments from the Big River and Flat River Creek of Missouri's Old Lead Belt. Environmental Geochemistry and Health 26, Giannakopoulou L., Neofitou C. (2014). Heavy metal concentrations in Mullus barbatus and Pagellus erythrinus in relation to body size, gender, and seasonality. Environmental Science and Pollution Research 21, Gupta A., Rai D.K., Pandey R.S., Sharma B. (2009). Analysis of some heavy metals in the riverine water, sediments and fish from river Ganges at Allahabad. Environmental Monitoring and Assessment 157, Ikem A., Egilla J. (2008). Trace element content of fish feed and bluegill sunfish (Lepomis macrochirus) from aquaculture and wild source in Missouri. Food Chemistry 110, Joint Food and Agriculture Organization/World Health Organization Expert Committee on Food Additives (JECFA) (2003). Summary and Conclusions of the 61 st Meeting of the Joint FAO/ WHO Expert Committee of Food Additives. JECFA/61/Sc, Rome, Italy, 10, Kalantzi I., Black K.D., Pergantis S.A., Shimmield T.M., Papageorgiou N., Sevastou K., Karakassis I. (2013). Metals and other elements in tissues of wild fish from fish farms and comparison with farmed species in sites with oxic and anoxic sediments. Food Chemistry 141, Linnik P.M., Zubenko I.B. (2000). Role of bottom sediments in the secondary pollution of aquatic environments by heavy metal compounds. Lakes and Reservoirs: Research and Management 5, Malik N., Biswas A.K., Qureshi T.A., Borana K., Virha R. (2010). Bioaccumulation of heavymetals in fish tissues of a freshwater lake of Bhopal. Environmental Monitoring and Assessment 160, Onsanit S., Ke C., Wang X., Wang K.J., Wang W.X. (2010). Trace elements in two marine fish cultured in fish cages in Fujian province, China. Environmental Pollution 158, Saha M., Sarkar S.K., Bhattacharya B. (2006). Interspecific variation in heavy metal body concentrations in biota of Sunderban mangrove wetland, northeast India. Environment International 32, Salomons W., Förstner U. (1984). Metals in the hydrocycle. Springer Berlin Heidelberg, New York, pp 352. Tsangaris C., Kaberi H., Catsiki V.A. (2013). Metal levels in sediments and transplanted mussels in Pagasitikos Gulf (Aegean Sea, Eastern Meditteranean). Environmental Monitoring and Assessment 185, United States Environmental Protection Agency (USEPA) (1996). Method 3052: microwave assisted acid digestion of silicious and organically based matrices, physical/ chemical methods. USEPA, Washington, DC. United States Environmental Protection Agency (USEPA) (2012). Fish Tissue Screening Levels. U.S. EPA, Region 3, Philadelphia, PA. 154

155 THE EFFECTS OF RAINBOW TROUT (Oncorhynchus mykiss) FARMS ON WATER QUALITY OF KHALKAI RIVER, MASAL, GUILAN Shariati F. *, Rahimi S., Ooshaksaraie L., Khara H. 1. Department of Environment, Islamic Azad University, Lahijan Branch, Iran ABSTRACT Khalkaie River is located in the northern part of Iran enters international Anzali wetland, Iran. In this study, the effects of trout farm effluents on the water quality parameters and self-purification in Khalkai River were investigated. Four trout farms and eight stations were selected. Physicochemical characteristics and nutrients of water were monitored monthly in a five-month period. All the parameters showed fluctuations at different stations. BOD, COD, nitrite and nitrate of water had significant differences between farm and control stations (p<0.05). Temperature, phosphate and dissolved oxygen showed significant monthly differences (p< 0.05). These results were due to the effects of trout farms and the self-purification of river. These factors have had changes during different months, which the main reason of that are changing environmental conditions and severity of rainbow trout farms activities. Keywords: aquaculture, biochemical oxygen demand, chemical oxygen demand, Khalkaie River, nitrate, phosphate, self-purification. Corresponding author: Fatemeh Shariati (shariat_20@yahoo.com)* 1. INTRODUCTION In recent years, construction of fish farms along rivers has increased the discharging of effluent from fish farms into streams, causing a loss of balance in the water ecosystems (Sani, 1997). Aquaculture effluents enter rivers and streams without any purification process. Papatryphon et al, 2005 and Sindilariu and Alabaster found that there was for every ton of fish produced, kg unused food and kg stool is discharged into the water system (Philips & Ross, 1985). Salmon farm effluent consists mainly of three pollutants; 1: suspended solids (fish faeces and food residues); 2: dissolved substance by the fish is released to the environment that contains more organic carbon and soluble nitrogen compounds (ammonium and urea) and 3: residual chemicals from drug therapy, antibiotics and various fungicides. The first two categories cause chemical disturbances in the water (Camargo and Pulatsu, 2007). Khalkai River located in Masal city is one of the branches of Anzali wetland which is important due to its entry into this international lagoon. The construction of fish farms besides Khalkai River is common and every year the establishment of new farms is growingly increased. Thus, regarding the importance of Khalkai River whether from environmental point of view or in terms of its role and impact on the local and national economy, the impact of rainbow trout farm effluents on Khalkai River can be specified and water quality of river can be assessed by measuring some physicochemical properties of water in different areas of the river and comparing them in different locations of those rainbow trout farms. 2. Materials and Methods In this study, four trout farms called Chesli (A), Shalma (B), Ramine(C), Salimabad (D) were selected based on the given information of the location of farms. There was an entrance station before each trout farm (control farm) and an outlet station after each trout farm (farm station) (Fig.1). Sampling water for determination of its physiochemical characteristics and nutrients was performed from control and farm water of each farm of the river during five months period (May-September) according to the growing period of Rainbow Trout. Parameters including electrical conductivity (EC), ph, dissolved oxygen (DO) was measured in place by multi-meter instrument (WTW, Germany). To 155

156 measure BOD in the sampling station, the water samples were taken to the lab by Winkler bottles and reagents manganese sulfate, alkali iodide and sulfuric acid were added to stabilize the dissolved oxygen. In order to measure other parameters (COD, NO 3, NO 2 and or PO 4 ) the water were taken in polyethylene containers and the samples were then transported to the laboratory in the possible shortest time. Measurement of COD and BOD 5 was conducted by using standard method (standard method, 1996). Measurement of dissolved oxygen was conducted by using Winkler method (Standard method, 2005) and TDS by TDS-meter (Hughes, 1978; Tarzwell, 1965). Measuring NO 2, NO 3 and PO 4 were performed by spectrophotometric method by adding appropriate chromogenic reagents (Jenway UV.Vis-610, 5 England) (standard method, 1996). Data analyzed using the SPSS software version 17. In this software, non-parametric Kruskal-Wallis test and Mann Whitney test were used to study the significant difference s of physico-chemical data and between the scrutiny of study stations. Comparison of the calculated data and drawing graphs were done with Excel software packages. Figure1. Location of sampling stations and trout farms on the Khalkaie River. 3. Results Mean values of water physicochemical parameters of Khalkai River for each station in five month are given in Table 1. Mean minimum control and farm temperature at in the month of May and June have been and17.05 C, respectively, and the maximum in control and farm temperature in August have been19 and 20 C, respectively. The Analysis showed that there was a significant difference in control and farm temperatures between stations and different seasons (p < 0.05). One of the most important hydrochemical parameters of water is DO which decreased in the most critical conditions in summer following the increase in temperature sand high levels of BOD 5.The analysis showed there were not significant differences between stations and between different seasons (P>0.05). The minimum control and farm BOD is 3.66 and 7.41 mg/l, respectively, and the maximum in control and farm BOD is 8.52 and 16.14, respectively. The analysis showed significant differences between stations during the study period (P<0.05). The minimum in control and farm COD is 5.56 and mg/l, respectively, and the maximum in control and farm COD is and mg/l, respectively. Based on the results, COD had significant difference between the control stations (P<0.05). During the study of phosphate in each season, it was shown that the minimum amount of control and farm phosphate in May was 0.05 and 0.02 mg/l, respectively and maximum in control and farm phosphate at December was and 0.16, respectively. The results analyses is revealed that there was a significant difference in incoming PO 4 among different seasons (P<0.05).The minimum in control and farm NO 3 is 5.08 and 5.37 mg/l, respectively, and the maximum in control and farm NO 3 is 9.71 and 10.31, respectively. NO 3 between farm and control stations have had a significant difference (P<0.05). Also, studying NO 3 in different seasons showed that the minimum amount of control and farm NO 3 in July has been 7.34 and 7.50 mg/l, respectively, and the maximum in control 156

157 and farm NO 3 was in August which have been 8.21 and 8.65 mg/l, respectively. Analysis of the results showed that there were not significant differences in NO 3 between different seasons (P>0.05). Also, studying NO 2 in different seasons showed that the minimum amount of control NO 2 was in May and its maximum amount was in July, also the minimum farm NO 2 in June and its maximum in August. Analysis of the results showed that there were not significant differences in nitrate between different seasons (P>0.05). The TDS analysis showed no significant difference among stations during the study, and between different seasons (P>0.05). In revision of the two parameters EC and ph, the analysis showed there were not significant difference among stations and among different seasons during the study (P>0.05). Table 1: Water quality parameters of Khalkai River during study period (Mean ± Standard error) 157

158 COD NO2 temprature BOD HydroMedit 2014, November 13-15, Volos, Greece Seasons Seasons entrance out entrance out entrance out Seasons entrance out Seasons 158

159 May June July August Septem PO4 NO3 HydroMedit 2014, November 13-15, Volos, Greece entrance out Seasons entrance out Seasons Fig.2. Analysis results of parameters temperature, COD, BOD, PO 4, NO 3 and NO 2 in different seasons 4. Discussion An important factor that determines the water quality in streams is BOD 5, which the average amount of BOD 5 in survey stations was in the range of mg/l during the study period. This parameter at the surveyed stations had raise and fall, so that there was less amount of DO in downstream stations of each farm than its upstream ones, and there was more amount of BOD 5 in those areas than the upstream ones. Numerous scientific studies were performed regarding the effluent amount and composition of fish farms and their environmental impacts on aquatic ecosystems in the world (Esmaili,Sari, 2004; Kazemzade Khajui.et al, 2002; Bergheim and Brinker, 2003). Phosphate level in surface natural waters based one existing resources and environmental standards, have been expressed a maximum of 0.1mg/L (EPA, 1996).According to the values obtained in the survey stations, there were significant differences between different months,and the stations after the fish farms are not in good conditions. Nitrite should not be more 0.51 mg/l than in terms of environmental standard (McNeely and Neiman is, 1979). In the survey performed in all stations, nitrite levels are in a desirable condition except Station2. Nitrate has been reported less than 1 mg/l in surface waters based on environmental standards (EPA, 1996). In the present study, nitrate have shown a significant differences in the stations before and after the fish farms, and nitrite levels are in an undesirable condition in all stations. Also, it was determined that the nutrients have been decreasing, so that in summer by increased rate of farm activities and increased flow rate of river water and increased temperature, impacts of farms effluents on the river ecosystem severely increased. Also, studies conducted by The Fisheries organization of Mazandaran province in2005, Ghane Sasan Saraie (2004) and Boaventura et al.,(1997) confirmed producing significant amounts of nutrients from the fish farms. In the present study, there was a significant difference in temperature between different months, but no significant differences between stations observed. It can also be inferred that temperature is increasing in the stations that are affected by the fish farm effluents, however, this temperature difference is not too noticeable. Sani (1998) also concluded the trend of changes in dissolved oxygen in Dohezar River follows monthly changes and subsequent change in water temperature. The results from COD level indicate significant changes of index in survey stations, so that reaches its highest amount with rate of mg/l in station 8 which is affected by the fish farm 159

160 effluents from upstream farms, that can be ensured from the waste water impact of the fish farms on COD of Khalkai River water. Trojanaowski (1990) showed that increased temperature in summer accelerates the mineralization process and COD increases. Kelly.et al (1998) conducted studies on inland waters in America showed that waters with electrical conductivity µs/cm have mixed fishery value and outside this range indicates that they are not suitable for specific groups of fisheries and invertebrates. EC higher than this range and its significant changes in studied places can indicate the arrival of another pollution source, especially industrial pollutants to the river. In the present study, this factor did not show a significant difference between different stations within the study period. So, EC of the studied area at Khalkai River is in a normal range and this area has fisheries and environmental capabilities. Regarding what expressed, it can be inferred that wastewater output of rainbow trout farms at Khalkai River have impact on water quality parameters and the results of their impacts on some basic parameters such as BOD, COD, NO 3, NO 2 and PO 4 were clear. It must be noted that activity of each farm alone have not a reasonable impact on the water quality parameters but all activities of fish farms in the studied area in a process have resulted in differences of water quality. The study of self-purification trend of the river also demonstrates its high capacity in self-purification, but also the fish farms effluent is discussed as a major problem of water quality in the studied area, especially in hot seasons. Since organic nutritional value of handy food is more than concentrated food, so it is better to use good-quality concentrated food in feed fish of all fields, and given that the effluents of all the farms and also sewages of villages located in the border of the river directly enters into the river ecosystem, so it is better all these units to use systems equipped with effluent and sewage treatment plant. Now it seems that the specified distances between the farms in Khalkaie River have no scientific basis, therefore it is necessary to prevent dispersed works by supplementary studies and by creating complexes of fish production until the river is given more opportunity for self-purification. Finally, with proper management of fish farms and determining the right distance between fish farms based on the self-purification rate of the river which have scientific basis, we can make sustainable fisheries exploitation without being worried about the natural landscapes of Khalkaie River ecosystem. References Bergheim A., Brinker A. (2003). Effluent treatment for flow through systems and European Environmental Regulations. Aquacultural Engineering 27, Boaventura, R., A. M. J. Pedro Coimbra, E. Lencastre (1997). Trout farm effluents : Characterization and impact on the receivingstreams; Environmental Pollution. 95: Camargo J., Gonzalo C. (2007). Physicochemical and biological changes downstream from a trout farm outlet: Comparing 1986 and 2006 sampling surveys. Journal of Limnetica 26, Environmental Protection Agency (1996). Quality criteria for waters,washington D.C. Esmaili Sari, A. (2004). Hydrochemistry: foundations of aquaculture; Tehran, Aslani publications. Esmaili Sari, A. (2000). Principles of Water Quality Management in aquaculture; Tehran: Iranian Fisheries Research Institute. Hughes, B. D. (1978). The influence of factors other than pullotion on the value of Shannon,s diversity index for benthic macroinvertebrates in streams. Water. Res. 12: Ghane Sasan Saraie. A. (2004). Identifying the population structure of Chafrood River macrobenthos in Gilan province regarding some water quality parameters (in the scope of Or man Malal village); M.S Thesis;Teacher Training University; P98. Kazemzade Khajui A., Ismaili Sari A., Ghasempouri M. (2012). The pollution investigation resulting from trout farms at HarazRiver.Iran Marine Science and Technology Journal.Summer 81. p8. Kelly, T. R., J. Herida, and J. Mothes (1998). Sampling of the Mackinaw River in central Illinois for physicochemical and bacterial indicators of pollution. Transaction of Illinois State Academy of Science, 91, McNeely, R. N. and V. P. Neimanis (1979).Water quality sourcebook, A guide to waterquality parameter, water quality branch.otawa, Canada. Naderi Jelodar M., Esmaili Sari A., Ahmadi M., SaifAbadi J., Abdoli A. (2006). The pollution investigation resulting from rainbow trout farms on the water quality parameters of Haraz River. Environmental Sciences. 4(2), 18. Papatryphon, E., Petit, J., Hayo, V., Kaushik, S.J., and Claver, K. (2005). Nutrient-balance modelling as a tool for environmental management in aquaculture: The case of trout farming in France. Environmental Management, 35 (2),

161 Philips M. G. and Ross, L. (1985) The environmental impact of salmonid cage culture on inland fisheries. Journal of fish biology 27, Pulatsu S., Rad F., Kaksal G., Aydin F., Karasu Benli A., Topçu A. (2004). The impact of rainbow trout farm effluents on water quality of Karasu stream, Turkey. Turkish Journal of Fisheries and Aquatic Sciences 4, Sani H. A. (1997) The survey on pollution from trout farms on Dohezar River ecosystem and its self purification, MS Thesis, Faculty of natural resources, Tehran University, p.95. Tarzwell, C. M. (1965). Biological problems in water pollution: Third Seminar U.S. Pub. Health Serv. Div. Water Supply and Pollut. Control, Cincinnati. Trojanowski, J. (1990). Various forms of phosphorus in bottom sediments of selected coastal lakes. Pol. Arch. Hydrobiol. 37(3):

162 BIOCHEMICAL EFFECTS OF ALMIX HERBICIDE IN THREE FRESHWATER TELEOSTEAN FISHES Samanta P. 1, Pal S. 2, Mukherjee A.K. 3, Senapati T. 4 Ghosh A.R. 1 * 1 Ecotoxicology Lab, Department of Environmental Science, The University of Burdwan, Golapbag, Burdwan, West Bengal , India 2 Department of Environmental Science, Aghorekamini Prakashchandra Mahavidyalaya, Subhasnagar, Bengai, Hooghly, West Bengal , India 3 P.G. Department of Conservation Biology, Durgapur Government College, Durgapur,West Bengal , India 4 School of Basic and Applied Sciences, Poornima University, Jaipur, Rajasthan , India Abstract Freshwater teleostean fishes Anabas testudineus, Heteropneustes fossilis and Oreochromis niloticus were exposed to almix (66.67 mg/l) for a period of 30 days to investigate the toxicological responses on acetylcholinesterase (AChE), oxidative and antioxidant enzymes. AChE activity was increased significantly (p< 0.05) in muscle, brain and spinal cord in all test fishes, highest in muscle of H. fossilis but lowest in spinal cord of A. testudineus. Significant increased lipid peroxidation (LPO) level in all tissues was observed after almix intoxication, maximum in liver of O. niloticus and minimum in brain of H. fossilis. Catalase (CAT) activity was increased significantly in all fish tissues after almix exposure while glutathione-s-transferase (GST) showed significant reduced activity in liver, in particular, maximum in liver of H. fossilis. Protein content in all concerned tissues was significantly declined and highest reduction was observed in muscle of A. testudineus while lowest in liver of H. fossilis. So, the present study is able to shed light on the changes in acetylcholinesterase activity, oxidative parameters and antioxidant enzyme profile under long-term exposure of almix and these responses can be used as indicators of herbicidal contamination. Keywords: Almix, Antioxidant enzymes, Teleostean fishes *Corresponding author: Apurba Ratan Ghosh (apurbaghosh2010@gmail.com) 1. Introduction Bioaccumulation and non-biodegradable nature of the pollutants may pose a serious threat to the non-target aquatic organisms and ultimately cause health risk to human beings (Binelli & Provini 2004). These surface water contaminants from industrial processes or agricultural runoff are the major contributors of aquatic system at local, regional, national, even at global levels (Palus et al. 1999; Cerejeira et al. 2003). Almix 20WP (a third generation herbicide) attacks and destroys the broad leaf weeds and sedges by stifling the growth of rice crop. It is a combination of 10% metsulfuron methyl, 10% chlorimuron ethyl and 80% adjuvants (Safety Data Sheet 2012). Fishes are recognized as sentinel organisms for ecotoxicological studies because they are continuously exposed to different types of toxic chemicals coming from different anthropogenic sources. They also play a significant role in evaluating the potential risk associated with contamination in aquatic environment (Lakra & Nagpure 2009) and can predict an early detection of aquatic contamination (van der Oost et al. 2003). Fishes possess a defensive mechanism to counteract the impact of oxidative stress posed by environmental contaminants such as herbicides, heavy metals and insecticides. These create imbalance between pro-oxidants and antioxidants ratio, leading to generation of reactive oxygen species (ROS) such as hydrogen peroxide (H 2 O 2 ), superoxide anion (O 2 - ) and hydroxyl radical (OH ) which have recently come into focus in the field of ecotoxicology (Facerney et al. 2001; Monteiro et al. 2006). ROS reacts with biological macromolecules at supramolecular levels having gained potency and leads to enzyme inactivation, lipid peroxidation (LPO), DNA damage and even cell death (Peña-Llopis et al. 2003). Catalase, an enzymatic antioxidant, catalyzes H 2 O 2 produced by dismutation of superoxide anions into less toxic water and oxygen molecules (Lushchak et al. 2001). Glutathione-S-transferases, a phase II biotransformation enzyme, catalyze the conjugation of glutathione into a variety of compounds which are involved in transportation and elimination of reactive compounds (Sies 1993). The Lipid peroxidation (LPO) is a secondary LPO product and regarded as an indicator of biochemical toxicity of environmental contaminants (Draper et al. 1993). AChE activity also has been selected as biomarker of pesticidal toxicity in fish by different authors (Moraes et al. 2007) and hence plays a vital role in physiological functioning of fish (Dutta & Arends 2003). Here, three Indian air-breathing food teleosts viz., Anabas testudineus (Bloch), Heteropneustes fossilis (Bloch) and Oreochromis niloticus (Linnaeus) were 162

163 selected for toxicity testing of almix and its effect on aceylcholinesterase activity, oxidative parameters and antioxidant enzyme levels in these fishes. 2. Materials and methods 2.1. Experimental Design: Three Indian freshwater teleosts, Anabas testudineus (Bloch), Heteropneustes fossilis (Bloch), and Oreochromis niloticus (Linnaeus) of both sexes with an average weight of ± 2.47 g, ± 5.41 g, and ± 5.28 g respectively and total length of ± 0.55 cm, ± 0.74 cm, and ± 0.54 cm respectively were procured from the local market and were acclimatized separately to congenial laboratory condition for 15 days in aquaria of 250 L capacity. After 15 days, fishes were divided into two groups the nonexposed group (control) and exposed group (almix-treated) and maintained in 250 L aquaria, containing 10 fishes in each (triplicate). The treated sets of fishes were exposed to sublethal dose of almix, i.e., mg/l in 250 L aquaria for a period of 30 days (Samanta et al. 2013). Doses were applied on every alternate day. During the period of experiment both the treated and control group of fishes were fed with minced goat liver and maintained very carefully Sampling: After completion of the experiment i.e., 30 days, fishes were sacrificed and desired tissues of liver, gill, brain, spinal cord and muscle were rapidly removed. Then tissues were quickly washed with 0.75% saline solution, soaked with filter paper, packed in Teflon tubes and finally stored at -20 o C for biochemical analysis, viz., AChE activity, lipid peroxidation, catalase activity, glutathione-s-transferase activity and total protein content Biochemical analysis: Acetylcholinesterase activity was measured according to the method of Ellman et al. (1961). Lipid peroxidation level was assessed by measuring the TBARS formation as described by Ohkawa et al. (1979). Activity of catalase (CAT) was determined according the procedure of Aebi (1974). The activity of GST was determined according to the method of Habig et al. (1974). All assays were run in triplicate. The protein content was estimated by the Folin-Phenol reaction method as described by Lowry et al. (1951). 3. Results and Discussion The present study is the maiden attempt to report on the toxicity of the almix herbicide with regard to biochemical activities of enzymes namely AChE, CAT, LPO and GST in three Indian freshwater teleosts, A. testudineus, H. fossilis, and O. niloticus, although some authors worked on some other biochemical parameters such as alkaline phosphatase, aspartate aminotransferase, alanine aminotransferase and glucose-6-phosphatase in different fish tissues under almix exposure in the laboratory condition (Jabeen et al in Cyprinus carpio and Samanta et al in A. testudineus, H. fossilis and O. Niloticus) Acetylcholinesterase (AChE) activity induction Acetylcholinesterase activity in all tissues of the test fishes exposed to almix herbicide in the laboratory condition is presented in the Table 1. Acetylcholinesterase activity was significantly increased (p< 0.05) in all tissues. In muscle, AChE was raised to % (0.057 to 0.165) in H. fossilis followed by % (0.062 to 0.179) in O. niloticus and % (0.076 to 0.199) in A. testudineus; similar pattern was also observed in spinal cord while brain showed % (0.069 to 0.197) in H. fossilis followed by % (0.066 to 0.187) in A. testudineus and % (0.075 to 0.202) in O. niloticus. Overall highest AChE activity was observed in muscle of H. fossilis. Increased acetylcholinesterase activity in the present investigation in all concerned fish tissues may be due to an accumulation of acethylcholine in the tissues which ultimately lead to overstimulation of the receptors or undesirable effects due to herbicide toxicity. Similar trend of increased AChE activity in muscle of L. obtusidens exposed to clomazone (0.5 mg/l) was reported by Moraes et al. (2007), by Moraes et al. (2009a) in brain of Cyprinus carpio exposed to imazethapyr and imazapic and by Miron et al. (2005) in brain of Rhamdia quelen exposed to quinclorac (5 20 mg/l) and metsulfuron methyl ( mg/l). Inhibition of muscle AChE activity in fish species was reported by Ferna ndez-vega et al. (2002) in Anguilla anguilla; and by Dutta & Arends (2003) in Lepomis macrochirus. Therefore, this induced AChE activity may adversely affect cholinergic neurotransmission process which ultimately causing undesirable effects in fish and the response of these fish species to almix could be considered as biomarker of herbicide toxicity. 163

164 Table 1 Analysis of acetylecholinesterase (unit/mg protein/min) in control and almix-treated fishes Tissues A. testudineus H. fossilis O. niloticus Control Treated Control Treated Control Treated Muscle 0.076± ±0.041* 0.057± ±0.007* 0.062± ±0.003** Brain 0.066± ±0.088** 0.069± ±0.078* 0.075± ±0.086* SC 0.059± ±0.023* 0.057± ±0.059* 0.062± ±0.036* Paired t test: * p< 0.05 ** p< Data are reported as mean ± SEM (n = 9) Oxidative stress markers Lipid peroxidation is one of the commonly used markers of oxidative stress. Lipid peroxidation level in different tissues of test fish species enhanced significantly (p< 0.05) and is presented in the Table 2. LPO level in case of liver was raised up to % (2.38 to 6.25) in O. niloticus followed by % (2.77 to 6.26) in H. fossilis and % (3.12 to 6.37) in A. testudineus, while other tissues namely muscle, gill and brain showed significant highest elevation in O. niloticus and lowest in H. fossilis. Considering all the tissues, liver of O. niloticus (262.99%) showed highest elevation in LPO level but lowest in brain of H. fossilis (134.71%). The result revealed that O. niloticus was more sensitive than other two fish species. Enhanced LPO levels in liver, muscle, gill and brain of test fishes indicated development of oxidative stress in these tissues as a compensatory response by the fish against the herbicidal stress. Present results are also in agreement with Ballesteros et al. (2008) and Li et al. (2003) who observed increased LPO level in Jenynsia multidentata exposed to endosulfan for a period of 24 h and in Carassius auratus exposed to 3, 4- dichloroaniline (0.4 mg/l) for 15 days respectively. Different LPO level in different fish tissues in the present study confirmed varied defence mechanism of fish species in relation to pesticide (Ahmad et al. 2000). The present result ensures the significant changes in LPO production in all the tissues of the concerned test fishes. Table 2 Analysis of lipid peroxidation (unit/mg protein/min) in control and almix-treated fishes Tissues A. testudineus H. fossilis O. niloticus Control Treated Control Treated Control Treated Liver 3.12± ±0.199** 2.77± ±0.467** 2.38± ±0.559** Muscle 2.05± ±0.270* 3.42± ±0.413** 1.62± ±0.117** Gill 3.03± ±0.196** 5.64± ±0.524* 3.19± ±0.360* Brain 3.41± ±0.238* 12.39± ±1.04** 3.47± ±0.200** Paired t test: * p< 0.05 ** p< Data are reported as mean ± SEM (n = 9) Antioxidant enzyme activity Antioxidant enzyme, catalase plays a vital role in detoxifying the xenobiotics. In the present study, catalase activity in concerned tissues showed significant elevation (p< 0.05) (Table 3). Catalase activity in liver showed maximum elevation % (57.03 to ) in H. fossilis followed by173.68% (77.37 to ) in A. testudineus and % (66.49 to 99.18) in O. niloticus. Similar pattern of enhanced activity was also observed in muscle and brain tissue. CAT activity in case of gill was raised maximally up to % (48.71 to 74.28) in O. niloticus while lowest increment was observed % ( to ) in H. fossilis. Enhanced CAT activity in all tissues may probably due to increased hepatic levels of oxyradicals such as ROS and indicated lack of antioxidant response against herbicide toxicity. Increased LPO level in all tissues in the present work also led to increased CAT activity. Here, different CAT levels in different fish tissues and species may be due to variation in the antioxidant defence mechanism of fish in relation to type species or habitat or feeding behaviour of the species. The results were also in consonance with the findings of Peixoto et al. (2006) and Moraes et al. (2007). Therefore, present study reflects two things: oxidative change in the tissues due to increased CAT activity, and subsequent detoxification of the herbicide. Glutathione-S-transferase is an enzymatic antioxidant and plays a vital role to protect the cell against the effects of xenobiotic substances. Here, GST activity was significantly decreased (p< 0.05) in liver of all the test fishes (Table 4). GST reduction in liver of H. fossilis was 81.43% (8.70 to 7.09) followed by71.45% (5.57 to 3.98) in O. niloticus and 69.21% (2.89 to 2.00) in A. testudineus. 164

165 Decreased GST activity in liver may be due to the failure of detoxification phenomenon of herbicide and development of oxidative stress. The result was also in agreement with Ballesteros et al. (2009b) who observed decreased GST in gills, liver, and muscle of Jenynsia multidentata exposed to endosulfan and with Menezes et al. (2011) who observed reduced GST level in liver of R. quelen exposed to Roundup. Reduced GST activity here indicated that almix caused damage to the antioxidant defence system as well as in detoxification process of teleostean fishes. So it may be used as a biomarker of almix toxicity. Table 3 Analysis of catalase (unit/mg protein/min) in control and almix-treated fishes Tissues A. testudineus H. fossilis O. niloticus Control Treated Control Treated Control Treated Liver 77.37± ±5.57* 57.03± ±6.49** 66.49± ±3.51** Muscle 52.95± ±2.17* 81.30± ±14.90* 67.26± ±5.07* Gill ± ±7.18* ± ±3.02* 48.71± ±2.97* Brain 92.76± ±2.51** ± ±4.79** 90.32± ±7.34* Paired t test: * p< 0.05 ** p< Data are reported as mean ± SEM (n = 9). Table 4 Analysis of glutathione-s-transferase (nmol/mg protein/min) in control and almix-treated fishes Tissue A. testudineus H. fossilis O. niloticus Control Treated Control Treated Control Treated Liver 2.89± ±0.265* 8.70± ±0.334** 5.57± ±2.35* Paired t test: * p< 0.05 ** p< Data are reported as mean ± SEM (n = 9) Metabolic parameter Protein content, in the present work, showed significant decline (p< 0.05) in all concerned fish tissues under herbicide contaminated condition (Table 5). Here, reduction of protein content was highest in muscle of A. testudineus i.e., 91.79% (70.55 to 64.76) and lowest in liver of H. fossilis i.e., 53.71% (62.99 to 33.83). Similar results were also reported by David et al. (2004) and Fonseca et al. (2008). Present results reflect the catabolism of proteins as a compensatory defence mechanism under oxidative stress condition to meet the high energy demand, so it can be inferred that catabolism of proteins play an important role in maintaining the cellular architecture and physiology of energy production. Table 5 Analysis of protein content (mg/g) in control and almix-treated fishes Tissues A. testudineus H. fossilis O. niloticus Control Treated Control Treated Control Treated Liver 53.29± ±1.05** 62.99± ±0.99* 56.75± ±1.38** Muscle 70.55± ±2.16* 57.15± ±3.66** 57.56± ±6.14** Gill 49.51± ±3.86* 52.08± ±2.11** 42.22± ±1.33* Brain 26.00± ±1.67** 24.65± ±2.09** 30.16± ±1.31* SC 72.73± ±4.45* 56.94± ±4.40* 44.17± ±0.90** Paired t test: * p< 0.05 ** p< Data are reported as mean ± SEM (n = 9). 4. Conclusion Present study discloses that commercial herbicide almix causes changes in AChE activity, oxidative stress parameters, and antioxidant defence mechanism in three freshwater teleosts, A. testudineus, H. fossilis, and O. niloticus. The altered activity of AChE, LPO, CAT and GST in different fish tissues indicated perturbation in internal integrity of biochemical and/or physiological processes by almix-induced free radical toxicity and the responses displayed by these fish species could be considered as bioindicators of herbicide toxicity in aquatic ecosystem. Finally, from an 165

166 ecotoxicological view point, use of this herbicide in agriculture and aquatic bodies must be handled very carefully and monitored judicially. Acknowledgements The authors would like to thank Department of Science & Technology, Govt. of India for the financial assistance. We would also like to thank the Head, Department of Environmental Science, The University of Burdwan, Burdwan, West Bengal, India for providing the laboratory facilities during the course of research. We do also like to acknowledge Dr Sukriti Ghosal, Principal, MUC Women s College, Burdwan and Part-time Faculty of Dept. of English, The University of Burdwan for necessary editing the English language of the manuscript. References Aebi H. (1974). Catalase in vitro. Methods in Enzymology 105, Ahmad I., Hamid T., Fatima M., Chand H.S., Jain S.K., Athar M., Raisuddin S. (2000). Induction of hepatic antioxidants in freshwater catfish (Channa punctatus bloch) is a biomarker of paper mill effluent exposure. Biochimica et Biophysica Acta 1523(1), Ballesteros M.L., Wunderlin D.A., Bistoni M.A. (2009b). Oxidative stress responses in different organs of Jenynsia multidentata exposed to endosulfan. Ecotoxicology and Environmental Safety 72(1), Ballesteros S., Reales J.M., Mayas J., Heller M.A. (2008). Selective attention modulates visual and haptic repetition priming: Effects on ageing and Alzheimer s disease. Experimental Brain Research 189(4), Binelli A., Provini A. (2004). Risk for human health of some POPs due to fish from Lake Iseo. Ecotoxicology and Environmental Safety 58(1), Cerejeira M.J., Vianab P., Batistaa S., Pereiraa T., Silvaa E., Valerio M.J., Silvaa A., Ferreirab M., Silva-Fernandes A.M. (2003). Pesticides in Portuguese surface and ground waters. Water Research 37(5), David M., Mushiger S.B., Shivakumar R., Philip G.H. (2004). Response of Cyprinus carpio (Linn.) to sublethal concentration of cypermethrin: alterations in protein metabolic profiles. Chemosphere 56(4), Draper H.H., Squires E.J., Mahmoodi H., Wu J., Agarwal S., Hadley M. (1993). A comparative evaluation of thiobarbituric acid methods for the determination of malondialdehyde in biological materials. Free Radical Biology and Medicine 15(4), Dutta H.M., Arends D.A. (2003). Effects of endosulfan on brain acetylcholinesterase activity in juvenile bluegill sunfish. Environmental Research 91(3), Ellman G.L., Courtney K.D., Andres Jr.V. (1961). A new and rapid colorimetric determination of acetylcholinesterase activity. Biochemical Pharmacology 7(2), Facerney C.R.D., Devaux A., Lafaurie M., Girard J.P., Bailly B., Rahmani R. (2001). Cadmium induces apoptosis and genotoxicity in rainbow trout hepatocytes through generation of reactive oxygen species. Aquatic Toxicology 53(1), Ferna ndez-vega C., Sancho E., Ferrando M.D., Andreu E. (2002). Thiobencarb-induced changes in acetylcholinesterase activity of the fish Anguilla anguilla. Pesticide Biochemistry and Physiology 72(1), Fonseca M.B., Glusczak L., Moraes B.S., Menezes C.C., Pretto A., Tierno M.A., Zanella R., Gonçalves F.F., Loro V.L. (2008). 2,4-D herbicide effects on acetylcholinesterase activity and metabolic parameters of piava freshwater fish (Leporinus obtusidens). Ecotoxicology and Environmental Safety 69(3), Habig W.H., Pabst M.J., Jakoby W.B. (1974). Glutathione S-transferases. The first enzymatic step in mercapturic acid formation. Journal of Biological Chemistry 249(22), Jabeen A.A., Bindhuja M.D., Revati K. (2008). Biochemical changes induced by rice herbicide ALMIX20 WP (Metsulfuron-methyl 10%+Chlorimuron-ethyl 10%) on fresh water fish, Cyprinus carpio. Journal of Experimental Zoology, India 11(1), Lakra W.S., Nagpure N.S. (2009). Genotoxicological studies in fishes: A review. Indian Journal of Animal Sciences 79(1), Li W., Yin D., Zhou Y., Hu S., Wang L. (2003). 3,4-Dichloroaniline induced oxidative stress in liver of crucian carp (Carassius auratus). Ecotoxicology and Environmental Safety 56(2), Lowry D.H., Rosenbrough N.J., Farr A.L., Randall R.J. (1951). Protein measurement with folin phenol reagent. Journal of Biological Chemistry 193,

167 Lushchak V.I., Lushchak L.P., Mota A.A., Hermes-Lima M. (2001). Oxidative stress and antioxidant defenses in goldfish Carassius auratus during anoxia and reoxygenation. American Journal of Physiology 280(1), R100-R107. Menezes C.C., Fonseca M.B., Loro V.L., Santi A., Cattaneo R., Clasen B., Pretto A., Morsch V.M. (2011). Roundup effects on oxidative stress parameters and recovery pattern of Rhamdia quelen. Archives of Environmental Contamination and Toxicology 60(4), Miron D., Crestani M., Schetinger M.R., Morsch V.M., Baldisserotto B., Tierno M.A., Moraes G., Vieira V.L.P. (2005). Effects of the herbicides clomazone, quinclorac, and metsulfuron methyl on acetylcholinesterase activity in the silver catfish (Rhamdia quelen) (Heptapteridae). Ecotoxicology and Environmental Safety 61(3), Monteiro D.A., Almeida J.A., Rantin F.T., Kalinin A.L. (2006). Oxidative stress biomarkers in the freshwater characid fish Brycon cephalus, exposed to organophosphon insecticide Folisuper 600 (Methyl parathion). Comparative Biochemistry and Physiology 143(2), Moraes B.S., Loro V.L., Fonseca M.B., Menezes C.C., Marcehsan E., Reimche G.B., Aliva L.A.D. (2009a). Toxicological and metabolic parameters of the teleost fish (Leporinus obtusidens) in response to commercial herbicides containing clomazone and propanil. Ecotoxicology and Environmental Safety 95(2), Moraes B.S., Loro V.L., Glusczak L., Pretto A., Menezes C., Marchezan E., de Oliveira Machado S. (2007). Effects of four rice herbicides on some metabolic and toxicology parameters of teleost fish (Leporinus obtusidens). Chemosphere 68(8), Ohkawa H., Ohishi N., Yagi K. (1979). Assay for lipid peroxides in animal tissues by thiobarbituric acid reaction. Analytical Biochemistry 95(2), Palus J., Dziubattowska E., Rydzynski K. (1999). DNA damage detected by the comet assay in the white blood cells of workers in a wooden furniture plant. Mutation Research 444(1), Peixoto F., Alves-Fernandes D., Santos D., Fontaı nhas-fernandes A. (2006). Toxicological effects of oxyfluorfen on oxidative stress enzymes in tilapia Oreochromis niloticus. Pesticide Biochemistry and Physiology 85(2), Peña-Llopis S., Ferrando M.D., Peña J.B. (2003). Fish tolerance to organophosphateinduced oxidative stress is dependent on the glutathione metabolism and enhanced by N-acetylcysteine. Aquatic Toxicology 65(4), Safety Data Sheet (2012). DuPont Almix 20 WP. Version 2.1, Revision Date (Ref ). Samanta P., Pal S., Mukherjee A.K., Senapati T., Ghosh A.R. (2013). Evaluation of enzymatic activities in liver of three teleostean fishes exposed to commercial herbicide, Almix 20 WP. Proceedings of the Zoological Society, doi: /s z Sies H. (1999). Glutathione and its role in cellular functions. Free Radical Biology and Medicine 27(9&10), van der Oost R., Beyer J., Vermeulen N.P.E. (2003). Fish bioaccumulation and biomarkers in environmental risk assessment: a review. Environmental Toxicology and Pharmacology 13(2),

168 EFFECTS OF CHROMIUM ON TISSUE-SPECIFIC BIOCHEMICAL PARAMETERS IN FRESHWATER CATFISH, Anabas testudineus (Bloch) Kole D. 1, Pal S. 2, Mukherjee A.K. 3, Samanta P. 1, Ghosh A.R. 1 * 1 Ecotoxicology Laboratory, Department of Environmental Science, The University of Burdwan, Golapbag, Burdwan, West Bengal , India 2 Department of Environmental Science, Aghorekamini Prakashchandra Mahavidyalaya, Subhasnagar, Bengai, Hooghly, West Bengal , India 3 P.G. Department of Conservation Biology, Durgapur Government College, Durgapur,West Bengal , India Abstract Present study investigated the effects on glutathione-s-transferase (GST), alkaline phosphatase (ALP), alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in one perch, Anabas testudineus (Bloch) of chromium at two concentrations (25% i.e., mg/l and 50% i.e., mg/l) of sublethal concentration (LC mg/l for 96 hours) for a chronic exposure of 30 days under laboratory condition. The result of different tissues were compared under two different concentrations. GST activity was significantly decreased (p < 0.01) in liver at both the concentrations. The mean value of ALP in intestine and kidney was significantly increased (p < 0.01) under 25% but significantly reduced (p < 0.05) at 50% concentration. But in liver ALP level was significantly decreased (p < 0.05) in both the concentrations. ALT level in gill, liver and heart was significantly increased (p < 0.01) under 25% concentration but reduced significantly (p < 0.05) at 50% while in case of muscle it was increased significantly. AST activity was significantly increased (p < 0.01) in all the tissues at 25% but significantly decreased (p < 0.01) at 50% concentration. These results revealed that different sublethal concentrations of chromium may cause different enzymatic activities in ALP, ALT and AST in freshwater fishes. So, these enzymes may be considered as biomarkars in view of ecotoxicological monitoring as in case of chromium toxicity. Keywords: Chromium, Sublethal concentration, GST, ALP, ALT, AST, Anabas testudineus (Bloch) *Corresponding author: Apurba Ratan Ghosh (apurbaghosh2010@gmail.com) Introduction Metal pollution in the aquatic environment gradually becomes a potential threat to non-target aquatic organisms especially in fish due to their bioaccumulative and non-biodegradable properties. Different sources of heavy metals like industrial, agricultural, and anthropogenic activities are causing hazardous effects to metabolic, physiological and biochemical systems of fishes (Heath 1987; Dethloff et al. 1999; Atli & Canli 2007) at high concentration. It is very unstable in water. Cr among other deleterious heavy metals is considered as potent toxicant to fish as well as other aquatic life even at low concentration showing effects at physiological, histological, biochemical, enzymatic and genetic levesl (Heath 1987). Adverse toxic effects of Cr on biochemical toxicity, immune response and non-specific immunity, genotoxicity in different fish species have also been reported by various researchers (Prabakaran et al. 2007; Maples & Bain 2004; Lemos et al. 2001; Sastry & Sunita 1983). Among the enzymes, glutathione-s-transferases (GST) is very important enzymatic antioxidant, which are involved in transportation and elimination of reactive compounds (Livingstone 2003; Sies 1993). Alkaline phosphatase is a polyfunctional enzyme and plays a vital role in mineralization of the skeleton of aquatic animals (Lan et al. 1995; Zikic et al. 2001). Aminotransferases [alanine aminotransferases (ALT) and aspartate aminotransferase (AST)] are the most significant enzymes involved in transamination for synthesis and deamination of amino acids Zikic et al. (2001). These enzymatic studies under toxicosis of heavy metals are very few in number (Frasco et al. 2007) but this can be identified as enzymatic probes of biomarkers. Therefore, the aim of the present study is to evaluate the different enzymatic responses at two different concentrations in different tissues, so as to compare the level of damage at particular concentration of chromium under long term exposure. Materials and Methods Experimental Design: Freshwater teleost, Anabas testudineus (Bloch) of both sexes with an average weight of ± 5.64 g and length of ± 0.35 cm respectively were collected from local freshwater pond and acclimatised to congenial laboratory condition for 15 days in aquaria of 250 L capacity. Fishes were fed with live fishfood viz., Tubifex sp. regularly. Fishes were grouped in three sets containing 10 fishes in each designated as Group I (control), Group II and III (treated). Treated 168

169 groups (II &III) were intoxicated with two sublethal concentrations of hexavalent chromium (K 2 Cr 2 O 7 ), i.e., 25% and 50% of LC 50 value [61.80 mg/l for 96 h (Kumar et al. 2012)] respectively for a period of 30 days. Doses were applied on every alternate day and all aquaria were maintained very carefully. Tissue Sampling and Biochemical Evaluation: After completion of the experiment i.e., 30 days, fishes from each group of control and chromium treated were weighed and desired tissues of gill, stomach, intestine, liver, kidney, brain, spinal cord, heart, and white muscle, for respective enzymes were taken and washed quickly in 0.75% saline solution, dried with filter paper, packed in teflon tubes and stored at -80 o C for biochemical analysis. The following enzymes viz., glutathione-s-transferase activity was determined according to the method of Habig et al. (1974), and alkaline phosphatase (Merck cat. # 1730PDLFT.0045), alanine aminotransferase (Erba cat. # FBCEM0047) and aspartate aminotransferase (Erba cat. # FBCEM0045) activities were measured by Bergmeyer et al. (1976) for the present study along with protein content was estimated by the Folin-Phenol reaction methods as described by Lowry et al. (1951). All assays were run in triplicate. Finally, the results were statistically analysed by using SPSS package (Version 16) for these specific enzymes. Results Glutathione-S-transferase activity A significant reduction in GST activity in liver of A. testudineus at both the concentrations were recorded (Figure 1) maximum reduction was from ±0.760 to 3.829±0.336 at 25% in compare to 50% concentration. Alkaline phosphatase activity Alkaline phosphatase activity in intestine, liver and kidney of A. testudineus varied significantly (p< 0.01) at both the concentrations (Figure 2). In liver, it was reduced significantly at both the concentrations but maximum in 50%. In case of intestine and kidney, it was increased at 25% concentration from 7.881±0.546 to ±0.603 and ±0.440 to 30.88±1.708 unit/mg protein respectively but at 50% it was declined from 7.881±0.546 to 3.562±0.882 and ±0.440 to 6.310±0.540 unit/mg protein respectively. Alanine aminotransferase activity Alanine aminotransferase activity in all the tissues of A. testudineus was significantly different at both the Cr concentrations (Figure 3). Gill showed enhanced ALT activity from ±0.957 to ±1.137 at 25% concentration but was reduced at 50% from ±0.957 to 9.645±1.765 unit/mg protein. In case of liver, it was raised from ±1.853 to ±1.498 at 25% but reduced in gill at 50%. In case of muscle, ALT activity was significantly raised at both the concentrations and was highest at 50% from ±0.892 to ±1.423 and lowest at 25% while in heart it was elevated significantly from ±0.859 to ±1.573 at 25% but declined at 50% concentration. Aspartate aminotransferase (AST) activity AST activity in liver, muscle, gill and heart of A. testudineus was increased significantly (p< 0.01) at 25% but significantly reduced (p < 0.01) at 50% (Figure 4). In case of gill, AST activity was raised significantly from ±0.787 to ±9.218 at 25% concentration but reduced from ±0.787 to 50.24±5.452 at 50%. Liver showed increased AST activity from ±2.969 to ± at 25% while reduced from ±2.969 to 63.89±3.842 at 50%. AST activity in case of muscle and heart was significantly raised from ±2.014 to ± and ±1.299 to ±7.744 at 25% respectively but at 50% it was reduced significantly (p< 0.01) from ±2.014 to ±9.494 and ±1.299 to ±3.950 unit/mg protein respectively. Discussion Glutathione-S-transferase, an anti-oxidant enzyme plays a vital role in catalyzing the conjugation of a wide variety of electrophilic substrates to reduce glutathione to protect the cell against effects of xenobiotics Ferrari et al. (2007). The elevation or reduction of GST activity in fish tissues is considered as beneficial for handling a stress condition. In the present work, fishes exposed to chromium in the laboratory condition showed significant decreased activity of GST in liver which suggest a failure of detoxification and the occurrence of oxidative stress. Reduction of GST activity in the hepatic tissue may occur because liver is one of the first organs exposed to metals. Alkaline phosphatise Alkaline phosphatase is considered as an important biomarker because of its adaptive cellular response to the cytotoxic and genotoxic pollutants Lohner et al. (2001). These results showed the highest enhanced ALP activity in kidney and lowest in intestine at 25% concentration while highest reduction in liver but less in kidney at 50% concentration. Kidney showed maximum enhancement in 169

170 enzyme activity in comparison to liver and intestine due to strategic role played by the organs to compensate the toxic effects of chromium and proper management of their metabolic wastes. Similar results were reported by Borges et al. (2007); Das & Mukherjee (2003); El-Sayed & Saad (2008). In liver tissue, ALP activity decreased at both the concentrations and may be taken as an index of hepatic parenchymal damage and hepatocytic necrosis. Similar results were reported by Sastry & Subhadra (1985) in cadmium exposed to Heteropneustes fossilis. Alanine aminotransferase Aminotransferase is sensitive indicator of even minor cellular damage and considered as indicator of stress based tissue impairment (Palanivelu et al. 2005). In the present study, the highest enhanced ALT activity was observed in muscle at 50% and comparatively less in heart at 25%; but maximum reduction of ALT was observed in gill followed by heart and liver (24.39%) at 50% concentration. Increased ALT activities indicated degenerative changes in tissue system by disrupting the physiological and biochemical processes caused mainly due to leakage of enzyme from liver cytosol into the blood stream. Gill tissue at 25% seemed to be mostly affected by chromium poisoning and this may be due to direct exposure of the heavy metal followed by muscle at 50% concentration due to catabolism of protein molecules to meet the high energy demand for carbohydrate and its precursors. The results were also in agreement with observations reported by Jee et al. (2005); Begum (2004) & Gill et al. (1991); although, some results were disagreed with the findings of Li et al. (2009) & Okechukwu & Auta (2007) who reported the decreased ALT activity in rainbow trout exposed to carbamazepine and in Clarias gariepinus exposed to lambda-cyhalothrin. In the present study, maximum elevation of ALT activity was occurred in liver at 50% concentration; this was also agreed by De Smet & Blust (2001) in cadmium exposed to Cyprinus carpio. Aspartate aminotransferase Aspartate aminotransferase plays a vital role in transamination process whose induction, thereby, enabling carbohydrate and protein metabolism by the inter-conversion of strategic compound like α-ketoglutarate and alanine to pyruvic and glutamic acid (Gabriel & George 2005; Salah El-Deen & Rogers 1993). AST is considered as an enzymatic biomarker and its changes due to xenobiotic exposure identify damages in the tissues/organs in fish (Philip & Rajarsee, 1996). The results showed the highest enhanced activity of AST in liver and low in heart at 25% concentration but maximum reduction was observed in muscle followed by heart at 50% concentration. These findings were also similar with the observation of Yildirim et al. (2006) who reported increased activity of AST in gill, liver and kidney of Oreochromis niloticus exposed to deltamithrin for four days and with Jee et al. (2005) who also found similar results in Korean rockfish (Sebastes schlegeli) exposed to cypermethrin. In the present study, exposure of A. testudineus to chromium at the 25% concentration showed enhanced activity of AST enzyme in liver, gill, muscle and heart tissue indicating serious tissue damage as well as an augmentation of stress condition and subsequently efficient utilization of amino acids for metabolic processes for meeting the fluctuating energy demand to keep both the glycolytic pathway and TCA cycles at equilibrium levels. Present study showed higher liver AST activity in comparison to other tissues of test fishes at both the concentrations suggested that hepatic damage may be due to hypofunction of liver activity and their leakage into the body fluid. Acknowledgements The authors would like to thank Department of Science & Technology, Govt. of India for the financial assistance. We would also like to thank the Head, Department of Environmental Science, The University of Burdwan, Burdwan, West Bengal, India for providing the laboratory facilities during the course of research. References Atli G., Canli M. (2007). Enzymatic responses to metal exposures in a freshwater fish Oreochoromis niloticus. Comparative Biochemistry and Physiology Part C: Toxicology and Pharmacology 145, Begum G. (2004). Carbofuran insecticide induced biochemical alterations in liver and muscle tissues of fish Clarias batrachus (Linn) and recovery response. Aquatic Toxicology 66(1), Bergmeyer H.U., Bowers Jr. G.N., Hörder M., Moss D.W. (1976). Provisional recommendations on IFCC Methods for the measurement of catalytic concentrations of enzymes. Part 2. IFCC method for aspartat aminotransferase. Clinica Chimica Acta 70, Borges A. (2007). Changes in hematological and serum biochemical values in Jundiá Rhamdia quelen due to sub-lethal toxicity of cipermethrin. Chemosphere 69,

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172 Prabakaran M., Binuramesh C., Steinhagen D., Dinakaran M.R. (2007). Immune response in the tilapia,oreochromis mossambicus on exposure to tannery effluent. Ecotoxicology and Environmental Safety 68(3), Sastry K. V., Subhadra K. (1985). In vivo effects of cadmium on some enzyme activities in tissues of the freshwatercatfish, Heteropneustes fossilis. Environmental Research 36 (1), Sastry K.V., Sunita K.M. (1983). Enzymological and biochemical changes produced by chronic chromium exposure in a Teleost fish, Channa punctatus. Toxicology Letters 16, Sies H. (1993). Strategies of antioxidant defenses. Europian Journal of Biochemistry 215, Yildirim M.Z., Benli K.C., Selvi M., Ozkul A., Erko F., Kocak O. (2006). Acute toxicity behavioural changes and histopathological effects of deltamethrin on tissues (gills, liver, brain, spleen, kidney, muscle, skin) of Nile Tilapia (Oreochromis niloticus) fingerlings. Environmental Toxicology 21, Zhi-Hua L., Vladimir Z., Josef V., Roman G., Jana M., Tomas R. (2009). Physiological condition status and muscle based biomakers in rainbow trout after long exposure to carbamazopine. Journal of Applied Toxicology 30, Zikic R.V., Stajn S., Pavlovic Z., Ognjanovic B.I., Saicic Z.S. (2001). Activities of superoxide dismutase and catalase in erytrocyte and plasma transaminases of goldfish (Carassius auratus gibelio Bloch.) exposed to cadmium. Physiological Research 50, Figure 1. GST activity (unit/mg protein/min) in liver of Anabas testudineus under control and treated conditions. 172

173 Figure 2. ALP activity (unit/mg protein) in intestine, liver and kidney of Anabas testudineus under control and treated conditions. Figure 3. ALT activity (unit/mg protein) in gill, liver, muscle and heart of Anabas testudineus under control and treated conditions. 173

174 Figure 4. AST activity (unit/mg protein) in gill, liver, muscle and heart of Anabas testudineus under control and treated conditions. 174

175 1 ORAL PRESENTATIONS IN GREEK TOLERANCE OF SEAGRASS Cymodocea nodosa PHOTOSYNTHETIC ACTIVITY ΣΟ SALINITY Tsioli S.* 1, Papathanasiou V. 1, Katsaros C. 2, Exadactylos A. 3, Orfanidis S. 1 Benthic Ecology & Technology Laboratory, Fisheries Research Institute (Hellenic Agricultural Organization-DEMETER), 64007, Nea Peramos, Kavala, Greece 2 Department of Botany, Faculty of Biology, National and Kapodistrian University of Athens, 15784, Athens, Greece 3 Department of Ichthyology & Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Fytokou 38, 38446, Volos, Greece ABSTRACT The tolerance of Cymodocea nodosa photosynthetic activity to salinity was studied to understand key mechanisms of its physiology in the Kavala Gulf, Northern Aegean. Shoots of the plant were placed in Plexiglas aquariums with different salinities (5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60) for 20 days. The effective quantum yield (ΓF/Fm') was measured every fourth day and the chlorophyll-a (Chl-a) leaf content was estimated at the end of the experiment. The experiment was conducted in a constant temperature chamber (21-22 μ C) with controlled lighting conditions (70-90 ιmol photons m -2 s -1, 14 hours light). The results reveal that the species has rather euryhaline characteristics and high physiological plasticity, with both ΓF/Fm' and leaf Chl-a yielding lower values in extreme salinities (<15, >45). The results are in agreement with the literature and explain the presence in coastal waters and absence in the lagoons of Eastern Macedonia and Thrace. They also provide insight on possible future changes in its distribution due to climate change in the region. Key words: Effective quantum yield, chlorophyll-a, Kavala Gulf *Corresponding author: Soultana Tsioli (stsioli@inale.gr) 1 ΑΝΟΥΖ ΣΖ ΦΧΣΟΤΝΘΔΣΗΚΖ ΓΡΑΣΖΡΗΟΣΖΣΑ ΣΟΤ ΘΑΛΑΗΟΤ ΑΓΓΔΗΟΠΔΡΜΟΤ Cymodocea nodosa ΣΖΝ ΑΛΑΣΟΣΖΣΑ Σζηψιε.* 1, Παπαζαλαζίνπ Β. 1, Καηζαξφο Υ. 2, Δμαδάθηπινο Α. 3 Οξθαλίδεο. 1 Δνβαζηήνζμ Βεκεζηήξ Οζημθμβίαξ & Σεπκμθμβίαξ, Ηκζηζημφημ Αθζεοηζηήξ Ένεοκαξ (ΔΛΓΟ- ΓΖΜΖΣΡΑ), 64007, Νέα Πέναιμξ, Κααάθα, Δθθάδα 2 Σμιέαξ Βμηακζηήξ, Σιήια Βζμθμβίαξ, Δεκζηυ Καπμδζζηνζαηυ Πακεπζζηήιζμ Αεδκχκ, 15784, Αεήκα, Δθθάδα 3 Σιήια Γεςπμκίαξ Ηπεομθμβίαξ & Τδάηζκμο Πενζαάθθμκημξ, πμθή Γεςπμκζηχκ Δπζζηδιχκ, Πακεπζζηήιζμ Θεζζαθίαξ, Φοηυημο 38, 38446, Βυθμξ, Δθθάδα Πεξίιεςε Μεθεηήεδηακ ηα υνζα ακμπήξ ηδξ θςημζοκεεηζηήξ δναζηδνζυηδηαξ ημο είδμοξ Cymodocea nodosa ζηζξ ιεηααμθέξ ηδξ αθαηυηδηαξ, ςξ ιζα πνμζπάεεζα ηαηακυδζδξ ααζζηχκ ιδπακζζιχκ ηδξ μζημθοζζμθμβίαξ ημο πθδεοζιμφ ημο είδμοξ ζηδ εαθάζζζα πενζμπή ημο Κυθπμο ηδξ Κααάθαξ, Βυνεζμ Αζβαίμ. Βθαζημί ημο θοημφ ημπμεεηήεδηακ ζε εκοδνεία Plexiglas δζαθμνεηζηχκ αθαημηήηςκ (5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60) βζα 20 ιένεξ, ηαηά ηδ δζάνηεζα ηςκ μπμίςκ ιεηνμφκηακ δ εκενβυξ θςημκζαηή ημοξ απυδμζδ (ΓF/Fm'), εκχ ζημ ηέθμξ ημο πεζνάιαημξ ιεηνήεδηε δ πενζεηηζηυηδηα ηςκ θφθθςκ ζε πθςνμθφθθδ-α (Chl-a). Σμ πείναια δζελήπεδ ζε εάθαιμ ηαθθζένβεζαξ ζηαεενήξ εενιμηναζίαξ (21-22 μ C) ηαζ θςηζζιμφ (70-90 ιmol θςημκίςκ m -2 s -1, 14 χνεξ θςξ). Σα απμηεθέζιαηα ηδξ ενβαζίαξ έδεζλακ υηζ ημ είδμξ έπεζ ιάθθμκ εονφαθα (euryhaline) παναηηδνζζηζηά ηαζ ορδθή θοζζμθμβζηή πθαζηζηυηδηα ιε ιείςζδ ηδξ ΓF/Fm' ηαζ ηδξ Chl-α ηςκ θφθθςκ ζηζξ αηναίεξ αθαηυηδηεξ (<15, >45). Σα απμηεθέζιαηα είκαζ ζε ζοιθςκία ιε ηδ δζεεκή αζαθζμβναθία ηαζ ελδβμφκ ηδ ζδιενζκή ελάπθςζδ ημο είδμοξ ζηζξ αηηέξ, αθθά υπζ ζηζξ θζικμεάθαζζεξ ηδξ Ακαημθζηήξ 175

176 Μαηεδμκίαξ & Θνάηδξ, εκχ δίκμοκ ηδ δοκαηυηδηα πνυβκςζδξ ηςκ πζεακχκ ιεθθμκηζηχκ ιεηααμθχκ ηδξ ηαηακμιήξ ελαζηίαξ ηςκ ηθζιαηζηχκ αθθαβχκ ζηδκ εονφηενδ πενζμπή. Λέξειρ κλειδιά: Δλεξγόο θσηνληαθή απόδνζε, ρισξνθύιιε-α, Κόιπνο Καβάιαο *οββναθέαξ Δπζημζκςκίαξ: Σζζχθδ μοθηάκα 1. ΔΗΑΓΧΓΖ Σα εαθάζζζα αββεζυζπενια ή θακενυβαια εεςνμφκηαζ μνβακζζιμί «ηθεζδζά» ζε πμθθά αααεή πενζαάθθμκηα, υπςξ είκαζ ηα ιεηαααηζηά ηαζ πανάηηζα φδαηα, βζαηί δδιζμονβμφκ ζφκεεηα, ιςζασημφ ηφπμο, ορδθήξ μζημθμβζηήξ ηαζ μζημκμιζηήξ ζδιαζίαξ εκδζαζηήιαηα (Costanza et al. 1997, Heck et al. 2003, Bloomfield & Gillanders 2005). ηα εαθάζζζα πενζαάθθμκηα, δ αθαηυηδηα εεςνείηαζ έκαξ ηαηά πνμζέββζζδ ζηαεενυξ πανάβμκηαξ, βεβμκυξ πμο ελδβεί βζαηί ηα οδνυαζα αββεζυζπενια είκαζ, ζε βεκζηέξ βναιιέξ, ζηεκυαθα είδδ (den Hartog & Kuo 2006). Χζηυζμ, επεζδή μζ ηζιέξ ηδξ αθαηυηδηαξ ζηα αααεή πανάηηζα ηαζ ιεηαααηζηά φδαηα ηδξ οδνμβείμο είκαζ ζδζαίηενα εοιεηάαθδηεξ, ηα είδδ ηςκ βεκχκ Cymodocea, Zostera ηαζ Ruppia πμο επζηναημφκ παναηηδνίγμκηαζ απυ ορδθή θαζκμηοπζηή πθαζηζηυηδηα (phenotypic plasticity) (Hemminga & Duarte 2000) ηαζ δοκαηυηδηεξ ειθάκζζδξ ημπζηχκ βεκεηζηχκ δμιχκ (Alberto et al. 2005). Σα είδδ αοηά εηηυξ ηςκ θοζζμθμβζηχκ αθθαβχκ ελαζηίαξ ηδξ επμπζηυηδηαξ ηαζ ηςκ νεοιάηςκ, ιπμνεί κα δέπμκηαζ ηδκ επίδναζδ ορδθχκ ιεηααμθχκ ηδξ αθαηυηδηαξ πμο μθείθμκηαζ είηε ζε έιιεζεξ (ηθζιαηζηέξ αθθαβέξ) είηε ζε άιεζεξ (απυννζρδ θοιάηςκ άθιδξ απυ ιμκάδεξ αθαθάηςζδξ) ακενςπμβεκείξ δναζηδνζυηδηεξ (Fernandez-Torquemada et al. 2009, Gacia et al. 2007, Koch et al. 2013). Αοηέξ μζ αθθαβέξ, ιυκεξ ημοξ ή ζοκδοαζηζηά, ιπμνμφκ κα μδδβήζμοκ ζε ηαηαπυκδζδ (stress), επδνεάγμκηαξ ηδ αζςζζιυηδηα ηςκ εαθάζζζςκ θζααδζχκ (Waycott et al. 2009). Με ζημπυ ηδκ αεζθμνζηή πνμζηαζία ημοξ ζηζξ ζδιενζκέξ ηαζ ιεθθμκηζηέξ πενζααθθμκηζηέξ ζοκεήηεξ, δδιζμονβείηαζ δ ακάβηδ πεναζηένς ιεθέηδξ ηδξ μζημ-θοζζμθμβίαξ ηςκ εαθάζζζςκ αββεζμζπένιςκ ζηζξ πενζααθθμκηζηέξ ηαηαπμκήζεζξ πμο πνμηαθμφκ αοημί μζ πανάβμκηεξ. H Cymodocea nodosa είκαζ έκα είδμξ ιε ζδιακηζηή ελάπθςζδ ζηδ Μεζυβεζμ Θάθαζζα ηαζ ζηζξ Κακάνζεξ Νήζμοξ (Mascaró et al. 2009) ηαζ ακαπηφζζεηαζ ζε πμθθέξ πενζμπέξ ηδξ πχναξ, ηονίςξ ζε αιιχδεζξ πνμθοθαβιέκεξ πενζμπέξ, π.π. ηθεζζημί ηυθπμζ, ή πενζμπέξ ιε ιέηνζμ οδνμδοκαιζζιυ, υπμο ηαζ ζπδιαηίγεζ ιςζασημφ ηφπμο θζαάδζα (Orfanidis et al. 2005). Δπίζδξ, έπεζ εονεία ελάπθςζδ ζε ζοκεήηεξ αολακυιεκδξ θοζζηήξ (ηθίζδ αθαηυηδηαξ: Nikolaidou et al. 2005) ηαζ ακενςπμβεκμφξ (ηθίζδ νφπακζδξ: Orfanidis et al. 2010, Malea & Kevrekidis 2013, Papathanasiou, 2013) ηαηαπυκδζδξ. ημπυξ ηδξ πανμφζαξ ιεθέηδξ είκαζ μ πνμζδζμνζζιυξ ηςκ μνίςκ ακμπήξ ηδξ θςημζοκεεηζηήξ δναζηδνζυηδηαξ ημο θακενυβαιμο Cymodocea nodosa ζε ζπέζδ ιε ηδκ ααζμηζηή πανάιεηνμ αθαηυηδηα, ςξ ιζα πνμζπάεεζα ηαηακυδζδξ ααζζηχκ ιδπακζζιχκ ηδξ θοζζμθμβίαξ ημο πθδεοζιμφ ημο είδμοξ ζηδ εαθάζζζα πενζμπή ημο Κυθπμο ηδξ Κααάθαξ, Βυνεζμ Αζβαίμ. Χξ πανάιεηνμξ απυηνζζδξ πνδζζιμπμζήεδηε δ εκενβυξ θςημκζαηή απυδμζδ ηςκ αθαζηχκ, δ μπμία ααζίγεηαζ ζημ θεμνζζιυ ηδξ πθςνμθφθθδξ-α (Ralph et al. 1995). 2. ΤΛΗΚΑ ΜΔΘΟΓΟΗ 2.1 οθθμβή, εβηθζιαηζζιυξ θοηχκ: Πναβιαημπμζήεδηε ζοθθμβή αθαζηχκ Cymodocea nodosa αάεμοξ 3 ιέηνςκ απυ ημ Αηνςηήνζμ Βναζίδαξ (νιμξ Δθεοεενχκ, Κυθπμξ Κααάθαξ) ζηζξ 31/05/2013. Αημθμφεδζε ημπμεέηδζδ ημοξ ζε εκοδνείμ Plexiglas 6 lt ενεπηζημφ ιέζμο (ΘΜ) ηαζ ιεηαθμνά ζε εάθαιμ ηαθθζένβεζαξ ζηαεενήξ εενιμηναζίαξ (21-22 μ C) ηαζ θςηζζιμφ (60 ιmol θςημκίςκ m -2 s -1, 14 χνεξ θςηυξ) ιε ζημπυ ημκ εβηθζιαηζζιυ βζα ιζα εαδμιάδα. Σμ ΘΜ δδιζμονβήεδηε απυ ηδκ πνμζεήηδ αθαηζμφ εκοδνείςκ (Münster Meersalz) ζε απζμκζζιέκμ (ζηήθδ νδηίκδξ) κενυ φδνεοζδξ ηαζ ενεπηζηχκ αθάηςκ. Ζ αθαηυηδηα ημο ΘΜ ήηακ 33,5 ηαζ δ ζοβηέκηνςζδ αγχημο ηαζ θςζθυνμο 0,3 ιmol/lt N-ΝΟ 3 ηαζ 0,02 ιmol/lt P-PO 4, ακηίζημζπα. 2.2 Πείναια, ιέηνδζδ θςημζοκεεηζηήξ δναζηδνζυηδηαξ: Μεηά ημκ εβηθζιαηζζιυ ( ), ηα θοηά ημπμεεηήεδηακ ζε εκοδνεία 3 θίηνςκ απυ Plexiglas ζπήιαημξ μνεμβςκίμο παναθθδθεπζπέδμο, ηαεέκα απυ ηα μπμία πενζείπε 3 δεζιίδεξ ημο θοημφ Cymodocea nodosa ηαζ 1 θίηνμ ΘΜ, υιμζμ ιε αοηυ ηδξ θάζδξ εβηθζιαηζζιμφ. Σμ πείναια δζελήπεδ ζε εάθαιμ ηαθθζένβεζαξ ζηαεενήξ εενιμηναζίαξ, μ C. Οζ ζοκεήηεξ - αθαηυηδηεξ πμο ιεθεηήεδηακ πνμζδζμνίζηδηακ ιε θμνδηυ αθαηυιεηνμ (WTW) ηαζ ήηακ μζ ελήξ: 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60. Μεθεηήεδηακ 6 δεζιίδεξ (επακαθήρεζξ, replicates) βζα ηάεε ζοκεήηδ πεζνάιαημξ. Σμ πείναια δζήνηδζε 20 διένεξ. Γζα ηζξ ζοκεήηεξ θςηζζιμφ πνδζζιμπμζήεδηακ ζςθδκμεζδείξ θαιπηήνεξ θεμνζζιμφ 110 cm πμο ελαζθάθζγακ ιmol θςημκίςκ m -2 s -1 ζηδκ επζθάκεζα ηςκ δμπείςκ ηαθθζένβεζαξ, 14 χνεξ ηδκ διένα. Ζ αθθαβή ΘΜ πναβιαημπμζμφκηακ ηάεε δφμ (2) ιένεξ ηαζ δ ιέηνδζδ ηδξ εκενβμφξ θςημκζαηήξ απυδμζδξ (ΓF/F m ') ζημ κευηενμ θφθθμ, πενίπμο 2 εη. απυ ημκ 176

177 ιίζπμ, ηάεε ηέζζενζξ (4) ιένεξ, ιε ηδ πνήζδ οπμανφπζμο θεμνζυιεηνμο (Underwater Diving-PAM, Walz, GmbH, Effeltrich, Germany). ημ ηέθμξ ημο πεζνάιαημξ ηναηήεδηακ δείβιαηα ζηδκ ηαηάρολδ (-20 μ C) βζα ακάθοζδ πενζεηηζηυηδηαξ ζε πθςνμθφθθδ α (Chl-α) ζημ θφθθμ ιέηνδζδξ ηδξ ΓF/F m '. 2.3 Ακάθοζδ πενζεηηζηυηδηαξ θφθθμο ζε πθςνμθφθθδ-α: Γζα ηδκ ακάθοζδ ηδξ ζοβηέκηνςζδξ ηδξ πθςνμθφθθδξ ζηα θφθθα ηδξ C. nodosa αημθμοεήεδηε δ ιέεμδμξ ηςκ Granger & Lizumi (2001) 2.4 ηαηζζηζηή ακάθοζδ: Ζ ζηαηζζηζηή επελενβαζία ηςκ δεδμιέκςκ πναβιαημπμζήεδηε ιε ιμκηέθα ιζηηχκ επζδνάζεςκ (mixed effects models) ζε πενζαάθθμκ R. 3. ΑΠΟΣΔΛΔΜΑΣΑ ημ πήια 1α δίκμκηαζ μζ ιέζεξ ηζιέξ ηςκ ηζιχκ ηδξ εκενβμφξ θςημκζαηήξ απυδμζδξ (ΓF/Fm') πμο ιεηνήεδηακ ηαευθδ ηδ δζάνηεζα ημο πεζνάιαημξ ζηζξ δζαθμνεηζηέξ αθαηυηδηεξ. Δκχ μζ ορδθυηενεξ ιέζεξ ηζιέξ ΓF/Fm' ιεηνήεδηακ ζηζξ αθαηυηδηεξ απυ 25 ιέπνζ 50 (0,734-0,720), μζ παιδθυηενεξ ιέζεξ ηζιέξ ιεηνήεδηακ ζηζξ αθαηυηδηεξ 5 (0,432) ηαζ 60 (0,515). Με αάζδ ημ ζπήια 1 α, ηα θοηά ζηδκ αθαηυηδηα 5 δείπκμοκ κα ηαηαπμκήεδηακ ακεπακυνεςηα ζηδ δζάνηεζα ημο πεζνάιαημξ, ιε απμηέθεζια ηδ δναιαηζηή ιείςζδ ηδξ ΓF/Fm ζημ ηέθμξ ημο πεζνάιαημξ. Μάθζζηα δφμ απυ ημοξ 6 αθαζημφξ δεκ άκηελακ ιέπνζ ημ ηέθμξ ημο πεζνάιαημξ ηαζ απμιαηνφκεδηακ απυ ηα εκοδνεία. Ακηίεεηα, υζμκ αθμνά ζημοξ αθαζημφξ ζηζξ αθαηυηδηεξ 55 ηαζ 60, εκχ ζηδκ ανπή δ ΓF/Fm επδνεάγεηαζ ανκδηζηά, ζηδ ζοκέπεζα θαίκεηαζ κα επακαηάιπηεζ, πςνίξ ςζηυζμ κα επακένπεηαζ ζηα ανπζηά επίπεδα (πήια 1β, διένεξ 16, 20). φιθςκα ιε ηδ ζηαηζζηζηή ακάθοζδ (δεκ δίκεηαζ) οπάνπεζ ζηαηζζηζηά ζδιακηζηή δζαθμνμπμίδζδ ακάιεζα ζηζξ αθαηυηδηεξ πμο ελεηάζηδηακ ςξ πνμξ ηδκ 5, εηηυξ απυ ηδκ αθαηυηδηα 60 (p<0,05). ημ πήια 1δ δίκμκηαζ μζ ιέζεξ ηζιέξ ηδξ πενζεηηζηυηδηαξ ημο θφθθμο ζε Chl-α ζηζξ δζαθμνεηζηέξ αθαηυηδηεξ. Δκχ μζ ορδθυηενεξ ιέζεξ ηζιέξ Chl-α ιεηνήεδηακ ζηζξ αθαηυηδηεξ 25 (3,94 ιg/g) ηαζ 35 (3,96 ιg/g), μζ παιδθυηενεξ ιέζεξ ηζιέξ ιεηνήεδηακ ζηζξ αθαηυηδηεξ 5 (1,2 ιg/g) ηαζ 60 (1,4 ιg/g. ηδκ αθαηυηδηα 5 δ Chl-α ιεηνήεδηε ιυκμ ζε 4 αθαζημφξ (αθ. παναπάκς). φιθςκα ιε ηδ ζηαηζζηζηή ακάθοζδ (δεκ δίκεηαζ) οπάνπεζ ζηαηζζηζηά ζδιακηζηή δζαθμνμπμίδζδ ακάιεζα ζηζξ αθαηυηδηεξ πμο ελεηάζηδηακ ςξ πνμξ ηδκ 5 (p<0,05). ρήκα 1: α) Μέζε ηηκή ΓF/F m ' (± ηππηθφ ζθάικα-σ, n=42) γηα θάζε πεηξακαηηθή ζπλζήθε, β) Γηαθχκαλζε ηηκψλ ΓF/F m ' (Μέζε Σηκή ± Σ, n=6) αλά εκέξα κέηξεζεο γηα ηηο αιαηφηεηεο 5-30, γ) Γηαθχκαλζε ηηκψλ ΓF/F m ' (ΜΣ ± Σ, n=6) αλά εκέξα κέηξεζεο γηα ηηο αιαηφηεηεο θαη 177

178 δ) Μέζε ηηκή ρισξνθχιιεο-α ζηα θχιια (± Σ, n=4-6) ζην ηέινο ηνπ πεηξάκαηνο γηα θάζε πεηξακαηηθή ζπλζήθε. 4. ΤΕΖΣΖΖ Σα απμηεθέζιαηα ηδξ ενβαζίαξ έδεζλακ υηζ ημ είδμξ C. nodosa έπεζ ιάθθμκ εονφαθα (euryhaline) παναηηδνζζηζηά, πανμοζζάγμκηαξ ιείςζδ ηδξ ΓF/Fm' ηαζ ηδξ Chl-α ηςκ θφθθςκ ιυκμ ζηζξ αηναίεξ αθαηυηδηεξ (<15, >45). Πανυιμζα απμηεθέζιαηα ανέεδηακ ηαζ απυ άθθμοξ ζοββναθείξ. Γζα πανάδεζβια, μζ Pagès et al. (2010) πμο ιεθέηδζακ ηδκ επίδναζδ ηδξ αθαηυηδηαξ ζηδκ C. nodosa ζε πείναια ιζηνυημζιμο βζα 17 ιένεξ ζοιπέναζκακ, υηζ άκηελε ζηδκ 44 πςνίξ ειθακή αθάαδ, αθθά δ αζςζζιυηδηα ιεζχεδηε ζηζξ 54 ηαζ 62. Οζ Sandoval-Gil et al. (2012) ιεθέηδζακ ηδκ επίδναζδ ηδξ αθαηυηδηαξ ζηδ θςημζφκεεζδ, ηδκ ακάπηολδ ηαζ ηδκ επζαίςζδ ηδξ C. nodosa ζε πείναια ιεζυημζιμο βζα 47 ιένεξ. Σα απμηεθέζιαηά ημοξ έδεζλακ ιέηνζα, αθθά ειθακή ιείςζδ ηδξ θςημζοκεεηζηήξ δναζηδνζυηδηαξ (12-17%) ζε υθεξ ηζξ ορδθέξ αθαηυηδηεξ (39-43). φιθςκα ιε ημοξ Caye & Meinesz (1986), δ ακάπηολδ ηςκ ζπενιάηςκ είκαζ ιεβαθφηενδ ιεηαλφ ηςκ αθαημηήηςκ 15 ηαζ 20, έκα εφνμξ αθαημηήηςκ πμο ζηδ Μεζυβεζμ ζοκδοάγεηαζ ιε βθοηά κενά ή πενζπηχζεζξ ηαηαζβίδςκ. Οζ ζοβηεηνζιέκμζ ζοββναθείξ πνμηείκμοκ υηζ μ πνμκζζιυξ ηδξ θφηνςζδξ ηαζ δ ηαηακμιή C. nodosa ζηδκ δοηζηή Μεζυβεζμ πενζμνίγμκηαζ απυ ηδκ ορδθή αθαηυηδηα. Απυ ηα παναπάκς θαίκεηαζ υηζ δ C. nodosa έπεζ ορδθή θοζζμθμβζηή πθαζηζηυηδηα ηαζ ζηακυηδηα κα ακαπηφζζεηαζ ζε πανάηηζα μζημζοζηήιαηα ιε εονεία αθθά υπζ αηναία επίπεδα αθαημηήηςκ. Σμ βεβμκυξ αοηυ ιάθθμκ ελδβεί ηδκ εονεία ελάπθςζδ ημο είδμοξ ιυκμ ζηζξ αηηέξ ηαζ υπζ ζηζξ πανάηηζεξ θζικμεάθαζζεξ ηδξ Πενζθένεζαξ Ακαημθζηήξ Μαηεδμκίαξ & Θνάηδξ, μζ αθαηυηδηεξ ηςκ μπμίςκ ηοιαίκμκηαζ ιεηαλφ 18 ηαζ 60 (Nikolaidou et al. 2005, Orfanidis et al. 2008). οκεπχξ, δ αφλδζδ ηδξ αθαηυηδηαξ, ζε ζοκδοαζιυ ιε ηδκ ακφρςζδ ηδξ ζηάειδξ ηδξ εάθαζζαξ ηαζ ηδξ ιείςζδξ ηςκ βθοηχκ κενχκ, ελαζηίαξ ηςκ ηθζιαηζηχκ αθθαβχκ, ιπμνεί κα ζοιαάθθεζ ηαηά πενίπηςζδ ζηδκ αθθαβή ηδξ ζδιενζκήξ ηαηακμιήξ (αθ. Short & Neckles, 1999). Γζα πανάδεζβια, εκχ ιάθθμκ εα αμδεήζεζ ζηδκ οπένααζδ ημο ζδιενζκμφ «θνάβιαημξ» ελάπθςζδξ ημο είδμοξ ζημκ πενζμνζζιέκμ (restricted type) ηφπμ θζικμεαθαζζχκ ηδξ πενζμπήξ, θαίκεηαζ υηζ εα πενζμνίζεζ ηδκ ακαπαναβςβή ηαζ ηδκ ηαηακμιή αοημφ ημο είδμοξ ζε άθθεξ θζικμεάθαζζεξ ηδξ Μεζμβείμο ηαζ ηδξ Δθθάδαξ ιε πενζζζυηενμ εαθάζζζα (leaky type) παναηηδνζζηζηά. οιπεναζιαηζηά, δ πεζναιαηζηή ιεθέηδ ηδξ θςημζοκεεηζηήξ δναζηδνζυηδηαξ αθαζηχκ ημο είδμοξ C. nodosa, δ μπμία ααζίζηδηε ζοκδοαζηζηά ζε ζφβπνμκεξ (θεμνζζιυξ ηδξ πθςνμθφθθδξ) ηαζ ηθαζζζηέξ (ζοβηέκηνςζδ πθςνμθφθθδξ) ιεευδμοξ ηδξ θοζζμθμβίαξ ηςκ θοηχκ, έδεζλε υηζ ιπμνεί κα αλζμπμζδεεί ζηδκ ηαηακυδζδ ηδξ οπάνπμοζαξ ηαζ ιεθθμκηζηήξ ηαηακμιήξ ημο είδμοξ ζηδκ εονφηενδ πενζμπή ηδξ Ακαημθζηήξ Μαηεδμκίαξ & Θνάηδξ. ΔΤΥΑΡΗΣΗΔ: Ζ ενβαζία αοηή πναβιαημπμζήεδηε ιε ηδ ζοβπνδιαημδυηδζδ ημο πνμβνάιιαημξ «ΘΑΛΖ» (Σίηθμξ οπμένβμο «Ακμπή ηςκ εαθάζζζςκ αββεζμζπένιςκ ζε πενζααθθμκηζηέξ ηαηαπμκήζεζξ: ιεηααθδηυηδηα ηςκ θοζζμθμβζηχκ - ηοηηανζηχκ - αζμπδιζηχκ - ιμνζαηχκ ιδπακζζιχκ ζε ζπέζδ ιε είδμξ ηαζ εκδζαίηδια») απυ ηδκ Δονςπασηή Έκςζδ (Δονςπασηυ Κμζκςκζηυ Σαιείμ) ηαζ απυ εεκζημφξ πυνμοξ (Τπμονβείμ παζδείαξ, δζα αίμο ιάεδζδξ ηαζ ενδζηεοιάηςκ, Δζδζηή οπδνεζία δζαπείνζζδξ επζπεζνδζζαημφ πνμβνάιιαημξ εηπαίδεοζδ & δζα αίμο ιάεδζδ). ΒΗΒΛΗΟΓΡΑΦΗΑ Alberto F., Gouveia L., Arnaud Haond S., Pérez Lloréns J. L., Duarte C. M., Serrao E. A. (2005). Within population spatial genetic structure, neighbourhood size and clonal subrange in the seagrass Cymodocea nodosa. Molecular Ecology 14, Bloomfield A. L., Gillanders B. M. (2005). Fish and invertebrate assemblages in seagrass, mangrove, saltmarsh, and nonvegetated habitats. Estuaries 28, Costanza R., D'Arge R., De Groot R., Farber S., Grasso M., Hannon B., Limburg K., Naeem S., O'Neill R.V., Paruelo J., Raskin R.G., Sutton P., Van Den Belt M. (1997). The value of the world's ecosystem services and natural capital. Nature 387, den Hartog C., Kuo J. (2006). Taxonomy and biogeography of seagrasses. In Seagrasses: Biology, Ecology and Conservation Larkum A. W. D., Orth R. J., Duarte C. M. (eds.), p Fernández-Torquemada Y., Gónzalez-Correa J.M., Loya A., Ferrero L.M., Díaz- Valdés M., Sánchez- Lizaso J.L. (2009). Dispersion of brine discharge from a seawater reverse osmosis desalination plants. Desalination and Water Treatment 5, Gacia E., Invers O., Manzanera M., Ballesteros E., Romero J. (2007). Impact of the brine from a desalination plant on a shallow seagrass (Posidonia oceanica) meadow. Estuarine, Coastal and Shelf Science 72,

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180 PRELIMINARY RESULTS ON THE BENEFITS FROM THE RESTORATION OF LAKE KARLA TO ITS WIDER PROTECTED AREA POPULATION Kotinas Υ. 1*, Matsiori S 1 Department of Ichthyology and Aquatic Environment School of Agricultural Sciences, University of Thessaly Fytoko Street, , Nea Ionia Magnesia ABSTRACT This research aims to study the socio-economical benefits of a protected area especially the economic influence on the local finances. Specifically, the survey was conducted in a Protected Area that is part of the new Lake Karla. For this reason a survey of 200 respondents randomly selected residents of Volos city was carried out with the use of a contracted questionnaire. The questionnaire was designed to reflect residents attitudes for the benefits which were resulted by membership of the lake in a special protected status Principal Components Analysis was used as a tool for measuring different public perceptions and preferences with regard to benefits of Lake Karla. We have extracted three factors explaining 54.2 % of the fluctuation of the total variance. The main conclusion of the research is that the restored lake is a unique opportunity for sustainable development of alternative forms of tourism which will bring substantial economic benefits. ΠΡΟΚΑΣΑΡΣΙΚΑ ΑΠΟΣΕΛΕΜΑΣΑ ΕΡΕΤΝΑ ΓΙΑ ΣΟΝ ΕΝΣΟΠΙΜΟ ΣΩΝ ΩΦΕΛΕΙΩΝ ΠΟΤ ΘΑ ΠΡΟΚΤΨΟΤΝ ΑΠΟ ΣΗΝ ΑΝΑΤΣΑΗ ΣΗ ΛΙΜΝΗ ΚΑΡΛΑ Κνηηλάο Υ. 1*, Μαηζηψξε 1 1 Σιήια Γεςπμκίαξ, Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ, πμθή Γεςπμκζηχκ Δπζζηδιχκ, Πακεπζζηήιζμ Θεζζαθίαξ, Οδυξ Φοηυημο 38446, Βυθμξ, Δθθάδα Πεξίιεςε Ζ πανμφζα ένεοκα είπε ςξ ζηυπμ ηδκ απμηφπςζδ ηςκ ςθεθεζχκ πμο εα πνμηφρμοκ απυ ηδκ ακαζφζηαζδ ηδξ θίικδξ Κάνθα. Γζα ηδκ οθμπμίδζδ ηςκ ζηυπςκ ηδξ ένεοκαξ δζελήπεδ πνςημβεκήξ ένεοκα ιε ηδ πνήζδ δμιδιέκμο ενςηδιαημθμβίμο ζε έκα δείβια 200 ηαημίηςκ ημο Γδιμηζημφ Γζαιενίζιαημξ ημο Βυθμο. Σμ ενςηδιαημθυβζμ είπε ςξ ζηυπμ ηδ δζενεφκδζδ ηςκ απυρεςκ ηςκ πμθζηχκ βζα ηζξ εζδζηά πνμζηαηεουιεκεξ πενζμπέξ αθθά ηαζ ηδκ έκηαλδ ηδξ εονφηενδξ πενζμπήξ ηδξ θίικδξ Κάνθα ζε εζδζηυ ηαεεζηχξ πνμζηαζίαξ. Γζα ηδκ ελαβςβή ηςκ παναβυκηςκ πμο απμηοπχκμοκ ηα παναπάκς μθέθδ εθανιυζηδηε Ακάθοζδ Κονίςκ οκζζηςζχκ (PCA), ιε ηδ αμήεεζα ιζαξ πμθοεειαηζηήξ ενχηδζδξ ιε 39 εέιαηα. Ζ ακάθοζδ έδςζε ηνεζξ πανάβμκηεξ πμο ελδβμφκ ημ 54,2 % ηδξ ζοκμθζηήξ ιεηααθδηυηδηαξ. φιθςκα ιε ηα απμηεθέζιαηα, δ ακαζφζηαζδ ηδξ θίικδ, απμηεθεί ιζα ιμκαδζηή εοηαζνία βνήβμνδξ αθθά ηαζ αζχζζιδξ ακάπηολδξ εκαθθαηηζηχκ ιμνθχκ ημονζζιμφ πμο εα απμθένεζ ζδιακηζηά ημζκςκζημμζημκμιζηά μθέθδ. Λέμεηο θιεηδηά: Λίικδ Κάνθα, πνμζηαηεουιεκεξ πενζμπέξ, ημζκςκζημμζημκμιζηά μθέθδ, παναβμκηζηή ακάθοζδ * οββναθέαξ επζημζκςκίαξ: Κμηζκάξ Υνήζημξ gewix8io@gmail.com 1.Δηζαγσγή O εεζιυξ ηςκ πνμζηαηεοιέκςκ πενζμπχκ απμηέθεζε, παβημζιίςξ, έκα απυ ηα ααζζηά «ενβαθεία» πμθζηζηήξ βζα ηδ δζαηήνδζδ ημο θοζζημφ πενζαάθθμκημξ. Σαοηυπνμκα, δ ίδνοζδ ιζαξ πνμζηαηεουιεκδξ πενζμπήξ ζημπεφεζ, εηηυξ απυ ηδκ πνμζηαζία ημο θοζζημφ πενζαάθθμκημξ, ηαζ ζηδκ πανμπή εοηαζνζχκ οπαίενζαξ ακαροπήξ ηαζ πενζααθθμκηζηήξ εηπαίδεοζδξ αθθά ηαζ ηζκήηνςκ 180

181 ηυκςζδξ ηαζ εκίζποζδξ ημο ημζκςκζημμζημκμιζημφ ζζημφ, ζδίςξ ηςκ μνεζκχκ ημζκςκζχκ ηαζ άνζδξ ηςκ ημζκςκζηχκ απμηθεζζιχκ. Οζ πνμζδμηίεξ ηςκ ημπζηχκ ημζκςκζχκ απυ ημ εεζιυ είκαζ αολδιέκεξ ηαζ εζηζάγμκηαζ ζε έκα ζδιακηζηυ ανζειυ ημζκςκζημμζημκμιζηχκ ςθεθεζχκ, ζδζαίηενα ζήιενα πμο δ μζημκμιζηή ηνίζδ έπεζ ςξ απμηέθεζια ηδ ζοκεπή ζοννίηκςζδ ηςκ εζζμδδιάηςκ ηαζ ηδκ αφλδζδ ηδξ ακενβίαξ. Ζ δζενεφκδζδ ηςκ ςθεθεζχκ πμο πδβάγμοκ απυ ηδκ φπανλδ ιζαξ εζδζηά πνμζηαηεουιεκδξ πενζμπήξ απμηέθεζε ακηζηείιεκμ πμθθχκ ενεοκχκ (Costanza 2000; Heal 2000; Constanza and Farber 2002; de Groot et al. 2002; Ferber et al 2002). Έπεζ δζαπζζηςεεί υηζ φπανλδ ιζαξ πνμζηαηεουιεκδξ πενζμπήξ ζοκδέεηαζ ιε μθέθδ ηυζμ ζε ημπζηυ (Smith 2001; Ngugi 2002; Saayman et al. 2009) υζμ ηαζ ζε εεκζηυ επίπεδμ (Oberholzer et all. 2009) πμο ζοκδέμκηαζ ιε ηδκ αφλδζδ ηδξ παναβςβήξ, ηδκ εκίζποζδ ημο εζζμδήιαημξ ηςκ ημπζηχκ ημζκςκζηχκ ηαζ ηδξ απαζπυθδζδξ ηαζ ηδκ ημονζζηζηή ακάπηολδ. ηδ πχνα ιαξ έπμοκ πναβιαημπμζδεεί πανυιμζεξ ένεοκεξ πμο ζημπυ ηδκ απμηφπςζδ ηςκ ζηάζεςκ ηςκ πμθζηχκ απέκακηζ ζημ εεζιυ ηςκ πνμζηαηεουιεκςκ πενζμπχκ (Dimitrakopoulos et all. 2010), ημκ εκημπζζιυ ηαζ ηδ ζηζαβνάθδζδ ηςκ ςθεθεζχκ πμο μζ πμθίηεξ ακαιέκμοκ απυ ηδ δδιζμονβία ιζαξ εζδζηά πνμζηαηεουιεκδξ πενζμπήξ (Μαζημνμβζάκκδ ηαζ ζοκ 2012) ηαζ ηδκ μζημκμιζηή απμηίιδζδ ηςκ ςθεθεζχκ πμο πνμένπμκηαζ απυ ηδκ φπανλή ημοξ (Κoutseris 2001). Οζ δφμ ηεθεοηαίεξ ενβαζίεξ ακαθένμκηαζ ζηδ Λίικδ Κάνθα. ημπυξ ηδξ πανμφζαξ ένεοκαξ ήηακ δ δζενεφκδζδ ηαζ μ πνμζδζμνζζιυξ ηςκ ςθεθεζχκ (ημζκςκζηχκ, πενζααθθμκηζηχκ, ακαπηολζαηχκ ηαζ μζημκμιζηχκ), πμο ζφιθςκα ιε ημοξ ηαημίημοξ εα πνμηφρμοκ βζα ηδκ πενζμπή απυ ηδκ ακαζφζηαζδ ηδξ θίικδξ Κάνθα ηαζ ηδκ έκηαλδ ηδξ εονφηενδξ πενζμπήξ ζε εζδζηυ ηαεεζηχξ πνμζηαζίαξ. 2.Τιηθά θαη κέζνδνη Ζ πανμφζα ένεοκα πναβιαημπμζήεδηε ζηδκ θίικδ Κάνθα ημο κμιμφ Μαβκδζίαξ. Ζ πενζμπή ένεοκαξ πενζθαιαάκεζ δφμ πενζμπέξ πμο έπμοκ ηδνοπεεί ςξ πνμζηαηεουιεκεξ ηαζ έπμοκ εκηαπεεί ζε εζδζηυ ηαεεζηχξ πνμζηαζίαξ NATURA 2000 (Κάνθα-Μαονμαμφκζμ-Κεθαθυανοζμ Βεθεζηίκμο ηαζ νμξ Μαονμαμφκζμ). Ζ θίικδ Κάνθα πνζκ ηδκ απμλήνακζή ηδξ (ημ έημξ 1962) απμηεθμφζε έκαξ απυ ημοξ ζπμοδαζυηενμοξ οβνμαζυημπμοξ ζηδκ Δθθάδα ηαζ ζηα Βαθηάκζα. Πανυθα αοηά, ημ Δθθδκζηυ Γδιυζζμ πνμπχνδζε ζηδκ απμλήνακζή ηδξ ιε ηδκ εθπίδα ηδξ ελαζθάθζζδξ πμηζζηζηχκ, πεδζκχκ εηηάζεςκ βζα ηαθθζένβεζα. Ζ ακάθδρδ, υιςξ, εκυξ ηέημζμο ένβμο, ιεβάθδξ ηθίιαηαξ, πςνίξ κα πνμδβδεεί ιεθέηδ πενζααθθμκηζηχκ επζπηχζεςκ είπε ζμαανέξ πενζααθθμκηζηέξ, ημζκςκζηέξ ηαζ μζημκμιζηέξ ζοκέπεζεξ ζηδκ εονφηενδ πενζμπή (Εαθίδδξ ηαζ ζοκ. 1995). ήιενα, δ ακαζφζηαζδ ηδξ θίικδξ ηαζ δ έκηαλή ηδξ ζε ηαεεζηχξ εζδζηά πνμζηαηεουιεκδξ πενζμπήξ ακαιέκεηαζ κα απμθένεζ ζηδκ πενζμπή ζδιακηζηά ημζκςκζημμζημκμιζηά μθέθδ πένακ ηςκ πενζααθθμκηζηχκ. Ζ οθμπμίδζδ ηςκ ζηυπςκ ηδξ πανμφζαξ ένεοκαξ ηαζ δ ζοθθμβή υθςκ ηςκ απαναίηδηςκ πνςημβεκχκ δεδμιέκςκ πνμτπυεεηε ηδ δζελαβςβή πνςημβεκμφξ ένεοκαξ ιε ηδ πνήζδ δμιδιέκμο ενςηδιαημθμβίμο. Πθδεοζιυξ ζηυπμξ ηδξ πανμφζαξ ένεοκαξ ήηακ μζ ηάημζημζ ημο Γδιμηζημφ Γζαιενίζιαημξ ημο Βυθμο ηαζ ζοθθέπεδηακ ζοκμθζηά 200 ενςηδιαημθυβζα. Γζα ηδκ οθμπμίδζδ ηςκ ζηυπςκ ηδξ ένεοκαξ ηαηανηίζηδηε κέμ ενςηδιαημθυβζμ, ημ μπμίμ ααζίζηδηε, ζε ηάπμζμ ααειυ, ζε ενςηδιαημθυβζμ πνμδβμφιεκδξ ένεοκαξ πμο δζελήπεδ ζημ ηιήια ιε πανυιμζμ ζηυπμ. Σμ ενςηδιαημθυβζμ ηδξ πανμφζαξ ένεοκαξ απμηεθμφκηακ απυ ενςηήζεζξ πμο ζημπυ είπακ κα ζηζαβναθήζμοκ ηζξ απυρεζξ ηςκ πμθζηχκ βζα ηδκ πνμζηαζία ημο πενζαάθθμκημξ, κα απμηοπχζμοκ ηα μζημκμιζηά μθέθδ πμο εα πνμηφρμοκ απυ ηδ ακαζφζηαζδ ηδξ θίικδξ Κάνθα ηαζ ηδκ έκηαλή ηδξ ζε εζδζηυ ηαεεζηχξ θεζημονβίαξ ηαζ ηέθμξ κα απμηζιήζμοκ μζημκμιζηά ηα παναπάκς μθέθδ. Ζ αλζμπζζηία ημο ενςηδιαημθμβίμο ηνίεδηε ιε ηδ αμήεεζα ημο ζοκηεθεζηή a-cronbach, μ μπμίμξ πνδζζιμπμζείηαζ ζοκήεςξ βζα ηδ ιέηνδζδ ηδξ εζσηεξηθήο ζπλέπεηαξ ιζαξ δμηζιαζίαξ (Churchill 1995). Γζα ηδ δζενεφκδζδ ηςκ απυρεςκ ηςκ ηαημίηςκ ημο Βυθμο ζπεηζηά ιε ηα μθέθδ πμο εα πνμηφρμοκ απυ ηδκ επακαζφζηαζδ ηδξ θίικδξ Κάνθαξ ζοιπενζθήθεδηε ζημ ενςηδιαημθυβζμ ιζα πμθοεειαηζηή ενχηδζδ 39 εειάηςκ, ηα μπμία εκηάζζμκηακ ζε ιζα απυ ηζξ ααζζηέξ ηαηδβμνίεξ ςθεθεζχκ πμο ζφιθςκα ιε ηδ αζαθζμβναθία πνμηφπημοκ βζα ιζα εζδζηά πνμζηαηεουιεκδ πενζμπή (μζημκμιζηά, ημζκςκζηά, ακαπηολζαηά ηαζ πενζααθθμκηζηά μθέθδ). Γζα ηδκ ελαβςβή ηςκ παναβυκηςκ μζ ενςηχιεκμζ ηθήεδηακ κα αλζμθμβήζμοκ, ιε ηδ αμήεεζα ιζαξ πεκηάααειδξ ηθίιαηαξ Likert (ηαευθμο, ιέηνζα, ανηεηά, πμθφ, πάνα πμθφ) ηα παναπάκς εέιαηα. Ζ ακαβκχνζζδ ηςκ παναβυκηςκ, μζ μπμίμζ πενζβνάθμοκ ηζξ ιεηααθδηέξ πμο πενζηθείμοκ, έβζκε ιε πενζζηνμθή ηςκ παναβυκηςκ ιε ηδ ιέεμδμ ηδξ μνεμβςκζηήξ πενζζηνμθήξ ή ιέεμδμ ηδξ πενζζηνμθήξ ηδξ ιέβζζηδ δζαηφιακζδξ (Varimax). Αοηυ ζδιαίκεζ υηζ μζ πανάβμκηεξ (ζοκζζηχζεξcomponents) πμο ελήπεδζακ είκαζ βναιιζηά αζοζπέηζζημζ (Υνζζημδμφθμο η.ά., 2002). Ζ 181

182 ζοβηεηνζιέκδ ιέεμδμξ πνμηείκεηαζ απυ ημκ Kaiser ηαζ είκαζ δ πθέμκ πνδζζιμπμζμφιεκδ. Γζα ημκ ηαεμνζζιυ ηςκ παναβυκηςκ πμο ελήπεδζακ δεκ πνδζζιμπμζήεδηε ημ ηνζηήνζμ ηδξ ζδζμηζιήξ αθθά μ ανζειυξ επζθέπεδηε ιε αάζδ ηδ ζοιαμθή ημο επυιεκμο πανάβμκηα ζηδκ ελδβμφιεκδ δζαηφιακζδ. 3. Απνηειέζκαηα ημκ Πίκαηα 1 δίκμκηαζ ηα ααζζηά ημζκςκζημμζημκμιζηά παναηηδνζζηζηά ημο δείβιαημξ. Πίλαθαο I. Κνηλσληθννηθνλνκηθά ραξαθηεξηζηηθά ησλ ζπκκεηερφλησλ ζηελ έξεπλα Μέζμξ υνμξ Σοπζηή απυηθζζδ Γέκμξ (%) Γοκαίηεξ (56 %) Ζθζηία (έηδ) 44,88 12,95 Δπίπεδμ ζπμοδχκ Απυθμζημζ ΑΔΗ 2,82 (51,5%) Οζημβεκεζαηή ηαηάζηαζδ Έββαιμξ/δ (53,5%) Ανζειυξ ιεθχκ μζημβέκεζαξ 3,37 1,09 Μέζμ ιδκαίμ πνμζςπζηυ εζζυδδια ( ) 843,41 515,218 Μέζμ ιδκζαίμ μζημβεκεζαηυ εζζυδδια ( ) 1.589,18 908,99 Ζ ακάθοζδ ζε ηφνζεξ ζοκζζηχζεξ έδςζε 4 πανάβμκηεξ, πμο ελδβμφκ ημ 54,2 % ηδξ ζοκμθζηήξ ιεηααθδηζηυηδηαξ. Ζ δζαηφιακζδ πμο ελδβείηαζ απυ ηδκ πνχηδ ηφνζα ζοκζζηχζα είκαζ 43,047, απυ ηδ δεφηενδ 6,156% ηαζ απυ ηδκ ηνίηδ 4,997% (Πίκ. 2). Ο έθεβπμξ ζθαζνζηυηδηαξ ημο Bartlett έδεζλε υηζ οπάνπεζ ορδθή ζηαηζζηζηή ζδιακηζηυηδηα ημο ζηαηζζηζημφ x 2 (x 2 = 5429,803, α.ε=741, ν=0,000). Ο δείηηδξ ηςκ Kaiser Mayer Olkin (ΚΜΟ) ήηακ 0,932. Καηά ημκ Hair et al (1995) ημ επζηνεπηυ υνζμ είκαζ δ ηζιή 0,5, εκχ ηαηά ημκ Sharma (1996) δ ηζιή 0,6. Πίλαθαο 2. Απνηειέζκαηα εθαξκνγήο PCA Πανάβμκηεξ Δλδβμφιεκδ δζαηφιακζδ οκηεθεζηή αλζμπζζηίαξ a-cronbach οκμθζηυξ ζοκηεθεζηή αλζμπζζηίαξ a-cronbach ΚΜΟ Bartlett's Test of Sphericity Ακάπηολδ πενζμπήξ 43,047 0,943 0,958 0,932 App. π Κμζκςκζημμζημκμιζηά 6,156 0,846 (5429,803) μθέθδ Πενζααθθμκηζηή αεθηίςζδ 4,997 0,891 df = 741 p= 0,000 Ο πνχημξ πανάβμκηαξ πμο ακαβκςνίγεηαζ απυ ημοξ ενςηχιεκμοξ ιπμνεί κα μκμιαζηεί, ακαπηολζαηυξ βζαηί ηαζ μζ 17 ιεηααθδηέξ ημο ζπεηίγμκηαζ ιε ηα πζεακά ακαπηολζαηά μθέθδ πμο εα πνμηφρμοκ ζηδκ πενζμπή. Ο πνχημξ πανάβμκηαξ είκαζ ηαεμνζζηζηήξ ζδιαζίαξ αθμφ ενιδκεφεζ ημ 37,245% ηδξ ζοκμθζηήξ ιεηααθδηυηδηαξ. οκεπχξ, εηείκμ πμο ελδβεί ηδ ιεβάθδ ζδιαζία πμο δίκμοκ μζ ηάημζημζ ηςκ παναηάνθζςκ πςνζχκ ζηδκ ηεθεζμπμίδζδ ηςκ ένβςκ ακαζφζηαζδξ ηδξ θίικδξ Κάνθαξ είκαζ δ δδιζμονβία οπμδμιχκ ηαζ εοκμσηχκ ζοκεδηχκ βζα ηδκ πναβιαημπμίδζδ κέςκ, ζοιααηχκ ιε ηδ αζχζζιδ ακάπηολδ δναζηδνζμηήηςκ. Δηηυξ απυ αοηά μζ ενςηχιεκμζ έδςζακ πμθφ ιεβάθδ ζδιαζία ζηζξ εοηαζνίεξ βζα ακάπηολδ εεκζηχκ ηαζ ημζκμηζηχκ πνμβναιιάηςκ ζηδκ πενζμπή, ηα μπμία εα ζοιαάθθμοκ μοζζαζηζηά ζηδκ ακάπηολδ ηδξ πενζμπήξ ηαζ ηδ δδιζμονβία ηδξ απαζημφιεκδξ οπμδμιήξ, ηονίςξ ζημκ ημιέα ημο αβνμημονζζιμφ. Έηζζ εα αεθηζςεεί ημ αμζςηζηυ επίπεδμ ηςκ ηαημίηςκ ηδξ πενζμπήξ. Σα δεοηενεφμκηα εέιαηα πμο ζοιπενζθήθεδζακ ζημκ πνχημ πανάβμκηα, υπςξ δ δζάζςζδ ημο πενζααθθμκηζημφ πθμφημο ηδξ πενζμπήξ, δ πνμαμθή ηδξ πανάδμζδξ ηδξ ηαεχξ ηαζ δ δζάδμζδ ηδξ πμθζηζζιζηήξ ηθδνμκμιζάξ, αμδεμφκ ζηδκ επίηεολδ ηςκ ζηυπςκ ηςκ εειάηςκ πμο είπηδηακ πνμδβμοιέκςξ. Ο δεφηενμξ πανάβμκηαξ ζοκδέεηαζ ιε ηα ημζκςκζηά ηαζ μζημκμιζηά μθέθδ πμο ακαιέκμοκ μζ ηάημζημζ κα πνμέθεμοκ απυ ηδκ ακαζφζηαζδ ηδξ θίικδξ Κάνθαξ. Σα εέιαηα πμο θμνηχκμοκ ζημκ πανάβμκηα αοηυ αθμνμφκ ζηα μζημκμιζηά μθέθδ πμο εα πνμηφρμοκ απυ ηζξ κέεξ επζπεζνδιαηζηέξ δναζηδνζυηδηεξ ζηδκ πενζμπή ηαεχξ επίζδξ ηαζ απυ ηζξ αεθηίςζδ ακάπηολδ ηδξ ημπζηήξ μζημκμιίαξ ιέζα απυ ηδκ πνμζέθηοζδ επζζηεπηχκ. Οζ ηάημζημζ αζζζμδμλμφκ βζα ηδ δδιζμονβία, εκυξ κέμο 182

183 ημονζζηζημφ πνμμνζζιμφ, πμο εα ακαδείλεζ ηδ δοκαηυηδηα ανιμκζηήξ ακάπηολδξ ακενχπζκςκ δναζηδνζμηήηςκ ζε ζζμννμπία ιε ημ θοζζηυ πενζαάθθμκ. Ηενανπμφκ ορδθά ζηδ ζοκείδδζή ημοξ εέιαηα παζδείαξ, ηαζ πμθζηζζιμφ αθθά ηαζ εέιαηα πμο ζπεηίγμκηαζ ιε ηδκ ακάπηολδ εκαθθαηηζηχκ ιμνθχκ ημονζζιμφ. ημπεφμοκ ζηδ δδιζμονβία εκυξ πνυηοπμο πχνμο βζα ηδκ ακάδεζλδ ηδξ ζζημνζηήξ ζδιαζίαξ ηδξ πενζμπήξ ηαζ ηδ ζπέζδ ηςκ παθαζυηενςκ μζηζζιχκ ηδξ πενζμπήξ, ιε ηδ θίικδ αθθά ηαζ ζηδ ακάδεζλδ ημο θζικαίμο πμθζηζζιμφ. Σέθμξ, μ ηνίημξ πανάβμκηαξ ζοκδέεηαζ ιε ηα πενζααθθμκηζηά μθέθδ πμο εα πνμηφρμοκ ζηδκ πενζμπή. Οζ ενςηχιεκμζ ακαιέκμοκ υηζ δ ακαζφζηαζδ ηδξ θίικδξ εα έπεζ ςξ απμηέθεζια ηδ εκίζποζδ ηδξ μζημθμβζηήξ ζζμννμπίαξ, ηδκ πνμζηαζία ηδξ αζμπμζηζθυηδηαξ ηαζ ηδ απμηαηάζηαζδ ημο οδνμθυνμο μνίγμκηα. Οζ ενςηχιεκμζ έπμοκ ακηζθδθεεί υηζ ιεηά ηδκ απμλήνακζδξ ηδξ θίικδξ αημθμφεδζε δ απχθεζα ηςκ εκδζαζηδιάηςκ ηαζ ηδξ άβνζαξ πακίδαξ, δ μπμία ζήιενα ηζκδοκεφεζ ιε ελαθάκζζδ. Δίκαζ, θμζπυκ, πεπεζζιέκμζ βζα ηδκ ακαβηαζυηδηα ηδξ επακαζφζηαζδξ ημο ζδιακηζημφ οβνμηυπμο βζα ηδκ ακηζιεηχπζζδ ηςκ μλοιέκςκ πενζααθθμκηζηχκ πνμαθδιάηςκ ηαζ απεζθχκ πμο πνμέηορακ απυ ηζξ ιεβάθεξ πανειαάζεζξ ζηδκ εονφηενδ πενζμπή ηδξ θίικδξ. 4. πδήηεζε Ζ πανμφζα ένεοκα είπε ςξ ζηυπμ ημκ εκημπζζιυ ηςκ εζδζηχκ ημζκςκζηχκ ηαζ μζημκμιζηχκ ςθεθεζχκ πμο εα πνμηφρμοκ απυ ηδκ έκηαλδ ηδξ εονφηενδξ πενζμπήξ ζε εζδζηυ ηαεεζηχξ πνμζηαζίαξ, αθθά ηαζ κα δζενεοκήζεζ ηζξ απυρεζξ ηςκ πμθζηχκ βζα ηζξ επζδνάζεζξ αοημφ ημο εζδζημφ ηαεεζηχημξ ζηδκ εονφηενδ πενζμπή ηδξ θίικδξ Κάνθαξ ηαζ εζδζηυηενα ζηζξ ημπζηέξ ημζκςκίεξ. Οζ ηάημζημζ πνμζδμημφκ ζε κέεξ εοηαζνίεξ ζηα ήδδ οπάνπμκηα επαββέθιαηα ιέζα απυ εκαθθαηηζηέξ ιμνθέξ ημονζζιμφ, ζηδκ πνμζέθηοζδ ημονζζηχκ, ιαεδηχκ ηαζ ενεοκδηχκ ζημκ ηαζκμφνζμ αοηυκ αζυημπμ. Οζ ακενχπζκεξ δναζηδνζυηδηεξ ζε ζζμννμπία ιε ημ θοζζηυ πενζαάθθμκ αθθά ηαζ ιε ηδκ πνμαμθή ηδξ πανάδμζδξ, ηδξ πμθζηζζηζηήξ ηθδνμκμιζάξ ηαζ ηδκ ακάδεζλδ ημο θζικαίμο πμθζηζζιμφ ηδξ πενζμπήξ, εα έπμοκ ςξ απμηέθεζια ηδκ άκμδμ ημο αζμηζημφ επζπέδμο ημο ημπζημφ πθδεοζιμφ. Ζ απμηαηάζηαζδ ηδξ μζημθμβζηήξ ζζμννμπίαξ ζηδκ εονφηενδ πενζμπή ηαζ ηα πενζααθθμκηζηά μθέθδ είκαζ αοηά πμο δ πθεζμρδθία ηςκ πμθζηχκ εεςνεί επίζδξ ζδιακηζηά μθέθδ απυ ηδ δδιζμονβία ηαζ έκηαλδ ηδξ θίικδξ ζε εζδζηυ ηαεεζηχξ πνμζηαζίαξ. Σα απμηεθέζιαηα ηδξ ένεοκαξ ζοιθςκμφκ ζε ιεβάθμ ααειυ ιε αοηά πνμδβμφιεκδξ ένεοκαξ, δ μπμία είπε δζελαπεεί ζηδκ εονφηενδ πενζμπή ηδξ θίικδξ ζε δείβια ηαημίηςκ ηδξ πενζμπήξ ηαζ ζφιθςκα ιε ηδκ μπμία μζ πανάβμκηεξ μθέθδ πμο εα πνμηφρμοκ απυ ηδκ ακαζφζηαζδ ηδξ θίικδξ ήηακ ηονίςξ ακαπηολζαηά (Μαζημνμβζάκκδ ηαζ ζοκ 2012). Γζα κα επζηφπμοκ υθα ηα παναπάκς πνεζάγεηαζ δ άιεζδ ζοκενβαζία ιεηαλφ ηςκ θμνέςκ ηαζ ηδξ ημπζηήξ ημζκςκίαξ. Ακ υθα ελεθζπημφκ μιαθά ηαζ ακαζοζηαεεί δ θίικδ πνέπεζ κα πενζιέκμοιε κα δμφιε ακ εα εθανιμζημφκ πναηηζηά ηα μθέθδ.ε πενίπηςζδ εθανιμβήξ ημοξ εα πνέπεζ κα δζελαπεεί ηαζκμφνζα ένεοκα ζηδκ μπμία εα δζακειδεμφκ εη κέμο ενςηδιαημθυβζα ηαζ εα βίκεζ εη κέμο ζηαηζζηζηή ακάθοζδ βζα ηδ ιεθέηδ ημο πμζμζημφ επίηεολδξ ημο ζηυπμο ηςκ ςθεθεζχκ. Βηβιηνγξαθία Costanza R. (2000). Social goals and the valuation of ecosystem services. Ecosystems 3(1): Costanza R. and S. Farber (2002). Introduction to the special issue on the dynamics and value of ecosystem services: integrating economic and ecological perspectives. Ecological Economic 42 (3): De Groot R.S., M.A. Wilson and R.M.J. Boumans (2002). A typology for the classification, description and valuation of ecosystem functions, goods and services. Ecological Economics 41 (3): Ferber, S.C., R. Costanza and M.A. Wilson (2002). Economic and ecological concepts for valuing ecosystem services. Ecological Economics 41 (3): Oberholzer S, M. Saayman A. Saayman and E. Slabbert (2009). The Socio Economic Impact of Africa s Oldest Marine Park. Proceedings of CMT2009, the 6 th International Congress and Marine Tourism, June Ngugi,I. (2002). Economic impacts of marine protected areas: A case study of the Mambasa Marine Park. Saayman M. Saayman A. and Ferreira M. (2009). The socio economic impact of the Karoo National Park in

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185 COASTAL WATER POLLUTION FROM THE URBAN RUNOFF NETWORK IN CHANIA, GREECE Stavroulakis G., A. Kirkou, A. Bampala Department of Environmental & Natural Resources Engineering, Technological Educational Institute of Crete School of Applied Sciences. PO Box 89, Chania ABSTRACT The central urban runoff pipe outlet of the city of Chania is located in the west side of the city, on the coastal area of Koum Kapi, close to a beach used for swimming by the public. Throughout the period, water samples were collected from the central urban runoff pipe outlet, in the framework of ARCHIMEDES project. Seawater samples were also collected from the coastal area of Koum Kapi, 5m, 15m and 30m away from the urban runoff pipe outlet. During this research period, the total and fecal coliforms, E. coli and enterococcus were measured. The high level of the pollution load measured in the urban runoff pipe outlet, was reduced by 90-97% in a vertical distance of 5m from the pipe outlet and at 0.7m depth. A diffusion model - based on additional data obtained from pollution diffusion measurements at each side of the pipe - could support decision makers to prevent future coastal water pollution. Key words : coastal water, urban runoff, water pollution. *Corresponding author: Stavroulakis George (gstav@chania.teicrete.gr) ΕΠΙΒΑΡΤΝΗ ΠΑΡΑΚΣΙΩΝ ΤΔΑΣΩΝ ΑΠΟ ΣΟΝ ΑΓΩΓΟ ΟΜΒΡΙΩΝ ΣΗ ΠΟΛΗ ΣΩΝ ΧΑΝΙΩΝ Σηαςποςλάκηρ Γ.*, Κύπκος Αμ.,. Μπαμπάλα Αγγ. Σιήια Μδπακζηχκ Φοζζηχκ Πυνςκ & Πενζαάθθμκημξ TE, πμθή Δθανιμζιέκςκ Δπζζηδιχκ, Σεπκμθμβζηυ Δηπαζδεοηζηυ Ίδνοια Κνήηδξ. ΣΘ 89, Υακζά, Δθθάδα. Πεξίιεςε Ζ εηνμή ημο ηεκηνζημφ αβςβμφ υιανζςκ ηδξ πυθδξ ηςκ Υακίςκ ανίζηεηαζ ζηδκ δοηζηή πθεονά ηδξ αηηήξ Κμοι-Καπί ιεηαλφ «ηαηά πανάδμζδ» ζδιείςκ ημθφιαδζδξ ηαημίηςκ ηδξ πενζμπήξ ηαζ επζζηεπηχκ ηδξ παθζάξ πυθδξ. Σδκ πενίμδμ , ζηα πθαίζζα ημο οπμένβμο ΑΡΥΗΜΖΓΖ, πναβιαημπμζήεδηακ δεζβιαημθδρίεξ απυ ηδκ εηνμή ημο αβςβμφ ηαζ ηδκ εαθάζζζα πενζμπή, ζε δζάθμνεξ απμζηάζεζξ απυ ημκ αβςβυ. Πνμζδζμνίζηδηε δ ζοβηέκηνςζδ ηςκ ιζηνμαζμθμβζηχκ δεζηηχκ: μθζηά ηαζ ημπνακχδδ ημθμααηηήνζα, E. coli, ηαζ εκηενυημηημξ. Σμ ιζηνμαζμθμβζηυ θμνηίμ πμο απμαάθθεηαζ ιέζς ημο αβςβμφ είκαζ ζδζαίηενα ζδιακηζηυ αθθά δ αναίςζδ πμο παναηδνήεδηε ζηδκ εαθάζζζα πενζμπή έθηαζε ζημ 90-97% ζηδκ ζζμααεή 0,7 ι ηαζ ζε απυζηαζδ ιεβαθφηενδ ηςκ 5 ι απυ ηδκ έλμδμ ημο αβςβμφ. Ζ εθανιμβή ηςκ απμηεθεζιάηςκ ζε ηαηάθθδθμ ιμκηέθμ δζάποζδξ νφπςκ ιπμνεί κα απμηεθέζεζ ενβαθείμ πνυαθερδξ ηδξ επζαάνοκζδξ πανάηηζςκ πενζμπχκ απυ πνυεεζδ ή αηφπδια ιέζς ηςκ αβςβχκ υιανζςκ. Λέμεηο θιεηδηά: πανάηηζα φδαηα, αβςβυξ υιανζςκ, ιζηνμαζμθμβζηυ θμνηίμ, ιυθοκζδ. *οββναθέαξ επζημζκςκίαξ : ηαονμοθάηδξ Γζχνβμξ (gstav@chania.teicrete.gr ) 1. Δηζαγσγή Οζ αβςβμί υιανζςκ αζηζηχκ πενζμπχκ ζοκδέμκηαζ ζοπκά ιε ηδκ επζαάνοκζδ ηςκ πανάηηζςκ πενζμπχκ εηθυνηζζδξ ηαζ ηδκ οπμαάειζζδ ηδξ πμζυηδηαξ ηςκ κενχκ ημθφιαδζδξ ηδξ πενζμπήξ ηαεχξ ιπμνμφκ κα ιεηαθένμοκ πδιζηυ ηαζ αζμθμβζηυ νοπμβυκμ θμνηίμ άβκςζηδξ ζοβηέκηνςζδξ (Parker 185

186 etal, 2010, Jeng etal, 2005). Οζ πανάβμκηεξ πμο ζοιαάθθμοκ ζηδκ δδιζμονβία αοημφ ημο νοπμβυκμο θμνηίμο είκαζ, ιεηαλφ άθθςκ, δ δζάανςζδ ημο εδάθμοξ, ηα λεπθφιαηα ηςκ αηαεανζζχκ ηςκ δνυιςκ, δ ζοζζχνεοζδ ηαζ ημ λέπθοια ηδξ αηιμζθαζνζηήξ ζηυκδξ ηαζ ηα ηαηαηνδικίζιαηα (Nazahiyah etal, 2007), ιε απμηέθεζια κα εκημπίγεηαζ μνβακζηυ θμνηίμ, αανέα ιέηαθθα, ενεπηζηά ζοζηαηζηά, θοημθάνιαηα, θίπδ, έθαζα, οδνμβμκάκεναηεξ ηαζ ααηηήνζα (Gnecco etal 2005, Bedan etal 2009). ζμκ αθμνά ημ ιζηνμαζμθμβζηυ θμνηίμ, αοηυ απμηεθεί ζδιακηζηυ νφπμ ηςκ αζηζηχκ απμννμχκ ηαεχξ ζοπκά ζοκακηάηαζ ανηεηά ιεβάθμξ ανζειυξ απμζηζχκ παεμβυκςκ ιζηνμμνβακζζιχκ, ιεηαλφ ηςκ μπμίςκ είκαζ ηαζ ηα μθζηά ηαζ ημπνακχδδ ημθμααηηήνζα, E.coli ηαζ εκηενυημηημξ, (Jeng etal, 2005). Ζ πανμοζία ιζηνμαζμθμβζημφ θμνηίμο ζηζξ αζηζηέξ απμννμέξ, ηζξ ηαεζζηά ελαζνεηζηά επζηίκδοκεξ βζα ηδ δδιυζζα οβεία, αθμφ έπεζ ακαθενεεί υηζ μνζζιέκεξ θμνέξ δ ζοβηέκηνςζή ηςκ ιζηνμαζαηχκ απμζηζχκ ιπμνεί κα θηάζεζ εηείκδ ηςκ απμζηζχκ πμο πενζέπμκηαζ ζε αναζςιέκα αηαηένβαζηα απυαθδηα (Qureshi etal 1979). Ζ πανμφζα ιεθέηδ είπε ζημπυ ηδκ εηηίιδζδ ημο νοπμβυκμο θμνηίμο πμο ιπμνεί κα ιεηαθενεεί ιέζς ημο ηεκηνζημφ αβςβμφ υιανζςκ ηδξ πυθδξ ηςκ Υακίςκ ζημ ζδιείμ εηθυνηζζδξ ημο ζηδκ εαθάζζζα πενζμπή ημο Κμοι Καπί ηαζ ημο ααειμφ επζαάνοκζδξ ηςκ κενχκ ημθφιαδζδξ ζηδκ πενζμπή βφνς απυ ημ ζδιείμ εηθυνηζζδξ. Σα απμηεθέζιαηα πμο πανμοζζάγμκηαζ αθμνμφκ ηδκ δζάποζδ ημο ιζηνμαζμθμβζημφ θμνηίμο ηαεχξ ανέεδηε κα έπεζ ζοκεπή πανμοζία ηαζ ορδθή ζοβηέκηνςζδ ζηα δείβιαηα πμο ζοβηεκηνχεδηακ απυ ηδκ πενζμπή ιεθέηδξ ηαζ εοκμεί ηδκ ιεθέηδ ημο ααειμφ ιείςζδξ ημο νοπμβυκμο θμνηίμο ακάθμβα ιε ηδκ απυζηαζδ απυ ημ ζδιείμ εηθυνηζζδξ. 2. Τιηθά θαη Μέζνδνη Ζ εαθάζζζα πενζμπή ημο ηυθπμο Κμοι Καπί ανίζηεηαζ ζημ δοηζηυ άηνμ ηδξ παθζάξ πυθδξ ηςκ Υακίςκ ηαζ απμηεθεί ακέηαεεκ ζδιείμ ημθφιαδζδξ βζα ημοξ ηαημίημοξ ηδξ πενζμπήξ αθθά ηαζ ημοξ επζζηέπηεξ (Δζηυκα 1 ζδιεία 2,3). Ζ δζάανςζδ ηδξ αηηήξ απυ ημκ ζοπκά έκημκμ ηοιαηζζιυ αθθάγεζ ηδκ ιμνθή ηδξ παναθίαξ ηαζ δεκ επζηνέπεζ ηδκ δζαηήνδζδ αιιχδμοξ ηιήιαημξ ζε υθμ ημ ιήημξ ηδξ παναθίαξ πανά ιυκμ ζημ ηεκηνζηυ ζδιείμ ημο ηυθπμο ηαζ ζε απυζηαζδ 500 ι πενίπμο κμηζυηενα απυ ημ ζδιείμ εηνμήξ ημο αβςβμφ υιανζςκ (Δζηυκα 1 ζδιείμ 3). Ζ πενζμπή έπεζ ακμζηηυ ιέηςπμ ιε ημκ ηυθπμ ηςκ Υακίςκ πςνίξ ειπυδζα ή ένβα πνμζηαζίαξ απυ ηδκ ιακία ηςκ ηοιάηςκ. Ο αβςβυξ υιανζςκ οδάηςκ πμο εηαάθεζ ζηδκ εαθάζζζα πενζμπή ημο Κμοι Καπί ζοβηεκηνχκεζ ημκ ιεβαθφηενμ υβημ ηςκ αζηζηχκ απμννμχκ ηδξ πυθδξ ηςκ Υακίςκ (Δζηυκα 1 ζδιείμ 1). Ο ζοκμθζηυξ υβημξ ηςκ υιανζςκ οδάηςκ πμο ιεηαθένμκηαζ εηδζίςξ ιέζς ημο ζοβηεηνζιέκμο αβςβμφ οπμθμβίγμκηαζ, ηαηά ιέζμ υνμ, ζηα 350*10 3 m 3 ιε ηαηακμιή πμο ελανηάηαζ άιεζα απυ ημ εηήζζμ φρμξ ανμπήξ ηαζ ηδκ έκηαζδ ηςκ ηαζνζηχκ θαζκμιέκςκ. Δπζπθέμκ, ιεβάθμ ιένμξ ηδξ λδνήξ πενζυδμο, εηηζιάηαζ υηζ απμννέμοκ πενίπμο 60 m 3 διενδζίςξ, ζοπκά ζδζαίηενα ορδθμφ, νοπμβυκμο θμνηίμο. Σδκ πενίμδμ ιεθέηδξ, Φεανμοάνζμξ Μάζμξ 2014, πναβιαημπμζήεδηακ 18 δεζβιαημθδρίεξ κενμφ ζημ ζδιείμ εηθυνηζζδξ ημο ηεκηνζημφ αβςβμφ υιανζςκ ηδξ πυθδξ ηςκ Υακίςκ ζηδκ παναθία Κμοι-Καπί ηαεχξ ηαζ ζε ζδιεία ηδξ εαθάζζζαξ πενζμπήξ ζε ζοβηεηνζιέκεξ απμζηάζεζξ απυ ημ ζδιείμ εηνμήξ ημο αβςβμφ (Δζηυκα 1 ζδιείμ 1). Ανπζηά έβζκακ δεζβιαημθδρίεξ ζε απυζηαζδ 5 ι, 15 ηαζ 30ι απυ ηδκ έλμδμ ημο αβςβμφ ηαεχξ ηαζ 30ι δελζά ηαζ ανζζηενά ηάεε ζδιείμο, χζηε κα πνμζδζμνζζηεί δ απυζηαζδ ζηδκ μπμία δ αναίςζδ εα θηάκεζ πάκς απυ 90% ημο ανπζημφ θμνηίμο ηδξ εηνμήξ. Δπζθέπεδηε δ απυζηαζδ ηςκ 5 ι απυ ημκ αβςβυ υιανζςκ ηαζ έβζκακ μζ δεζβιαημθδρίεξ. Οζ ηαζνζηέξ ζοκεήηεξ ζε υθεξ ηζξ δεζβιαημθδρίεξ ήηακ ήπζεξ ιε φρμξ ηφιαημξ <0,5ι ηαζ έκηαζδ ακέιμο 1-2Beaufort. 186

187 2 60μ Β 1 5μ 15μ 30μ 3 Δηθφλα 1. Ζ παξαιία Κνπκ Καπί. Ζ εθξνή ηνπ αγσγνχ βξίζθεηαη ζην ζεκείν 1. Σα ζεκεία θνιχκβεζεο ησλ θαηνίθσλ ηεο πεξηνρήο είλαη ηα ζεκεία 2 θαη 3. Μπξνζηά απφ ηελ εθξνή ηνπ αγσγνχ (ζεκείν 1) θαίλεηαη ην πιέγκα ησλ ζεκείσλ δεηγκαηνιεςίαο ζηα 5κ, 15κ, 30κ. Σα δείβιαηα κενμφ ιεηαθενυηακ ιε θμνδηυ ροβείμ (4 o C) ζημ Δνβαζηήνζμ βζα ημκ πνμζδζμνζζιυ ημο ιζηνμαζμθμβζημφ θμνηίμο (APHA, 1998). Οζ ιζηνμαζμθμβζηέξ ακαθφζεζξ έβζκακ ιε ηδκ ιέεμδμ ηδξ δζήεδζδξ κενμφ ζε απμζηεζνςιέκα θίθηνα ηοηηανίκδξ 47mm/0.45por (Gelman GN 66191) ηαζ ηδκ επχαζδ ημοξ ζε ηαηάθθδθα οπμζηνχιαηα (IDG, 2002). Γζα μθζηά ηαζ ημπνακχδδ ημθμααηηήνζα πνδζζιμπμζήεδηε οπυζηνςια Membrane Lauryl Sulphate Broth (Lab Μ 82), βζα E. coli οπυζηνςια Harlequin TBGA (HAL 003) ηαζ βζα εκηενυημηημ Slanetz & Bartle Medium (LAB 166). Σα ηνοαθία ημπμεεηήεδηακ ζε εαθάιμοξ επχαζδξ 37 μ C ή 44 μ C ακηίζημζπα βζα 24 ή 48. Μεηά ημκ ηαηάθθδθμ πνυκμ επχαζδξ έβζκε ηαηαιέηνδζδ ηςκ απμζηζχκ μθζηχκ ηαζ ημπνακςδχκ ημθμααηηδνίςκ, E.coli ηαζ εκηενμηυηηςκ. Γζα κα είκαζ εθζηηή δ ηαηαιέηνδζδ ηςκ απμζηζχκ ζηα δείβιαηα απυ ηδκ εηνμή ημο αβςβμφ απαζηήεδηε αναίςζδ ημο δείβιαημξ ιέπνζ ηαζ 1: Απνηειέζκαηα - πδήηεζε Πνμηεζιέκμο κα πνμζδζμνζζημφκ ηα ζδιεία δεζβιαημθδρίαξ ζηδκ εαθάζζζα πενζμπή εηνμήξ ημο αβςβμφ έβζκακ ζεζνέξ ακαθφζεςκ δεζβιάηςκ απυ δζάθμνεξ μνζγυκηζεξ ηαζ ηάεεηεξ απμζηάζεζξ απυ ηδκ εηνμή υπςξ πνμζδζμνίγεηαζ απυ ημ πθέβια ηςκ βναιιχκ ζηδκ Δζηυκα 1. Ζ ακάθοζδ ηςκ δεζβιάηςκ κενμφ απυ απυζηαζδ 5 (αάεμξ 0,7ι), 15 (αάεμξ 1,0ι), ηαζ 30ι (αάεμξ 1,5ι), απυ ηδκ έλμδμ ημο αβςβμφ (Πίκαηαξ 1) έδεζλε ηδκ ιείςζδ ηςκ ηζιχκ ηςκ ιζηνμαζμθμβζηχκ δεζηηχκ ηαηά 98-99,5% ζε απυζηαζδ ιεβαθφηενδ ηςκ 5 ι. Με αάζδ αοηυ ημ πμζμζηυ ιείςζδξ επζθέπεδηε δ απυζηαζδ ηςκ 5 ι απυ ηδκ μπμία θήθεδηακ δείβιαηα κενμφ ηαε υθδ ηδκ δζάνηεζα ημο έημοξ πενζθαιαάκμκηαξ οβνή ηαζ λδνή πενίμδμ. Πίλαθαο 1. Μείσζε ηνπ κηθξνβηνινγηθνχ θνξηίνπ αλάινγα κε ηελ απφζηαζε απφ ηνλ αγσγφ φκβξησλ ζηελ ζαιάζζηα πεξηνρή Κνπκ Καπί Οθζηά Κμπνακχδδ E.coli Δκηενυημηημζ ημθμααηηήνζα ημθμααηηήνζα 30 ι απυ εηνμή αβςβμφ & 30 ι δελζά ι απυ εηνμή αβςβμφ & 30 ι δελζά ι απυ εηνμή αβςβμφ ι απυ εηνμή αβςβμφ

188 3/2/ /2/ /3/2012 6/4/ /4/ /5/ /6/ /9/ /11/ /1/2013 2/4/ /5/2013 8/7/2013 4/9/ /1/ /2/ /3/ /5/2014 HydroMedit 2014, November 13-15, Volos, Greece 5 ι απυ εηνμή αβςβμφ Δηνμή αβςβμφ ι απυ εηνμή αβςβμφ & 30 ι ανζζηενά ι απυ εηνμή αβςβμφ & 30 ι ανζζηενά Σα απμηεθέζιαηα ηςκ ακαθφζεςκ ζηα δείβιαηα ημο αβςβμφ υιανζςκ οδάηςκ έδεζλακ ηδκ ορδθή ζοβηέκηνςζδ υθςκ ηςκ ιζηνμαζμθμβζηχκ δεζηηχκ ηαηά ηδκ 3εηία οθμπμίδζδξ ηδξ ένεοκαξ (πήια 1). Ζ ζοβηέκηνςζδ απμζηζχκ βζα ηα μθζηά ημθμααηηήνζα ηοιάκεδηε ιεηαλφ cfu/100ml εκχ βζα ηα ημπνακχδδ ημθμααηηήνζα ήηακ ιεηαλφ cfu/100ml. Ακάθμβα ορδθή ήηακ ηαζ δ ζοβηέκηνςζδ απμζηζχκ Δ. coli cfu/100ml ηαζ εκηενμηυηημο cfu/100ml. Σμ βεβμκυξ υηζ μζ ηζιέξ ηςκ δεζηηχκ είκαζ ζδζαίηενα ορδθέξ, ζε ζοκδοαζιυ ιε ηδκ ζοκεπή πανμοζία ημο ιζηνμαζμθμβζημφ θμνηίμο ηυζμ ηδκ οβνή υζμ ηαζ ηδκ λδνή πενίμδμ ημο έημοξ, μδδβμφκ ζημ ζοιπέναζια υηζ δεκ είκαζ ιυκμ μζ ζοκήεεζξ νοπμβυκεξ αζηίεξ υπςξ μζ απμννμέξ ηςκ δνυιςκ ηαζ δ έηπθοζδ ηςκ γςζηχκ αηαεανζζχκ (Nazahiyah etal, 2007) πμο δδιζμονβμφκ αοηυ ημ απμηέθεζια. Ακαιέκεηαζ υηζ οπάνπμοκ ζδιεζαηέξ εηθμνηίζεζξ νοπμβυκμο θμνηίμο είηε αηοπήιαηα θυβς αθααχκ ημο ηεκηνζημφ δζηηφμο αζηζηχκ θοιάηςκ υπςξ ζοκέαδ ζε δεζβιαημθδρία πμο πναβιαημπμζήεδηε ζε δζάθμνα ζδιεία ημο αβςβμφ ηαηά ιήημξ ηδξ πυθδξ. Ζ αναίςζδ ημο νοπμβυκμο θμνηίμο ζηδκ πανάηηζα πενζμπή ηαζ ζε απυζηαζδ 5 ι απυ ηδκ έλμδμ ημο αβςβμφ πανυηζ ηοιάκεδηε ιεηαλφ 90% ηαζ 97% ακάθμβα ιε ημκ ιζηνμαζμθμβζηυ δείηηδ (πήια 1), παναιέκεζ υιςξ ορδθυ βζα ηα ηνζηήνζα πμο αθμνμφκ ηδκ πμζυηδηα ηςκ κενχκ ημθφιαδζδξ. Οζ ζοβηεκηνχζεζξ απμζηζχκ μθζηχκ ηαζ ημπνακςδχκ ημθμααηηδνίςκ ηοιάκεδηακ απυ 100 cfu/100ml έςξ cfu/100ml ηαζ 72 cfu/100ml έςξ cfu/100ml ακηίζημζπα. Τρδθέξ επίζδξ ήηακ μζ ζοβηεκηνχζεζξ απμζηζχκ Δ. coli πμο ηοιάκεδηακ απυ 12 cfu/100ml έςξ cfu/100ml υπςξ ηαζ εκηενμηυηημο πμο ηοιάκεδηακ απυ 8 cfu/100ml έςξ cfu/100ml. Λαιαάκμκηαξ οπυρδ ηα ζζπφμκηα υνζα ηςκ ιζηνμαζμθμβζηχκ δεζηηχκ βζα ηα κενά ημθφιαδζδξ (ππ εκηενυημηημξ <100 cfu/100ml), μζ ηζιέξ πμο ιεηνήεδηακ απμηνέπμοκ ηάεε ηέημζα πνήζδ ζηδκ πενζμπή ημο ζδιείμο δεζβιαημθδρίαξ. Ζ δζάποζδ υιςξ ημο νοπμβυκμο θμνηίμο ηαζ δ αναίςζδ ημο ζηδκ εονφηενδ εαθάζζζα πενζμπή εθαπζζημπμζεί ηδκ ζοβηέκηνςζδ ηςκ ιζηνμαζμθμβζηχκ δεζηηχκ ζε απυζηαζδ ιεβαθφηενδ ηςκ 30 ι (Πίκαηαξ 1). Ζ δζάποζδ αοηή ημο νοπμβυκμο θμνηίμο είκαζ ζδζαίηενα ζδιακηζηή πνμξ ηδκ ανζζηενή πθεονά (Δζηυκα 1 ζδιείμ 2) πμο πνδζζιμπμζείηαζ ηαζ ςξ παναθία ημθφιαδζδξ απυ ημοξ ηαημίημοξ ηδξ πενζμπήξ εκχ δεκ θάκδηε κα επδνεάγεζ ηδκ παναθία δελζά ημο αβςβμφ δ μπμία απέπεζ 500 ι πενίπμο (Δζηυκα 1 ζδιείμ 3) Ολικά κολοβακηήρια (cfu/100ml) Θάλαζζα 5μ από αγωγό Εκροή αγωγού 100 Ολικά κολοβακηήρια (% μείωζη ζσγκένηρωζης 5μ από αγωγό) /2/ /2/ /3/2012 6/4/ /4/ /5/ /6/ /9/ /11/ /1/2013 2/4/ /5/2013 8/7/2013 4/9/ /1/ /2/ /3/ /5/

189 3/2/ /2/ /3/2012 6/4/ /4/ /5/ /6/ /9/ /11/ /1/2013 2/4/ /5/2013 8/7/2013 4/9/ /1/ /2/ /3/ /5/2014 6/4/ /4/ /5/ /6/ /9/ /11/ /1/2013 2/4/ /5/2013 8/7/2013 4/9/ /1/ /2/ /3/ /5/2014 3/2/ /2/ /3/2012 6/4/ /4/ /5/ /6/ /9/ /11/ /1/2013 2/4/ /5/2013 8/7/2013 4/9/ /1/ /2/ /3/ /5/2014 HydroMedit 2014, November 13-15, Volos, Greece Κοπρανώδη κολοβακηήρια (cfu/100ml) Θάλαζζα 5μ από αγωγό Εκροή αγωγού 100 Κοπρανώδη κολοβακηήρια (% μείωζη ζσγκένηρωζης 5μ από αγωγό) /2/ /2/ /3/2012 6/4/ /4/ /5/ /6/ /9/ /11/ /1/2013 2/4/ /5/2013 8/7/2013 4/9/ /1/ /2/ /3/ /5/ E coli (cfu/100ml) Θάλαζζα 5μ από αγωγό Εκροή αγωγού 100 E coli (% μείωζη ζσγκένηρωζης 5μ από αγωγό) /4/ /4/ /5/ /6/ /9/ /11/ /1/2013 2/4/ /5/2013 8/7/2013 4/9/ /1/ /2/ /3/ /5/ Ενηερόκοκκοι (cfu/100ml) Θάλαζζα 5μ από αγωγό Εκροή αγωγού 100 Ενηερόκοκκοι (% μείωζη ζσγκένηρωζης 5μ από αγωγό) /2/ /2/ /3/2012 6/4/ /4/ /5/ /6/ /9/ /11/ /1/2013 2/4/ /5/2013 8/7/2013 4/9/ /1/ /2/ /3/ /5/2014 ρήκα 1. Μεηαβνιή ηεο ζπγθέληξσζεο νιηθψλ θαη θνπξαλσδψλ θνινβαθηεξηδίσλ, E. coli θαη εληεξνθφθθσλ ζην λεξφ ηνπ θεληξηθνχ αγσγνχ φκβξησλ ηεο πφιεο ησλ Υαλίσλ θαη ζηελ ζάιαζζα ζε απφζηαζε 5 κ απφ ηνλ αγσγφ ηελ πεξίνδν Φεβξνπάξηνο 2012-Μάηνο πςξ θαίκεηαζ ζηα απμηεθέζιαηα ημο Πίκαηα 1 ημ ιζηνμαζμθμβζηυ θμνηίμο ανζζηενά ηαζ δελζά ημο αβςβμφ ζε αάεμξ 1,5 ι ηαζ ζε απυζηαζδ 30 ι είκαζ εθάπζζημ ηαζ εκηυξ ηςκ ηνζηδνίςκ πμζυηδηαξ ηςκ κενχκ ημθφιαδζδξ. Σα απμηεθέζιαηα ηςκ ακαθφζεςκ ηδξ ένεοκαξ πμο πναβιαημπμζήεδηε ζε δζάζηδια 3 εηχκ δδιζμονβμφκ αζθαθή πνμκμζεζνά δεδμιέκςκ πμο πενζβνάθμοκ ημ πνυαθδια ηδξ επζαάνοκζδξ ηςκ πανάηηζςκ οδάηςκ απυ ημοξ αβςβμφξ υιανζςκ οδάηςκ. Ζ εθανιμβή ηςκ δεδμιέκςκ πμο εα ζοβηεκηνςεμφκ, ιεηά ηδκ μθμηθήνςζδ ηδξ ιεθέηδξ, ζε ιαεδιαηζηυ ιμκηέθμ ηίκδζδξ ημο νοπακηζημφ θμνηίμο εα επζηνέπεζ ηδκ δδιζμονβία ζεκανίςκ δζαπείνζζδξ έηηαηηςκ ηαηαζηάζεςκ νφπακζδξ. ιςξ παναιέκεζ απμθφηςξ ακαβηαία δ ζοζηδιαηζηή παναημθμφεδζδ ηςκ δζηηφςκ βζα ημκ έβηαζνμ εκημπζζιυ ηαζ ηδκ επζζηεοή δζαννμχκ πμο απμηεθμφκ πδβή νοπμβυκμο θμνηίμο πμο μδεφεηαζ εφημθα ιέζς ηςκ αβςβχκ υιανζςκ οδάηςκ πνμξ ηδκ πανάηηζα γχκδ. 189

190 Δπραξηζηίεο Σμ ένβμ οθμπμζείηαζ ζημ πθαίζζμ ημο Δπζπεζνδζζαημφ Πνμβνάιιαημξ "Δηπαίδεοζδ ηαζ Γζα Βίμο Μάεδζδ", Πνάλδ Ανπζιήδδξ ΗΗΗ ηαζ ζοβπνδιαημδμηείηαζ απυ ηδκ Δονςπασηή Έκςζδ (Δονςπασηυ Κμζκςκζηυ Σαιείμ) ηαζ απυ εεκζημφξ πυνμοξ (Δεκζηυ ηναηδβζηυ Πθαίζζμ Ακαθμνάξ ). Βιβλιογραφία. APHA, (1998). Standard methods: for the examination of water and wastewater. 20 th Edition, Washington DC. Bedan Erik S., John C. Clausen. (2009) Stormwater Runoff Quality and Quantity from Traditional and Low Impact Development Watersheds, Journal of the American Water Resources Association 45, (4) Gnecco I., C. Berretta, L.G. Lanza, P. La Barbera, 2005, Storm water pollution in the urban environment of Genoa, Italy, Atmospheric Research 77, Hueiwang A.C.J., A.J. Englande, R. M. Bakeer, H.B.Bradford. (2005). Impact of urban stormwater runoff on estuarine environmental quality. Estuarine, Coastal and Shelf Science 63, IDG. (2002). The Microbiology Manual LAB M. pp 98. Nazahiyah R., Z. Yusop, I. Abustan. (2007) Stormwater quality and pollution loading from an urban residential catchment in Johor, Malaysia, Water Science and Technology 56(7) :1-9 Parker J.K., D. McIntyre, R.T. Noble. (2010) Characterizing fecal contamination in stormwater runoff in coastal North Carolina, USA. Water Research 44, Qureshi A. A., Dutka B.J. (1979) Microbiological Studies on the Quality of Urban Stormwater Runoff in Southern Ontario, Canada, Water Research 13,

191 CHEMICAL WATER QUALITY OF LAKE AND LAGOON OF VISTONIS (PORTO LAGOS, N. GREECE) Klaoudatos D.S.*, Conides A. Hellenic Centre for Marine Research, Institute for Marine Biological Resources and Inland Waters, 46.7 km Athens-Sounion, Anavyssos Attikis, Greece ABSTRACT The study of the chemical quality of the Vistonis lagoon and lake complex was carried out during within a research project funded by the Ministry of Agricultural Development and Food. The study was based on the analysis of water samples taken from 13 selected locations in the lake, the lagoon and the coastline in front of the complex. The results have shown that apart from nitrates, the rest nitrogen nutrients show less or equal concentration values with past reports regarding their annual average values. The phosphates have shown a reduction in relation to the past. The sulfides which are toxic for the aquatic organisms, show elevated values. The results of the concentration distributions of nutrients show that (a) there is a general positive trend in the improvement of the water quality obviously due to the urban liquid waste management and the control of the river waters which supply the complex, (b) they show that there exist 2 bottom depressions within the lake which can act as morphological formation able to concentrate nutrients and which have never been before reported, (c) except from the rivers which provide organic matter to the complex there have been recognised at least 2 or 3 coastal underwater gushes which require further study as to what they contribute to the lake water in terms of nutrients and (d) the complex of brackish water lagoons shows physico-chemical similarities with the lake or the open sea depending on the season. Keywords: Vistonis lake and lagoon complex, nutrients, chemical quality Corresponding Author: Dimitris Klaoudatos (dklaoudat@yahoo.com) ΜΔΛΔΣΖ ΣΖ ΥΖΜΗΚΖ ΠΟΗΟΣΖΣΑ ΤΓΑΣΧΝ ΣΟΤ ΤΜΠΛΔΓΜΑΣΟ ΛΗΜΝΖ ΚΑΗ ΛΗΜΝΟΘΑΛΑΧΝ ΒΗΣΧΝΗΓΑ (ΠΟΡΣΟ ΛΑΓΟ, Β. ΔΛΛΑΓΑ) Κιανπδάηνο Γ., Κνλίδεο A. ΠΔΡΗΛΖΦΖ Ζ ιεθέηδ ηδξ πδιζηήξ πμζυηδηαξ ημο ζοιπθέβιαημξ ηδξ Βζζηςκίδαξ έβζκε ηδ πενίμδμ ζηα πθαίζζα ενεοκδηζημφ ένβμο πμο πνδιαημδμηήεδηε απυ ημ Τπμονβείμ Αβνμηζηήξ Ακάπηολδξ ηαζ Σνμθίιςκ. Ζ ιεθέηδ ααζίζηδηε ζε δείβιαηα κενμφ πμο εθήθεδζακ απυ 13 ζηαειμφξ ζηδ θίικδ, ηζξ θζικμεάθαζζεξ ηαζ ηδκ αηημβναιιή ημο ζοιπθέβιαημξ Βζζηςκίδαξ. Σα απμηεθέζιαηα έδεζλακ υηζ εηηυξ ηςκ κζηνςδχκ, ηα οπυθμζπα αγςημφπα ενεπηζηά είηε ιεζχεδηακ ζε ζπέζδ ιε παθαζυηενεξ ιεηνήζεζξ (1985) είηε πανέιεζκακ ζε πανυιμζα επίπεδα ςξ πνμξ ηζξ εηήζζεξ ιέζεξ ηζιέξ. Δπίζδξ ηαζ ηα θςζθμνζηά άθαηα πανμοζίαζακ ιείςζδ ζε ζπέζδ ιε παθαζυηενεξ ηζιέξ. Οζ ηζιέξ ηςκ εεζςδχκ, πμο είκαζ ημλζηά βζα ημοξ μνβακζζιμφξ, είκαζ αολδιέκεξ. Σα απμηεθέζιαηα ηςκ ηαηακμιχκ δείπκμοκ υηζ: (α) οπάνπεζ βεκζηή αεθηίςζδ ςξ πνμξ ημ πανεθευκ πνμθακχξ θυβς ηςκ ένβςκ δζαπείνζζδξ 191

192 αζηζηχκ απμαθήηςκ ηαζ ηςκ πανειαάζεςκ ζηδ νμή ηςκ πμηαιχκ, (α) παναηδνμφκηαζ 2 θεηάκεξ ζοζζχνεοζδξ ιέζα ζηδ θίικδ πμο δεκ έπμοκ ακαθενεεί πνμδβμοιέκςξ, (β) εηηυξ ηςκ 3 πμηαιχκ πμο είκαζ μθεαθιμθακέξ υηζ ζοκεζζθένμοκ ζημ μνβακζηή θμνηίμ πμο δέπεηαζ ημ ζφζηδια, οπάνπμοκ ηαζ 2 έςξ 3 αθακείξ πδβέξ νφπςκ (ίζςξ οπυβεζεξ ακααθφζεζξ πμο πνήζμοκ επζηυπμο δζενεφκδζδξ) πμο επίζδξ ζοκεζζθένμοκ ζε μνβακζηυ θμνηίμ ηαζ (δ) ημ ζφιπθεβια ηςκ οθάθιονςκ θζικμεαθαζζχκ πμο πανειαάθθεηαζ ιεηαλφ ηδξ θίικδξ ηαζ ηδξ εάθαζζαξ, ακάθμβα ηδκ επμπή ηαζ ηζξ ζοκεήηεξ ζοιπενζθένεηαζ θοζζημπδιζηά υπςξ δ θίικδ ή δ ακμζπηή εάθαζζα. Λέξειρ κλειδιά: Βηζησλίδα, ζξεπηηθά άιαηα, ρεκηθή πνηόηεηα 1. Δηζαγσγή Σμ ζφιπθεβια ηδξ Βζζηςκίδαξ, ιε ηδκ ημπζηή μκμιαζία Μπμονμφ, απμηεθεί θοζζηή πνμέηηαζδ ημο ηυθπμο ημο Πυνημ-Λάβμξ πμο δζαηυπηεηαζ ιε έκα εηηεηαιέκμ πνμζπςιαηζηυ ηυλμ πμο δζαιμνθχεδηε απυ ηζξ ακηαβςκζζηζηέξ δοκάιεζξ ημο ηοιαηζζιμφ ηαζ ηδξ νμήξ βθοημφ κενμφ απυ ημοξ πμηαιμφξ πμο εηαάθθμοκ ζηδ θίικδ. Σμ ζφιπθεβια ηδξ Βζζηςκίδαξ δέπεηαζ ηζξ οδνμθμβζηέξ επζδνάζεζξ απυ έκα εηηεηαιέκμ ζφζηδια θεηακχκ απμννμήξ πμο πενζθαιαάκμοκ υπζ ιυκμ ημοξ ηνείξ ηφνζμοξ πμηαιμφξ πμο εηαάθθμοκ ζε αοηυ αθθά ηαζ έκακ ανζειυ πμηαιμπείιαννςκ πμο θηάκμοκ ηα 1300 km². Απυ παθαζυηενα (ΔΚΘΔ 1985), έπεζ πνμζδζμνζζηεί υηζ οπάνπεζ δζαηάναλδ ηδξ ηνμθζηήξζαπνμαζςηζηήξ ζζμννμπίαξ θυβς ηδξ ηαηήξ πμζυηδηαξ ηςκ εζζνεμιέκςκ οδάηςκ απυ ημοξ πμηαιμφξ ηαζ ηα ηακάθζα απμζηνάββζζδξ χζηε κα ειθακίγμκηαζ ζε ακδζοπδηζηέξ πμζυηδηεξ μνβακζζιμί-δείηηεξ εοηνμθζζιμφ, κα πανμοζζάγμκηαζ πενζπηχζεζξ άκεζζδξ ημο κενμφ ηαζ κα πανμοζζάγμκηαζ ελάνζεζξ αζεεκεζχκ ζηα ράνζα ηδξ θίικδξ ζοκέπεζα ιαηνμπνυκζμο ζηνεξ (Aggelides & Kotsovinos 2001). Μέπνζ ημ 1986, είπε παναηδνδεεί ιζα ζηαζζιυηδηα ζηδκ αθζεοηζηή παναβςβή ημο ζοιπθέβιαημξ, ιε ζηαεενμπμίδζδ πενί ημοξ ηυκκμοξ εηδζίςξ. Χζηυζμ παθαζυηενα (πνζκ ημ 1970) δ εηήζζα παναβςβή έθηακε ηαζ ημοξ 400 ηυκκμοξ (ΔΚΘΔ 1985, Γμοθζαιηγήξ 1986). ήιενα εκημπίγμκηαζ 35 είδδ ζπεφςκ ζημ ζφιπθεβια Βζζηςκίδαξ (Κμοηνάηδξ ηαζ ζοκ. 2000, Koutrakis et al. 2005) εη ηςκ μπμίςκ 6 είδδ είκαζ ημο βθοημφ κενμφ, 12 εονφαθα ηαζ 17 είκαζ εαθάζζζα είδδ. διακηζηυηενα απυ αοηά ηα είδδ απυ ειπμνζηήξ απυρεςξ είκαζ μζ μιάδα ηςκ ηεθάθςκ (3 είδδ) ηαζ ηα πέθζα (Κμοηνάηδξ & ίκδξ 1997). Δζδζηά ζηζξ θζικμεάθαζζεξ ημοξ ζοζηήιαημξ, δ αεενίκα απμηεθεί πενίπμο ημ 46,6% ηδξ παναβςβήξ ιε δεφηενμοξ ημοξ βςαζμφξ (Potamoschistus, Koutrakis et al. 2005). Δπίζδξ απακημφκ ζηδκ πενζμπή ζδιακηζηά είδδ βθοημφ κενμφ υπςξ Abramis, Aspius, Leucisus ηαζ Lucioperca (Economidis & Banarescu, 1991). ημπυξ ηδξ πανμφζαξ ενβαζίαξ είκαζ κα πανμοζζάζεζ ηα απμηεθέζιαηα ηδξ πενζααθθμκηζηήξ ιεθέηδξ ημο ζοιπθέβιαημξ Πυνημ-Λάβμξ ζηα πθαίζζα ημο ενεοκδηζημφ πνμβνάιιαημξ ΒΔΛΣΗΧΖ ΑΛΗΔΤΣΗΚΖ ΓΗΑΥΔΗΡΗΖ ΣΖ ΛΗΜΝΟΘΑΛΑΑ ΒΗΣΧΝΗΓΟ ΜΔ ΥΡΖΖ ΤΣΖΜΑΣΧΝ ΣΖΛΔΜΔΣΡΗΑ ΠΔΡΗΒΑΛΛΟΝΣΗΚΧΝ ΤΝΘΖΚΧΝ ΚΑΗ ΣΟ ΥΔΓΗΑΜΟ ΚΑΣΑΚΔΤΑΣΗΚΧΝ ΠΑΡΔΜΒΑΔΧΝ πμο πνδιαημδμηήεδηε απυ ηδκ Γζαπεζνζζηζηή Ανπή ΔΠΑθ ημο Τπμονβείμο Αβνμηζηήξ Ακάπηολδξ ηαζ Σνμθίιςκ ζηα πθαίζζα ημο Δ.Π.Αθ., Μέηνμ 4.4. Γνάζδ 3 (εκένβεζεξ πμο ηίεεκηαζ ζε εθανιμβή απυ επαββεθιαηίεξ). 2. Τιηθά θαη Μέζνδνη Ζ ιεθέηδ ηδξ πενζμπήξ έβζκε ιε δεζβιαημθδρία κενμφ απυ 13 πνμεπζθεβιέκμοξ ζηαειμφξ ζηδκ είζμδμ ηαζ ιέζα ζηδ θίικδ Βζζηςκίδα ηζξ θζικμεάθαζζεξ ηαζ ηδκ αηηή ημο Βζζηςκζημφ ηυθπμο (Δζη. 1). Γείβιαηα κενμφ εθήθεδζακ απυ πθςηυ ιέζμ ιε πνήζδ εζδζηήξ θζάθδξ Nisskin 2 θίηνςκ. Σα δείβιαηα ημπμεεηήεδηακ ζε θζάθεξ πθαζηζηέξ ηςκ 250 ml εκχ βζα ηδκ αδνακμπμίδζδ μνβακζζιχκ πμο εα αθθμζχζμοκ ηδκ ζοβηέκηνςζδ ηςκ ενεπηζηχκ αθάηςκ, πνμζηέεδηε ιζηνή πμζυηδηα (έςξ 1 ml) δζαθφιαημξ HgCl 2 0.1Μ. Σα δείβιαηα ιεηαθένεδηακ ζημ ενβαζηήνζμ ηαζ απμεδηεφηδηακ ζε ροβείμ (-4 C) ιέπνζ ηδκ ακάθοζή ημοξ. Ζ πδιζηή ακάθοζδ ηςκ δεζβιάηςκ έβζκε ιε ηδ αμήεεζα θαζιαημθςηυιεηνςκ HACH DR/4000 ηαζ HACH DR/2800 ιε απμεδηεοιέκεξ ηζξ ηοπζηέξ ηαιπφθεξ θςημιέηνδζδξ. Σα δείβιαηα ακαθφεδηακ βζα Ν-ΝΖ 3, Ν-ΝΟ 2, Ν-ΝΟ 3, Ρ-ΡΟ 4 ηαζ S = ηαζ Cl 2. Ζ ιέηνδζδ θοζζηχκ παναιέηνςκ ημο κενμφ έβζκε επί ηυπμο ηαηά ηζξ δεζβιαημθδρίεξ πεδίμο ιε πνήζδ 192

193 εζδζηχκ θμνδηχκ ζοζηεοχκ. 3. Απνηειέζκαηα 3.1. Φπζηθέο παξάκεηξνη φιθςκα ιε ηα απμηεθέζιαηα, δ εενιμηναζία ηδξ θίικδξ; Βζζηςκίδαξ πανμοζζάγεζ παιδθυηενεξ ηζιέξ ηαηά ηδ πεζιενζκή πενίμδμ απυ αοηέξ πμο ιεηνήεδηακ ζηδ θζικμεάθαζζα ηαζ ζηδκ αηηή ημο Βζζηςκζημφ ηυθπμο ηαζ ημ ακηίεεημ ηαηά ηδ εενζκή πενίμδμ. Ζ πανυιμζα ηαηακμιή εενιμηναζίαξ ζηζξ θζικμεάθαζζεξ ηαζ ζηδκ αηηή ημο ηυθπμ είκαζ ακαιεκυιεκδ θυβς ηδξ ζοκεπμφξ ζφκδεζδξ ιεηαλφ ηςκ δφμ βεςβναθζηχκ ζδιείςκ ιέζς 3 ηακαθζχκ. Ζ εενιμηναζία ηδξ θίικδξ ηοιαίκεηαζ ιεηαλφ 4 ηαζ 28,5 C εκχ ζηζξ θζικμεάθαζζεξ ηαζ ηδκ αηημβναιιή, ιεηαλφ 8 ηαζ 26,7 C. Ζ αθαηυηδηα ζημ ζηδ θίικδ ηαζ ηζξ θζικμεάθαζζεξ πανμοζζάγεζ πανυιμζεξ αολμιεζχζεζξ. Ζ δζαηφιακζδ ηδξ αθαηυηδηαξ ζηδ θίικδ είκαζ ιεηαλφ 2,5 ηαζ 13, ζηζξ θζικμεάθαζζεξ ιεηαλφ 7 ηαζ 36 εκχ ζηδκ αηημβναιιή ιεηαλφ 16 ηαζ 36. Ζ παιδθή ηζιή ημκ Απνίθζμ ζηδκ αηηή ημο ηυθπμο εηηζιάηαζ υηζ μθείθεηαζ ζε ηοπαίμ βεβμκυξ εηνμήξ βθοημφ κενμφ ιάθθμκ απυ ανμπυπηςζδ. Ζ ζδιενζκή ηαηακμιή ηδξ ιέζδξ μλφηδηαξ ιέζα ζηδ θίικδ Βζζηςκίδα είκαζ ιεηαλφ 8,0 ηαζ 9,0 δδθαδή ιπμνεί κα εεςνδεεί ςξ ακαιεκυιεκδ ηαζ θοζζηή βζα κενά αοηήξ ηδξ αθαηυηδηαξ. Πανυιμζα είκαζ ηαζ δ δζαηφιακζδ ηδξ ιέζδξ μλφηδηαξ ηαζ ζηζξ πενζμπέξ ηςκ θζικμεαθαζζχκ ηαζ ηδκ αηηή ημο Βζζηςκζημφ ηυθπμο. Ζ δζαθάκεζα ηοιάκεδηε ιεηαλφ 40 ηαζ 150 cm ζημοξ ζηαειμφξ ηδξ θίικδξ. Ακηίεεηα ζηζξ θζικμεάθαζζεξ ηαζ ζηδκ αηηή ημο ηυθπμο μζ ηζιέξ είκαζ δζπθάζζεξ ( cm) ηαζ ηνζπθάζζεξ ( cm). Καηά ηδ πεζιενζκή πενίμδμ ζηδ θίικδ Βζζηςκίδα δεκ πανμοζζάγεηαζ οπενημνεζιυξ δζαθοιέκμο μλοβυκμο. Ακηίεεηα οπενημνεζιυξ παναηδνήεδηε ιεηαβεκέζηενα ηαηά ηδκ εανζκή πενίμδμ. Ζ δζαηφιακζδ ημο δζαθοιέκμο μλοβυκμο ήηακ 5,8-11 mg/l, 5,8-8,7 mg/l ηαζ 6-9 mg/l ζηδ θίικδ, ηζξ θζικμεάθαζζεξ ηαζ ηδ αηημβναιιή Θξεπηηθά άιαηα Σα αιιςκζαηά άθαηα πανμοζζάγμκηαζ αολδιέκα ηαηά ηδκ εενζκή πενίμδμ ζηδ θίικδ Βζζηςκίδα ηαζ ζδζαίηενα παιδθά ηαηά ηδκ οπυθμζπδ πνμκζηή πενίμδμ ημο έημοξ. Μεηνήεδηε ιέζδ ηζιή ηα 0,1163 mg/l. Ζ ζοβηέκηνςζδ ηςκ αιιςκζαηχκ ζηζξ θζικμεάθαζζεξ ημο ηυθπμο ηαζ ζηδκ αηηή ηοιάκεδηακ ζε θίβμ ιεβαθφηενα επίπεδα ιε ιέζδ ηζιή ηα 0,13 mg/l. Οζ ιέζεξ ιδκζαίεξ ηζιέξ κζηνςδχκ ηοιάκεδηακ απυ 0,03 έςξ 0,15 mg/l ιε ζοκμθζηή ιέζδ ηζιή 0,056 mg/l. Πανυιμζμ πνμθίθ ηδξ ζοβηέκηνςζδξ κζηνςδχκ πανμοζζάγεηαζ ηαζ ζηζξ θζικμεάθαζζεξ ηαζ ηδκ αηημβναιιή ημο Βζζηςκζημφ ηυθπμο, ιε ιέβζζηεξ ιέζεξ ιδκζαίεξ ηζιέξ 0,11 ηαζ 0,19 mg/l ηαηά ηδ εενζκή πενίμδμ. Οζ ιέζεξ ηζιέξ κζηνςδχκ εηεί είκαζ 0,032 ηαζ 0,039 mg/l ακηίζημζπα. Σμ κενυ ηδξ θίικδξ πανμοζζάγεζ ζπεηζηά ορδθέξ ηζιέξ κζηνζηχκ έςξ 1,3 mg/l ιε ιέζδ ηζιή 0,395 mg/l. Οζ ιέζδ ιδκζαία ζοβηέκηνςζδ κζηνζηχκ ζηζξ θζικμεάθαζζεξ ημο ηυθπμο ηοιάκεδηακ απυ 0,11 έςξ 1,20 mg/l ιε ιέζδ εηήζζα ηζιή ηα 0,42 mg/l. ηδκ αηηή ημο ηυθπμο ηοιάκεδηακ απυ 0,28 έςξ 0,42 mg/l ιε ιέζδ εηήζζα ηζιή ηα 0,20 mg/l. ηδκ πανμφζα ιεθέηδ ιεηνήεδηακ ιέζεξ ιδκζαίεξ ηζιέξ ιεηαλφ 0,013 ηαζ 0,047 mg/l ιε ιέζδ εηήζζα ηζιή 0,03 mg/l εκηυξ ηδξ θίικδξ Βζζηςκίδαξ. ηζξ θζικμεάθαζζεξ ηοιάκεδηε ιεηαλφ 0,005 ηαζ 0,06 mg/l εκχ ζηδκ αηημβναιιή ιεηαλφ 0,05 ηαζ 0,15 mg/l. ηδκ πανμφζα ιεθέηδ εκηυξ ηδξ θίικδξ Βζζηςκίδαξ ιεηνήεδηακ ηζιέξ απυ 0 έςξ ηαζ 0,280 mg/l ιε ιέζδ εηήζζα ηζιή 0,080 mg/l. Ζ ζοβηέκηνςζδ ηςκ εεζςδχκ ζηζξ θζικμεάθαζζεξ ηοιάκεδηε ιεηαλφ 0 ηαζ 0,050 mg/l ιε ιέζδ εηήζζα ηζιή 0,017 mg/l εκχ ζηδκ αηημβναιιή ιεηαλφ 0 ηαζ 0,047 mg/l ιε ιέζδ εηήζζα ηζιή 0,020 mg/l. 193

194 4. πδήηεζε 4.1. Φπζηθέο παξάκεηξνη Ζ εενιμηναζία ηςκ ηθεζζηχκ ζοζηδιάηςκ ηαζ υπςξ ηςκ πανάηηζςκ ηαζ ηςκ θζικμεαθαζζχκ επδνεάγεηαζ ζδιακηζηά απυ ηα βεςβναθζηά παναηηδνζζηζηά ηδξ πενζμπήξ. Ζ θίικδ Βζζηςκίδα επίζδξ επδνεάγεηαζ ηαζ απυ ηζξ εζζνμέξ εαθαζζζκμφ κενμφ ζημ κυηζμ ηιήια ηδξ ηαζ ηδ νμή πμηαιχκ πμο πνμένπμκηαζ απυ εηηεκείξ μνεζκέξ θεηάκεξ απμννμήξ ιε απμηέθεζια ημοθάπζζημκ ηαηά ηδ πεζιενζκή πενίμδμ κα ζοκεζζθένμοκ ζδιακηζηά ζηδκ απχθεζα εενιυηδηαξ απυ ηδ θίικδ. ηδκ πενζμπή ηδξ Βζζηςκίδαξ, είκαζ βκςζηυ απυ παθαζμηένα υηζ ηα κενά δεκ πάβςκακ ηαηά ηδ δζάνηεζα ηδξ πεζιενζκήξ πενζυδμο (Κμοζμονήξ ηαζ ζο. 1985). Χζηυζμ ηα ηεθεοηαία πνυκζα, θυβς ηςκ ηθζιαηζηχκ αθθαβχκ οπήνλακ πενζπηχζεζξ ιαγζηήξ εκδζζιυηδηαξ ρανζχκ θυβς ημο παβχιαημξ ηςκ κενχκ πμο ιάθζζηα απμγδιζχεδηακ απυ ημκ μνβακζζιυ ΔΛΓΑ. Ζ πνμζθμνά κενμφ απυ ημοξ πμηαιμφξ πμο νέμοκ ζηδ θίικδ Βζζηςκίδα αθθά ηαζ δ ακηίεεηδ δνάζδ ηδξ εζζνμήξ εαθαζζζκμφ κενμφ πμο είκαζ επμπζαηά ζδιακηζηέξ είκαζ μζ ηφνζεξ δοκάιεζξ πμο επδνεάγμοκ ηαζ ηαεμνίγμοκ ηδκ αθαηυηδηα ζηδ θίικδ, ζηζξ θζικμεάθαζζεξ ηαζ ηδκ αηηή. ε παθαζυηενεξ ιεθέηεξ, έπμοκ ιεηνδεεί ηζιέξ έςξ ηαζ ζημ εζςηενζηυ ηδξ θίικδξ ηαζ ζηδκ κυηζα θεηάκδ αοηήξ, ςξ απμηέθεζια ηδξ εζζνμήξ εαθαζζζκμφ κενμφ ηαηά ημοξ εενζκμφξ ιήκεξ (Κμοζμονήξ ηαζ ζοκ. 1985). ήιενα υπςξ ιεηά απυ ηδκ ζδιακηζηή αθθμίςζδ ηδξ νμήξ ηςκ πμηαιχκ ηαζ ηδ ζοκεπή νμή ημοξ θυβς ηδξ βεςνβζηήξ εηιεηάθθεοζδξ βφνς απυ ηδ θίικδ, μζ ηζιέξ αθαηυηδηαξ ιέζα ζηδ θίικδ δεκ λεπενκμφκ ημ 8 αηυια ηαζ ζημοξ ζηαειμφξ ηδ κυηζαξ θεηάκδξ. Τθίζηαηαζ δδθαδή αθθμίςζδ ημο οδνμθμβζημφ ηαεεζηχημξ ηα ηεθεοηαία 20 πνυκζα. Ζ μλφηδηα ζπεηίγεηαζ ιε ηζξ πδιζηέξ δζενβαζίεξ πμο θαιαάκμοκ πχνα ζημ κενυ. Οζ ηζιέξ μλφηδηαξ έπμοκ ηοιακεεί ζημ πανεθευκ ιεηαλφ 7,9 έςξ ηαζ 9,9 (Κμοζμονήξ ηαζ ζοκ. 1985, Φχηδξ ηαζ ζοκ. 1976, Κζθζηίδδξ ηαζ ζοκ. 1984, Οογμφκδξ & Γζακκαημπμφθμο 1983, Ouzounis & Yiannakopoulou 1984). Οζ ηζιέξ αοηέξ δζηαζμθμβμφκηαζ δζυηζ ηα παθαζυηενα πνυκζα δ θίικδ Βζζηςκίδα απμηεθμφζε ημκ απμδέηηδ ακεπελένβαζηςκ θοιάηςκ απυ ηζξ βφνς πενζμπέξ ηαζ ηδκ πυθδ ηδξ Ξάκεδξ. Ζ ζδιενζκή ηαηακμιή ηδξ ιέζδξ μλφηδηαξ ιέζα ζηδ θίικδ Βζζηςκίδα είκαζ ιεηαλφ 8,0 ηαζ 9,0 δδθαδή ιπμνεί κα εεςνδεεί ςξ ακαιεκυιεκδ ηαζ θοζζηή βζα κενά αοηήξ ηδξ αθαηυηδηαξ. Σμ θςξ είκαζ ιζα θοζζηή πανάιεηνμξ ζδζαίηενα ζδιακηζηή βζα ηδκ ακάπηολδ ηςκ θοηχκ ηαζ επαηυθμοεα ηςκ γχςκ ζε οδαηζηά ζοζηήιαηα ηαεχξ έηζζ ζηδνίγεηαζ δ ηνμθζηή αθοζίδα ηαζ εζζένπεηαζ πνςημβεκήξ εκένβεζα ζε αοηή. ε παθζυηενεξ ιεθέηεξ έπμοκ ιεηνδεεί ηζιέξ δζαθάκεζαξ ιέζα ζηδ θίικδ Βζζηςκίδα cm εκχ ακηίεεηα ηαηά ηδκ πανμφζα ιεθέηδ ιεηνήεδηακ ορδθυηενεξ ηζιέξ, 40 έςξ ηαζ 140 cm θακενχκμκηαξ υηζ μζ ζοκεήηεξ ζηδ θίικδ έπμοκ αεθηζςεεί ζπεηζηά. Σμ δζαθοιέκμ μλοβυκμ ζε ηθεζζηά ζοζηήιαηαείκαζ δοκαηυκ κα πανμοζζάζμοκ ορδθά πμζμζηά ημνεζιμφ θυβς ηδξ έκημκδξ θςημζφκεεζδξ ηαζ ηονίςξ ζηα επζθακεζαηά κενά. Καηά ηδ εενζκή πενίμδμ ημ δζαθοιέκμ μλοβυκμ ηαηακαθχκεηαζ ημκηά ζημκ ποειέκα θυβς ηςκ πδιζηχκ ακηζδνάζεςκ απμζφκεεζδξ ηδξ μνβακζηήξ φθδξ ηαζ έηζζ ακαιέκεηαζ ιείςζδ ηδξ ζοβηέκηνςζδξ (Κμοζμονήξ ηαζ ζοκ. 1985). Παθαζυηενεξ ένεοκεξ έδεζλακ υηζ ηα κενά ηδξ θίικδξ Βζζηςκίδαξ δεκ είκαζ ηαθά μλοβμκςιέκα ηδ εενζκή ηαζ ηδ θεζκμπςνζκή πενίμδμ (Κμοζμονήξ ηαζ ζοκ. 1985) εκχ είπακ ιεηνδεεί ηαζ ακμλζηέξ ζοκεήηεξ (ηάης ηςκ 2 mg/l). ε βεκζηέξ βναιιέξ είπακ ιεηνδεεί ηζιέξ απυ 3 έςξ ηαζ 14 mg/l. Αοηυ ημ πνμθίθ δεκ παναηδνήεδηε ζηδ θίικδ Βζζηςκίδα ζηα πθαίζζα ηδξ πανμφζαξ ιεθέηδξ. θεξ μζ ηζιέξ πανμοζζάγμκηαζ ανηεηά ορδθέξ εζδζηά ζηζξ πενζμπέξ πμο εζζνέμοκ βθοηά κενά (αυνεζα ηαζ ακαημθζηή αηηή) Θξεπηηθά άιαηα Σα αιιςκζαηά άθαηα (Δζη. 2) πανμοζζάγμκηαζ αολδιέκα ηαηά ηδκ εενζκή πενίμδμ ζηδ θίικδ Βζζηςκίδα ηαζ ζδζαίηενα παιδθά ηαηά ηδκ οπυθμζπδ πνμκζηή πενίμδμ ημο έημοξ. ε παθαζυηενεξ ιεθέηεξ ιεηνήεδηακ ιέζεξ ηζιέξ αιιςκζαηχκ πενί ημ 1,5 mg/l (Κμοζμονήξ ηαζ ζοκ. 1985) εκχ ζήιενα ιεηνήεδηακ ζδιακηζηά παιδθυηενεξ ηζιέξ ιε ιέζδ ηα 0,1163 mg/l. Οζ δζαθμνέξ αοηέξ πνέπεζ 194

195 κα μθείθμκηαζ ζηα ένβα αλζμπμίδζδξ ηδξ θίικδξ ιε ηδκ πενζθενεζαηή αφθαηα ηαζ ηδ νφειζζδ ηδξ νμήξ ηςκ πμηαιχκ πμο εζζνέμοκ ζηδ θίικδ βζα άνδεοζδ ιε απμηέθεζια κα ιδκ θηάκεζ ζηδ θίικδ δ ιεβαθφηενδ πμζυηδηα αγςημφπςκ εκχζεςκ. Σα κζηνχδδ (Δζη.3) είκαζ ημλζηά βζα ημοξ οδνυαζμοξ μνβακζζιμφξ ηαζ απμηεθμφκ έκακ επζπθέμκ θυβμ βζα ηδ εκδζζιυηδηα ημοξ ζε πενζπηχζεζξ ιμθοζιέκςκ κενχκ. ε παθζυηενεξ ιεθέηεξ ιέζα ζηδ θίικδ Βζζηςκίδα ιεηνήεδηακ ηζιέξ απυ 0,0017 έςξ 0,10 mg/l (Κμοζμονήξ ηαζ ζοκ. 1985) εκχ ζήιενα ιεηνήεδηακ ιέζεξ ιδκζαίεξ ηζιέξ απυ 0,03 έςξ 0,15 mg/l ιε ζοκμθζηή ιέζδ ηζιή 0,056 mg/l. Οζ ορδθυηενεξ ηζιέξ ειθακίγμκηαζ ηδ εενζκή πενίμδμ πμο θυβς ηδξ ορδθήξ εενιμηναζίαξ έπμοιε ιαγζηή απμζφκεεζδ ηδξ μνβακζηήξ φθδξ ηυζμ ζηδκ αηηή (πανυπεζα θοηά) υζμ ηαζ εκηυξ ηδξ θίικδξ ηαζ πανάθθδθδ ηαηακάθςζδ ημο μλοβυκμο ιε απμηέθεζια κα ζοζζςνεφμκηαζ ηα κζηνχδδ. Πανυιμζμ πνμθίθ ηδξ ζοβηέκηνςζδξ κζηνςδχκ πανμοζζάγεηαζ ηαζ ζηζξ θζικμεάθαζζεξ ηαζ ηδκ αηημβναιιή ημο Βζζηςκζημφ ηυθπμο. Πνμθακχξ δ βεζημκία ιε ηα κενά ηδξ ακμζηηήξ εάθαζζαξ ηαζ μζ πζμ ηαθέξ ζοκεήηεξ ακακέςζδξ ηςκ κενχκ ζηζξ δφμ αοηέξ πενζμπέξ επζηνέπεζ ηδκ δζαηήνδζδ ηαθφηενμο πδιζημφ πενζαάθθμκημξ ηαζ ηδκ δζαηήνδζδ ηςκ κζηνςδχκ ζε παιδθυηενα επίπεδα απυ αοηά ηδξ θίικδξ. Σμ κενυ ηδξ θίικδξ πανμοζζάγεζ ζπεηζηά ορδθέξ ηζιέξ κζηνζηχκ (Δζη.4) έςξ 1,3 mg/l ιε ιέζδ ηζιή 0,395 mg/l. ε παθαζυηενεξ ιεθέηεξ είπακ ιεηνδεεί ακάθμβεξ ηζιέξ ιε ιέβζζηδ έςξ 1,46 mg/l ηαζ ιέζδ ηζιή έςξ 2,2 mg/l (Κμοζμονήξ ηαζ ζοκ. 1985). Ο Φοηζάκμξ (1975 ζημ Κμοζμονήξ ηαζ ζοκ. 1985) ιέηνδζε ηζιέξ 0,170-0,350 mg/l ιε ιέζδ ηζιή ηα 0,27 mg/l. Ζ Γζακκαημπμφθμο (1989) ιέηνδζε βζα ηδκ ίδζα πενίμδμ ηζιέξ ιεηαλφ 0,01 ηαζ 1,2 mg/l. Δίκαζ πνμθακέξ υηζ μζ ηζιέξ κζηνζηχκ δεκ πανμοζίαζακ αθθαβή ηα ηεθεοηαία 20 πνυκζα. Ο ηφηθμξ ηςκ θςζθμνζηχκ αθάηςκ (Δζη.5) επδνεάγεηαζ ανηεηά απυ ηδκ πανμοζία μλοβυκμο ζημ κενυ. Με επάνηεζα μλοβυκμο δεζιεφεηαζ εκχ ιε έθθεζρδ μλοβυκμο επακαδζαθοημπμζείηαζ ζημ κενυ. Παθαζυηενεξ ιεηνήζεζξ έδεζλακ υηζ ηα θςζθμνζηά άθαηα ζηδ θίικδ Βζζηςκίδα ηοιαίκμκηακ ιεηαλφ 0,04 ηαζ 0,23 mg/l εκχ ηαηά πενίπηςζδ ηονίςξ ιεηά απυ επεζζυδζα αολδιέκδξ νμήξ κενχκ ζηδ θίικδ ππ. ανμπυπηςζδ ιεηνήεδηακ ηζιέξ έςξ ηαζ 1,4 mg/l (Κμοζμονήξ ηαζ ζοκ. 1985). Ο Φοηζάκμξ (1985 ζημ Κμοζμονήξ ηαζ ζοκ. 1985) ιέηνδζε ιέζεξ ηζιέξ 0,157 mg/l ιε παιδθυηενεξ αοηέξ ημκηά ζηδκ έλμδμ ηδξ θίικδξ πνμξ ηδ εάθαζζα ηαζ ορδθυηενεξ ηζξ ηζιέξ ζηζξ εηαμθέξ ηςκ πμηαιχκ ιέζα ζηδ θίικδ. Ζ Γζακκαημπμφθμο (1989) ιέηνδζε ηζιέξ ιεηαλφ 0,044 ηαζ 0,500 mg/l. Σα εεζχδδ άθαηα είκαζ εκχζεζξ ημο εείμο πμο πνμένπμκηαζ απυ ηδκ παναβςβή οδνυεεζμο θυβς ηδξ απμζφκεεζδξ ηδξ μνβακζηήξ φθδξ πάζδξ θφζεςξ ιέζα ζημ κενυ. Δπίζδξ πανάβεηαζ ζε ιεβάθεξ πμζυηδηεξ υηακ έπμοιε ιαγζηή εακάηςζδ ημο πθδεοζιμφ ημο θοημπθαβηημφ εζδζηά ιεηά απυ επεζζυδζμ άκεδζδξ ημο κενμφ (water bloom) ή υηακ οπάνπεζ ναβδαία ακαζηνμθή ημο πενζαάθθμκημξ ηδξ θίικδξ ππ δ εζζνμή εαθαζζζκμφ κενμφ απυ ηα κυηζα πμο επίζδξ ιπμνεί κα πνμηαθέζεζ εακάηςζδ ημο πθαβηημφ βθοημφ κενμφ ηδξ θίικδξ ηαζ ηδ ιαγζηή ηαείγδζδ αολδιέκςκ πμζμηήηςκ μνβακζηήξ φθδξ. Σμ οδνυεεζμ ηαζ ηα εεζχδδ ζυκηα είκαζ ελαζνεηζηά ημλζηά βζα ημοξ οδνυαζμοξ μνβακζζιμφξ. ε παθζυηενεξ ιεθέηεξ ζηδ θίικδ Βζζηςκίδα ιεηνήεδηακ ηζιέξ πμο ηοιαίκμκηακ ιεηαλφ 0,07 ηαζ 0,790 mg/l (Κμοζμονήξ ηαζ ζοκ. 1985). ηδκ πανμφζα ιεθέηδ ιεηνήεδηακ ηζιέξ εεζςδχκ (Δζ.7) απυ 0 έςξ ηαζ 0,280 mg/l ιε ιέζδ εηήζζα ηζιή 0,080 mg/l. Οζ ιεβαθφηενεξ ηζιέξ πανμοζζάγμκηαζ ζηδκ ανπή ημο ηαθμηαζνζμφ ηαζ πνμθακχξ ζοκδέμκηαζ ιε ηδκ αολδιέκδ απμζφκεεζδ ηδξ μνβακζηήξ φθδξ. Ζ ζοβηέκηνςζδ ηςκ εεζςδχκ αθάηςκ ζηζξ θζικμεάθαζζεξ ηοιάκεδηε ιεηαλφ 0 ηαζ 0,050 mg/l ιε ιέζδ εηήζζα ηζιή 0,017 mg/l. Οζ πςνζηέξ ηαηακμιέξ ηδξ ιέζδξ εηήζζαξ ζοβηέκηνςζδξ ενεπηζηχκ πανμοζζάγμοκ ηαζκμφνζα απμηεθέζιαηα βζα ηδ θίικδ Βζζηςκίδα. Ζ πζμ ζδιακηζηή πδβή ενεπηζηχκ είκαζ μ πμηαιυξ Κμιράημξ ηαζ ηαηυπζκ μ Σναφμξ ηαζ ηεθεοηαίμξ, ζε ζοκεζζθμνά, μ Κυζοκεμξ. Πανάθθδθα παναηδνμφκηαζ ηαζ 3 αηυια αθακή ζδιεία απμννμήξ ενεπηζηχκ ζημ κενυ ηδξ θίικδξ πμο πνήγμοκ επζηυπμο δζενεφκδζδξ. Δπίζδξ παναηδνμφκηαζ ηαζ 2 θεηάκεξ ζοζζχνεοζδξ εκηυξ ηδξ θίικδξ πμο δεκ έπμοκ ακαθενεεί πνμδβμοιέκςξ. Δπραξηζηίεο Ζ ενβαζία πανμοζζάγεζ ηα απμηεθέζιαηα ενεοκδηζημφ πνμβνάιιαημξ ιε ηίηθμ ΒΔΛΣΗΧΖ ΑΛΗΔΤΣΗΚΖ ΓΗΑΥΔΗΡΗΖ ΣΖ ΛΗΜΝΟΘΑΛΑΑ ΒΗΣΧΝΗΓΟ ΜΔ ΥΡΖΖ ΤΣΖΜΑΣΧΝ ΣΖΛΔΜΔΣΡΗΑ ΠΔΡΗΒΑΛΛΟΝΣΗΚΧΝ ΤΝΘΖΚΧΝ ΚΑΗ ΣΟ ΥΔΓΗΑΜΟ 195

196 ΚΑΣΑΚΔΤΑΣΗΚΧΝ ΠΑΡΔΜΒΑΔΧΝ πμο πνδιαημδμηήεδηε απυ ηδκ Γζαπεζνζζηζηή Ανπή ΔΠΑθ ημο Τπμονβείμο Αβνμηζηήξ Ακάπηολδξ ηαζ Σνμθίιςκ ζηα πθαίζζα ημο Δ.Π.Αθ., Μέηνμ 4.4. Γνάζδ 3 (εκένβεζεξ πμο ηίεεκηαζ ζε εθανιμβή απυ επαββεθιαηίεξ). Βηβιηνγξαθία Aggelides, P.B.,, & Kotsovinos, N.E., Management of agricultural run-offs pollution: the case of lake Vistonis. Proceedings of the Ecological Protection of the Planet earth I, volume I, ΔΛ.ΚΔ.Θ.Δ. (1985). Αλζμπμίδζδ ηαζ πνμζηαζία ηςκ εζςηενζηχκ οδάηςκ ηδξ πχναξ: ΗΗΗ. Λίικδ Βζζηςκίδα. Σεπκζηή Έηεεζδ 3, 47 ζεθ. Κζθζηίδδξ,., Καιανζακυξ, Α., Φχηδξ, Γ., Κμοζμονήξ Θ., Καναιακθήξ, Κ., & Οογμφκδξ, Κ., Οζημθμβζηή ένεοκα ζηζξ θίικεξ ηδξ Βμνείμο Δθθάδμξ: Αβίμο Βαζζθείμο, Γμσνάκδξ ηαζ Βζζηςκίδαξ. Δπζζηδιμκζηή Έηεεζδ, Ανζζημηέθεζμ Πακεπζζηήιζμ Θεζζαθμκίηδξ, Κηδκζαηνζηυ Σιήια Κμοζμονήξ, Θ., Γζαπμφθδξ, Α., & Φχηδξ, Γ., Αλζμπμίδζδ ηαζ πνμζηαζία ηςκ εζςηενζηχκ οδάηςκ ηδξ πχναξ. ΗΗΗ. Λίικδ Βζζηςκίδα. Σεπκ. Έηεεζδ Νμ 3, Δθθδκζηυ Κέκηνμ Θαθαζζίςκ Δνεοκχκ, ζεθ. 47 Κμοηνάηδξ, Δ., & ίκδξ, Α., φκεεζδ πθδεοζιχκ ηςκ ηεθάθςκ (Mugilidae) ζηδ θζικμεάθαζζα ημο Πυνημ-Λάβμξ ηαζ ηδ θίικδ Βζζηςκίδα. Πναηηζηά 5μο Πακεθθήκζμο οιπμζίμο Χηεακμβναθίαξ ηαζ Αθζείαξ, ηυιμξ ΗΗ, Κααάθα, Απνζθίμο 1997, Κμοηνάηδξ, Δ., Σζίηθδναξ, Α., & ίκδξ, Α., Δπμπζαηέξ δζαηοιάκζεζξ ζηδκ αθεμκία ηαζ ζφκεεζδ ηδξ ζπεομπακίδαξ ζηδκ θζικμεάθαζζαξ ημο Πυνημ-Λάβμξ. Πναηηζηά 6με Πακεθθήκζμο οιπμζίμο Χηεακμβναθίαξ ηαζ Αθζείαξ, Υίμξ, Μαΐμο 2000, Koutrakis, E.T., Tsikliras, A.C., & Sinis, A.I., Temporal variability of the ichthyofauna in a northern Aegean coastal lagoon (Greece). Influence of environmental factors. Hydrobiologia, 543, Οογμφκδξ, Κ., & Γζακκαημπμφθμο, Σ., Ρφπακζδ ηδξ θίικδξ Βζζηςκίδαξ απυ ηα αζηζηά θφιαηα ηαζ απμννίιιαηα ηδξ πυθδξ ηδξ Ξάκεδξ. Πναηηζηά Ζ' Πακεθθ. οκεδνίμο έκςζδξ Δθθήκςκ Υδιζηχκ, ζεθ. 4 Ouzounis, K., & Yiannakopoulos, T., Some physic-chemical characteristics of Vistonis lake (North Greece). Thalassographica, 7, Φχηδξ, Γ., Κμοζμονήξ, Θ., ηαζ Κνζάνδξ, Ν., Πνυδνμιμξ ιεθέηδ επί ημο ιμθοζιαηζημφ φδνςπμξ ημο ηοπνίκμο ηαζ ηζκχκ παναβυκηςκ ηδξ θίικδξ Βζζηςκίδαξ. Κηδκζαηνζηά Νέα, 5(4-5),

197 EFFECTS OF BISPHENOL-A (BPA) ON SEX DIFFERENTIATION AND ON GROWTH OF F1 GENERATION NAYPLII OF THE AMPHIGONIC POPULATION Artemia franciscana EKONOMOU G. 1*, CASTRITSI-CATHARIOS J. 1, TSIROPOULOS Ν.G. 2, NEOFITOU C. 1, EXADACTYLOS A. 1 1 Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Fytokou str., 38446, Nea Ionia, Volos, Greece 2 Department of Agriculture Crop Production and Rural Environment, School of Agricultural Sciences, University of Thessaly, Fytokou str., 38446, Nea Ionia, Volos, Greece Abstract Every year large quantities of bisphenol-a are channeled to the environment. Σhis compound acts as an endocrine disrupter and modifies the action of endogenous estrogen in organisms exposed to it. Since Artemia franciscana is a well established test animal for acute toxicity tests, the aim of this study was to examine the effect of BPA on sex differentiation of the strain A. franciscana and on the growth of the F1 generation. The results showed variation in sex, as the ratio Male / Female in controls was 0.92:1, while in all treatments with BPA more males were found than females, with the ratio Male / Female to reach the value 2:1 at the concentration of 35 ppm. In addition, the measurement of the length of the F1 generation nauplii showed inhibition of growth when the parental generation was exposed to BPA concentrations higher than 10 ppm. Key words: Artemia franciscana, bisphelon-a,sex differentiation, growth *Corresponding author: Ekonomou George (geoikono@hotmail.com) ΔΠΗΓΡΑΖ ΣΖ ΓΗΦΑΗΝΟΛΖ-Α (ΒΡΑ) ΣΖ ΦΤΛΔΣΗΚΖ ΓΗΑΦΟΡΟΠΟΗΖΖ ΚΑΗ ΣΖΝ ΑΝΑΠΣΤΞΖ ΣΧΝ ΝΑΤΠΛΗΧΝ ΣΟΤ ΑΜΦΗΓΟΝΗΚΟΤ ΠΛΖΘΤΜΟΤ Artemia franciscana F1 ΓΔΝΗΑ ΟΗΚΟΝΟΜΟΤ Γ. 1*, ΚΑΣΡΗΣΖ-ΚΑΘΑΡΗΟΤ Η. 1, ΣΗΡΟΠΟΤΛΟ Ν. 2, ΝΔΟΦΤΣΟΤ Υ. 1, ΔΞΑΓΑΚΣΤΛΟ Α. 1 1 Σιήια Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ, πμθή Γεςπμκζηχκ Δπζζηδιχκ, Πακεπζζηήιζμ Θεζζαθίαξ, Οδυξ Φοηυημο, 38446, Ν. Ηςκία Μαβκδζίαξ, Δθθάδα 2 Σιήια Γεςπμκίαξ Φοηζηήξ Παναβςβήξ ηαζ Αβνμηζημφ Πενζαάθθμκημξ, πμθή Γεςπμκζηχκ Δπζζηδιχκ, Πακεπζζηήιζμ Θεζζαθίαξ, Οδυξ Φοηυημο, 38446, Ν. Ηςκία Μαβκδζίαξ, Δθθάδα Πεξίιεςε Κάεε πνυκμ δζμπεηεφμκηαζ ζημ πενζαάθθμκ ιεβάθεξ πμζυηδηεξ δζζθαζκυθδξ-α. Έπεζ δζαπζζηςεεί υηζ δ έκςζδ αοηή δνα ςξ εκδμηνζκζηυξ δζαηανάηηδξ ηαζ ηνμπμπμζεί ηδ δνάζδ ηςκ εκδμβεκχκ μζζηνμβυκςκ ζημοξ μνβακζζιμφξ πμο έπμοκ εηηεεεί ζε αοηήκ. Γεδμιέκμο υηζ δ Artemia franciscana είκαζ ζδακζηυ γχμ βζα πεζνάιαηα μλείαξ ημλζηυηδηαξ, ζημπυξ ηδξ πανμφζαξ ενβαζίαξ ήηακ κα ιεθεηδεεί δ επίδναζδ ηδξ ΒΡΑ ζηδ θοθεηζηή δζαθμνμπμίδζδ ημο ζηεθέπμοξ A. franciscana ηαζ ζηδκ ακάπηολδ ηδξ F1 197

198 βεκζάξ πμο πνμέηορε απυ ηα άημια πμο είπακ εηηεεεί ζηδ ΒΡΑ. Απυ ηα πεζνάιαηα παναηδνήεδηε δζαθμνμπμίδζδ ζημ θφθμ ηαεχξ δ ακαθμβία Ανζεκζηά/Θδθοηά ζημοξ ιάνηονεξ ήηακ 0,92:1, εκχ ζε υθεξ ηζξ επελενβαζίεξ ιε ΒΡΑ ηα ανζεκζηά ήηακ πενζζζυηενα απυ ηα εδθοηά, ιε ηδκ ακαθμβία Ανζεκζηά/Θδθοηά κα θηάκεζ κα ζζμφηαζ ιε 2:1 ιεηά απυ έηεεζδ ζε ζοβηέκηνςζδ 35 ppm. Δπίζδξ, απυ ηδ ιεθέηδ ημο ιήημοξ ηςκ καοπθίςκ ηδξ F1 βεκζάξ, πνμέηορε ακαζημθή ηδξ ακάπηολήξ ημοξ υηακ δ παηνζηή βεκζά είπε εηηεεεί ζε ζοβηεκηνχζεζξ ΒΡΑ πάκς απυ 10 ppm Λέμεηο θιεηδηά: Artemia franciscana, δηζθαηλόιε-α, θπιεηηθή δηαθνξνπνίεζε, ηαρύηεηα αλάπηπμεο *οββναθέαξ επζημζκςκίαξ: Οζημκυιμο Γεχνβζμξ Δηζαγσγή H δζζθαζκυθδ Α (ΒΡΑ) είκαζ εκδμηνζκζηυξ δζαηανάηηδξ πμο ακήηεζ ζηα λεκμμζζηνμβυκα ηαζ πνμηαθεί δζαηαναπέξ ηονίςξ ζηδκ ακάπηολδ ημο ακαπαναβςβζημφ ζοζηήιαημξ, ηαεχξ ηνμπμπμζεί ηδ δνάζδ ηςκ εκδμβεκχκ μζζηνμβυκςκ (Crain et al. 2007). Ζ ΒΡΑ είκαζ ιία μνβακζηή πδιζηή έκςζδ πμο πανάβεηαζ ζε ιεβάθεξ πμζυηδηεξ ηάεε πνυκμ, πνδζζιμπμζείηαζ ηονίςξ ζηδκ ηαηαζηεοή πθαζηζηχκ (Staples et al. 1998) ηαζ απυ ηδκ επελενβαζία ημοξ εθεοεενχκμκηαζ ζηδκ αηιυζθαζνα πάκς απυ 100 ηυκμζ εηδζίςξ (Tsai 2006). Δπεζδή ηα οπμθείιιαηα BPA απυ ηδκ παναβςβή, ηδ ιεηαπμίδζδ ηαζ ηα ενβμζηάζζα επελενβαζίαξ θοιάηςκ δζμπεηεφμκηαζ ζημ οδάηζκμ πενζαάθθμκ, ηα ηεθεοηαία πνυκζα μζ πενζζζυηενεξ ένεοκεξ έπμοκ επζηεκηνςεεί ζηδ ιεθέηδ ηδξ ημλζηήξ ηδξ δνάζδξ ιε έιθαζδ ζημοξ οδνυαζμοξ μνβακζζιμφξ (Staples et al. 2002, Cousins et al. 2002). Ζ ανηέιζα, ακ ηαζ απμηεθεί έκακ non target organism, είκαζ ζφιθςκα ιε ηδ αζαθζμβναθία ζδακζηυ πεζναιαηυγςμ βζα πεζνάιαηα μλείαξ ημλζηυηδηαξ (MacRae et al 1988, Warner et al. 1989). Πνυζθαηα δδιμζζεοιέκδ ένεοκα βζα ηδκ ημλζηυηδηα ηδξ ΒΡΑ ζηδκ ανηέιζα (Castritsi-Catharios et al. 2013), δζαπίζηςζε υηζ υζμ αολάκεηαζ δ ζοβηέκηνςζδ ηδξ ΒΡΑ ιεζχκεηαζ ημ ιήημξ ηςκ πεζναιαηυγςςκ ηαζ δ εακαηδθυνμξ ζοβηέκηνςζδ LC50 ανέεδηε 44,8 ppm βζα 24 h έηεεζδξ ηαζ 34,7 ppm βζα 48 h έηεεζδξ. ημπυξ ηδξ πανμφζαξ ενβαζίαξ είκαζ δ ιεθέηδ ηδξ επίδναζδξ ηδξ BPA ζηδ θοθεηζηή δζαθμνμπμίδζδ ηςκ αηυιςκ ημο ζηεθέπμοξ Artemia franciscana ηαζ δ πζεακή επίδναζή ηδξ ζηδκ ακάπηολδ ηδξ 2 δξ βεκζάξ πμο εα πνμηφρεζ απυ ηα άημια πμο είπακ εηηεεεί ζηδ ΒΡΑ. Τιηθά θαη Μέζνδνη Ζ παναζηεοή δζαθοιάηςκ δζζθαζκυθδξ-α (ΒΡΑ) έβζκε ζφιθςκα ιε ημ πνςηυημθθμ ηςκ Fun et al. (2007). Οζ ζοβηεκηνχζεζξ ηςκ δζαθοιάηςκ πμο πνδζζιμπμζήεδηακ ήηακ 3, 5, 8, 10, 15, 20, 25 ηαζ 35 ppm. Κφζηεζξ ημο ηανηζκμεζδμφξ Α. franciscana ημπμεεηήεδηακ βζα εηηυθαρδ ζε ζοκεεηζηυ εαθαζζζκυ κενυ 35. Μεηά ηδκ εηηυθαρδ ζε ηάεε ζοβηέκηνςζδ ΒΡΑ εηηέεδηακ 50 καφπθζμζ βζα 24 h ηαζ ζηδ ζοκέπεζα μζ καφπθζμζ ιεηαθένεδηακ ζε ηαεανυ ζοκεεηζηυ εαθαζζζκυ κενυ 35. Ζ ηαθθζένβεζα πναβιαημπμζήεδηε ζε ηςκζηέξ θζάθεξ ημο 1 L πμο πενζείπακ 500 ml ζοκεεηζημφ εαθαζζζκμφ κενμφ, ηάης απυ ζηαεενέξ ζοκεήηεξ (εενιμηναζία μ C, 35 S, ζοκεπήξ πανμπή μλοβυκμο ηαζ ζοκεπήξ θςηζζιυξ lux). Σα πεζναιαηυγςα ηνεθυηακ ιε ιαβζά ηαζ ηάεε ιένα ηα κεηνά άημια απμιαηνφκμκηακ. Μεηά ηδκ εκδθζηίςζδ ιεηνήεδηε δ ακαθμβία ανζεκζηχκ ηαζ εδθοηχκ ηαζ ημπμεεηήεδηακ ζε γεοβάνζα λεπςνζζηά ιέπνζ κα δχζμοκ απμβυκμοξ. Γζα ηδ ιεθέηδ ηδξ επίδναζδξ ηδξ ΒΡΑ ζηδκ ακάπηολδ ηδξ F1 βεκζάξ, απυ ηάεε ζοβηέκηνςζδ θήθεδηακ μζ απυβμκμζ ηνζχκ γεοβανζχκ ηαζ ιεηνήεδηε ημ μθζηυ ιήημξ ημοξ ζηζξ 24, 48 ηαζ 72 h ζε ζηενεμζηυπζμ ζοκδεδειέκμ ιε ηάιενα, ιε ηδ πνήζδ ημο θμβζζιζημφ analysis getit 5.1. Γζα ηζξ ιεηνήζεζξ ιήημοξ πνδζζιμπμζήεδηε ζηαηζζηζηή ακάθοζδ ANOVA βζα κα ελαηνζαςεεί εάκ οπήνπακ ζηαηζζηζηχξ ζδιακηζηέξ δζαθμνέξ ιεηαλφ ημοξ. Έβζκακ ηνεζξ επακαθήρεζξ ημο πεζνάιαημξ βζα κα δζαπζζηςεεί εάκ είπαιε επακαθδρζιυηδηα ζηα απμηεθέζιαηα. Πνμηεζιέκμο κα βίκεζ δζενεφκδζδ ηδξ ζηαεενυηδηαξ ηςκ δζαθοιάηςκ ΒΡΑ ιε ηδκ πάνμδμ ημο πνυκμο, θήθεδηε δείβια κενμφ απυ ηάεε ηαθθζένβεζα ηαηά ηδκ ημπμεέηδζδ ηςκ καφπθζςκ ζηα δζαθφιαηα BPA ηαζ ηαηά ηδκ απμιάηνοκζή ημοξ απυ αοηά. Σα δείβιαηα ιεηνήεδηακ ζε ζφζηδια οβνήξ πνςιαημβναθίαξ ορδθήξ απυδμζδξ (HPLC) ηφπμο Agilent 1100 ιε ακίπκεοζδ ζηα 230 nm. 198

199 Απνηειέζκαηα φιθςκα ιε ηα απμηεθέζιαηα ηςκ ακαθφζεςκ ηςκ κενχκ ηδξ ηαθθζένβεζαξ ιε ημ ζφζηδια HPLC, ανέεδηε υηζ δ ζοβηέκηνςζδ ηδξ BPA ζημ κενυ δε ιεηααθήεδηε ζε υθα ηα επίπεδα ηςκ ζοβηεκηνχζεςκ πμο δμηζιάζηδηακ (3-35 mg/l). Πίλαθαο 1. Απνηειέζκαηα αλαινγίαο θχινπ θαη ζλεζηκφηεηαο κεηά απφ έθζεζε ηνπ ζηειέρνπο A. franciscana ζε δηαθνξεηηθέο ζπγθεληξψζεηο ΒΡΑ. A Θ Α/Θ Θκδζζιυηδηα Θκδζζιυηδηα % Μάνηονεξ ,92: ppm ,13: ppm ,08: ppm ,14: ppm ,88: ppm ,41: ppm ,40: ppm ,54: ppm ,00: Α= Αξζεληθά, Θ= Θειπθά, Α/Θ= Αλαινγία αξζεληθψλ πξφο ζειπθά Ζ ακαθμβία θφθμο ηαζ δ εκδζζιυηδηα ηδξ παηνζηήξ βεκζάξ ημο ζηεθέπμοξ A. franciscana πανμοζζάγμκηαζ ζημκ Πίκαηα 1. Σα απμηεθέζιαηα απυ ηδ ιέηνδζδ ημο ιήημοξ ηςκ καοπθίςκ 2 δξ βεκζάξ ηαζ απυ ηδ ζηαηζζηζηή ημοξ επελενβαζία δίκμκηαζ ζημ πήια 1 ηαζ ζημκ Πίκαηα 2, ακηίζημζπα. 199

200 ρήκα 1. Μήθνο ησλ λαχπιησλ ηεο F1 γεληάο πνπ πξνήιζαλ απφ γνλείο πνπ είραλ εθηεζεί ζε δηαθνξεηηθέο ζπγθεληξψζεηο ΒΡΑ Πίλαθαο 2. Απνηειέζκαηα κήθνπο ησλ λαππιίσλ (F1) πνπ πξνέθπςαλ απφ γνλείο πνπ είραλ εθηεζεί ζε δηαθνξεηηθέο ζπγθεληξψζεηο ΒΡΑ. Οη ηηκέο ηνπ κήθνπο ησλ λαππιίσλ πνπ είραλ ζηαηηζηηθά ζεκαληηθή δηαθνξά ζε ζρέζε κε ηνπο κάξηπξεο παξνπζηάδνληαη κε θίηξηλν ρξψκα 24 h 48 h 72 h AVG (ιm) SD (ιm) AVG (ιm) SD (ιm) AVG (ιm) SD (ιm) Μάνηονεξ 765,95 43,15 801,34 32,23 927,43 62,11 3 ppm 760,59 51,46 797,75 25,91 903,31 57,66 5 ppm 741,06 34,76 782,00 49,08 886,94 52,64 8 ppm 720,82 33,49 752,16 35,66 859,78 55,32 10 ppm 713,55* 44,75 734,97* 22,12 827,65* 43,07 15 ppm 701,77** 51,22 718,53* 47,62 812,74** 54,16 20 ppm 695,30** 39,83 708,44** 51,43 800,40** 47,88 25 ppm 682,11** 52,31 693,99** 41,79 786,13** 65,79 35 ppm 675,45** 46,87 690,89** 57,01 764,52** 60,55 ηαηζζηζηά ζδιακηζηή δζαθμνά ζε επίπεδμ *P<0,05 ή **P<0,005. AVG (Average) = Μέζδ ηζιή μθζημφ ιήημοξ, SD (Standard Deviation) = Σοπζηή Απυηθζζδ. 200

201 πδήηεζε Απυ ηα απμηεθέζιαηα πνμέηορε υηζ δ εκδζζιυηδηα ήηακ ακάθμβδ πνμξ ηδ ζοβηέκηνςζδ ΒΡΑ ζηδκ μπμία είπακ εηηεεεί ηα πεζναιαηυγςα. Ζ ιέβζζηδ εκδζζιυηδηα (40%) πανμοζζάζηδηε ζηδ ιεβαθφηενδ ζοβηέκηνςζδ δζζθαζκυθδξ-α (35 ppm) πμο πνδζζιμπμζήεδηε βζα ηα ζοβηεηνζιέκα πεζνάιαηα (Πίκαηαξ 1). θεξ μζ ζοβηεκηνχζεζξ BPA ήηακ οπμεακάηζεξ (δ εκδζζιυηδηα ήηακ ιζηνυηενδ απυ 50%) ηαεχξ δ LC50 βζα 24 h έηεεζδξ ηδξ A. franciscana ζηδ ΒΡΑ είκαζ 44,8 ppm (Castritsi-Catharios et al. 2013). ηα άημια πμο εηηέεδηακ ζε ΒΡΑ παναηδνήεδηε δζαθμνμπμίδζδ ζημ θφθμ ζε ζπέζδ ιε ημοξ ιάνηονεξ. οβηεηνζιέκα, ζημοξ ιάνηονεξ ηα εδθοηά άημια ήηακ πενζζζυηενα ηαζ δ ακαθμβία Ανζεκζηά/Θδθοηά ήηακ 0,92:1. Ακηίεεηα, ζε υθεξ ηζξ ιεηαπεζνίζεζξ ιε ΒΡΑ ηα ανζεκζηά ήηακ πενζζζυηενα απυ ηα εδθοηά ιε ηδκ ακαθμβία Ανζεκζηά/Θδθοηά κα θηάκεζ κα ζζμφηαζ ιε 2:1 ζηδκ ζοβηέκηνςζδ ηςκ 35 ppm. Αοηυ πζεακχξ κα μθείθεηαζ ζηζξ δζαηαναπέξ ζημ ακαπαναβςβζηυ ζφζηδια πμο πνμηαθεί δ ΒΡΑ (Crain et al. 2007) ηαζ ζοιθςκεί ιε ιζα ιεθέηδ ηςκ Monje et al. (2009) πμο έβζκε ζε ανμοναίμοξ ηαζ δζαπζζηχεδηε υηζ δ επίδναζδ ηδξ ΒΡΑ αθθμζχκεζ ιυκζια ηδκ δνάζδ ηςκ μζζηνμβυκςκ. Απυ ηδ ιέηνδζδ ημο ιήημοξ ηςκ καοπθίςκ ηδξ F1 βεκζάξ, ανέεδηε ακαζημθή ζηδκ ακάπηολή ημοξ ζε ζπέζδ ιε ημ ιάνηονα ηαζ ζηζξ ηνεζξ πνμκζηέξ ζηζβιέξ πμο ιεθεηήεδηακ. Σμ ιήημξ ηςκ καοπθίςκ ήηακ ιζηνυηενμ υζμ ιεβαθφηενδ ήηακ δ ζοβηέκηνςζδ ηδξ ΒΡΑ πμο είπε εηηεεεί δ παηνζηή βεκζά. Απυ ηδ ζηαηζζηζηή ακάθοζδ ANOVA πνμέηορε υηζ ζημοξ απυβμκμοξ ηςκ αηυιςκ πμο είπακ εηηεεεί ζε ζοβηεκηνχζεζξ ΒΡΑ 10 ppm ηαζ πάκς, ημ ιήημξ δζέθενε ζηαηζζηζηά ζδιακηζηά (P<0,05) ζε ζπέζδ ιε ημ ιήημξ ηςκ ιανηφνςκ (Πίκαηαξ 2). Ζ παναηήνδζδ αοηή ζοιθςκεί ιε ηα απμηεθέζιαηα ηδξ πνμδβμφιεκδξ ένεοκαξ πμο είπε βίκεζ απυ ημοξ Castritsi-Catharios et al. (2013) βζα ηδκ επίδναζδ ηδξ ΒΡΑ ζημ ζηέθεπμξ A. franciscana, υπμο απμδείπεδηε δ ακαζηαθηζηή ηδξ δνάζδ ζηδκ ηαπφηδηα ακάπηολδξ ηαζ ημ ιέβεεμξ καοπθίςκ ζηαδ. ΗΗ-ΗΗΗ πμο είπακ εηηεεεί. Δπίζδξ, δ ακαζημθή ηδξ ακάπηολδξ ημο ζηεθέπμοξ A. franciscana ιεηά απυ έηεεζή ημο ζε ημλζηά έπεζ ακαθενεεί ηαζ ζηδκ ενβαζία ηςκ Castritsi-Catharios et al. (2014), υηακ ιεθέηδζακ ηδκ επίδναζδ ηςκ οθαθμπνςιάηςκ ζηδκ ηαπφηδηα ακάπηολδξ ηςκ καοπθίςκ. Απυ αοηυ ζοιπεναίκμοιε υηζ μζ ημλζηέξ μοζίεξ δνμοκ ακαζηαθηζηά ζηδκ ακάπηολδ ημο ζοβηεηνζιέκμο μνβακζζιμφ ηαζ δ πνμηαθμφιεκδ ακαζημθή είκαζ ακάθμβδ ιε ηδ ζοβηέκηνςζδ ηδξ ημλζηήξ μοζίαξ αηυιδ ηαζ ζε οπμεακάηζεξ ζοβηεκηνχζεζξ. Δπεζδή δ ανηέιζα απμηεθεί μνβακζζιυ οπυδεζβια βζα ηα ηανηζκμεζδή εα ιπμνμφζε κα αζηζμθμβδεεί ζημ άιεζμ ιέθθμκ ημ θαζκυιεκμ ημο κακζζιμφ ηςκ ηανηζκμεζδχκ ζε νοπαζιέκμοξ οδάηζκμοξ μζηυημπμοξ. Βηβιηνγξαθία Castritsi-Catharios J., Alambritis G., Miliou H., Cotou E., Zouganelis D.G. (2014). Comparative Toxicity of Tin Free Self-Polishing Copolymer Antifouling Paints and Their Inhibitory Effects on Larval Development of a Not-Target Organism. Materials Sciences and Applications 5, Castritsi-Catharios J., Syriou V., Miliou H., Zouganelis D.G. (2013). Toxicity effects of bisphenol A to the nauplii of the brine shrimp Artemia franciscana. Journal of Biological Research- Thessaloniki 19, Cousins I.T., Staples C.A., Klecka G.M., Mackay D. (2002). A Multimedia Assessment of the Environmental Fate of Bisphenol A. Human and Ecological Risk Assessment 8(5), Crain A.D., Eriksen M., Iguchi T., Jobling S., Laufer H., LeBlanc G.A., Guillette LJ.Jr. (2007). An ecological assessment of Bisphenol A: Evidence from comparative biology. Reproductive Toxicology 24, Fan J., Guo H., Liu G., Peng P. (2006). Simple and sensitive fluorimetric method for determination of environmental hormone bisphenol A based on its inhibitory effect on the redox reaction between peroxyl radical and rhodamine 6G. Analytica Chimica Acta 585, MacRae T.H., Bagshaw J.C., Warner A.H. (1988). Biochemical and cell biology of Artemia. CRC Press Inc, Boca Raton, FL. 201

202 Monje L., Varayoud J., Munoz-de-Toro M., Luque E.H. Ramos J.G. (2009). Neonatal exposure to bisphenol A alters estrogen dependent mechanisms governing sexual behavior in the adult female rat. Reproductive Toxicology 28(4), Staples C.A., Dorn P.B., Klecka G.M., O Block S.T., Harris L.R. (1998). A review of the environmental fate, effects, and exposures of bisphenol A. Chemosphere 36(10), Staples C.A., Woodburn K., Caspers N., Hall T., Kleka G. (2002). A Weight of Evidence Approach to the Aquatic Hazard Assessment of Bisphenol A. Human and Ecological Risk Assessment 8(5), Tsai W.T. (2006). Human health risk on environmental exposure to bisphenol-a: a review. Journal of Environmental Science and Health C 24, Warner A.H., MacRae T.H., Bagshaw J.C. (1989). Cell and molecular biology of Artemia development. Plenum Press, NY. 202

203 TEMPORAL CHANCES OF THE TECHNICAL AND SPATIAL FEATURES OF AQUACULTURE FARMS IN GREECE AND TURKEY Petrou Charilaos, Katselis George* Department of Fishery and Aquaculture Technology, TEI of Western Greece, Nea Ktiria, 30200, Mesolonghi ABSTRACT The present study examined temporal changes on the technical and spatial features of marine aquaculture farms for two Mediterranean countries (Greece, Turkey), for the period based on available historical images from Google earth (free software).the cages type and dimensions as well as their sites (geographic coordinates) that provided by the satellite images, were examined. The pattern of changes of the technical and the spatial features of cages were differed between the two countries during the period and In Greece, the spatial features of fish farms seem to remain stable whereas in Turkey there is relocation of fish farms which associated by longer distance from the shore and increase of the available rearing volume. In both countries the changes of the technical features of cages refer to the usage of cyclical cages. Key words: Aquaculture, farm, type of cages, spatial features, cages technical features, satellite image Corresponding author: Katselis George( ) ΓΗΑΥΡΟΝΗΚΔ ΜΔΣΑΒΟΛΔ ΥΧΡΗΚΧΝ ΚΑΗ ΣΔΥΝΗΚΧΝ ΥΑΡΑΚΣΖΡΗΣΗΚΧΝ ΜΟΝΑΓΧΝ ΗΥΘΤΟΚΑΛΛΗΔΡΓΔΗΑ ΣΖΝ ΔΛΛΑΓΑ ΚΑΗ ΣΟΤΡΚΗΑ Πέηξνπ Υαξίιανο, Καηζέιεο Γεψξγηνο * Σιήια Σεπκμθμβίαξ Αθζείαξ-Τδαημηαθθζενβεζχκ, ΣΔΗ Γοηζηήξ Δθθάδαξ, Νέα Κηίνζα, Μεζμθυββζ, Πεξίιεςε ηδκ πανμφζα ιεθέηδ ελέηαζηδηακ μζ δζαπνμκζηέξ αθθαβέξ ζηα ηεπκζηά ηαζ πςνζηά παναηηδνζζηζηά ηςκ εαθάζζζςκ ιμκάδςκ οδαημηαθθζένβεζαξ βζα δφμ πχνεξ ηδξ Μεζμβείμο (Δθθάδα, Σμονηία), βζα ηδκ πενίμδμ ιε αάζδ ηζξ δζαεέζζιεξ ζζημνζηέξ απεζημκίζεζξ απυ ημ Google earth (εθεφεενμ θμβζζιζηυ). Ο ηφπμξ ηθςαχκ ηαζ μζ δζαζηάζεζξ ημοξ, ηαεχξ ηαζ δ πενζμπή εβηαηάζηαζδξ (βεςβναθζηέξ ζοκηεηαβιέκεξ), πμο πανέπμκηαζ απυ ηζξ δμνοθμνζηέξ εζηυκεξ, ελεηάζηδηακ. Σμ πνυηοπμ ηςκ αθθαβχκ ηςκ ηεπκζηχκ ηαζ ηςκ πςνζηχκ παναηηδνζζηζηχκ ηςκ ηθςαχκ δζέθενε ιεηαλφ ηςκ δφμ πςνχκ ηαηά ηζξ πενίμδμοξ ηαζ ηδκ Δθθάδα, ηα πςνζηά παναηηδνζζηζηά ηςκ ιμκάδςκ θαίκεηαζ κα παναιέκμοκ ζηαεενά, εκχ ζηδκ Σμονηία παναηδνμφκηαζ εηηεηαιεκεξ ιεηεβηαηάζηαζεζξ ιμκάδςκ πμο ζοκδέμκηαζ ιε ιεβαθφηενδ απυζηαζδ απυ ηδκ αηηή ηαζ ιε αφλδζδ ημο δζαεέζζιμο υβημο εηηνμθήξ. Καζ ζηζξ δφμ πχνεξ μζ αθθαβέξ ηςκ ηεπκζηχκ παναηηδνζζηζηχκ ηςκ ηθςαχκ αθμνμφκ ζηδ πνήζδ ηςκ ηοηθζηχκ ηθμοαχκ. Λέξειρ κλειδιά: Μεζνγεηαθή ηρζπνθαιιηέξγεηα, ρσξηθή θαηαλνκή, ηερληθά ραξαθηεξηζηηθά,google earth *οββναθέαξ επζημζκςκίαξ:καηζέθδξ Γεχνβζμξ (gkatsel@teimes.gr) 203

204 1.Δηζαγσγή Οζ εαθαζζμηαθθζένβεζεξ ζηδ Μεζυβεζμ έπμοκ ηαοηζζηεί ιε ηδκ εκηαηζηή εηηνμθή ημο θααναηζμφ ηαζ ηδξ ηζζπμφναξ ηαζ απμηεθμφκ έκακ απυ ημοξ πθέμκ δοκαιζημφξ ηθάδμοξ ηδξ εονςπασηήξ αζμιδπακίαξ παναβςβήξ ηνμθίιςκ απυ ηδ εάθαζζα. Ζ ιεζμβεζαηή παναβςβή ζδιείςζε αθιαηχδδ ακάπηολδ απυ ηυκμοξ ημ 1995 (Theodorou, 2002) ζημοξ ηυκμοξ ημ 2012, ιε ηδκ παναβςβή ηδξ Δθθάδαξ ηαζ ηδξ Σμονηίαξ ημ 2012 κα ακηζπνμζςπεφμοκ πενίπμο ημ 47% ηαζ 40% αοηήξ ακηίζημζπα (FAO, 2014). Σμ ιεβαθφηενμ πμζμζηυ ηςκ ιμκάδςκ είκαζ εβηαηεζηδιέκμ ζηδκ πανάηηζα γχκδ, ζε ζοκαενμίζεζξ ιμκάδςκ, ςξ απμηέθεζια αεθηζζημπμίδζδξ ηςκ δζαδζηαζζχκ παναβςβήξ ηαζ δζάεεζδξ ημο πνμσυκημξ (Πέηνμο, 2013). Ζ πςνμηαλία ημοξ ανίζηεηαζ οπυ ηδκ ηναηζηή επμπηεία ηδξ ηάεε πχναξ, εκχ ηαηαβνάθμκηαζ πενζπηχζεζξ μθζηήξ ακαεεχνδζδξ ημο πςνμηαλζημφ ζπεδζαζιμφ ηδξ δναζηδνζυηδηαξ (Yücel - Gier et al., 2009). Σα ηεπκζηά παναηηδνζζηζηά ηςκ ιμκάδςκ ζοκδέμκηαζ ιε ηδκ παναβςβζηή δοκαιζηυηδηα ημοξ (Trujillo et al., 2012) ηαζ ηδ πςνμηαλία ημοξ, εκχ δ αφλδζδ ηδξ παναβςβήξ θαίκεηαζ υηζ ζοκμδεφεηαζ απυ ηζξ δζαπνμκζηέξ αθθαβέξ ημοξ (Theodorou, 2002). Σα παναηηδνζζηζηά ηδξ ηαηακμιήξ ημοξ ζημ πχνμ επδνεάγμοκ πανάθθδθα ηαζ ηα μζημζοζηήιαηα ζημ επίπεδμ ημο αέκεμοξ ηαζ ηδξ πμζυηδηαξ ημο κενμφ (Kalantzi & Karakassis, 2006), ηςκ δδιμβναθζηχκ παναηηδνζζηζηχκ (Dimitriou, et al., 2007) ηαζ ηδξ πςνζηήξ ηαηακμιήξ ηςκ αβνίςκ πθδεοζιχκ ρανζχκ (Dempster et al., 2002). Σμ θμβζζιζηυ Google earth (εθεφεενδξ πνυζααζδξ) δζαεέηεζ δμνοθμνζηέξ απεζημκίζεζξ, μζ μπμίεξ πνδζζιμπμζμφκηαζ απυ ηδκ επζζηδιμκζηή ημζκυηδηα βζα επζηφνςζδ (validation) ηαζ ελαβςβή πθδνμθμνίαξ πμο αθμνά ζηδ πνμκζηή ελέθζλδ βεβμκυηςκ (Clarke et al.,2010;taylor et al.,2011). ηδκ πανμφζα ενβαζία βίκεηαζ ιεθέηδ ηςκ δζαπνμκζηχκ ιεηααμθχκ ηςκ ηεπκζηχκ ηαζ πςνζηχκ παναηηδνζζηζηχκ ηςκ ιμκάδςκ ζπεομηαθθζένβεζαξ ζηδκ Δθθάδα ηαζ ηδκ Σμονηία, αλζμπμζχκηαξ ζημζπεία δμνοθμνζηχκ απεζημκίζεςκ δζαεέζζιςκ απυ ημ θμβζζιζηυ Google earth. 2. Τιηθά θαη κέζνδνη Σα ζημζπεία αθμνμφκ ζε 590 βεςβναθζηέξ εέζεζξ (βεςβναθζηέξ ζοκηεηαβιέκεξ) υπμο θεζημφνβδζακ ή θεζημονβμφκ ιμκάδεξ ζπεομηαθθζένβεζαξ ζηζξ αηηέξ ηδξ Δθθάδαξ, ζηζξ δοηζηέξ αηηέξ ηδξ Σμονηίαξ ζημ Αζβαίμ (απυ ηα Γανδακέθζα ιέπνζ ηδκ Αηηάθεζα), ηζξ αηηέξ ηδξ Αθαακίαξ ηαζ ηδξ Μάθηαξ, ημ πνμκζηυ δζάζηδια Χξ ίδζαξ εέζδξ εεςνήεδηακ μζ ζοζημζπίεξ ηθςαχκ, μζ μπμίεξ απέπμοκ ιεηαλφ ημοξ m (ηαηά ακαθμβία ηςκ μνίςκ απυζηαζδξ ηδξ πάνηςκ ηδξ ίδζαξ ιμκάδαξ αάζδ ηδξ ημζκήξ εβηοηθίμο /1866/ ηςκ οπμονβείςκ ΠΔ.ΥΧ.ΓΔ ηαζ Α.Α.ΣΡ.) Σα ζημζπεία θήθεδηακ απυ ημ ζφκμθμ ηςκ δζαεέζζιςκ δμνοθμνζηχκ απεζημκίζεςκ ακά ιμκάδα, απυ ημ θμβζζιζηυ Google earth, βζα ηδκ παναπάκς πενίμδμ ηαζ αθμνμφκ ζηδ εέζδ (βεςβναθζηυ πθάημξ ηαζ ιήημξ), ζημκ ανζειυ, ζημκ ηφπμ (ηοηθζηυ, ηεηνάβςκμ) ηαζ ζηζξ δζαζηάζεζξ ηςκ ηθςαχκ (πθεονά βζα ηα ηεηνάβςκα, δζάιεηνμξ βζα ηα ηοηθζηά) ηαζ ζηδκ εθάπζζηδ απυζηαζδ απυ ηδκ αηηή ακά ιμκάδα. Απυ ηζξ δζαζηάζεζξ ηςκ ηθςαχκ οπμθμβίζεδηε ημ ειααδυκ ημοξ ηαζ μ υβημξ εηηνμθήξ εεςνχκηαξ ςξ αάεμξ ηθςαμφ ίζμ ιε ηδκ πθεονά βζα ημοξ ηεηνάβςκμοξ ηθςαμφξ ηαζ ηδ δζάιεηνμ βζα ημοξ ηοηθζημφξ, βζα ημοξ ηθςαμφξ ιε ειααδυκ ιέπνζ ηα 150 m 2, εκυζς βζα ιεβαθφηενδξ επζθάκεζαξ ηθςαμφξ ςξ αάεμξ εηηνμθήξ οπμθμβίζεδηε ημ 75% ηςκ παναπάκς δζαζηάζεςκ πςνίξ κα λεπενκάηε ημ αάεμξ ηςκ 18 m. H ακάθοζδ ημο πνμηφπμο ζφκεεζδξ ηθςαχκ ηςκ ιμκάδςκ έβζκε ιε ηδκ εθανιμβή ηδξ ακάθοζδξ ζε μιάδεξ (cluster analysis: hierarchical agglomerative Ward s method) ζηα δεδμιέκα: ιμκάδεξ Υ ηφπμξ ηαζ δζαζηάζεζξ ηθςαχκ. Γζα ηάεε εέζδ βζα ηδ μπμία οπήνπακ δζαεέζζιεξ πενζζζυηενεξ απυ δφμ δμνοθμνζηέξ απεζημκίζεζξ ιε πνμκζηή απυζηαζδ ηδξ πνχηδξ ηαζ ηδξ ηεθεοηαίαξ ιεβαθφηενδ ηςκ 7 εηχκ ή έςξ 5 εηχκ (υηακ δ πνχηδ απεζηυκζζδ εκηάζζεηαζ ζηδκ πενίμδμ ιεηά ) εθέβπεδηακ μζ δζαθμνμπμζήζεζξ ζηδκ μιάδα ηφπμο ηθςαχκ ηδξ ιμκάδαξ. Ζ απμοζία ιμκάδμξ ζηδκ ανπζηή απεζηυκζζδ ζε ζοκδοαζιυ ιε ηδκ πανμοζία ζηδκ ηεθζηή, ζε ιζα εέζδ, αθμνά ζε εβηαηάζηαζδ ιμκάδμξ, εκχ μ ακηίζηνμθμξ ζοκδοαζιυξ ζε δζάθοζδ ιμκάδμξ. Οζ ζηαηζζηζημί έθεβπμζ ιεηαλφ ηςκ μιάδςκ έβζκακ ιε ακάθοζδ δζαηφιακζδξ (ANOVA, P=0.05) ηαζ π 2 (P=0.05). 3. Απνηειέζκαηα Απυ ηζξ δζαεέζζιεξ απεζημκίζεζξ ηδξ πενζυδμο , ζηδ πενζμπή ιεθέηδξ ηαηαβνάθδηακ 393 εέζεζξ ιμκάδςκ υπμο βζα έζης ηαζ ζε ιζα απεζηυκζζδ, ηαηά ηδκ πενίμδμ ιεθέηδξ, ακαβκςνίζεδηε ιμκάδα εηηνμθήξ. Οζ εέζεζξ αοηέξ αθμνμφκ ζε 245 ζηα πςνζηά φδαηα ηδξ Δθθάδαξ, 138 ηδξ Σμονηίαξ, ηαζ απυ 5 εέζεζξ ζηα πςνζηά φδαηα ηδξ Αθαακίαξ ηαζ ηδξ Μάθηαξ. ε αοηέξ ηζξ 204

205 εέζεζξ ζοκμθζηά ηαηαβνάθδηακ 767 απεζημκίζεζξ, μζ μπμίεξ αθμνμφκ ζε δζάθμνεξ πνμκζηέξ ζηζβιέξ ηαηά ηδκ πενίμδμ ιεθέηδξ. Οζ 181 (46.0%) εέζεζξ αθμνμφκ ζε ιζα απεζηυκζζδ ηαζ μζ 212 (53.9%) ζε πενζζζυηενεξ απυ ιία απεζημκίζεζξ ακά εέζδ ιμκάδμξ. ε 178 (23.3%) εέζεζξ ιμκάδςκ δ πνμκζηή δζαθμνά ιεηαλφ ηςκ αηναίςκ απεζημκίζεςκ είκαζ ιεβαθφηενδ ηςκ 7 εηχκ ή ιεβαθφηενδ ηςκ 5 εηχκ εάκ αοηή εκηάζζεηαζ ζημ πνμκζηυ δζάζηδια ιεηά ημ 2005 (Πίκαηαξ Η). Ζ ακάθοζδ ηςκ απεζημκίζεςκ ιε ηθςαμφξ, ζε μιάδεξ ζφκεεζδξ ηφπμο ηαζ δζαζηάζεςκ ηθςαχκ (cluster analysis) έδεζλε μηηχ μιάδεξ ιε δζαθμνεηζηή ζφκεεζδ ηθςαχκ (π 2 ;P<0.05). ηδ μιάδα 1 ημ 90% ηςκ ηθςαχκ αθμνά ηοηθζημφξ ηθςαμφξ δζαιέηνμο 10-20m (51,8%) ηαζ m (39.0%), ζηδ μιάδα 2 ημ 89% ηςκ ηθςαχκ αθμνά ζε ηοηθζημφξ ηθςαμφξ δζαιέηνμο m, ζηδκ μιάδα 3 ημ 85.7% ηςκ ηθςαχκ αθμνά ζε ηεηνάβςκμοξ ηθςαμφξ 5-10m (32,1%) ηαζ 10-16m (53.6%), ζηδκ μιάδα 4 ημ 81.5% ηςκ ηθςαχκ αθμνά ζε ηεηνάβςκμοξ ηθςαμφξ 5-10m, ζηδκ μιάδα 5 ημ 91% ηςκ ηθςαχκ αθμνά ζε ηοηθζημφξ ηθςαμφξ δζαιέηνμο 20-40m, ζηδκ μιάδα 6 ημ 93.2% ηςκ ηθςαχκ αθμνά ζε ηοηθζημφξ ηθςαμφξ 10-20m (49.1%) ηαζ ηεηνάβςκμοξ 5-10m (44.1%), ζηδκ μιάδα 7 ημ 88,3% ηςκ ηθςαχκ αθμνά ζε ηοηθζημφξ ηθςαμφξ 5-10 (38.4%) ηαζ 10-20m (49.9%) ηαζ ζηδκ μιαδα 8 ημ 89.4% ηςκ ηθςαχκ αθμνά ζε ηοηθζημφξ ηθςαμφξ 40-60m (Πίκαηαξ ΗΗ). Ζ ιέζδ επζθάκεζα είκαζ 5.09 ζην ηαζ ηοιαίκεηαζ απυ 3.44 ζην (μιάδα 4)-13.3 ζην (μιάδα 8). Ο ιέζμξ υβημξ εηηνμθήξ είκαζ 86.67x10 3 m 3 ηαζ ηοιαίκεηαζ απυ 33.3 x10 3 m 3 (μιάδα 4)-399 x10 3 m 3 (μιάδα 8). Ο ιέζμξ ανζειυξ είκαζ 43.7 ηθςαμί ηαζ ηοιαίκεηαζ απυ 7.42 (μιάδα 8) 80.5 ηθςαμί (μιάδα 4). ηαηζζηζηά ζδιακηζηέξ δζαθμνέξ παναηδνήεδηακ ιεηαλφ ηςκ μιάδςκ ζηδκ ιέζδ επζθάκεζα (ANOVA; p<0.05; ηαζ Tukey t-test: μιάδα 4 7=3 2=6<1=5 8), ζημκ ιέζμ υβημ εηηνμθήξ (ANOVA; p<0.05; ηαζ Tukey t-test: μιάδα 4<2=3=6=7<1=5<8) ηαζ ζημκ ιέζμ ανζειυ ηθςαχκ (ANOVA; p<0.05; ηαζ Tukey t-test: μιάδα 8<5 1=2<3=7 6=4) (Πίκαηαξ ΗΗ). ημ ζφκμθμ ηςκ ιμκάδςκ, μ υβημξ εηηνμθήξ (V) πανμοζζάγεζ ζζπονή βναιιζηή ζπέζδ ιε ηδκ επζθάκεζα ηςκ ηθςαχκ S (V=20.02*S-11.84;R2=0.90;SE estimate=41.08;p<0.05). Πίλαθαο Η. Αξηζκφο απεηθνλίζεσλ (FG) κε (FG 1 )ή ρσξίο θισβνχο (FG 0 ), ζχλνιν ζέζεσλ κνλάδσλ κε απεηθνλίζεηο κε θισβνχο (n), κε κηα απεηθφληζε (n 1 ), κε πεξηζζφηεξεο απφ κία απεηθφληζε (n >1 ) θαη αξηζκφο ζέζεσλ κνλάδσλ φπνπ νη αθξαίεο ρξνληθά απεηθνλίζεηο έρνπλ ρξνληθή δηαθνξά κεγαιχηεξε ησλ 7 εηψλ ή 5 (φηαλ ε πξψηε απεηθφληζε εληάζζεηαη ζηελ πεξίνδν κεηά ) (n d ) Απεζημκίζεζξ (FG) Ανζειυξ εέζεςκ ιμκάδςκ Υχνα FG 0 FG 1 φκμθμ n n 1 n >1 n d Δθθάδα Σμονηία Μάθηα Αθαακία φκμθμ

206 Πίλαθαο ΗΗ. χλζεζε νκάδσλ κνλάδσλ αλά ηχπν θαη δηαζηάζεηο θισβνχ (%) θαη Μέζεο ηηκέο ησλ ηερληθψλ ραξαθηεξηζηηθψλ ησλ νκάδσλ κνλάδσλ ηρζπνθαιιηέξγεηαο (n: αξηζκφο κνλάδσλ, CG: κέζνο αξηζκφο θισβψλ, S: κέζε επηθάλεηα θισβψλ κνλάδαο, V: κέζνο φγθνο εθηξνθήο θισβψλ κνλάδαο θαη αξηζκφο απεηθνλίζεσλ ζέζεσλ κνλάδσλ κε θισβνχο (FG 1 ). Οη ίδηνη εθζέηεο αλά ζηήιε δειψλνπλ κε ζηαηηζηηθή δηάθνξα (ANOVA;Σukey t-test, P>0.05), ζηελ παξέλζεζε ε ηππηθή απφθιηζε. Κθςαμί: Κοηθζημί Σεηνάβςκμζ Γζαζηάζεζξ (m) μιάδα S (x10 3 m 2 ) V (x10 3 m 3 ) CG FG (5.6) β 164.(133.2) β 24.8(17.7) β,δ (2.8) α 71.2(50.1) α 26.6(18.3) β (2.9) α,α 67.6(62.7) α 36.1(19.0) α (4.0) α 33.3(43.5) α 80.5(110.1) α (5.5) β,δ 217.(148.1) β 17.0(12.9) δ (3.9) α 74.0(59.8) α 56.0(57.6) α (4.2) α,α,β 65.0(50.6) α 51.2(60.8) α,α (6.5) δ 399.0(195.6) δ 7.42(4.1) ε 14 φκμθμ 5.09(4.3) 86.67(102.0) 43.7(63.6) 590 Σμ πνυηοπμ ιεηααμθχκ ηςκ ιμκάδςκ πανμοζίαζε δζαθμνέξ ιεηαλφ Δθθάδαξ ηαζ Σμονηίαξ (π 2 =42.02;df=1;p<0.05). Γζα ηδκ Δθθάδα ημ ιεβαθφηενμ πμζμζηυ ηςκ ιμκάδςκ δεκ άθθαλε (43%), ή άθθαλε ηεπκζηά παναηηδνζζηζηά (31%). Σμ 6% ηςκ ιμκάδςκ δζαθφεδηε ηαζ ημ 20 % αθμνά ζε εβηαηάζηαζδ ιμκάδμξ ζε κέα εέζδ. Ακηίεεηα, ζηδκ Σμονηία ημ 47% ηςκ ιμκάδςκ δζαθφεδηε ηαζ ημ 34% αθμνά ζε εβηαηάζηαζδ ιμκάδμξ ζε κέα εέζδ (πήια 1Α). Ζ εθάπζζηδ απυζηαζδ απυ ηδκ αηηή πανμοζζάγεζ δζαθμνέξ ιεηαλφ ημο ηφπμο ιεηααμθχκ ηςκ ιμκάδςκ ιεηαλφ ηςκ δφμ πςνχκ (ANOVA;P<0.05), εκυζς μζ δζαθμνέξ αοηέξ εζηζάγμκηαζ ζηδκ απυζηαζδ απυ ηδκ αηηή ηςκ ιμκάδςκ πμο εβηαηαζημφκηαζ ζε κέα εέζδ (πήια 1Β). Ακ ηαζ δεκ ηαηαβνάθμκηαζ δζαθμνέξ ζημκ ζοκμθζηυ υβημ εηηνμθήξ ιεηαλφ ηςκ πενζυδςκ ηαζ βζα ηδκ Δθθάδα (t-test; P>0.05), o μπμίμξ εηηζιάηαζ ζηα 18219±3705x10 3 m 3 ηαζ 17330±2967x10 3 m 3 βζα ηζξ δφμ πενζυδμοξ ακηίζημζπα, εκημφημζξ δζαθμνέξ παναηδνμφκηαζ ζημ ζοκμθζηυ υβημ εηηνμθήξ ακά μιάδα ζφκεεζδξ ηθςαχκ ηςκ ιμκάδςκ (ANOVA;P<0.05). Οζ δζαθμνέξ εζηζάγμκηαζ ζηδκ αφλδζδ ημο ζοκμθζημφ υβημο εηηνμθήξ ηδξ μιάδαξ 2 ηαζ ιείςζδ ημο υβημο εηηνμθήξ ηςκ μιάδςκ 1, 3 ηαζ 6 (Tukey t-test; P<0.05) (πήια 2). Απυ ηδκ άθθδ, βζα ηδκ Σμονηία βζα ηζξ ακηίζημζπεξ πενζυδμοξ μ ζοκμθζηυξ υβημξ εηηνμθήξ αολάκεζ απυ 9103±1715x10 3 m 3 ζε 15145±3224x10 3 m 3 (t-test; P>0.05), δ μπμία ζοκμδεφεηαζ απυ δζαθμνέξ ζημ ζοκμθζηυ υβημ εηηνμθήξ ακά μιάδα ζφκεεζδξ ηθςαχκ ηςκ ιμκάδςκ (ANOVA;P<0.05). Οζ δζαθμνέξ εζηζάγμκηαζ ζηδκ αφλδζδ ημο ζοκμθζημφ υβημο εηηνμθήξ ηςκ μιάδςκ ζφκεεζδξ ιμκάδμξ 1,5 ηαζ 8 ηαζ ιείςζδ ημο υβημο εηηνμθήξ ηςκ μιάδςκ 4, 6 ηαζ 7 (Tukey t-test; P<0.05) (πήια 2). 206

207 πδήηεζε ημ ζφκμθμ ημοξ μζ ιμκάδεξ ζπεομηαθθζένβεζαξ ζηδκ Δθθάδα είκαζ εβηαηεζηδιέκεξ ζηδκ πανάηηζα γχκδ ηαζ ζοκαενμίγμκηαζ ζε 24 πςνζηέξ μιάδεξ, εκχ μζ ιμκάδεξ ηδξ Σμονηίαξ ζε 5 πςνζηέξ μιάδεξ. Ζ εζηυκα αοηή πένακ ηςκ πζεακχκ αέθηζζηςκ ζοκεδηχκ εηηνμθήξ, είκαζ ηαζ απμηέθεζια αεθηζζημπμίδζδξ ηδξ απυδμζδξ ηςκ επζπεζνήζεςκ, αθμφ ακαιέκεηαζ ιείςζδ θεζημονβζηχκ ελυδςκ ιέζς ηςκ ζοκαενμίζεςκ αθθά ηαζ ηςκ ελυδςκ δζακμιήξ ηαζ πανάθθδθδ ιείςζδ ημο νίζημο ηαηαζηνμθχκ ιε επζθμβή πνμζηαηεουιεκςκ εέζεςκ (Πέηνμο, 2013). Πανυθδ ηδκ ειθακζζδ ιζαξ πμζηζθίαξ ηεπκζηχκ παναηηδνζζηζηχκ ιμκάδςκ δ μπμία δεκ δζαθμνμπμίεζηαζ πςνζηά (Πέηνμο, 2013), αοηή οπμζηδνίγεζ ηαηά ηφνζμ θυβμ ηδκ εηηνμθή ηζζπμφναξ ηαζ θααναηζμφ (FAO, 2014). Δλαίνεζδ απμηεθμφκ μζ ιμκάδεξ ιε ηοηθζημφξ ηθςαμφξ δζαιέηνμο 40-60m (Πίκαηαξ ΗΗ: μιάδα 8) πμο πνδζζιμπμζμφκηαζ ηαηά ηφνζμ θυβμ βζα πάποκζδ ηυκμο (Trujillo et al., 2012). ρήκα 1. Α) Πνζνζηφ ηχπνπ κεηαβνιήο ηερληθψλ ραξαθηεξηζηηθψλ κνλάδαο ηελ πεξίνδν ζε ζρέζε κε ηελ πεξίνδν (C: Όρη κεηαβνιή, CH: αιιαγή νκάδαο ζχλζεζεο θισβψλ, E: δηάιπζε θαη Η: εγθαηάζηαζε κνλάδαο) θαη Β κέζε απφζηαζε ειάρηζηεο απφζηαζεο απφ ηελ αθηή αλά ηχπν κεηαβνιήο ζηελ Διιάδα (GR) θαη Σνπξθία (TR). Οη κπάξεο ππνδειψλνπλ ην δηπιάζην ηνπ ζηαζεξνχ ζθάικαηνο. Οζ ιεηααμθέξ ηεπκζηχκ παναηηδνζζηζηχκ ηςκ ιμκάδςκ ιεηαλφ ηςκ πενζυδςκ ηαζ ζηζξ δφμ πχνεξ πανμοζζάγμοκ δζαθμνμπμίδζδ. ηδκ Δθθάδα βζα ημ ιεβαθφηενμ πμζμζηυ ηςκ ιμκάδςκ δε επεζ επέθεεζ ιεηααμθή ή έπεζ αθθάλεζ μιάδα (ηάζδ πνμξ ηοηθζημφξ ηθςαμφξ δζαιέηνμο 10-20m), πςνίξ αθθαβέξ ζημκ ηεθζηυ δζαεέζζιμ υβημ εηηνμθήξ ηαζ ηδ πςνμεέηδζδ ηςκ ιμκάδςκ ζε ζπέζδ ιε ηδκ αηηή. ηδκ Σμονηία, απυ ηδκ άθθδ, ημ ιεβαθφηενμ πμζμζηυ ηςκ ιεηααμθχκ αθμνά ζε δζάθοζδ ιμκάδμξ ηαζ εβηαηάζηαζδ, ιε αθθαβέξ ηςκ ηεπκζηχκ παναηηδνζζηζηχκ ηςκ ιμκάδςκ (ηάζδ πνμξ ηοηθζημφξ ηθςαμφξ δζαιέηνμο 20-40m), εβηαηάζηαζδ ζε ιεβαθφηενεξ απμζηάζεζξ απμ ηδκ αηηή ηαζ αφλδζδ ημο υβημο εηηνμθήξ (πήια 1 Α,Β). Ζ αθθαβή ζηδκ Σμονηία ελδβείηαζ απυ ηδκ εθανιμβή κμιμεεζίαξ ιε έκανλδ εθανιμβήξ ηα ιέζα ημο 2007, βζα ηδκ πνμζηαζία απυ ηδ νφπακζδ πμο πνμηαθείηαζ απυ ηδκ εηηνμθή ζπεφςκ ζε ηθεζζημφξ ηυθπμοξ, ιε ηδ δναζηδνζυηδηα ηδξ οδαημηαθθζένβεζαξ κα εεςνείηαζ πανάβμκηαξ εοηνμθζζιμφ ηαζ κα εθέβπεηαζ απυ ηδκ ημονηζηή κμιμεεζία (Yücel Gier et al., 2009). φιθςκα ιε αοηήκ εάκ μζ ιμκάδεξ εηηνμθήξ ανίζημκηαζ ήδδ ζε πενζμπέξ ορδθήξ επζηζκδοκυηδηαξ, εα πνέπεζ κα ακαζηέθθμοκ ηδ θεζημονβία ημοξ εκηυξ εκυξ έημοξ ηαζ δεκ εα επζηνέπεηαζ ηαιία κέα εβηαηάζηαζδ εαθάζζζαξ οδαημηαθθζένβεζαξ, ζηδκ πενζμπή αοηή, μδδβχκηαξ έηζζ, είηε ζε δζάθοζδ είηε ζε ιεηεβηαηάζηαζδ ημοξ ζε απμζηάζεζξ ιεβαθφηενεξ ημο 1km απυ ηδκ αηηή. Απυ δζαεέζζια ζημζπεία (FAO, 2014) βζα ηζξ δφμ παναπάκς πενζυδμοξ ζηδκ Δθθάδα δ παναβςβή έπεζ αολδεεί ηαηά 42% ηαζ ζηδκ Σμονηία βζα ηδκ ίδζα πενίμδμ ηαηά 82%. Οζ παναπάκς 207

208 ιεηααμθέξ ζηα ηεπκζηά παναηηδνζζηζηά ζοκμδεφμκηαζ απυ αφλδζδ ημο δζαεέζζιμο υβημο εηηνμθήξ ζηδκ Σμονηία ηαηά 66% (ζπήια 2) βεβμκυξ πμο δζηαζμθμβεί ηδκ αολδζδ ηδξ παναβςβήξ δ μπμία ηαηαβνάθεηαζ ηζξ ακηίζημζπεξ πενζυδμοξ. Γζα ηδκ Δθθάδα, παναηδνείηαζ ιζα ακακηζζημζπία ηςκ ιεηααμθχκ ηςκ δφμ πενζυδςκ ζηα ηεπκζηά παναηηδνζζηζηά ηςκ ιμκάδςκ ηαζ ημ δζαεέζζιμ υβημ εηηνμθήξ (μ μπμίμξ δεκ πανμοζζάγεζ ιεηααμθέξ) ιε ηδκ αφλδζδ ηαηά 42% ηδξ παναβςβήξ. Ζ ακακηζζημζπία αοηή ηαηά έκα ιένμξ ηδξ ιπμνεί κα αθμνά ζημ θάεμξ εηηίιδζδξ ημο δζαεέζζιμο υβημο εηηνμθήξ ημ μπμίμ ακενπεηαζ ζημ 20% ηδξ ιέζδξ ηζιήξ. Απυ ηδκ άθθδ, εκδεπυιεκμ απμηεθεί επίζδξ ημ βεβμκυξ υηζ ηα ζημζπεία παναβςβήξ ημο FAO βζα ηδκ πνχηδ πενίμδμ ( ) κα βίκμκηακ ααζδ ηδξ ζοκμθζηήξ δοκαιζηυηδηαξ ηςκ ιμκάδςκ υπςξ αοηή ηαηαβνάθεηαζ ζηδκ άδεζα θεζημονβίαξ ηαζ υπζ ηδξ πναβιαηζηήξ (πνμζςπζηή επζημζκςκία ιε οδαημηαθθζενβδηέξ). ρήκα 2. Όγθνο εθηξνθήο ζηηο πεξηφδνπο θαη αλά νκάδα ζχλζεζεο θισβψλ κνλάδνο θαη ζχλνιν ζηελ Διιάδα (GR) θαη Σνπξθία (TR). Οη κπάξεο ππνδειψλνπλ ην δηπιάζην ηνπ ζηαζεξνχ ζθάικαηνο, θαη ηα βέιε ηηο νκάδεο φπνπ παξαηεξείηαη ζηαηηζηηθή δηαθνξά. Σέθμξ, δεκ πνέπεζ κα αβκμδεεί ημ βεβμκυξ υηζ ηα δζαεέζζια ζημζπεία βζα ηδκ Δθθάδα πμο πνδζζιμπμζμφκηαζ βζα ηδ ιεθέηδ ηςκ ιεηααμθχκ, αθμνμφκ ηονίςξ ζηζξ πενζμπέξ ηδξ αβζάδαξ ηαζ ηδξ Κεθαθμκζάξ (ζημζπεία δεκ θαίκμκηαζ ζηδκ πανμφζα), ηαζ ζοκεπχξ δεκ εκζςιαηχκμοκ ηζξ ιεβάθεξ ζπεομηαθθζενβδηζηέξ ζοκαενμίζεζξ ιμκάδςκ ηδξ Δθθάδαξ (Δοαμζημφ, Δπζκάδςκ κήζςκ, Ανβμθζημφ ηαζ ανςκζημφ ηυθπμο) (Πέηνμο, 2013), πνμαάθθμκηαξ ημ εκδεπυιεκμ μζ παναπάκς ιεηααμθέξ κα δζέπμκηαζ απυ πςνζημφξ πενζμνζζιμφξ. Βιβλιογραφία Πζτρου Χ. (2013). Μελζτθ τθσ χωρικισ κατανομισ και τεχνικά χαρακτθριςτικά των μονάδων τθσ Μεςογειακισ ιχκυοκαλλιζργειασ μζςω διακζςιμων δορυφορικϊν απεικονίςεων του λογιςμικοφ Google earth TM. Μεταπτυχιακι εργαςία, Παν/μιο Θεςςαλίασ, ςελ 81. Clarke P., Jennifer A.,Melendez R., Bader M., Morenoff J. (2010). Using Google Earth to conduct a neighborhood audit:reliability of a virtual audit instrument. Health & Place 16, Dempster, T., Sanchez-Jerez, P., Bayle-Sempere, J. T., Gimenez- Casalduero, F., Valle, C. (2002). Attraction of wild fish to sea-cage fish farms in the south-western Mediterranean Sea: spatial and short-term temporal variability. Mar. Ecol. Prog. Ser. 242, Dimitriou, E., Katselis, G., Moutopoulos, D., Akovitiotis C., Koutsikopoulos C. (2007). Possible influence of reared gilthead sea bream (Sparus aurata, L.) on wild stocks in the area of the Messolonghi lagoon (Ionian Sea, Greece). Aquaculture Research38,

209 FAO (2014).Food and Agriculture Organization of the United Nations (Πνυζααζδ:20/7/2014)., update 6/7/2014 Kalantzi I., Karakassis I.(2006). Benthic impacts of fish farming: Meta-analysis of community and geochemical data. Marine Pollution Bulletin 52, Taylor B. T., Fernando P., Bauman A. E., Williamson A., Craig J. C., Redman S. (2011). Measuring the Quality of Public Open Space Using Google earth. American Journal of Preventive Medicine40(2), Theodorou, J A., (2002).Current and Future Technological Trends of European Seabass-Seabream culture.rev. in Fisheries Science, 10(3&4), Trujillo P., Piroddi C, Jacquet J. (2012).Fish Farms at Sea: The Ground Truth from Google Earth. PLoS ONE 7(2): e doi: /journal.pone Yücel-Gier G.Uslu O.,Kucuksezgin F.,(2009). Regulating and monitoring marine finfish aquaculture in Turkey. Journal of Applied Ichthyology 25,

210 SEASONALITY HAS AN IMPACT ON HEAVY METAL CONCENTRATION IN PAGASITIKOS GULF FISH SPECIMENS Giannakopoulou L. 1 *, Neofitou C. 1, Aifanti S. 1 1 Laboratory of Ichthyology Hydrobiology, Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Fytoko Street, Nea Ionia Magnesia 38446, Greece ABSTRACT Pagasitikos Gulf is located in central Greece and it is a sensitive marine ecosystem, which is inevitably exposed to pollution due to its proximity to the city of Volos and its use as a port and industrial area. The aim of this study was to examine the concentration levels of metals in the body tissue of two fish species and to determine whether metal concentration levels could be affected by season. Heavy metals concentrations were measured for a benthic (Mullus barbatus) and a benthopelagic fish species (Pagellus erythrinus). Both species are commercial and therefore, heavy metal examination on their bodies is important for human consumption. Fish samples were collected monthly from September 2009 until August Chromium (Cr), Copper (Cu) and Zinc (Zn) concentrations were measured. Cadmium (Cd) concentration was determined in muscle samples for the risk analysis assessment. The maximum safe consumption (MSC) was also calculated daily, depending on mean concentrations of Cr, Cu, Zn and Cd in the muscle of both species (39 samples). The results of this study demonstrated significant differences for both Cu and Zn concentrations in M. barbatus. Seasonality showed also statistical significance for all metal concentrations in P. erythrinus tissues (Kruskal-Wallis, df=3; P<0.05). Highest heavy metal concentrations were recorded in M. barbatus samples for both autumn and winter measurements, while P. erythrinus highest heavy metal concentrations were noted in spring. Both species showed lowest metal concentrations in summer.the risk analysis showed no danger for human consumption. Keywords: Pagasitikos Gulf, Mullus barbatus, Pagellus erythinus, seasonality, metals. *Corresponding author: Loukia Giannakopoulou (logianna@apae.uth.gr) 1 ΔΠΗΓΡΑΖ ΣΖ ΔΠΟΥΗΚΟΣΖΣΑ ΣΗ ΤΓΚΔΝΣΡΧΔΗ ΣΧΝ ΒΑΡΔΧΝ ΜΔΣΑΛΛΧΝ Δ ΓΤΟ ΔΗΓΖ ΗΥΘΤΧΝ ΣΟΤ ΠΑΓΑΖΣΗΚΟΤ ΚΟΛΠΟΤ Γζακκαημπμφθμο Λ. 1 *, Νεμθφημο Υ. 1, Ατθακηή. 1 Δνβαζηήνζμ Ηπεομθμβίαξ ηαζ Τδνμαζμθμβίαξ, Σιήια Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ, πμθή Γεςπμκζηχκ Δπζζηδιχκ, Πακεπζζηήιζμ Θεζζαθίαξ, Οδυξ Φοηυημο, Σ.Κ , Νέα Ηςκία Μαβκδζίαξ, Δθθάδα Πεξίιεςε Ο Παβαζδηζηυξ Κυθπμξ ανίζηεηαζ ζηδκ ηεκηνζηή Δθθάδα ηαζ είκαζ έκα εοαίζεδημ μζημζφζηδια πμο ακαπυθεοηηα εηηίεεηαζ ζηδ νφπακζδ ελαζηίαξ ηδξ εββφηδηαξ ιε ηδκ πυθδ ημο Βυθμο ηαζ ηδ πνήζδ ηδξ ςξ θζιάκζ, αθθά ηαζ ηδξ αζμιδπακζηήξ πενζμπήξ ημο. ημπυξ ηδξ πανμφζαξ ενβαζίαξ ήηακ κα ζοζπεηζζεεί δ επμπζηυηδηα ιε ηζξ ζοβηεκηνχζεζξ ηςκ αανέςκ ιεηάθθςκ ζε έκα αεκεζηυ (Mullus barbatus), ηαζ ζε έκα αεκεμπεθαβζηυ είδμξ (Pagellus erythrinus). Δίκαζ δφμ ειπμνζηά είδδ, επμιέκςξ, είδδ ορδθήξ επζηζκδοκυηδηαξ βζα ημκ άκενςπμ. Σα δείβιαηα ζοθθέπεδηακ ζε ιδκζαία αάζδ απυ ημ επηέιανζμ ημο 2009 ιέπνζ ηαζ ημκ Αφβμοζημ ημο 2010, ηαθφπημκηαξ έκα πθήνεξ διενμθμβζαηυ έημξ. Οζ ζοβηεκηνχζεζξ ημο πνςιίμο (Cr), ημο παθημφ (Cu) ηαζ ημο ρεοδανβφνμο (Zn) ιεηνήεδηακ ζε έκα ζφκμθμ 159 δεζβιάηςκ. Ζ ιέβζζηδ αζθαθήξ διενήζζα ηαηακάθςζδ οπμθμβίζηδηε ζε 39 δείβιαηα ιουξ. Οζ ζοβηεκηνχζεζξ ημο ηαδιίμο (Cd) ακζπκεφεδηακ ζηα δείβιαηα ιουξ βζα κα πνδζζιμπμζδεμφκ ζηδκ ακάθοζδ ηζκδφκμο. Ζ ζηαηζζηζηή επελενβαζία έδεζλε υηζ μζ ζοβηεκηνχζεζξ ημο Cu ηαζ ημο Zn επδνεάγμκηαζ άιεζα απυ ηδκ επμπή, υζμκ αθμνά ηδκ ημοηζμιμφνα, εκχ δ επμπή είκαζ ζδιακηζηή βζα υθεξ ηζξ ζοβηεκηνχζεζξ ηςκ αανέςκ ιεηάθθςκ ζημ θοενίκζ (Kruskal-Wallis, df=3, P<0,05). Αολδιέκεξ ζοβηεκηνχζεζξ παναηδνήεδηακ ημ θεζκυπςνμ ηαζ ημ πεζιχκα ζηδκ ημοηζμιμφνα, εκχ ηδκ άκμζλδ ήηακ αολδιέκεξ μζ ζοβηεκηνχζεζξ ζημ θοενίκζ. Υαιδθυηενεξ ήηακ μζ ζοβηεκηνχζεζξ ημο ηαθμηαζνζμφ ηαζ ζηα δφμ είδδ. Ζ ηαηακάθςζδ ζπεφςκ απμδείπεδηε αζθαθήξ βζα ημκ άκενςπμ. Λέξειρ κλειδιά: Παγαζεηηθόο θόιπνο, Mullus barbatus, Pagellus erythrinus, επνρηθόηεηα, κέηαιια. 210

211 *οββναθέαξ επζημζκςκίαξ: Λμοηία Γζακκαημπμφθμο 1. Δηζαγσγή Ζ πανμοζία ηςκ αανέςκ ιεηάθθςκ ζηα οδάηζκα μζημζοζηήιαηα ηνίκεηαζ ζδζαζηένςξ ζδιακηζηή, ελαζηίαξ ηδξ ιεβάθδξ δζεζζδοηζηήξ ημοξ ζηακυηδηαξ, αθθά ηαζ ημο βεβμκυημξ υηζ ιπμνμφκ κα ζοζζςνεφμκηαζ ζηδκ ηνμθζηή αθοζίδα (Erdogrul & Erbilir 2007). Καηακαθχκμοκ πθδεχνα ηνμθζηχκ ακηζηεζιέκςκ, ιε απμηέθεζια ηδ ιεβαθφηενδ ζοζζχνεοζδ ιεηάθθςκ ζημκ μνβακζζιυ ημοξ, ζε ζοκδοαζιυ πάκηα ιε ημοξ ιδπακζζιμφξ ζοζζχνεοζδξ πμο θένμοκ μζ ίδζμζ μζ μνβακζζιμί. Δπμιέκςξ απμηεθμφκ ημοξ ηαηαθθδθυηενμοξ μνβακζζιμφξ βζα ηδκ ελαβςβή ζοιπεναζιάηςκ ηδξ ηαηάζηαζδξ εκυξ εαθάζζζμο μζημζοζηήιαημξ (Alibalic et al. 2007). Σα αανέα ιέηαθθα εζζνέμοκ ζημοξ ζπεείξ ιέζς ημο επζεδθίμο ηςκ αναβπίςκ, ημο δένιαημξ, αθθά ηαζ ιέζς ημο πεπηζημφ ζοζηήιαημξ ηαηά ηδκ ηαηάπμζδ ηδξ ηνμθήξ (Bordajandi et al. 2003). Ζ ημλζηυηδηα ηςκ ιεηάθθςκ πμζηίθθεζ απυ επζδνάζεζξ ζημοξ ζπεείξ ηυζμ ζηδκ ακαπαναβςβή ηαζ ηδκ ακάπηολδ (Bervoets & Blust 2003), υζμ ηαζ ζηδ εκδζζιυηδηά ημοξ, αηυιδ ιέπνζ ηαζ ηδκ μθζηή απχθεζα ηάπμζςκ πθδεοζιχκ (Greig et al. 2010). Ο έθεβπμξ ηςκ ζοβηεκηνχζεχκ ημοξ έπεζ άιεζδ ζπέζδ ιε ηδ δδιυζζα οβεία, βζαηί ηα αανέα ιέηαθθα έπμοκ ηδκ ζηακυηδηα κα πνμηαθμφκ ιμνθμθμβζηέξ δοζιμνθίεξ, κεονμθοζζμθμβζηέξ δζαηαναπέξ, ηεναημβεκέζεζξ ηαζ ηανηζκμβεκέζεζξ (Idris et al. 2007). 2. Τιηθά θαη Μέζνδνη Ο Παβαζδηζηυξ Κυθπμξ είκαζ έκα εοαίζεδημ μζημζφζηδια. Ζ αζμιδπακζηή γχκδ ημο Βυθμο πενζθαιαάκεζ ενβμζηάζζα επελενβαζίαξ ιεηάθθμο, δναζηδνζυηδηεξ πμο ζπεηίγμκηαζ ιε ηδκ παναβςβή ηνμθίιςκ ηαζ ηδ ζοζηεοαζία ημοξ, αθθά ηαζ ιμκάδεξ επελενβαζίαξ λφθμο, υπςξ επίζδξ ηαζ ιζα ιμκάδα επελενβαζίαξ ηζζιέκημο ζηα ακαημθζηά ημο Κυθπμο (Tsangaris et al. 2013). Σα δείβιαηα ζοθθέβμκηακ ζε ιδκζαία αάζδ, ζημ ιέζμ πενίπμο ηάεε ιήκα, απυ ημ επηέιανζμ ημο 2009 ιέπνζ ηαζ ημκ Αφβμοζημ ημο 2010, ηαθφπημκηαξ έκα πθήνεξ διενμθμβζαηυ έημξ. Ζ ζοθθμβή ηςκ ζπεφςκ έβζκε ιε ηδ αμήεεζα επαββεθιαηία ρανά. Έπεζηα απυ ηδκ ακαημιία, δ ακίπκεοζδ ηςκ ιεηάθθςκ πναβιαημπμζήεδηε ζε 85 άημια M. barbatus (17,6-243,40 g) ηαζ 74 άημια P. erythrinus (18,59-221,70g), αθθά ηαζ 39 δείβιαηα ιουξ. Ζ Μέβζζηδ Αζθαθήξ Καηακάθςζδ (ΜΑΚ) οπμθμβίζηδηε ζε 21 δείβιαηα ιουξ M. barbatus (24,450 g 85,85 g) ηαζ 18 δείβιαηα P. erythrinus (23,42 g 195,54 g). Σα δείβιαηα πςκεφεδηακ ζε ζφζηδια οβνήξ πχκεοζδξ (Microwave 3000, Anton Paar, Austria). Γζα ηδ πχκεοζδ ηςκ δεζβιάηςκ πνδζζιμπμζήεδηε ημ πνςηυημθθμ EPA 3052 (ηοπμπμζδιέκδ δζαδζηαζία ζφιθςκα ιε ηδκ Αιενζηακζηή Τπδνεζία Πνμζηαζίαξ Πενζαάθθμκημξ US Environmental Protection Agency). Γζα ηδ πχκεοζδ, 0,5g ημκζμπμζδιέκμο δείβιαημξ πςκεφεδηακ ιε 3 ml οδνμθεμνζημφ μλέμξ (HF 39,5%, Carlo Erba) ηαζ 9 ml κζηνζημφ μλέμξ ακαθοηζημφ ααειμφ (ΖΝΟ 3 65%, Carlo Erba). Αημθμφεδζε πθήνςζδ ιε δζζαπεζηαβιέκμ κενυ (18Χ) ιέπνζ ηα 50 ml ηαζ θζθηνάνζζια ηςκ δεζβιάηςκ (θίθηνμ ζφνζββαξ, πυνμξ ιειανάκδξ 0,45 ιm, TPP). Ζ Φαζιαημιεηνία Αημιζηήξ Απμννυθδζδξ (Perkin Elmer, Aanalyst 400 Atomic Absorption Spectrometer, USA) πνδζζιμπμζήεδηε βζα ηδκ ακίπκεοζδ ηςκ ζοβηεκηνχζεςκ ηςκ ιεηάθθςκ. Ο ρεοδάνβονμξ (Zn) ιεηνήεδηε ιε ηδκ ηεπκζηή ηδξ θθυβαξ (FAAS Flame Atomic Absorption Spectrometry), ηαζ ηδ πνήζδ ζοκδοαζιμφ αηεηοθεκίμο ιε αένα, εκχ μζ ζοβηεκηνχζεζξ ημο παθημφ (Cu), ημο πνςιίμο (Cr) ηαζ ημο ηαδιίμο (Cd) ιεηνήεδηακ ιε ηδκ ηεπκζηή ημο θμφνκμο βναθίηδ (GFAAS Graphite Furnace Atomic Absorption Spectrometry, HGA 900 ελμπθζζιέκμ ιε αοηυιαημ ζοθθμβέα δεζβιάηςκ Auto sampler 800). Γζα ηδκ απμθοβή επζιμθφκζεςκ, υθα ηα δείβιαηα πμο ιεηνήεδηακ ζημ θμφνκμ βναθίηδ αναζχεδηακ πνζκ ηδκ ακάθοζδ. θεξ μζ αναζχζεζξ θήθεδηακ οπυρδ ζημκ ηεθζηυ οπμθμβζζιυ ηςκ ζοβηεκηνχζεςκ ηςκ δεζβιάηςκ. Σα πνυηοπα δζαθφιαηα δδιζμονβήεδηακ ιε ηδ πνήζδ ειπμνζηχκ οθζηχκ (STD AS WASTE WTR POLL 15 METAL). Γζα ηδκ ηεπκζηή ημο θμφνκμο βναθίηδ, πνδζζιμπμζήεδηε ημ ελαέκοδνμ κζηνζηυ ιαβκήζζμ (5 ιl) ςξ ηνμπμπμζδηήξ [(Mg (NO 3 ) 2 ) 6H 2 O], βζα ηδκ ακίπκεοζδ ημο Cr ηαζ ημο Cu, αθθά ηαζ μ ζοκδοαζιυξ παθθάδζμο ηαζ ελαέκοδνμο κζηνζημφ ιαβκδζίμο [Pd + Mg (NO 3 ) 2 6H 2 O] βζα ηδκ ακίπκεοζδ ημο Cd. Σμ υνζμ ακίπκεοζδξ (detection limit) βζα ημ Cd ήηακ 0,04 ιg/l. Γζα ηδ δζυνεςζδ ηςκ εμνφαςκ, ηαηά ηδ πνήζδ ηδξ ηεπκζηήξ ημο θμφνκμο βναθίηδ, πνδζζιμπμζήεδηε θάιπα δεοηενίμο (deuterium background corrector). Ζ αηνίαεζα ηδξ ιεευδμο εθέβπεδηε ιε ηδκ πνμεημζιαζία ηαζ ηδκ ακάθοζδ εκυξ πνμηφπμο δζαθφιαημξ βκςζηήξ ζοβηέκηνςζδξ (2 ppb) ηαζ ηνίεδηε ζηακμπμζδηζηή (ακάηηδζδ: 85,8 % ± 3,6%). Μζα αηυιδ ιέεμδμξ πμο αημθμοεήεδηε βζα ηδκ πζζημπμίδζδ ηδξ αηνίαεζαξ ηδξ ιεευδμο ήηακ δ πνήζδ «φπμπηςκ» δεζβιάηςκ» (spiked samples), δδθαδή δεζβιάηςκ πμο επζιμθφκεδηακ ιε βκςζηή ζοβηέκηνςζδ ακαθοηζημφ οθζημφ (ακάηηδζδ: 95,4 ± 4,6%). 211

212 Ζ ζηαηζζηζηή ακάθοζδ πναβιαημπμζήεδηε ιε ημ SPSS 17.0 (IBM, USA). Ο έθεβπμξ ηδξ ηακμκζηυηδηαξ έβζκε ιε ημ Kolmogorov Smirnoff Test ηαζ ημ Shapiro Wilk Test. ηακ δ ηαηακμιή ηςκ ζοβηεκηνχζεςκ ηςκ ιεηάθθςκ πμο εθέβπμκηακ ήηακ ιδ ηακμκζηή, ηυηε εθανιυγμκηακ ιδ παναιεηνζηέξ ζηαηζζηζηέξ ακαθφζεζξ πνμηεζιέκμο κα ανεεμφκ μζ ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ ακάιεζα ζηα είδδ, ζε ζπέζδ ιε ηδκ επμπή ηδξ δεζβιαημθδρίαξ πνδζζιμπμζχκηαξ ακάθοζδ δζαηφιακζδξ ηαηά έκα πανάβμκηα (Kruskal-Wallis test ή Mann-Whitney test ). Γζα ημκ οπμθμβζζιυ ηδξ Μέβζζηδξ Αζθαθμφξ Καηακάθςζδξ πνδζζιμπμζήεδηε δ οπυεεζδ (Metian et al. 2013): MSCA = (W ind *JL A )/X A. Σμ MSCA είκαζ δ Μέβζζηδ Αζθαθήξ Καηακάθςζδ ζφιθςκα ιε ηδκ Κμζκή Δπζηνμπή Διπεζνμβκςιυκςκ πενί Πνμζεέηςκ ηςκ Σνμθίιςκ - JECFA (ζε mg/kg wet wt). Σμ X A είκαζ δ ιέζδ ηζιή ηδξ ζοβηέκηνςζδξ ημο εηάζημηε ελεηαγυιεκμο ιεηάθθμο. Σμ Wind είκαζ ημ ακενχπζκμ ζςιαηζηυ αάνμξ (60 Kg βα ηδ βοκαίηα ηαζ 80 Kg βζα ημκ άκηνα), εκχ ημ JL A ακηζπνμζςπεφεζ είηε ημ Πνμζςνζκυ Μέβζζημ Ακεηηυ νζμ Ζιενήζζαξ Πνυζθδρδξ είηε ημ Πνμζςνζκυ Μέβζζημ Ακεηηυ νζμ Δαδμιαδζαίαξ Πνυζθδρδξ. Σα απμηεθέζιαηα ηδξ Μέβζζηδξ Αζθαθμφξ Καηακάθςζδξ (MSCA) δίκμοκ ηδ ιέβζζηδ πμζυηδηα ζπεφμξ (ζε g) πμο επζηνέπεηαζ βζα ακενχπζκδ ηαηακάθςζδ ακά διένα ή ακά αδμιάδα. Ζ ζοκζζηχιεκδ πμζυηδηα απυ ηδ JECFA (WHO 2003) βζα ηάεε ιμθφκμκ οθζηυ θήθεδηε οπυρδ. Οζ ιέζεξ ηζιέξ ηςκ ζοβηεκηνχζεςκ ηςκ ιεηάθθςκ πνδζζιμπμζήεδηακ αθυημο ιεηαζπδιαηίζεδηακ ζε οβνυ αάνμξ, θαιαάκμκηαξ οπυρδ ημ πμζμζηυ οβναζίαξ ηςκ δεζβιάηςκ ιουξ βζα ηδ ιεηαηνμπή. 3. Απνηειέζκαηα Ζ επμπζηυηδηα ηνίκεηαζ ςξ έκαξ απυ ημοξ πζμ ζδιακηζημφξ πανάβμκηεξ βζα ηδ ζοβηέκηνςζδ ηςκ αανέςκ ιεηάθθςκ. Ζ ζηαηζζηζηή επελενβαζία απέδεζλε υηζ μζ ζοβηεκηνχζεζξ ημο Cu ηαζ ημο Zn επδνεάγμκηαζ άιεζα απυ ηδκ επμπή, υζμκ αθμνά ηα άημια ηδξ ημοηζμιμφναξ (Kruskal-Wallis, df=3, P<0,05), εκχ, βζα ηα άημια ημο P. erythrinus, δ επμπζηυηδηα ηνίεδηε ζδιακηζηή βζα υθεξ ηζξ ζοβηεκηνχζεζξ υθςκ ηςκ ιεηάθθςκ (Kruskal-Wallis, df=3, P<0,05). Δζδζηυηενα, ζηαηζζηζηχξ ζδιακηζηέξ δζαθμνέξ πανμοζζάζηδηακ ακάιεζα ζηζξ ηζιέξ ημο θεζκμπχνμο ηαζ ημο πεζιχκα (π. 1) ζημ M. barbatus (Mann-Whitney test, P<0,05). Διθακχξ, μζ ιεβαθφηενεξ ζοβηεκηνχζεζξ πανμοζζάζηδηακ ηαηά ηδ δζάνηεζα ημο πεζιχκα ηαζ εζδζηά ημ ιήκα Γεηέιανζμ. Οζ ηζιέξ ημο Γεηειανίμο ήηακ ανηεηά ορδθυηενεξ ζε ζπέζδ ιε ηζξ ζοβηεκηνχζεζξ ημο Οηηςανίμο ηαζ ημο Νμειανίμο. Υαιδθυηενεξ ήηακ μζ ηζιέξ ημοξ ιήκεξ Ηακμοάνζμ ηαζ Φεανμοάνζμ. ζμκ αθμνά ηζξ ζοβηεκηνχζεζξ ημο Cr ζηα άημια ημο είδμοξ P. erythrinus, απμδείπεδηε υηζ μζ ζοβηεκηνχζεζξ πμο ειθάκζζε ημ είδμξ (π. 1) είκαζ ζηαηζζηζηά ζδιακηζηέξ (Kruskal Wallis, P<0,05) ακάιεζα ζηδκ πενίμδμ ηδξ άκμζλδξ ηαζ ηζξ οπυθμζπεξ πενζμπέξ. Δπζπνυζεεηα, μζ δζαθμνμπμζήζεζξ πμο ειθακίζηδηακ ζηζξ ηζιέξ ημο Cr ημο είδμοξ ειθακίζηδηακ ακάιεζα ζε ιήκεξ (π. 1) δζαθμνεηζηχκ επμπχκ (Mann-Whitney test, P<0,05). Οζ δζαθμνέξ εζηζάζηδηακ ηαηά ηφνζμ θυβμ ακάιεζα ζημοξ θεζκμπςνζκμφξ ηαζ πεζιενζκμφξ ιήκεξ ζε ζοκάνηδζδ ιε ηζξ ηζιέξ πμο επέδεζλε ημ είδμξ ηαηά ηδ δζάνηεζα ηςκ ακμζλζάηζηςκ ιδκχκ. Σμ πεζιχκα ειθακίζηδηακ μζ παιδθυηενεξ ζοβηεκηνχζεζξ ηαζ ζοβηεηνζιέκα ημ Γεηέιανζμ ιε ορδθυηενεξ ηζιέξ ημκ ιήκα Απνίθζμ (π. 1). ρήκα 2. πγθεληξψζεηο Cr (mg/kg μεξνχ βάξνπο) αλά είδνο θαη δεηγκαηνιεςία. Οζ ζοβηεκηνχζεζξ ημο Cu βζα ημ είδμξ M. barbatus (π. 2), πανμοζίαζακ ηζξ ορδθυηενεξ ηζιέξ ημοξ ημ πεζιχκα ηαζ ηδκ άκμζλδ, μζ μπμίεξ ηοιάκεδηακ πενίπμο ζηα ίδζα επίπεδα. Οζ ζοβηεκηνχζεζξ ημο Cu ζημ είδμξ M. barbatus (π. 2), πανμοζίαζακ ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ 212

213 ακάιεζα ζηζξ ηζιέξ ημο ηαθμηαζνζμφ ηαζ ηςκ οπμθμίπςκ επμπχκ (Mann-Whitney test, P<0,05). ηαηζζηζηά ζδιακηζηέξ δζαθμνέξ ιέζα ζημ θεζκυπςνμ πανμοζζάζηδηακ ακάιεζα ζημκ Οηηχανδ ηαζ ημ Νμέιανδ, εκχ ιέζα ζημ πεζιχκα ακάιεζα ζημ Γεηέιανδ ηαζ ημκ Ηακμοάνζμ ή ημ Φεανμοάνζμ (Mann-Whitney test, P<0,05). Δκηυξ ημο ηαθμηαζνζμφ, ζδιακηζηέξ δζαθμνέξ πανμοζζάζηδηακ ζηζξ ηζιέξ ηςκ ζοβηεκηνχζεςκ ζημοξ ιήκεξ Ημφκζμ ηαζ Ημφθζμ (π. 2). Οζ ζοβηεκηνχζεζξ ημο Cu βζα ημ είδμξ P. erythrinus (π. 2), πανμοζίαζακ ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ ακάιεζα ζηζξ ηζιέξ ημο ηαθμηαζνζμφ ηαζ ζηζξ ηζιέξ ηςκ οπμθμίπςκ επμπχκ (Mann-Whitney test, P<0,05). Τπήνλε ιζα ακμδζηή ηάζδ ηςκ ηζιχκ ιέπνζ ηδκ άκμζλδ ηαζ ιζα απυημιδ πηχζδ ημοξ ημ ηαθμηαίνζ. Οζ ζοβηεκηνχζεζξ ημο Cu ημο Μαΐμο, ημο Ημοκίμο ηαζ ημο Ημοθίμο, είκαζ μζ ζοβηεκηνχζεζξ πμο πανμοζίαζακ ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ (Mann-Whitney test, P<0,05) ζοβηνίκμκηαξ ηζξ ηζιέξ ημοξ ιε ζοβηεκηνχζεζξ άθθςκ ιδκχκ (π. 2). Μέζα ζηδκ ίδζα επμπή, δζαθμνέξ ειθάκζζακ μζ ζοβηεκηνχζεζξ ημο Μανηίμο ηαζ ημο Απνζθίμο, ιε ηζξ ζοβηεκηνχζεζξ ημο Μαΐμο, πμο πανμοζίαζακ ιζα απυημιδ πηχζδ ηςκ επζπέδςκ ημοξ. Πανάθθδθα, ζδιακηζηέξ δζαθμνέξ ακζπκεφεδηακ ακάιεζα ζε ιήκεξ ηδξ ίδζαξ επμπήξ ηαζ ζηζξ ζοβηεκηνχζεζξ ημο Zn (π. 3) ημο M. barbatus. Δζδζηυηενα, ηδκ πενίμδμ Οηηςανίμο-Νμειανίμο, αθθά ηαζ ακάιεζα ζηζξ ζοβηεκηνχζεζξ ημο Ημοθίμο ιε ηζξ ζοβηεκηνχζεζξ Ημοκίμο ηαζ Αοβμφζημο (Mann-Whitney test, P<0,05). ρήκα 3. πγθεληξψζεηο Cu (mg/kg μεξνχ βάξνπο) αλά είδνο, επνρή θαη δεηγκαηνιεςία. Οζ ζοβηεκηνχζεζξ ημο Zn ήηακ αολδιέκεξ ημ θεζκυπςνμ ηαζ ζηα δφμ είδδ. Οζ ζοβηεκηνχζεζξ ημο M. barbatus ειθάκζζακ ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ ακάιεζα ζηζξ ζοβηεκηνχζεζξ ημο είδμοξ ηαηά ηδκ πενίμδμ ημο ηαθμηαζνζμφ (π. 3), ζε ζπέζδ ιε ηζξ ζοβηεκηνχζεζξ πμο ακζπκεφεδηακ ημ θεζκυπςνμ, ημ πεζιχκα ηαζ ηδκ άκμζλδ (Mann-Whitney test, P<0,05). Γζα ημ θοενίκζ, παιδθυηενεξ ήηακ μζ ηζιέξ ημο ηαθμηαζνζμφ (π. 3). διακηζηέξ δζαθμνέξ ειθάκζζακ μζ ζοβηεκηνχζεζξ ημο P. erythrinus ηςκ ιδκχκ Ηακμοανίμο, Μανηίμο, Απνζθίμο, ιε ηζξ ζοβηεκηνχζεζξ ημο Zn ηαηά ημοξ ιήκεξ Μάζμ, Ημφκζμ ηαζ Ημφθζμ (Mann Whitney test, P<0,05). ρήκα 3. πγθεληξψζεηο Zn (mg/kg μεξνχ βάξνπο) αλά είδνο, επνρή θαη δεηγκαηνιεςία. 213

214 Ζ Μέβζζηδ Αζθαθήξ Ζιενήζζα Καηακάθςζδ ημο είδμοξ M. barbatus (εδχδζιμ ιένμξ) ήηακ άκς ηςκ 150 g βζα ηζξ βοκαίηεξ (ΜΑΖΚ, ζε g οβνμφ αάνμοξ επί ηαεδιενζκήξ), ηαζ δεκ οπενέααζκε ηα 200 g βζα ημοξ άκηνεξ (Cr: 12515g, Cu: 10496, Zn: 1771g, Cd: 155g ζηζξ βοκαίηεξ ηαζ Cr: 16686g, Cu: 13994, Zn: 2362g, Cd: 207g ζημοξ άκηνεξ). Δπζπνυζεεηα, δ ΜΑΖΚ βζα ηα ανχζζια ιένδ ημο P. erythrinus οπενααίκεζ ηα 160g βζα ηζξ βοκαίηεξ ηαζ ηα 220g βζα ημοξ άκηνεξ (Cr: 9799g, Cu: 13900, Zn: 3810g, Cd: 166g ζηζξ βοκαίηεξ ηαζ, Cr: 13065g, Cu: 18533, Zn: 5079g, Cd: 221g ζημοξ άκηνεξ). 4. πδήηεζε Ζ πανμφζα ενβαζία δζενεφκδζε εάκ ηνία ιέηαθθα δείπκμοκ πανυιμζα ηάζδ ζοζζχνεοζδξ ακά επμπή αθθά ηαζ ηζξ δζαθμνμπμζήζεζξ πμο ιπμνεί κα οπάνπμοκ ιέζα ζηδκ ίδζα επμπή, ζε δφμ είδδ ιε δζαθμνεηζηέξ ζοκήεεζεξ ζηδκ πενζμπή ημο Παβαζδηζημφ Κυθπμο. Σα δεδμιέκα απμδεζηκφμοκ υηζ δ δεζβιαημθδρία ήηακ ζδιακηζηή βζα ηδ δζακμιή ηςκ ιεηάθθςκ ζηα δζαθμνεηζηά είδδ. Αοηυ ζοιααίκεζ ελαζηίαξ ηςκ δζαθμνμπμζήζεςκ πμο οπάνπμοκ ακάιεζα ζημκ ηφηθμ ακάπηολδξ ηςκ εζδχκ ή ηςκ ακαπαναβςβζηχκ ηφηθςκ, αθθά ηαζ ηςκ ιεηααμθχκ ηδξ εενιμηναζίαξ ημο κενμφ ακάιεζα ζηζξ επμπέξ (Dural et al. 2010). Ζ επμπζηή ιεηααθδηυηδηα είκαζ ζδιακηζηυξ πανάβμκηαξ, δζυηζ ιπμνεί κα επδνεάζεζ ηα επίπεδα ζοζζχνεοζδξ ηςκ ιεηάθθςκ ζημοξ ζζημφξ ηςκ ζπεφςκ (Phillips 1980). Σέθμξ, ηα δεδμιέκα απμδεζηκφμοκ υηζ οπήνπακ παιδθέξ ζοβηεκηνχζεζξ Cr, Cu, Zn ηαζ Cd ζηα δείβιαηα ιουξ ηςκ παναπάκς εζδχκ. Αοηυ ζδιαίκεζ υηζ ηα ράνζα είκαζ ιζα αζθαθήξ ηνμθή βζα ημκ άκενςπμ. Οζ ζοβηεκηνχζεζξ ηςκ αανέςκ ιεηάθθςκ ζηα ανχζζια ιένδ ηςκ εζδχκ M. barbatus ηαζ P. erythrinus δεκ έδεζλακ εκδεπυιεκμ νίζημ ζηδκ ηαηακάθςζή ημοξ απυ ημκ άκενςπμ. Δπραξηζηίεο Ζ πανμφζα ενβαζία είκαζ ιένμξ ηδξ δζδαηημνζηήξ δζαηνζαήξ ηδξ Λμοηίαξ Γζακκαημπμφθμο. Οζ ζοββναθείξ εέθμοκ κα εηθνάζμοκ ηζξ εοπανζζηίεξ ημοξ ζε υζμοξ ζοκέααθακ ζηδκ οθμπμίδζδ ηαζ μθμηθήνςζδ ηδξ ένεοκαξ αοηήξ. Βηβιηνγξαθία Alibabic V., Vahcic N., Bajramovic M. (2007) Bioaccumulation of metals in fish of salmonidae family and the impact on fish meat quality. Environmental Monitoring and Assessment, 131, Bervoets L., Blust R. (2003) Metal concentrations in water, sediment and gudgeon (Gobio gobio) from a pollution gradient: relationship with fish condition factor. Environmental Pollution, 126, Bordajandi L.R., Gómez G., Fernández M.A., Abad E., Rivera J., González M.J. (2003) Study on PCBs, PCDD/Fs, organochlorine pesticides, heavy metals and arsenic content in freshwater fish species from the River Turia (Spain). Chemosphere, 53, Dural M., Genc E., Yemenicioglu S. and Sangun M.K. (2010). Accumulation of Some Heavy Metals Seasonally in Hysterotylacium aduncum (Nematoda) and Its Host Red Sea Bream, Pagellus erythrinus (Sparidae) from Gulf of Iskenderun (North-Eastern Mediterranean). Bulletin of Environmental Contamination and Toxicology, 84 (1), doi:doi /s Erdogrul O., Erbilir F (2007) Heavy metal and trace elements in various fish samples from Sir Dam Lake, Kahramanmaras, Turkey. Environmental Monitoring and Assessment, 130, Greig H.S., Niyogi D.K., Hogsden K.L., Jellyman P.G., Harding J.S. (2010) Heavy metals: confounding factors in the response of New Zealand freshwater fish assemblages to natural and anthropogenic acidity. Science of the Total Environment, 408, Idris A.M., Eltayeb M.A.H., Potgieter-Vemaak S.S., Van Grieken R., Potgieter J.H. (2007) Assessment of heavy metals pollution in Sudanese harbours along the Red Sea Coast. Microchemical Journal, 87, Metian M., Warnau M., Chouvelon T., Pedraza F., Rodriguez y Baena A.M., Bustamante P. (2013) Trace element bioaccumulation in reef fish from New Caledonia: Influence of trophic groups and risk assessment for consumers. Marine Environmental Research, (87-88), Phillips D.J.H. (1980). Introduction to seasonal variation. In Quantitative aquatic biological indicators, Applied Science Publishers Ltd (eds), UK, p Tsangaris C., Kaberi H., Catsiki V.A. (2013) Metal levels in sediments and transplanted mussels in Pagasitikos Gulf (Aegean Sea, Eastern Meditteranean). Environmental Monitoring and Assessment, 185(7), , DOI: /s z. WHO (2003) Joint FAO/WHO Expert Committee on Food Additives and Contaminants, Sixty-First Meeting. Summary and Conclusions, ftp://ftp.fao.org/es/esn/jecfa/jecfa61sc.pdf. 214

215 THEMATIC FIELD: FISHERIES TECHNOLOGY 215

216 ORAL PRESENTATIONS IN ENGLISH ANALYSIS OF TRAWL RESOURCES WITHIN MEDITS SURVEY 2013 ALONG THE MONTENEGRIN COAST (SOUTH ADRIATIC SEA) Joksimović A. 1*, Đurović M. 1, Marković O. 1, Ikica Z. 1, Pešić A. 1 1 Institute of Marine Biology, University of Montenegro, Dobrota bb, P.Box 69, , Kotor, ABSTRACT Montenegro The European Union has started a research of benthic communities in 1994 within the framework of MEDITS programme (MEDIterranean Trawl Survey). Sampling is performed according to the standardised protocol, annually, during the spring-summer period. Montenegro and Albania, although not EU member countries, also participate in the MEDITS surveys. In Montenegrin waters, ten haul positions were chosen based on the depth strata. The results of the MEDITS 2013 has shown a decrease in total biomass compared to the results of In 2013, the biomass index of all demersal resources along the Montenegrin coast was estimated at kg/km 2. As the total area amounts to 5000 km 2, the total biomass thus can be estimated at tons. In 2012, the biomass index was kg/km 2, and total biomass in the 5000 km 2 area was tons. The noticeable reduction in trawl resource biomass in 2013 can likely be considered as the result of natural fluctuations in biomass caused by available food resources in the sea, temperature fluctuations and other hydrographic factors. The fact that the contribution of Montenegrin fleet in total catch of demersal resources within GFCM GSA 18 (2013) was 1%, implies that the biomass reduction is not connected to the fishing effort (F) intensity, which (in Montenegro) has remained fairly constant for a long time. Key words: MEDITS, trawl fisheries, resources, Montenegrin coast * Correspoding author: Joksimović Aleksandar (acojo@ac.me) 1. Introduction The European Union started a detailed study of Mediterranean benthic resources in 1994 within the MEDITS programme (MEDIterranean Trawl Survey), which includes the trawling areas on continental shelf and continental slope. The sampling is done according to the standardised protocol, annually, during spring and summer seasons. Montenegro and Albania, although not the EU member countries, participate in the MEDITS surveys within the framework of FAO AdriaMed project (Scientific support to development of sustainable fisheries in the Adriatic Sea) (Vrgoĉ et al., 2004). In this way, important data on trawl resources within the GSA 18 are collected, which is important for GFCM reports and also for the biomass estimation and sustainable trawling in the Adriatic Sea. Montenegro has actively participated in the MEDITS surveys since Material and Methods According to the current MEDITS protocol (Instruction manual, Version 6, 2012), the sampling can be done in the period between 30 minutes after sunrise to 30 minutes before sunset. The hauls last for 30 minutes, except on haul positions with depths greater than 200 m, where hauls last for 1 hour (due to the extra time required to the trawl to drop and settle along the sea bottom). There are 216

217 10 haul positions in Montenegro (Fig. 1). Of those 10, seven are on the continental shelf area (at depths less than 200 m), where the majority of Montenegrin trawling activity occurs. Figure 1. MEDITS haul positions in Montenegro Cod-end mesh size for MEDITS survey is 10 mm, which is important for scientific purposes, as it allows for estimation of spawning areas of the economically important species, as well as for collecting a greater number of species for a more realistic demersal resource estimation. For target species, number of individuals, length frequency distribution, sex (including gonad maturity stages) and total weight of the individuals are recorded on board. MEDITS scale is used for gonad maturity stage determination (MEDITS Survey, Instruction Manual, Version 6.1, 2012). Total length of sampled fish and mantle length of cephalopods was measured using the fish measuring board with a 1-mm accuracy, and the cephalopthorax of crustaceans was measured with calliper, with a 0.1-mm accuracy. The weights were measured using electronic hand-held scales Bonso electronic 393 (max. 15 kg, accuracy of 0.02 kg). At certain haul positions, data on depth, temperature and sea water salinity were recorded using the Star-Oddi DST CTD probe. Species were determined using determination keys for fish (Šoljan, 1965; Whitehead et al., 1989; Jardas, 1996), cephalopods (Roper et al., 1984; Nesis, 1987; Jereb & Roper, 2005) and crustaceans (Fisher et al., 1987). All data collected were analysed using the ATrIS software (Adriamed TRawl Infromation System, Gramolini, 2005), developed within the framework of the FAO AdriaMed project. Abundance, biomass and length frequency distributions were estimated using the swept-area method, considering random stratified sampling (Souplet, 1996), and the estimation results are given as N/km 2 and kg/km 2, respectively. 3. Results and discusion The study of demersal resources within the framework of MEDITS survey in 2013 has shown the reduction in total biomass in comparison to the results from In 2013, the total biomass index of demersal resources was estimated at kg/km 2. Considering that the total study area was 5000 km 2, the total biomass can be estimated to tons. In 2012, the biomass index was kg/km 2, which amounts to a total estimated biomass of tons (GFCM, 2013), based on the 5000 km 2 survey area. The classification of faunistic categories and subcategories was defined according to the MEDITS protocol. The species are shown according to the main faunistic groups: A Fish, B Crustaceans, C Cephalopods, D Other commercial species edible, E Noncomercial species edible, V Plants, G Portions or products of animal species. A total of 151 species were recorded during the survey, which when divided according to categories come up to: A 70, B 17, C 19, D 8, E 33, V 3, G 1. Table 1 gives the overview of the 25 species with the highest abundance index (N/km 2 ) in the survey area, while table 2 shows the 25 species with the highest biomass index (kg/km 2 ). 217

218 Table 1. Species with the highest abundance index (N/km 2 ) (MEDITS, 2013) Vrsta MEDITS accronym N/Km2 Faunistic category Illex coindetii ILLE COI C Spicara flexuosa SPIC FLE A Trachurus trachurus TRAC TRA A Mullus barbatus MULL BAR A Merluccius merluccius MERL MER A Engraulis encrasicolus ENGR ENC A Sardina pilchardus SARD PIL A Alloteuthis media ALLO MED C Boops boops BOOP BOO A Pagellus erythrinus PAGE ERY A Spicara smaris SPIC SMA A Trachurus picturatus TRAC PIC A Macrorhamphosus scolopax MACO SCO A Loligo vulgaris LOLI VUL C Scyliorhinus canicula SCYO CAN A Pagellus bogaraveo PAGE BOG A Parapenaeus longirostris PAPE LON B Lepidotrigla cavillone LEPT CAV A Micromesistius poutassou MICM POU A Nezumia sclerorhynchus NEZU SCL A Stichopus regalis STIC REG E Todaropsis eblanae TODI EBL C Nephrops norvegicus NEPR NOR B Capros aper CAPO APE A Cidaris cidaris CIDA CIR E Table 2. Species with the highest biomass index (kg/km 2 ) (MEDITS, 2013) Vrsta MEDITS accronym Kg/Km2 Faunistic category Illex coindetii ILLE COI C Mullus barbatus MULL BAR A Spicara flexuosa SPIC FLE A Merluccius merluccius MERL MER A Trachurus trachurus TRAC TRA A Pagellus erythrinus PAGE ERY A 218

219 Raja clavata RAJA CLA A Scyliorhinus canicula SCYO CAN A Zeus faber ZEUS FAB A Stichopus regalis STIC REG E Boops boops BOOP BOO A Lophius budegassa LOPH BUD A Todaropsis eblanae TODI EBL C Galeus melastomus GALU MEL 9.98 A Engraulis encrasicolus ENGR ENC 9.89 A Trachyrhynchus trachyrhynchus TRAR TRA 9.86 A Trachinus radiatus TRAH RAD 8.34 A Trachurus picturatus TRAC PIC 8.33 A Pagellus bogaraveo PAGE BOG 8.31 A Raja miraletus RAJA MIR 8.11 A Sardina pilchardus SARD PIL 6.77 A Phycis blennoides PHYI BLE 6.44 A Spicara smaris SPIC SMA 6.15 A Micromesistius poutassou MICM POU 5.88 A Squalus blainvillei SQUA BLA 4.94 A The analysis of tables 1 and 2 shows that the shortfin squid, Illex coindetii, had highest values of both abundance and biomass indices among the demersal species in Montenegro. Red mullet (Mullus barbatus), hake (Merluccius merluccius), Mediterranean horse mackerel (Trachurus mediterraneus), red pandora (Pagellus erythrinus), rays (Raja spp.), John Dory (Zeus faber), blackbellied angler fish (Lophius budegassa) and bogue (Boops boops) have high biomass indices. Most of the listed species have had a small decrease in biomass from 2012, and I. coindetii, T. mediterraneus, Z. faber and L. budegassa actually had a biomass increase in All species in question are common in trawl catches, and the decrease in biomass should not have a pronounced financial effect in relevant subjects in the fishery sector, as in 2012 a large percent of the biomass (around 20%) was made of non-commercial species picarel (Spicara flexuosa and S. smaris). Comparison of biomass of the most important commercial species in 2012 and 2013 shows only a modest decrease in biomass. A parallel comparison of the biomass of commercial species between 2012 and 2013 (Fig. 2) shows a reduction in biomass in M. barbatus, M. merluccius, Engraulis encrasicolus and Parapenaeus longirostris, while an increase in biomass was evidenced for I. coindetii, P. erythrinus, L. budegassa and Z. faber. 219

220 Figure 2. Parallel comparison of biomass indices of commercial species; MEDITS According to categories (A Fish, B Crustaceans, C Cephalopods, D Other commercial species edible, E Noncomercial species edible, V Plants, G Portions or products of animal species), fish have the highest percent of biomass index (72%), with cephalopods having 18%, and crustaceans only 1%. Other categories combined take up 9% of the total biomass, and of that the most significant are the non-commercial edible species (E category). In 2012, the percentage of fish was slightly higher (87%), cephalopods had 12% and crustaceans 1%. Therefore, the ratio of fish in 2013 in total biomass was reduced by 15% when compared to 2012, while the cephalopod ratio increased by 6% in the same period. 18% 1% 8% 0% 0% A - Fish B - Crustaceans 1% 72% C - Cephalopods D - Other commercial species (edible) E - Noncommercial species (edible) V - Plants Figure 3. Percentile distribution of categories in Montenegro; MEDITS Conclucions The Adriatic Sea and its fisheries resources represent a shared resource of five countries situated along the Adriatic coast. Therefore, international scientific research and studies and scientific cooperation have a very important role towards the creation of fishery activity, especially considering that available data point to the reduction of biomass, especially along the western Adriatic coast. The evidenced reduction in biomass of trawl resources in 2013 can, in all likelihood, be tied to the natural biomass fluctuations caused by the available amount of food in the sea, temperature fluctuations and other hydrographic factors. The fact that the Montenegrin trawling fleet is responsible for 1-2% of total trawl catches in the GSA 18 (GFCM, 2013) implies that the biomass reduction is not caused by fishing effort intensity (F), which has remained fairly unchanged for a long time in Montenegro. 220

221 Based on this joint research, biomass index and length frequency distribution of populations, especially those of commercial interest, it is possible to point to the existence of certain trends, mostly negative ones, and to make correct decisions towards the joint resource preservation. References AdriaMed (2007). AtrIS Adriamed Trawl Information System. Software version 2.1. FAO MiPAF Scientific Cooperation to Support Responsible Fisheries in the Adriatic Sea. GCP/RER/010/ITA. Gramolini, R., P. Mannini, N. Milone and V. Zeuli, (2005). AdriaMed Trawl Survey Information System (AtrIS): User Manual. FAO-MiPAF Scitenic Cooperation to Support Responsabile Fisheries in the Adriatic Sea. GCP/RER/010/ITA/TD17. AdriaMed Technical Documents, 17: 141 pp. GFCM Technical document XXXVII/2013/2.35 pp. MEDITS (2012): Instruction manual, Version pp. Jardas I. (1999). Jadranska ihtiofauna. Školska knjiga. Zagreb, 538s str. Jereb, P. & C. F. E. Roper (eds). (2005). Cephalopods of the world. An annotated and illustrated catalogue of Cephalopod species known to date. Volume 1. Chambered nautiluses and sepioids (Nautilidae, Sepiidae, Sepiolidae, Sepidariidae, Idiosepiidae and Spirulidae). FAO Species Catalogue for Fishery Purposes. No. 4, Vol. 1. FAO, Rome, 262 pp. Fisher, W., Schneider, M., Bauchot, M.L. (eds.) (1987) Fishes FAO d identification des espèces pour les besoins de la pêche. Mediterranée et mer Noire. Vol. I II., Rome, FAO. 1-2: 760 pp. Roper, C. F. E., Sweeney, M. J., Nauen, C. E. (1984): FAO species catalogue. Vol.. 3. Caphalopods of the world. An annotated and illustrated catalogue of species of interest to fisheries. FAO Fisheries Synopsis, No. 25, Volume pp. Nessis, K. N. (1987). Cephalopods of the world. Squids, cuttlefishes, octopuses, and allies. T.H.F. Publications, Neptune City, N.J., USA. 351 pp.. Souplet, A., (1996). Calculation of abudance indices and lenght frequencies in the MEDITS survey. In: J.A. Bertrand et. al. (Editors). Campagne internationale de chalutage demersal en Mediterranee (MEDITS). Campagne Vol. III Raport final de contract CEE-IFREMER- IEO-SIBM-NCMR, 68. pp. Vrgoĉ, N., Arneri, E., Jukić-Peladić, S., Krstulović-Šifner, S., Mannini, P., Marĉeta, B., Osmani, K., Piccineti, C. And Ungaro, N. (2004). Review of current knowledge on shared demersal stocks of the Adriatic Sea. FAO-MiPAF Scientific Cooperation to Support Responsible Fisheries in the Adriatic Sea. GCP/RER/010/ITA/TD-12. AdriaMed Technical Documents, 12:91 pp. Whitehead, P. J. P., M.-L. Bauchot, J.-C. Hureau, J. Nielsen and E. Tortonese (Eds), (1989). Fishes of the North-eastern Atlantic and the Mediterranean. UNESCO, Richard Clay Ltd, Bungay (United Kingdom). Vols. I - III: 1473p. Šoljan, T., (1948). Ribe Jadrana, Fauna i Flora Jadrana, 1, Nakladni izavod Hrvatske: 437 str. 221

222 IDENTIFICATION OF FISHING GROUNDS FOR THE TARGET SPECIES OF BOTTOM TRAWL IN THE HELLENIC WATERS Maina I. 1,2*, Kavadas S. 1, Mantopoulou D. 1, Somarakis S. 1 1 Institute of Marine Biological Resources and Inland Waters, Hellenic Centre for Marine Research (IMBR/HCMR), Agios Kosmas, Elliniko, Athens, Greece 2. Department of Marine Sciences, School of the Environment, University of the Aegean, University Hill, 81100, Mytilene, Lesvos, Greece ABSTRACT The potential habitats of the most important commercial species and vessel monitoring system data (VMS) from trawlers were modeled in order to identify fishing grounds. The data for the analysis were collected during research activities conducted by HCMR since In this work, sixteen target species from trawlers were studied. The methodology is based on: (a) the assessment of the probability of species presence using Generalized Additive Model (GAM), (b) the estimation of a threshold of species presence using the Receiver Operating Characteristic analysis (ROC), (c) the combination of presence/absence model and the estimated fishing effort from trawlers using VMS data, (d) the identification of the main fishing grounds using Hot Spot analysis. The results revealed that the most important fishing grounds are identified in the Northern part of the Aegean Sea, in Euvoikos, Saronikos and Patraikos gulf and in the islands of Chios and Dodecanese. Key words: VMS, GAM, fishing effort, Hot Spot analysis, bottom trawl *Corresponding author: Maina Irida (imaina@hcmr.gr) 1. Introduction Commercial fishing vessels with total length greater than 15 meters are obligated to be equipped with VMS, which provides data to the fisheries authorities of fishing vessel s location, direction and speed at a two-hour interval (EC No2244/2003). Recently, VMS data have become available, allowing the analysis of spatial distribution of fishing effort for bottom trawlers and purse seiners The data were analyzed according to methodology proposed by Kavadas & Maina and the spatial distribution of fishing effort for bottom trawlers were used for this approach (Kavadas & Maina, 2012). In this work the following sixteen commercial species were studied: Merluccius merlucius, Mullus barbatus, Mullus surmuletus, Galeus melastomus, Parapenaeus longirostris, Pagellus erythrinus, Lophius budegasa, Illex coindetii, Aristeus antennatus, Aristaeomorpha foliacea, Eledone cirrhosa, Eledone moschata, Nephrops norvegicus, Octopus vulgaris, Trachurus mediterraneus and Trachurus trachurus. To overcome the scarcity problem of information, a new approach was devised to define the potential fishing grounds that are based on habitat modeling (probability of presence) of each particular species and the high deployed fishing effort of trawlers. In this approach, all available datasets stored on HCMR databank from surveys at sea (MEDITS, National sampling) and onboard samplings were used (Kavadas et al., 2013). The objective of this study is to model the potential habitats (probability of presence) for the above species, to define a threshold for species presence, to combine the fishing effort from trawlers with the probability of presence and to identify hot spot areas which can be considered as the most important fishing grounds for the species under investigation. The potential fishing grounds of the above species also was also investigated. 2. Material and Methods Habitat modeling was based on GAM, which employ non-linear and non-parametric techniques for regression modeling. The main advantage of GAM over traditional regression methods is their ability to deal with highly non-linear and non-monotonic relationships between a response and 222

223 a set of explanatory variables (Hastie & Tibshirani, 1990, Guisan et al., 2002, Elith & Burgman, 2002). Analysis of estimated goodness of fit statistics and diagnostic graphs, used for the working data set. In the analysis, the level of deviance explained (0 100%; the higher the better), R 2 (0-1, the higher the better), Un-Biased Risk Estimator (UBRE score; the lower the better) and Q-Q plots led to the selection of the model that fitted best the response data. The presence/absence data was modeled using a binomial error distribution and a logit link function, expressed in R formula syntax, using the MGET tool (Wood and Augustin, 2002, Roberts et al., 2010). The degree of smoothing of each parameter was chosen based on the observed data and the minimization of UBRE score (Craven and Wahba, 1979, Wood, 2006). To evaluate the predictive performance of the final presence/absence model the following statistics are used: (a) ROC plots, (b) the area under the ROC curve (AUC) and the threshold value, (Deleo, 1993, Fielding & Bell, 1997, Guisan & Zimmerman, 2000, Sing et al., 2005). For binary classification, a threshold value used to determine whether a given value of the response variable should be classified as positive or negative. The presence/absence model typically outputs predictions along a continual range (e.g. between 0 and 1). Response values less than the threshold are classified as negative and those greater than or equal to the threshold are classified as positive. The threshold is evaluated by the MGET tool for the point of the ROC curve that is closest to the point of the perfect classification (the upper left corner of the ROC plot) (Roberts et al., 2010). Potential habitats, i.e. areas in which the species was classified as presence, were used to combine probability of presence with fishing effort distribution maps. The product of fishing effort from trawlers probability of presence for each species was considered to represent the potential fishing grounds of a particular species. Trawlers fishing effort was estimated by VMS data and was expressed as days at sea multiplied by vessels Gross Tonnage. It was assumed that every vessel visits a fishing rectangle (5x5 km) more than once a day, thereby a weighted value is given in each rectangle depending on the number of visits it receives within 24 hours (Kavadas & Maina, 2012, Maina et al., 2013). A Getis-Ord Gi statistic was applied to the product of fishing effort and probability of species presence values, in order to identify statistically significant Hot and Cold Spots. The Hot Spot Analysis calculates the Getis-Ord Gi statistic for each feature (cell value) in a weighted set of features. The Getis-Ord Gi statistic shows whether features with high values or features with low values tend to be clustered in the study area. This tool works by looking at each feature within the context of neighboring features. If a feature's value is high, and the values for all of neighboring features are also high, can be considered as a hot spot. The local sum for a feature and its neighbors is compared proportionally to the sum of all features; when the local sum is much different than the expected local sum, and that difference is too large to be the result of random chance, a statistically significant Z score is the result (Getis & Ord, 1992, Mitchell, 2005). For statistically significant positive Z Scores (Hot Spots), the larger the Z score is, the more intense the clustering of high values. Areas that classified as Hot Spots are aggregated in a single output in order to identify the importance of the fishing grounds by the total number of species that appears in the Hellenic Seas. 3. Results The results revealed that the best GAM fit for the species under investigation, taking into consideration all statistical measures and diagnostic plots, is a combination of presence/absence data as a response variable and depth, longitude and latitude as explanatory variables. The maps produced during the implementation process are presented in Figures 1, 2. Figure 1 presents the maps for the entire steps of the process for Mullus barbatus as an example. By the combination of the (a) probability of presence for each species with the (b) fishing effort from trawlers derived two outputs. The first output is the (c) product between the two layers and the second is the (d) Hot Spots areas that derived after the implementation of Getis-Ord Gi statistic to the product output. 223

224 Figure 2 shows a combination of the Hot Spots for all species. The areas with the highest number of trawling species are the Northern part of the Aegean Sea (Thermaikos, Sigitikos and Kavala gulf), the Northern part of Euvoikos and Patraikos gulf and Chios Island. Other important fishing grounds found in Thracian Sea, Northern part of Euvoikos, Saronikos gulf, Dodecanese and Outer Part of Patraikos gulf. (a) Probability of presence Outputs (b) Fishing Effort for trawlers (c) Product (d) Hot Spots Fig. 1: Mapping the methodological steps for Mullus Barbatus 224

225 Fig. 2: Trawlers fishing grounds - aggregated output for sixteen species 4. Discussion The proposed methodology consist an innovative approach for the identification of the most important fishing grounds for bottom trawlers. This method may be very useful in sampling design and also to the investigation of important fishing grounds for other fishing gears (purse seiners, small scale fisheries etc.). In case that this methodology enriched by additional data (juveniles etc.) may constitute a useful tool for management purposes in order to avoid fishing activity in space and time in areas characterized as spawning grounds. Furthermore, some methodological improvements for the models could be the evaluation and redefinition of the presence/absence threshold that produced by ROC analysis by testing the abundance observations, which are possibly not included to the presence variation of the model and also fitting the remaining variation in abundance where the species are present. This can be also modeled by GAM and finally could derive more accurate results for the spatial distribution of species abundance. Acknowledgements This work is part of the on-going researches within the MAREA project Stock units: Identification of distinct biological units (stock units) for different fish and shellfish species and among different GFCM-GSA (STOCKMED; and also within the ARISTEIA ΗΗ project Ecosystem effect of fisheries Discards (ECODISC). References Craven P., Wahba G. (1979). Smoothing noisy data with spline functions Numerische Mathematik, 31 p. 377 Deleo, J.M. (1993). Receiver operating characteristic laboratory (ROCLAB): software for developing decision strategies that ac- count for uncertainty. In: Proceedings of the Second International Symposium on Uncertainty Modeling and Analysis, pp College Park, MD: IEEE Computer Society Press Elith, J. & Burgman, M.A. (2002). Predictions and their validation: rare plants in the Central Highlands, Victoria, Australia. In: Predicting Species Occurrences: Issues of Scale and Accuracy (eds Scott, J.M., Heglund, P.J., Morrison, M., Raphael, M., Haufler, J. & Wall, B.). Island Press, Covello, CA, pp

226 EC (European Commission), (2003). Council Regulation (EC) 2244/2003 of 18 December 2003 laying down detailed provisions regarding satellite based Vessel Monitoring Systems. Fielding A.H. & J.F. Bell (1997). A review of methods for the assessment of prediction errors in conservation presence/absence models, Environmental Conservation 24 (1): Getis, A. & J.K. Ord. (1992) The Analysis of Spatial Association by Use of Distance Statistics. Geographical Analysis 24, no. 3. Guisan, A., Edwards, J., Thomas, C. & Hastie, T. (2002). Generalized linear and generalized additive models in studies of species distributions: setting the scene. Ecological Modeling, 157, Guisan A, & N.E. Zimmermann (2000). Predictive habitat distribution models in ecology, Ecol. Model., 135, pp Hastie, T.J., Tibshirani, R.J. (1990). Generalized Additive Models. Chapman & Hall/CRC Kavadas, S., Damalas, D., Georgakarakos, S., Maravelias, C., Tserpes, G., Papaconstantinou, C., Bazigos, G. (2013). IMAS-Fish: Integrated Management System to support the sustainability of Greek Fisheries resources. A multidisciplinary web-based database management system: implementation, capabilities, utilization & future prospects for fisheries stakeholder. Mediterranean Marine Science, 14(1), Kavadas S., Maina I., (2012), Methodology of analysis of Vessel Monitoring System data: Estimation of fishing effort for the fleet of open sea fishery, Athens, 7-11 May, Abstr. 10 th Hel. Oceanogr. & Fish., p. 164 Maina, I., Kavadas, S., Dokos, J. (2013). Spatio-temporal patterns of fishing pressure on bathymetric zones in central and North Aegean Sea using vessel monitoring system data for open sea fisheries. Marseille, France, 28 Oct-1 Nov th CIESM Congress, Mitchell, A. (2005). The ESRI Guide to GIS Analysis, ESRI Press Vol. 2. Roberts J.J., Best B.D., Dunn D.C., Treml E.A., & P.N., Halpin (2010). Marine Geospatial Ecology Tools: An integrated framework for ecological geoprocessing with ArcGIS, Python, R, MATLAB and C++. Environmental Modeling & Software 25, pp Sing T.S., Beerenwinkel N., Lengauer T. (2005). ROCR: visualizing classifier performance in R Bioinformatics 21, pp Wood, S. N. (2006). Generalized Additive Models: An Introduction with R. Chapman & Hall/CRC. Wood, S.N., & N.H., Augustin, (2002). Improving GAMs for environmental modeling using GCV and penalized regression splines. Ecol. Mod Vol. 157, pp

227 COMPARISON OF SOME BIOLOGICAL CHARACTERISTICS OF EUROPEAN ANCHOVY, Engraulis encrasicolus (Linnaeus, 1758), BETWEEN BOKA KOTORSKA BAY AND OPEN SEA, SOUTH ADRIATIC SEA, MONTENEGRO Pešić, A. *, Đurović M., Ikica Z., Joksimović A., Marković O. and Mandić, M. Laboratory of Ichthyology and Marine Fishery, Institut of Marine Biology, University of Montenegro, P.O. Box 69, Kotor, Montenegro ABSTRACT The paper presents results of studies of biological characteristics of european anchovy, Engraulis encrasicolus (Linnaeus, 1758), between two areas of Montenegrin teritorial waters, Boka Kotorska Bay and open sea (South Adriatic Sea). Studies in Boka kotorska Bay were performed in the frame of FAO AdriaMed Pilot study during years 2010 and 2011, while samples from the open sea were collected during survey conducted in July 2010 in the frame of FAO AdriaMed and EU-MEDIAS projects. A total of 1430 individuals were processed, 650 individuals from Boka Kotorska Bay and 780 individuals from the open sea. Total length of E. encrasicolus in Boka Kotorska Bay ranged from 7.6 to 13.6 cm, wheres at the open sea total length ranged from 10.5 to 18.3 cm. The length weight relationship of individuals from Boka Kotorska Bay is described by the equation W = L T ; (r 2 = 0.962), while for individuals from open sea is W = L T ; (r 2 = 0.932). Females were more frequent in both studied areas, sex ratio was R=0.67 and R=0.52 respectively in Boka Kotorska Bay and at open sea. Key words: Engraulis encrasicolus, biological characteristics, Boka Kotorska Bay, open sea, South Adriatic Sea * Coresponding author (pesica@ac.me) Introduction Anchovy, E. encrasicolus, is one of the most abundant and commercially most important fish species in the Adriatic Sea. Montenegrin industrial fishing of small pelagic species, sardine and anchovy, is still undeveloped due to lack of trained and experienced crew, high transparency of water and strong currents in South Adriatic Sea. Anchovy and sardine are mainly caught through small-scale fishery, mostly using beach seines with small mesh size in the Boka Kotorska Bay and small purse seines in front of the Bay, targeting in high percentage of juvenile individuals. This type of fishing has been traditional in the region for centuries. Boka Kotorska Bay is one of the most productive areas of the Montenegrin coast and it seems to be a nursery ground for anchovy (Merker & Vujošević, 1972; Mandić et al., 2011), sardine and other small pelagic fish species (Mandić et al., 2013). The objective of this study was to gather and compare some information of the length-weight relationship, length frequency distribution and sex ratio of anchovy from two ecologicaly different areas of Montenegrin teritorial waters, Boka Kotorska Bay and open sea. Material and methods A total of 1430 individuals of anchovy were processed, 650 individuals from Boka Kotorska Bay and 780 individuals from the open sea (Figure 1). Samples from Boka Kotorska Bay were collected on a monthly basis during 2010 and 2011, while samples from the open sea were collected during July and 227

228 August Fish total length and body weight were measured to the nearest 0.1 cm and nearest 0.01 g, respectively. The general power equation (W = a*l T b ) was applied to estimate the length-weight relationship, where a and b are constants whose values were estimated by the least square method. Confidence intervals of 95% were calculated for the slope (b) to see if these were statistically different from 3. Sex was assigned macroscopically and sex ratio (R) was calculated using the expression R = F / (F+M), where F is the number of females and M that of males. Figure 1. Geographical position of Montenegro and Boka Kotorska Bay Results and discussion The total length of the anchovy from Boka Kotorska Bay ranged from 7.6 cm to 13.6 cm, with the mean at 10.3 ± 1.32 cm (SE 0.05) and W ranged from 2.28 g to g with the mean at 6.68 ± 2.93 g (SE 0.11). Length frequency distribution of anchovy from open sea shows presence of bigger individuals, total length ranged from 10.7 cm to18.3 cm, with the mean at 13.9 ± 1.41 cm (SE 0.06) and W ranged from 7 g to 47 g with the mean at ± 6.52 g (SE 0.29), Figure 2. The mean observed length of anchovy from Boka Kotorska Bay (10.3 cm) was higher than the value obtained in , 8.4 cm (Pešić et al., 2007), and almost the same with the value obtained in , cm (Pešić et al., 2013). Similar results for length distribution of anchovy in coastal areas are given by Sinovĉić (1998) and Sinovĉić & Zorica (2006), for Novigrad Sea (Central Adriatic). Reported results for length distribution of anchovy at open sea is wider cm for Central Adriatic (Sinovĉić, 2000) and 5-18 cm for South Adriatic (Regner et al., 2006). Figure 2. Length frequency distribution of anchovy, E. encrasicolus, from Boka Kotorska Bay and open sea 228

229 Differences in length distribution of anchovy in coastal areas and at open sea are explained by the fact that adult anchovy lives and spawns in the open sea in deeper waters (Mužinić, 1956, 1972; Regner, 1973; Sinovĉić, 1978), while junger individuals spend winter in coastal areas, usually bays, where they conduct first spawning at length of 8-9 cm and afterwards migrate towards open sea (Sinovĉić, 2000; Marano, 2001). In length weight relationship, the parameter b was higher than 3 for both investigated areas, b = for individuals from Boka Kotorska Bay, and b = for anchovy from open sea (Figure 3). For the area of Boka Kotorska Bay Đurović (2012) reported b = and b = 3.106, for period and respectively. Similar values are reported for closed area of Novigrad Sea, central Adriatic, b = 3.19 (Sinovĉić, 1998) and b TOT = (Sinovĉić & Zorica, 2006). The similarity of values of parameter b could be explained by similar conditions in these areas, especially in terms of eutrophication, since the amounts of nutrients are higher than in the open sea due to anthropogenic influence. Comparison of obtained values of parameter b with ideal value of alometric coefficient b = 3 for fish with T-test showed that there was no statistically significant difference of observed value b = from b = 3 (t = ; df = 1; p<0.001) for samples from the open sea. In the samples from Bokakotorska Bay T-test showed significant difference between observed value b = from b = 3 (t = ; df = 1; p>0.001), which was expected due to the fact that high amount of examined individuals from Boka Kotorska Bay were juvenile individuals, not mature, and their energy is used only for body growth. Figure 3. Length-weight relationship of anchovy, E. encrasicolus, from Boka Kotorska Bay and open sea In both investigated areas females show predominance over males (Table 1). From 650 individuals processed from Boka Kotorska Bay, there were 404 females (62.15%), 199 males (30.62%) and 47 individuals with unknown sex (7.23%). In the samples from the open sea there were 405 females (51.92%) and 375 males (48.08%). Sex ratio was R=0.67 and R=0.52 respectively for Boka Kotorska Bay and open sea. Sex ratio of individuals in Boka Kotorska Bay was significantly different from the expected value of 1:1 (ρ 2 =69.96, P < 0.05), while in the open sea there was no significant difference from the expected value of 1:1 (ρ 2 =1.154, P >0.05). In the samples from Boka Kotorska Bay females were predominant in all length classes, and unsexed individuals are present till the length of 10.1 cm. Similar results, predominance of females, are reported for the same area in period (Đurović, 2012), as well as in central Adriatic (Sinovĉić, 2000; Sinovĉić & Zorica, 2006), Albanian waters (South Adriatic Sea; Kolitari, 2006) and North Adriatic (Varangolo, 1967). In the samples from open sea results are quite different; in each length class till length of 13.8 cm males were predominant, while over length of 13.8 cm females were predominant in each length class. 229

230 Predominance of males in length classes less then 13.8 cm could be explained by the fact that males are predominant in the spawning period, and samplings of anchovy at the open sea were done during the peak of spawning (July-August). Table 1. Sex ratio of anchovy by sampling area Sex Boka Kotorska Bay Open sea Unknown N % N % F M Total R = F/(F+M) This study provides some usual information about differences in some biological parameters of anchovy in two ecologically different areas of Montenegrin territorial waters, Boka Kotorska Bay and open sea. Since the open sea inhabits longer anchovy than Boka Kotorska Bay, exploitation of those resources should be stimulated and fishing fleet should be developed. In this way pressure on anchovy population in Boka Kotorska Bay would be decreased, and juvenile part of population preserved. References Đurović, M. (2012). Ecological investigations of juvenile anchovy in Kotor Bay. Ph.D.Thesis, University of Belgrade. Kolitari, J Preliminary results of small pelagic sampling in the context of the project AdriaMed (for Albania). Data presented on AdriaMed Working Group on Shared Small Pelagic Fisheries Resources, Ancona May Mandić, M., Regner, S., Krpo Ćetković, J. & Joksimović, A. (2011). Unusual occurrence of anchovy (Engraulis encrasicolus Linnaeus, 1758) eggs in December 2006 in Boka Kotorska Bay (Adriatic Sea). Acta Adriat.,53(1): Mandić, M, Đurović, M, Pešić, A, Joksimović, A & Regner, S. (2013). Boka Kotorska Bay spawning and nursery area for pelagic fish species. Stud.Mar. 26/ Marano, G. (2001). Small pelagic stock assessment ( ). AdriaMed Tech. Doc. 3: Merker, K. & Vujošević, M. (1972). Density and distribution of anchovy (Engraulis encrasicolus L.) eggs in the Bay of Boka Kotorska (in Serbian). Poljoprivreda i šumarstvo., 18: Mužinić, R. (1956). Quelques observations sur la sardine, l anchois et le maquereau des captures au chalut dans l Adriatique. Acta Adriat. 11: Mužinić, R. (1972). O horizontalnoj raspodjeli srdele i brgljuna u Jadranu. Pomorski Zbornik, 10: Pešić, A., Đurović, M., Regner, S. & Simić, V. (2007). Boka Kotorska Bay as a feeding place for juvenile sardines and anchovies. III International Conference Fishery. February, 1-3th 2007, Zemun, Belgrade. Conference proceedings: Pešić, A., Regner, S., Mandić, M., Ikica, Z., Đurović M., Joksimović A. & Marković O. (2013). Bilogical characteristics of anchovy (Engraulis encrasicolus) in Boka Kotorska bay 230

231 (Montenegro). VI international conference Water and Fish, June, , Zemun, Serbia. Conference proceedings, Regner, S. (1973). Neki podaci o veliĉini jaja brgljuna, Engraulis encrasicolius (L.), u srednjem Jadranu. Ekologija, 8(1): Regner, S., Joksimović, A., Pešić, A. & Đurović, M. (2006). Anchovy 2005 DEPM in Serbia and Montenegro waters. Data presented at AdriaMed Working Group on Shared Small Pelagic Fisheries Resources, Ancona May. Sinovĉić, G. (1978). On the ecology of anchovy, Engraulis encrasicolus (L.) from the central Adriatic. Acta Adriat. 19(2): Sinovĉić, G. (1998). The Population Dynamics of the Juvenile Anchovy, Engraulis encrasicolus (L.) under the Estuarine Conditions (Novigrad Sea-Central Adriatic). Cah. Options Mediterr. 35, Sinovĉić, G. & Zorica, B. (2006). Reproductive cycle and minimal length at sexual maturity of Engraulis encrasicolus (L.) in the Zrmanja River estuary (Adriatic Sea, Croatia). Est. Coast. Shelf Sci. 69, Sinovĉić, G. (2000). Anchovy, Engraulis encrasicolus (Linnaeus, 1758): biology, population dynamics and fisheries case study. Acta Adriat. 41, Varagnolo, S. (1967). Osservazioni sulla riproduzione dell Engraulis encrasicolus, L.(acciuga) dell alto Adriatico. Archivi di Oceanografia e Limnologia 15 (Suppl):

232 MORPHOLOGICAL STUDY OF Parapenaeus longirostris (Penaidae), IN THE EASTERN MEDITERRANEAN SEA Chatzispyrou A.*, Lampri P-N., Fytilakos I., Mytilineou Ch., Kapiris K. Hellenic Centre for Marine Research, Institute of Marine Biological Resources and Inland Waters, 46.7 km Athens Sounio ave., P.O. Box 712, Anavyssos, 19013, Attiki, Greece Abstract Relative growth of several characteristics in the rose shrimp Parapenaeus longirostris were studied for the first time in the Eastern Mediterranean Sea. According to the median values, the morphometric characters of female and male individuals caught in the Aegean Sea were greater than those from the Ionian Sea. A negative allometry of swimming morphological characters (uropod, scaphocerite, telson) and of abdomen (related to the rapid locomotion, reproduction) was found in both sexes and areas. In contrast to this, the growth of the third pereiopod (involved in walking ability) in females from the Aegean Sea was positively allometric. Both sexes showed positive allometry of rostrum length with size in both areas. Key words: rose shrimp, relative growth, allometry, cephalothorax *Corresponding author: Chatzispyrou Archontia (a.chatzispyrou@hcmr.gr) 1. Introduction Parapenaeus longirostris is actually the target species of an important fishery of trawlers in the Mediterranean. The deep-water rose shrimp, Parapenaeus longirostris, is one of the most important species of crustacean landings in Greece (Kapiris et al. 2007; Sobrino et al. 2005). The higher mean annual landings of P. longirostris were in the period landed in the ports of Peiraias and Thessaloniki, followed by the ports of Kavala, Alexandroupolis and Patra (ETANAL data), while, according to EL.STAT. (Hellenic Statistical Authority) data the most important fishing areas in Greece for P. longirostris are mainly in the Aegean Sea: 13 (Thermaikos Gulf), 14 (N. Aegean Sea) and 18 (Kriti) (Mytilineou et al. 2001) An evaluation of the exploitation state of this species in the Greek waters indicates a general over- or full-exploitation (Kapiris et al. 2007). In the Mediterranean basin, the bathymetric distribution of the deep water rose shrimp ranges between 20 and 750 m, but the species is more common and abundant on sandy-muddy bottoms between 100 and 400 m (Politou et al. 2005). The knowledge on the exploitation state, spatial distribution and biology of this important species in the Greek seas is incomplete and is an outcome of the experimental surveys mainly carried out by the Hellenic Centre for Marine Research (Kapiris et al. 2002, 2012, 2013; Kapiris 2004; Politou et al. 2008) in the frame of European projects. Is worth noting that very few studies on the morphometric characters of the species have been published. The aim of this study is to present the intraspecific variation of the morphometric profile of both sexes of P.longirostris, from the Ionian and Aegean Sea, and compare specimens of both areas to investigate differences in the relative growth. Comparison to other shrimp species is not included, since there is no available data for deep water rose shrimp characteristics from other areas. The current study is a preliminary attempt of further investigation of the morphometric structure of the deep sea rose shrimp, in relation to its swimming and feeding behavior. 2. Material and Methods All specimens of Parapenaeus longirostris were collected during different trawl surveys in the Greek Ionian Sea and the Central Aegean Sea, between December 2013 and May 2014 in the frame of the National Fishery Data Collection Project (EPSAD) under the Reg. 199/2008. A total of 345 individuals (167 males and 178 females) caught in the Ionian Sea and 210 specimens from the Aegean Sea (105 males and 105 females) was measured with digital caliper to the nearest 0.1mm, and weighed to the nearest 0.01g. Seven morphometric characteristics were measured on each specimen (Fig.1): carapace length (CL), abdominal length (ABD), third pereiopod length (P), rostral length (R), scaphocerite length (S), telson length (T) and the uropodal exopodite length (U) (Figure 1). According ημ Sardà et al. (1995) these appendages are related to distinct functional aspects, such as swimming, walking-cropping, balance or orientation ability. The carapace length was considered as the independent variable for all relationships performed. The relationship between all measurements versus CL was investigated for each area and 232

233 sex separately using the simple linear model: Y=a*X b, where Y and X corresponded to the morphological dimensions and a, b the regression constants. The relationships obtained were log transformed to the form log 10 Y=log 10 a+blog 10 X. The log transformation is preferred in order to better satisfy the assumptions of regression analysis (Sokal & Rohlf, 1981). The pattern of allometry for each parameter was established by testing the slope (b) of the obtained regression equations against isometry applying the Student s t-test. (Ho:b=1 or 3 for length-weight).the Mann Whitney test was applied as a nonparametric test to compare independent samples. The comparison of the appendages slopes b and carapace length between sexes was carried out by ANCOVA (Zar, 1984). Figure 1. Morphometric measurements taken on Parapenaeus longirostris. CL, carapace length; T, telson; U, uropodal exopodite; S, scaphocerite; P, third pereiopod; R, rostrum; ABD, abdomen. 3. Results Carapace length (CL) ranged between 13 and 27 mm in males and 10 and 33 mm in females individuals caught in the Aegean Sea. On the other point, carapace length of males and females caught in the Ionian Sea were from 12 to 29 mm and from 10 to 31mm, respectively. The median values of all the morphological characters of the specimens showed a difference between the sexes (Mann-Whitney test, P>0.05 in all cases). Mean sizes of all females appendages were greater than those of males in both areas (Table 1). Both males and females specimens caught in the Aegean Sea showed greater median values compared those of the Ionian Sea (Mann-Whitney test, P>0.05). The equation parameters representing the relative growth of each parameter in relation to carapace length, after logarithmic transformation, for each sex in the Aegean and the Ionian Sea are presented in Table 2. For all the variables regressions were statistically significant (ANOVA, P<0.01).Correlation coefficient (r) and the type of allometry are also included, as a comparison of the slopes of the regression lines. Females in the Ionian Sea showed higher correlation coefficients (r) than those of males; In the Aegean Sea male and female shrimps had almost similar (r) values. For all variables, except the telson, regressions were statistically significant (ANCOVA, P=0.005). The allometry showed the same pattern for P.longirostris in both areas; the length of the rostrum for both sexes was positively allometric and the length of the third pereiopod in females in the Aegean Sea, while all other measurements indicated a significant negative allometry (b<1 or b<3 in carapace length-weight relationship) in both sexes. 233

234 Table 1. Mean sizes (mm) of Parapenaeus longirostris measurements of male (M) and female (F) specimens from the two study areas Measure ABD CL P R S T U W Sex Area Aegean Ionian Mean n Mean n M 48, , F 50, , M 20, , F 24, , M 34, , F 41, , M 14, , F 18, , M 22, , F 24, , M 13, , F 16, , M 19, , F 21, , M 4, ,4 167 F 6, , Table 2. Allometry of the seven measured appendages in P. longirostris in the Aegean and Ionian Sea Dimension Measured/CL ABD P R S T U W ABD Sex n a b r t-test Allometry AEGEAN M Negative F Negative M Negative F Positive M Positive F Positive M Negative F Negative M Negative F Negative M Negative F Negative M Negative F Negative IONIAN M Negative F Negative P M Negative 234

235 R S T U W F Negative M Positive F Positive M Negative F Negative M Negative F Negative M Negative F Negative M Negative F Negative 4. Discussion The present work provides for the first time important information relating to certain morphometric characters of the deep water rose shrimp in the Greek seas (Aegean and Ionian Seas). The current study shows no extensive variation in morphometric aspects exist in the populations of P. longirostris in Aegean and Ionian Seas. A clear sexual dimorphism size appears to exist for P. longirostris females, which reach larger dimensions than males, in both areas. Females weighted also more than males at the same cephalothorax sizes. This has also been reported by Sobrino et al. (2005). The parameters of the CL- W relationship estimated in this study are similar to those calculated by other authors in other Mediterranean areas (Sobrino et al. 2005). The relative growth between the sexes differs only slightly as indicated by morphometric relationships from both areas. All the above observed morphological variations between sexes could be attributed to the differences in growth pattern of males (much lower maximum carapace length and lower Von Bertalanffy values) compared with females (Sobrino et al., 2005) and/or the life span aspects of this species. A negative allometry of all the swimming appendages (scaphocerite, uropod, telson) observed in both sexes and regions, reflects the decreasing growth rate of these morphological characters in relation to CL. The slightly higher slopes (b) of the regression lines for the morphological swimming characters of the females would imply greater swimming ability compared to the ability exhibited by males. Similarly, a negative allometry in the length of the abdomen (directly related to overall metabolic process, primarily reproduction, rapid locomotion) was observed in both sexes and areas. The reduction of the ability for rapid locomotion with increasing size is in agreement with the above reduction of swimming ability. The positive allometry in the third pereiopod length (directly related to walking ability and cropping behavior when searching for food in the substratum, Sardà et al. 1995) in females caught in the Aegean Sea was expected, since the swimming ability decreases, walking ability should increase. Since the allometric growth pattern of the rostrum (an organ possibly related to mating and swimming behavior, sexual segregation and feeding) was found similar between sexes and areas, a faster rostrum growth rate than the carapace growth rate is indicated. The present study improves the few existed data and fills knowledge gaps on deep water rose shrimp biology and ecology in the Greek and international bibliography. In general, this study suggests that there is no morphological variability of P. longirostris amongst both Greek Seas (Aegean and Ionian Sea). Regardless of the more intense fishing pressure exercised in the Aegean Sea variations in morphometric variables are not extensive between the studied populations in both studied areas. Studies of the population structure, including biology, growth rate of the total or body s appendages, spawning season, of commercially important marine organisms as deep sea rose shrimp are of great interest to evolutionary biologists and to fishery managers, and thus provide an initial incentive for further investigation of this decapod in the whole Mediterranean. 235

236 References References in Articles: Kapiris K., Markovic O., Klaoudatos D., Djurovic M., (2013). Contribution to the biology and fishery characteristics of Parapenaeus longirostris (Lucas, 1846) in the South Ionian and South Adriatic Sea. Turkish Journal of Fisheries and Aquatic Sciences 13(4), Kapiris K. (2004). Feeding ecology of Parapenaeus longirostris (Lucas, 1846) (Decapoda: Penaeidae) from the Ionian Sea (Central and Eastern Mediterranean Sea). Scientia Marina 68(2), Politou C-Y., Maiorano P., D Onghia G. and Mytilineou Ch. (2005). Deep-water decapods crustacean fauna of the Eastern Ionian Sea. Belgian Journal of Zoology 135, Politou C-Y., Tserpes G., Dokos J. (2008). Identification of deep-water pink shrimp abundance distribution patterns and nursery grounds in the eastern Mediterranean by means of generalized additive modeling. Hydrobiologia 612, Sardà F., Bas C., Lleonart J. (1995). Functional morphometry of Aristeus antennatus (Risso1816) (Decapoda, Aristeidae). Crustaceana 68, Sobrino I., Silva C., Sbrana M, Kapiris K. (2005). Biology and Fisheries of Deep Water Rose Shrimp (Parapenaeus longirostris) in European Atlantic and Mediterranean waters. Crustaceana 78 (10): Conference Proceedings: Kapiris K., Kavadas S., Maina I., Tserpes G., Kallianiotis A., Peristeraki P., Politou C-Y. (2012). Spatial distribution of deep-water rose shrimp juveniles (Parapaenaeus longirostris) in the Aegean and Ionian Sea using predictive habitat modeling. 12th International Congress on the Zoogeography, Ecology and Evolution of Southeastern Europe and the Eastern Mediterranean, Athens, 18-22/6/2012, Book of Abstracts, 74 p. Kapiris K., Mytilineou Ch., Maiorano P., Kavadas S., Capezzuto F. (2002). Abundance and bathymetrical distribution of Parapenaeus longirostris in the South Ionian Sea. Fourth European Crustacean Conference, July, Poland. Mytilineou Ch., Politou C-Y., Kavadas S., Fourtouni A., Kapiris K., Dokos J. (2001). Crustacean fishery in Hellas. Life histories, assessment and management of Crustacean fisheries. A Coruna, Galicia, Spain. Book of abstracts 54. Book Chapter: Kapiris K., Mytilineou Ch., Politou C-Y., Kavadas S., Conides A. (2007). Research on shrimps resources and fishery in Hellenic waters. In: C. Papaconstantinou, A. Zenetos, V. Vassilopoulou, G. Tserpes (Eds.), HCMR Publications, Athens: Sokal RR., Rohlf F.J. (1981). Biometria, (Madrid: H. Blume Ediciones), 832 pp. Zar JH (1984) Biostatistical analysis, 2nd ed. Prentice-Hall, Englewood Cliffs, pp

237 PHYSICOMECHANICAL PROPERTIES OF BLACK MOUTH CROAKER SURIMI KAMABAKO GEL MADE FROM VARIOUS HYDROCOLLOIDS Hosseini S.E. 1*, Hosseini-Shekarabi S.P. 2 1 Department of Food Science and Technology, Science and Research Branch, Islamic Azad University, Tehran, Iran. 2 Department of Fisheries Science, Science and Research Branch, Islamic Azad University, Tehran, Iran. Abstract Black mouth croaker (Atrobucca nibe) species is one of the most important white-flesh fish stock in the Oman Sea. Kamabako gel samples with the addition of Iranian tragacanth gum (from Astragalusverus) (TG), xanthan gum (XG), chitosan (CS) and whey protein concentrate (WPC) at 1% (w/w) were prepared to evaluate their impacts as additives on the surimi, individually. Changes in the textural characteristics, expressible moisture content (EMC), color and microstructure features of the gels were determined. TG sample (555/50±29/698g), followed by WPC (503/00±8/16 g) showed the highest breaking force among other surimi kamabako gels (P<0.05). Adding hydrocolloids improved most parameters of texture profile analysis in comparison with control, except XG sample (P<0.05). CS sample showed the lowest EMC (5/58±29/698%) than others (P<0.05). Whiteness was improved significantly in TG sample (76.07±0.021) (P<0.05). Maximum and minimum number of polygonal structures in the microstructure surimi kamabako gels were observed in TG (13371±63.5 per mm2) and XG samples (7247±0.220 per mm2), respectively (P<0.05). Therefore TG at 1% could be a proper additive for producing of the high quality surimi, while the weakest protein network and gel strength were obtained in XG sample. Key words: black mouth croaker, gelatin, hydrocolloids, surimi, texture *Corresponding author: Seyed Ebrahim Hosseini (ebhoseini@srbiau.ac.ir) 1. Introduction Surimi is an intermediate product, which made by the removal of soluble proteins, pigments, lipids and other undesirable compounds of minced fish. Considering the high amount of myofibrillar protein in surimi, it has a unique capability to gel formation. Hence, quality of surimi is directly related to the gel-forming ability (Park, 1994; Benjakulet al., 2003a; Ramirez et al., 2011). Croakers (Family Scianidae) are mainly fish species for the production of surimi in Southeast Asia (Park, 2005). Additives to enhance the physical properties of surimi is common, however some of these additives have a negative impact on flavor, texture and color features of surimi kamabako gel and even may cause health problems (e.g. egg white and bovine plasma protein) (Rawdkuen & Benjakul, 2008; Balange & Benjakul, 2009). Using hydrocolloid as a food additive has been growing to enhance the gel-forming ability of surimi gel (Montero et al., 2000; Rawdkuen & Benjakul, 2008; Benjakul et al., 2003b) and may increase consumer acceptance of surimi-based products (Andrés-Bello et al., 2012). Several studies have investigated of gelling characteristics from different surimi fish by adding chitosan (Benjakulet al., 2002; Amiza & Kang, 2013), xanthan gum (Montero et al., 2000; Pérez-Mateos & Montero, 2000; Benjakulet al., 2003b; Santana et al., 2012) and whey protein concentrate (Piyachomkwan & Penner, 1995; Weerasingheet al., 1996; Rawdkuen & Benjakul, 2008). For instance, addition of whey protein concentrate was enhanced the textural properties and water holding capacity of surimi kamabako gels from 6 tropical fish species (Rawdkuen & Benjakul, 2008). Kataokaet al. (1998) found that addition of 1.5% chitosan improved the mechanical and functional properties of walleye Pollock surimi gel. Benjakulet al. (2003b) showed an approximately 24% increasing in breaking force of kamaboko surimi gel after addition of 1% prawn shell chitosan. Tragacanth gum is recorded in the GRAS list as a high quality hydrocolloid and naturally obtained from some Astragalus species (Imeson, 1992; Balaghiet al., 2010). Tragacanth gum recognized and used as a stabilizer, emulsifier, thickener and gel agent in foodstuffs for thousands of years (Anderson, 1989; Imeson, 1992; Mayes, 2010). However, so far nobody has reported the effect of tragacanth gum as an additive in surimi. 237

238 Generally, black mouth croaker (Atrobucca nibe) is abundant in the Oman Sea mid-water trawl fishery efforts and has small size. The aim of this study was to evaluate the gelling characteristics of surimi from black moth croaker which supplemented with xanthan gum, Iranian tragacanth gum, chitosan and whey protein concentrate at 1% (w/w). 2. Material and methods 2.1. Materials Black mouth croaker (A. nibe) caught by industrial trawler fishing vessel in the Oman Sea from the mesopelagic to deep water layers. Immediately after fishing, the samples (0.340±0.161g average weight) were gutted on board and kept on ice with a ratio of 1:2 (fish:ice w/w) during transportation to the laboratory. Iranian tragacanth gum was extracted from Astragalusverusthat native to the Golestan National Park (Golestan, Iran). Tragacanth gum samples were powdered using an electric grinder (Bosch, Germany) to uniform mesh size (particle size of 200 micron). Commercial cryoprotectant agents (sucrose, sorbitol and sodium tripolyphosphate mixture) from Sigma Aldrich Co., Ltd. (Dorset, UK), xanthan gum from Fufeng Co., Ltd. (Shandong, China), medium molecular weight chitosan (85% degree of deacetylation) from Sigma-Aldrich Co., Ltd. (Dorset, UK) and whey protein concentrate (36% crude protein) from Iranian Milk Industry (Tehran, Iran) were provided Surimi and Kamaboko gel preparation Surimi was produced as described by Lee (1984) with some modifications. Fish were filleted and deboned manually. The boneless white fish meat was minced by a meat mincer (Panasonic, France) with a mesh size of 3 mm. The minced meat was subjected to wash three times with a ratio of 3:1 (mince:water w/v), including two times with cold distilled water (4±2ºC) and once with cold dilute brine (0.3% sodium chloride). After each washing steps, the meat wrapped in a folded cheese cloth and squeezed manually. Eventually, commercial cryoprotectant agents (4% sucrose, 4% sorbitol and 0.3 % sodium tripolyphosphate w/w/w) were added to the dewatered fish paste by a mixer (Berjaya mixer, Malaysia) for a further 1 min. The produced surimi was packed in the zip luck polyethylene bags (500 g average weight) and freezed quickly by horizontal plate freezer (plate temperature -35 C) for 30 min, until the thermal core of samples reached at -25 C. The frozen surimi bags were maintained at -18±2 C prior to analysis (less than 1 month). For preparing kamaboko gels, frozen surimi was placed at refrigerator temperature (4±2 C) for 3-4 h to defrost before being cut into 2-3 cm3 cubes. Then, the small surimi pieces were chopped for 1 min using a food processor (FP 6001 Moulinex Food Processing, France) at medium speed to create homogeneous paste. During mixing, 2% sodium chloride (w/w) was sprinkled over the paste to soluble myofibrillar protein. Ice water (0 C) was also added to adjust the moisture content of the paste to 80% and the paste was chopped again for 1 min. At this stage, various hydrocolloids were added to the amount of 1% (w/w) directly. Chopping continued for a further 1 min with the temperature maintained cold (<5 C). The paste samples prepared above were stuffed into the common sausage casings (2.5 cm diameter) and both ends of each sample were sealed tightly. The samples were heated in a water bath (Memmert, Germany) at 40ºC for 30 min followed by 90ºC for 20 min. The cooked gel samples were quickly submerged in ice water (0 C) for 20 min to stop effect of heat on the samples texture. The gels were kept overnight (18±2 h) at refrigerator temperature (4±2ºC) for further experiments Puncture test Gel samples (20 25 mm) were equilibrated at room temperature (26-28ºC) for 30 min prior to determination of gel properties. Puncture test was carried out using a texture analyzer (CT3-4500, Brookfield Engineering Laboratories, USA) equipped with a stainless steel plunger (diameter 5 mm, load cell 25kg, cross-head speed of 60 mm/min). Breaking force (g), representing gel strength, and deformation (mm), illustrating elasticity/deformability, were recorded Texture Profile Analysis (TPA) TPA parameters of the gel samples were determined according to Hayes et al. (2005) with some modifications. Temperated gel samples (20 25 mm) were placed on a flat plate of the texture analyzer and were double compressed (50% of initial height, 25 Kg load cell and deformation rate 60 mm/min). The textural parameters like hardness-1, hardness-2, cohesiveness, springiness, gumminess and chewiness were determined from a typical force deformation curve as defined by Hayes et al. (2005) Determination of expressible moisture content (EMC) Expressible moisture content (EMC) of the kamaboko gel samples was performed according to Ng (1987) method. Briefly, a gel sample with a thickness of 5 mm was weighed (X in grams) and placed between two pieces of filter papers (Whatman filter paper no. 1, Maidstone, UK) at the top and 238

239 three pieces of the filter papers at the bottom. The standard weight (5 kg) was placed on the top of the sample and maintained for 2 min. The sample was then removed and weighed again (Y in grams). EMC was measured as follow: EMC (%) = (X Y) 100 X 2.6. Color evaluation Color parameters of the gels were performed by a colorimeter (HunterLabcolourflex, USA). L* (lightness), a* (redness/greenness) and b* (yellowness/ blueness) were measured and whiteness was calculated as described by Park (1994) as follow: Whiteness = 100 [ 100 L 2 + a 2 + b 2 ] 1/ Scanning electron microscope (SEM) Microstructure properties of the kamabako gel samples were visualized using a SEM (LEO 440i, Oxford, UK) at an accelerating voltage of 15 kv. The samples were cryo-fractured by Rawdkuen & Benjakul (2008) method. Briefly, the gels were cut (2-3 mm thickness) and fixed with 2.5% (v/v) glutaraldehyde in 0.2 M phosphate buffer (ph 7.2) for 2 h. Samples were then rinsed for 1 h in distilled water before being dehydrated in ethanol with a serial concentration of 50%, 70%, 80%, 90% and 100% (v/v). Prior to visualization, the dried samples were mounted around stubs perpendicularly using double sided adhesive tape, coated with gold and observed at the 50 magnifications. The SEM pictures were analyzed by the ImageJ program (ImageJ 1.48c, Wayne Rasband, National Institutes of Health, USA) to measure the number and area of the polygonal structures in the kamaboko gel networks Statistical analysis All experiments were done in triplicate. Data were analyzed by one-way analysis of variance (ANOVA) and significant differences between mean values using the SPSS program (SPSS, Inc. Version 15.0). The least significant difference test was used to find out significant differences between sample means. P-value of less than 5% was considered to be significant. Comparison between mean values was carried out by Duncan's multiple range tests. 3. Results and discussion 3.1. Gel strength Addition of different hydrocolloids significantly increased the gel-forming ability of the kamaboko gel samples compared to the control sample, except surimi kamabako gel composed with xanthan gum (Figure 1; P<0.05). Maximum breaking force (555.50± g) was observed in treatment TG (P<0.05). In another sense, a greater force required to penetrate the gel. In contrast, the minimum breaking force (288.00±2.828 g) and deformation (5.84±0.148 mm) were measured in the XG sample (P<0.05) which suggesting the weakest gel network. Breaking force of CS and WPC treatments were obtained without significant differences (p>0.05). b 239

240 Breaking force (g) Deformation (mm) HydroMedit 2014, November 13-15, Volos, Greece a f f ab ab ac ca 6 c ba C TG XG CS WPC C TG XG CS WPC Figure 1 Breaking force and deformation of kamaboko gels prepared from black mouth croaker surimi using different hydrocolloids. C, control (without hydrocolloid); TG, 1% tragacanth gum; CS, 1% chitosan; WPC, 1% whey protein concentrate and XG, 1% xanthan gum. Bars indicate the standard deviation (n=3). Different letters represent significant differences (P<0.05). From the results, addition of xanthan gum decreased 62% breaking force and 68% deformation of black mouth croaker surimi kamabako gel compared to the untreated sample. Similarly, Montero et al. (2000) reported that addition of xanthan gum reduced breaking force, deformation and textural parameters of cod surimi kamabako gel in comparison with control gel sample. The negative impact of xanthan gum on gel-forming ability was in agreement with several reports for surimi gel from other fish species comprising silver carp (Hasanpouret al., 2012) and blue whiting (Pérez-Mateos & Montero, 2000). Large pores and cavities in the surimi kamabako gel network are formed by xanthan gum due to the high molecular weight which was reflected lower values of surimi kamabako gel strength (Pérez-Mateos & Montero, 2000; Montero et al., 2000). In this study, chitosan and whey protein concentrate were both able to enhance the breaking force of the surimi kamabako gel in comparison to control. This result was in agreement with Kataokaet al. (1998) who indicated that the gel strength of walleye Pollock surimi kamabako gel was nearly doubled by the addition of 1.5% chitosan. The same results stated the increasing of surimi kamabako gel breaking force containing chitosan (Benjakulet al., 2003b; Kungsuwanet al., 2003). Chitosan has been reported to play an important role in cross-linkings of gel protein network induced by endogenous transglutaminase (TGase) (Benjakulet al., 2003b). Also, Rawdkuen & Benjakul (2008) indicated that low quality surimi kamabako gels were enhanced to strong and elastic gel (AA grade) by adding 0.5 to 2% WPC. Weerasingheet al. (1996) have demonstrated the WPC inhibitory effects on serine and cysteine proteinase enzymes of surimi which improved surimi kamabako gel quality. There is a lack of information about the effects of tragacanth gum on rheological-textural of surimi kamabako gel to compare with results of this study. However, tragacanth gum can rapidly reduce water in order to increase hydroxyl groups and hydrogen bonds with water molecules (Mayes, 2010). Therefore, surimi kamabako gel strength will be enhanced due to decrease of surimi kamabako gel water contents (Park et al., 2005) Textural properties The effect of various hydrocolloids on hardness, cohesiveness, chewiness and springiness of surimi kamaboko gel samples are shown in Table 1. Hardness-1 of all samples was higher than Hardness-2. Maximum and minimum hardness-1 and hardness-2 (maximum force in the first and 240

241 second stage of compression) were calculated in TG and XG samples, respectively (P<0.05). Cohesiveness parameter was similar in all samples except the XG sample. Table 1 Changes in textural parameters of kamaboko gels from black mouth croaker surimi using different hydrocolloids. C, control (without hydrocolloid); TG, 1% tragacanth gum; CS, 1% chitosan; WPC, 1% whey protein concentrate and XG, 1% xanthan gum. Samples Hardness 1 Hardness 2 Chewiness Springiness Cohesiveness (kgf) (kgf) (kgf/mm) (mm) C 2.01±0.232 a 1.85±0.235 c 0.73±0.014 bb 2.59±0.235 b 1.01±0.085 af TG 2.61±0.117 b 2.44±0.100 f 0.74±0.014 bb 2.93±0.280 bf 0.91±0.035 ff XG 1.82±0.080 c 1.48±0.057 aa 0.67±0.007 bd 1.97±0.209 ba 0.71±0.071 bb CS 2.14±0.074 d 1.97±0.078 ba 0.75±0.007 bb 2.59±0.214 b 1.13±0.049 dc WPC 2.40±0.205 f 2.25±0.209 ac 0.76±0.012 bb 2.83±0.235 cc 1.12±0.048 dc Different superscripts in the same column indicated significant differences (Mean ± SD, n=3, P<0.05) The results showed that TG sample had lower elasticity than CS and WPC samples (Tab 1). The decreased elasticity of TG sample was concomitant with their lower deformation. The firm and rigid gel assigned by the strong network generally losses its elasticity due to decrease the waterprotein interactions (Tanaka, 1981; Park et al., 2005). The presence of xanthan gum produced very soft gel and thus a decrease in surimi kamabako gel textural properties from different fish species were recorded (Montero et al., 2000; Ramirez et al., 2011; Hasanpouret al., 2012). Santana et al. (2012) showed that addition of 0.5% xanthan gum was able to decrease gel strength and hardness of threadfin bream surimi kamabako gel. Cohesiveness values close to 1 refer to the tendency of recovery to its original structure after the first compression is high (Munizaga & Canovas, 2004). In the present study, XG reduced cohesiveness value. From the results, WPC and chitosan were able to give ideal textural properties, respectively. Addition of 1% chitosan to grass carp surimi improved the hardness, springiness, cohesiveness, chewiness, and adhesiveness of the surimi gel texture (Wu & Mao, 2009). The same trend was observed in walleye Pollock surimi kamabako gel by adding 1.5% chitosan (Kataokaet al., 1998). Textural parameters of black mouth croaker surimi kamabako gel were improved by adding WPC (Tab 1). According to Rawdkuen & Benjakul (2008), proteolysis of surimi can be deferred by addition of whey protein concentrate (0.5-3%), leading to increased gel textural properties. Also, Benjakulet al. (2003c) reported that adding WPC into lizardfish surimi kamaboko gel inhibited the degradation of myosin heavy chain band (proteolysis of myofibrillar proteins) and caused the high quality gel Expressible moisture The lowest expressible moisture content was found in CS sample (P<0.05) suggesting the highest water holding capacity (Tab 2). Similarly, Mao & Wu (2009) reported that grass carp surimi kamabako gel containing 1% chitosan exhibited lower expressible moisture content than control sample, caused by increasing of chitosan-water interactions. XG sample had the highest expressible moisture (P<0.05), indicating that gel network was the lowest in water binding capacity in accordance with releasing more water from the protein network (Niwa, 1992). It is noted that xanthan gum entrapped lower released water by the myofibrillar protein (Montero et al., 2000; Hasanpouret al., 2012). Inhibitory effect of WPC on myofibrillar proteins was reported by many investigators (Kinoshita et al., 1990; Akazawaet al., 1993; Weerasingheet al., 1996; Benjakulet al., 2003c; Rawdkuen & Benjakul, 2008). In this research, WPC decreased the expressible moisture contents. Table 2 Expressible moisture and whiteness and of surimi kamabako gels from black mouth croaker with various hydrocolloids. Samples Expressible moisture (%) Whiteness C 6.71±0.159 a 74.10±0.006 fa TG 6.52±0.297 b 75.15±0.019 ac XG 13.50±0.519 c 75.12±0.003 ac CS 5.68±0.220 d 76.07±0.021 ad WPC 8.51±0.268 f 73.97±0.023 ab Different superscripts in the same column indicated significant differences (Mean ± SD, n=3, P<0.05) 241

242 3.4. Whiteness Slight differences in whiteness were recorded in different gels (Tab 2). In this study lustrous and translucent appearance of surimi kamabako gels were observed in CS sample (P<0.05). During cooking of kamaboko gels, not only lipid oxidation products may cause a decreased whiteness of gels but the Maillardnonenzymatic browning reaction may also affect the color of gels (Whistler & Daniel, 1985; Chaijanet al., 2004). However, chitosan showed a higher antioxidant capacity in surimi gel (No et al., 2007; Wu & Mao; 2009) which can improved whiteness of surimi kamabako gel. Furthermore, Mao & Wu (2007) reported that grass carp surimi gels with chitosan exhibited higher whiteness (72.26) than the untreated sample (63.81) due to chitosan-chitosan interactions and protein-chitosan cross-linking. The lowest whiteness was found in gel containing WPC (P<0.05). Similarly, addition of WPC at concentrations up to 3% (w/w) resulted in a decrease in whiteness of bigeye snapper, goatfish and threadfin bream surimi gel, due to its natural light cream-colored (Rawdkuen & Benjakul, 2008) Microstructure Kamaboko gels SEM and results of analyzing the images with ImageJ program are presented in Figure 2 and Table 3, respectively. Protein matrices of TG sample were observed denser and more compact in comparison to others (Figure 2; P<0.05). Secondly, WPC sample had a stronger and denser protein structure (Figure 2 and Tab 3). Conversely, the largest pores and maximum area of the polygonal structures (111.9±5.40 ιm2) were illustrated in XG (Tab 3; P<0.05). Figure 2 Microstructure of kamaboko gels from black mouth croaker using different hydrocolloids (50 magnification). C, control (without hydrocolloid); TG, 1% tragacanth gum; CS, 1% chitosan; WPC, 1% whey protein concentrate and XG, 1% xanthan gum. The surface microstructure of black mouth croaker kamaboko gel containing tragacanth gum associated the strong and rubbery gel texture due to increase in myofibrillar zones and small areas of polygonal. Oujifardet al. (2012) explained the best texture of threadfin bream surimi gel, with 0.25 g/100g bambara groundnut protein isolate, as one with a finer and coarse structure. Luoet al. (2004) showed similar results in Alaska pollocksurimi, with 10% soy protein isolate. In this study, the strong correlations between the textural parameters of surimi kamabako gel and microstructure attributes were observed. Whereas, XG sample allocated the lowest textural properties (Figure 2 and Tab 1) in order to weak protein network qualified with a number of smaller and larger polygonals in the microstructure (Figure 2 and Tab 2). Several investigators have explained the changes in textural properties are mainly correlated with myofibrillar protein microstructure 242

243 (Taguchi et al., 1987; Sano et al., 1988,1990). Consistent with the results, Alvarez et al. (1999) indicated that sardine surimi gel microstructure sample qualified with lower numbers of polygonals and larger cavities showed lower textural quality. Xanthan gum tends to aggregate upon itself, thus occupying large pores which would distort the myofibrillar protein matrix (Montero et al., 2000). In this study, improvement of gel microstructure attributes were found in the sample containing chitosan compared to control sample. It is recorded that stronger surimi kamabako gel protein-protein networks were formed by adding chitosan (Martin-Sanchez et al. 2009). Similar observation was made by Benjakulet al. (2000) and Kataoka (1998). Chitosan particles dispersed uniformly in the gel protein matrix markedly due to cross-linking reaction induced by endogenous TGase during heating of gel (Benjakulet al., 2000; Benjakulet al., 2003b). It was noted that chitosan might work as the filler in the gel network and associated with myofibrillar proteins via some electrostatic interactions (Muzzarelli, 1985). From the microstructure results, kamaboko gel containing added WPC was more compact with smaller clusters of aggregated protein than control and XG samples. Barbut & Foegeding (1993) indicated that finer and denser gels are usually formed by an ordered association of protein molecules. Similarly, Rawdkuen & Benjakul (2008) indicated that microstructure of kamaboko gels with WPC (0.5-3%), especially when a higher amount is used, had a compact gel matrix and fine threedimendimensional network compared to control (without WPC). Table 3 Parameters from SEM analysis of kamaboko gel samples from black mouth croaker using different hydrocolloids. C, control (without hydrocolloid); TG, 1% tragacanth gum; CS, 1% chitosan; WPC, 1% whey protein concentrate and XG, 1% xanthan gum. Samples Polygonal No. per Area of the polygonal structures mm 2 (ιm 2 ) C 10722±60.3 a 35.9±1.44 aa TG 13371±63.5 b 42.0±3.60 ac XG 7247±19.1 c 111.9±5.49 ad CS 16470±44.2 d 31.2±2.21 ba WPC 11117±12.9 ab 81.2±4.61 abc Different superscripts in the same column indicated significant differences (Mean ± SD, n=3, P<0.05). 4. Conclusion The addition of tragacanth gum, whey protein concentrate and chitosan at concentration of 1% (w/w) increased the breaking force and deformation of black mouth croaker kamaboko gel, respectively. The obtained results have shown that xanthan gum had a negative effect on the gelforming ability of the surimi kamabako gel. The ideal water holding capacity was found in the gel sample added with chitosan followed by tragacanth gum sample (P<0.05). Among the different treatments, WPC reduced the whiteness of surimi kamabako gel slightly due to its predominantly light cream-colored in nature. Kamaboko gel added with tragacanth had denser and more ordered myofibrillar structure than others. Further trials are necessary to to determine organoleptic effects of adding the various hydrocolloids in the surimi. References Akazawa, H., Miyauchi, Y., Sakurada, K., Wasson, D.H., Reppond, K.D. (1993). Evaluation of protease inhibitors in Pacific whiting surimi. Journal of Aquatic and Food Products Technology, 2(3), Amiza, M.A., Kang, W.C. (2013). Effect of chitosan on gelling properties, lipid oxidation, and microbial load of surimi gel made from African catfish (Clarias gariepinus). Food Research International, 20(4), Anderson, D.M.W. (1989). Evidence for the safty of gum tragacanth and modern criteria for the evaluation of food additives. Journal of Food Additives and Contaminants, 6, Andres-Bello, A., Iborra-Bernad, C., Garcia-Segovia, P., Martinez-Monzo, J. (2012). Effect of Konjac Glucomannan (KGM) and Carboxymethylcellulose (CMC) on some Physico-Chemical and Mechanical Properties of Restructured Gilthead Sea Bream (Sparus aurata) Products. Food Bioprocess Technology, 5, Balaghi, S., Mohammadifar, M.A., Zargaraan, A. (2010). Physicochemical and rheological characterization of gum tragacanth exudates from six species of Iranian Astragalus. Food Biophysics, 5(1),

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245 Park, S.H., Cho, S.Y., Kimura, M., Nozawa, H., Seki, N. (2005). Effects of microbial transglutaminase and starch on the thermal gelation of salted squid muscle paste. Fishries Science, 71, Park, J.W. (1994). Functional protein additives in surimi gels. Journal of Food Science, 59(3), Park, J.W. (2005). Surimi and Surimi Seafood. CRC Press, Boca Raton, Florida, p Perez-Mateos, M., Montero, P. (2000). Contribution of hydrocolloids to gelling properties of blue whiting muscle. European Food Research and Technology, 210, Piyachomkw,An K., Penner, M.H. (1995). Inhibition of Pacific whiting surimi-associated protease by whey protein concentrate. Journal of Food Biochemistry, 18, Ramirez, J.A., Uresti, R.M., Velazquez, G., Vazquez, M. (2011). Food hydrocolloids as additives to improve the mechanical and functional properties of fish products: A review. Food Hydrocolloids, 25, Rawdkuen, S., Benjakul, S. (2008). Whey protein concentrate: Autolysis inhibition and effects on the gel properties of surimi prepared from tropical fish. Food Chemistry, 106, Sano, T., Noguchi, S.F., Matsumoto, J.J., Tsuchiya, T. (1988). Dynamic viscoelastic behavior of natural actomyosin and myosin during thermal gelation. Journal of Food Science, 53(3), Sano, T., Noguchi, S.F., Matsumoto, J.J., Tsuchiya, T. (1990). Effect of ionic strength on dynamic viscoelastic behavior of myosin during thermal gelation. Journal of Food Science, 55(1), Santana, P., Huda, N., Yang, T.A. (2012). Gel characteristic of surimi powder added with hydrocolloids. UMT 11th International Annual Symposium on Sustainability Science and Management, Malaysia, p Taguchi, T., Ishizaka, H., Tanaka, M., Nagashima, Y., Amano, Y. (1987). Protein-protein interaction of fish myosin fragments. Journal of Food Science, 52 (4), Tanaka, T. (1981). Gels. American Journal of Science, 244, Weerasinghe, V.C., Morrissey, M.T., Chung, Y.C., An, H. (1996). Whey protein concentrate as a proteinase inhibitor in Pacific whiting surimi. Journal of Food Science, 61, Whistler, R.L., Daniel, J.R. (1985). Carbohydrates. In O.R. Fennema (eds), Food Chemistry, 2nd edn. Marcel Dekker, New York, p Wu, T., Mao, L. (2009). Application of chitosan to maintain the quality of kamaboko gels nade from grass carp (Ctenopharyngodon idellus) during storage. Journal of Food Processing and Preservation, 33,

246 SOME BIOLOGICAL CHARACTERISTICS OF BOGUE, Boops boops (Linnaeus, 1758) FROM BOKA KOTORSKA BAY, SOUTH ADRIATIC SEA (MONTENEGRO) Marković O. 1*, Djurović M., Pešić A., Ikica Z., Joksimović A. 1 Laboratory of Ichthyology and Marine Fishery, Institute of Marine Biology, University of Montenegro, P.O. Box 69, Kotor, Montenegro ABSTRACT The bogue, Boops boops (Linnaeus, 1758) is one of the commercially important species of the smallscale fishery in Montenegrin waters. A total of 283 specimens of bogue were collected by gill net and trammel net fishing between May 2013 and April 2014 in Boka Kotorska Bay (south Adriatic Sea). Total length ranged from 12.2 to 30.3 cm, while weight varied between and g. Female:male ratio was 2.6. A negative allometric growth was recorded for the all sampled specimen as well as for the both sexes. The highest gonadosomatic index value was in winter when Fulton's condition factor showed minimum value. Key words: Boops boops, small-scale fishery, Boka Kotorska Bay, South Adriatic Sea *Corresponding author: Olivera Marković ( omarkovic@ac.me) 1. Introduction One of the semi-pelagic species caught in Montenegrin territorial waters by vessels under 12 metres is bogue, Boops boops. During the sampling months, it was noted that bogue was mainly caught by gill and trammel nets. Gillnets are the most common type of fishing gear used in small scale fisheries, followed closely by trammel nets. Out of the 70 vessels registered, 71% operate in Boka Kotorska Bay (ports of Herceg Novi, Zelenika, Kotor and Tivat), the area where small scale fisheries, particularly those involving beach seines, have been present for centuries, and are part of the cultural identity of the people from the region. Around 61%, are vessels with length overall below 6 m, and the rest (39%) are in the 6 12 m segment (Ikica et al., 2013). Previous studies showed that significant quantities of bogue were caught by trawlers (Kasalica et al., 2011) and the few existing references concerning the species are from trawl fishery. The objective of this study was to gather some information of the length-weight relationship, length frequency distribution, sex ratio, spawning period and condition of bogue caught by the smallscale fishery in Boka Kotorska Bay. 2. Material and methods A total of 283 B. boops specimens (179 females; 68 males; 36 undetermined) were collected from monthly commercial catches using gill nets and trammel nets in the Boka Kotorska Bay, southern Adriatic Sea from May 2013 to April Sampling was conducted in the framework of the MORM-MONT national project (Monitoring of small-scale coastal fisheries and composition of fish fry with the aim of conservation and management of marine fishery resources). Collected fish were preserved with ice in a cooler box and immediately transported to the laboratory. Fish total length and body weight were measured to the nearest 0.1 cm and nearest 0.01 g, respectively. The general power equation (W = a*l b ) was applied to estimate the length-weight relationship, where a and b are constants whose values were estimated by the least square method. The significant difference of b values from 3, which represent isometric growth, was tested with the Student's t-test. Fulton s condition factor (K=100W/TL 3 ) (Fulton, 1904) was calculated for each specimen and for each season 246

247 (autumn, winter, spring and summer). Sex was assigned macroscopically. Gonads of all specimens were dissected and weighed to the nearest 0.01 g to calculate the GSI (GSI = weight of gonads/weight of fish x 100). This index was calculated for each of the analyzed specimen and, finally, a mean seasonal index was estimated. Correlation between GSI and Fulton's condition factor was examined using the Pearson's r coefficient. The sex ratio (female:male) was calculated and significant differences from the expected ratio (1:1) were tested by means of π 2 test. Maturity stages were recorded according to the MEDITS protocol: specimens were considered adult when classified as: 2b (recovering), 2c (maturing), 3 (mature/spawner), 4a (spent) and 4b (resting), while immature/juvenile ones were classified as 1 (immature virgin) and 2a (virgin developing) (ICES, 2008). 3. Results and Discussion Of the 283 collected specimens, 24% were males, 63.25% were females and 12.75% undetermined. Length frequency data for all collected specimen is presented in Figure 1. Total length of the sampled fish ranged from 12.2 to 30.3 cm TL with the mean length of cm TL. The body weight ranged between g and g. The mean observed length of the commercial catch of B. boops (17.35cm) was higher than that the value obtained in (13.95 cm: Marković et al., 2014) and almost the same with the value obtained in (17.10 cm; Kasalica et al, 2011). The lower value of the mean length in 2007/2008 could be explained by disappearance of larger fish from the catch and different fishing area because that catch was caught in the Montenegrin territorial waters and on continental shelf and significant quantities were caught by trawlers. The LFD of the whole sample (pooled data) shows that the majority of catches consisted of individuals ranging in length from 16.0 to 20.0 cm TL. The total length of females and males ranged from 12.2 to 30.3 cm (17.48 cm ± 2.91), and from 12.6 to 21.2 cm (17.61 ± 1.43), respectively. Females were more frequent at bigger size classes than males which is similar to what Mozara (2013) reports for the bogue in the southeastern Adriatic Sea. Gordo (1992) observed that the relative percentages of females increase with length class and he concluded that the bogue might be considered a rudimentary hermaphrodite species in which the majority of males develop from bisexual gonads in the juvenile stage (primary males) while a small proportion goes through sexual inversion (secondary males). Massaro (2012) reported the opposite situation, the predominance of females at the smaller sizes and the high number of males at larger sizes. So, we can conclude that variations of the sex ratio at different sizes are related to unequal rates of growth and mortality. The overall sex ratio during the study period was in favor of females (F/M=2.6). This ratio was significantly different from the expected value of 1:1 (ρ 2 =49.88, P < 0.01). High ratio of females in the catch may be caused by several factors related to the physiology and the ethology of the species, such as the age, a tendency for slower growth or a higher mortality rates in males (Desbrosses, 1933) as well as different catchability between two sexes. 247

248 Weight (g) Number HydroMedit 2014, November 13-15, Volos, Greece Total length (cm) Females Males Undetermined Figure 1. Length frequency distribution for Boops boops females, males and undetermined from the Boka Kotorska Bay, South Adriatic Sea The length-weight relationships of bogue was W=0.0338*L for females, W=0.0114*L for males and W=0.0218*L for the total sampled population (Figure 2). The b values were within the limits of reported by Froese (2006) and showed significant differences from 3. All relationships were statistically highly significant (r 2 > 0.85, P < 0.001). The length-weight relationship of B. boops shows a negative allometric growth which is not in agreement with various studies which indicated positive allometric growth or isometric growth (Petrakis & Stergiou, 1995; Özaydin & Taskavak, 2005, Massaro, 2012). Similar growth pattern was observed in Croatian waters (central and southeastern Adriatic) (Dulĉić & Glamuzina, 2006; Mozara, 2013) and in Egyptian Mediterranean waters off Alexandria (El-Okda, 2008). This variation in the b exponents for the same species could be attributed to differences in sampling, sample size or length ranges (Šantić et al., 2005) Males y = x R 2 = Females y = x R 2 = Females Males Total length (cm) Figure 2. Relationship between total length (TL) and body weight (W) in Boops boops (sexes separated) 248

249 GSI HydroMedit 2014, November 13-15, Volos, Greece The gonadosomatic index was used to determine the reproductive period and according to Tsikliras et al., (2013) it remains the best predictor of spawning period (i.e., onset and duration of spawning). The GSI reached maximum values in winter period and minimum in summer and autumn (Figure 3). Previous study on reproductive biology of bogue also observed that spawning activity occurred in winter season in Montenegrin waters (max GSI values for both sexes were recorded in February). (Kasalica et al., 2011). Both indices followed the same pattern. This time period is in line with reports in the literature on the maturity cycle of bogue in eastern Mediterranean (Vidalis, 1950; Hassan, 1990; Mozara, 2013) and eastern Atlantic (Gordo, 1995; Massaro, 2012). Alegria-Hernández (1990) found that the almost the entire population of bogue is spent in June from the mid-adriatic Dalmatian channels which is in agreement with our findings of post-spawning specimen in the early summer. The greatest number of specimen in stage 2c and stage 3 was in winter period as Massaro (2012) found in central-east Atlantic SPRING SUMMER AUTUMN WINTER Season Females Males Figure 3. Seasonal variation of mean GSI index by sex of bogue, B. boops Fulton's condition factor ranged from to Monthly changes of Fulton's condition factor showed a seasonal cycle with a peak in spring and minimum value in winter when the spawning begin. This factor and gonadosomatic index showed almost the same pattern, except in winter where they showed high negative correlation (r = ) (Figure 4). Mozara (2013) also found this negative correlation for bogue in southeastern Adriatic. Fulton's condition factor varied between season, with the highest value in spring probably caused by an inflow of nutrition and food as the sea temperatures increased. This high factor value could probably be attributed to ndividual recruits in spring using energy from food for both gonad development and muscle development. The condition factor normally decreases at the start of the spawning period due to very high metabolic rates. 249

250 GSI Fulton's condition factor HydroMedit 2014, November 13-15, Volos, Greece GSI Fulton SPRING SUMMER AUTUMN WINTER Season Figure 4. Fulton's condition factor and gonadosomatic index in bogue samples of the Boka Kotorska Bay (south Adriatic Sea), during May 2013-April 2014 In conclusion, this study provides the some useful information which are important data for the fisheries management. References Alegria-Hernández, V. (1990). Some aspects of reproductive biology of bogue (Boops boops L., Pisces Sparidae) from the Mid-Adriatic channels. Acta Adriatica., 31 (1/2): Desbrosses, P. (1933). Contribution a la biologie du rouget-barbet en Antlantique Nord (Contribution to the biology of red mullet in the North Atlantic). Revue des Travaux de l'office des Peches Maritimes, 6 (3): Dulĉić, J., Glamuzina, B. (2006). Length weight relationships for selected fish species from three eastern Adriatic estuarine systems (Croatia). Journal of Applied Ichthyology, 22 (4), El-Okda, N. I. (2008). Age and growth of Boops boops (L.) from Egyptian Mediterranean waters off Alexandria. Egyptian Journal of Aquatic Biology & Fisheries. Vol 12, No 1: Froese, R. (2006). Cube law, condition factor and weight-length relationships: History, meta-analysis and recommendations. Journal of Applied Ichthyology, 22, Fulton, T. W. (1904). The rate of growth of fishes. Twenty-second Annual Report, Part III. Fisheries Board of Scotland, Edinburgh, pp Gordo, L. S. (1992). Contribuição para o conhecimento da biologia e do estado de exploração do stock de boga (Boops boops Linné. 1758) da costa portuguesa. Faculdade de Ciências, Tese de Doutoramento, Lisboa, pp Gordo, L. S. (1995). On the sexual maturity of the bogue (Boops boops) (Teleostei, Sparidae) from the Portuguese coast. Scientia Marina, 59 (3-4): Hassan, M. W. A. (1990). Comparative biological studies between two species of family Sparidae, Boops boops and Boops salpa in Egyptian Mediterranean waters. M.Sc. Thesis, Faculty of Science, Alexandria University, pp ICES (2008). Report of Workshop on Maturity Ogive Estimation for Stock Assessment (WKMOG). 3 June 2008, Lisbon, Portugal, pp. 68. Ikica Z., Djurović M., Joksimović A., Mandić M., Marković O., Pešić A. (2012). Small-scale fisheries in Montenegro. In: AdriaMed Report of the AdriaMed Technical meeting on Adriatic Sea Small-scale Fisheries (Split, Croatia, 13th-14th November 2012). AdriaMed Technical Documents, 33: Kasalica, O., Regner, S., Djurović, M. (2011). Some aspects of the biology of the bogue, Boops boops (Linnaeus, 1758) in Montenegrin waters (south Adriatic Sea). Studia Marina, 25 (1):

251 Livadas, R. J. (1989). The growth and maturity of bogue (Boops boops L.), family Sparidae, in waters of Cyprus. F.A.O. Fisheries Report (412): Marković, O., Ikica, Z., Pešić, A., Joksimović, A., Djurović, M., Mandić, M. (2014). Length-weight relationship and condition factors of the bogue, Boops boops (Linnaeus, 1758) in the south Adriatic Sea (Montenegro). Natura Montenegrina 12 (3), in press. Massaro, A. (2012). Reproductive biology of bogue Boops boops (Linnaeus, 1758) off Gran Canaria (Canary Islands): a preliminary study. Phd in Sustainable Management of Fisheries Resources. Faculty of Marine Science, Universidad de Las Palmas de Gran Canaria, pp. 33. Mozara, R. (2013). Histological aspect of the reproductive cycle of bogue, Boops boops, (Linnaeus, 1758). Master in Mariculture. Department of Aquaculture, University of Dubrovnik, pp. 35. Özaydin, O, Taskavak, E. (2006) Length-weight relationship for 47 fish species from Izmir Bay (eastern Aegean Sea, Turkey). Acta Adriatica 47 (2): Petrakis, G., Stergiou, K. I. (1995). Weight-length relationships for 33 fish species in Greek waters. Fisheries Research, 21: Šantić, M., Pallaoro, A., Jardas, I. (2006). Co-variation of gonadosomatic index and parameters of length-weight relationships of Mediterranean horse mackerel, Trachurus mediterraneus (Steindachner, 1868), in the eastern Adriatic Sea. Journal of Applied Ichthyology, 22 (3): Tsikliras, A. C., Stergiou, K. I., Froese, R. (2013). Editorial note on reproductive biology of fishes. Acta Ichthyologica et Piscatoria., 43 (1): 1-5. Vidalis, E. (1950). Contribution to the study of the biology of the bogue (Boops boops Lin.) in Greek waters. Prak. Hell. Hidrobiol. Inst., 4 (1):

252 THE INVESTIGATION OF BROWN TROUT FEEDING REGIME IN TONEKABON RIVER Mehran Moslemi*, Department of Agrculture, Jouybar Branch, Islamic Azad University, Jouybar, Iran. * Corresponding author: m_moslemi1000@yahoo.com Abstract The present study was carried out from September during four seasons in Tonekabon River. Brown trout fish was fished from 5 stations with electeroshocker instrument. Toally, 91 fish were studied that number of female, male and unidentified was 40, 41 and 10, respectively. The age of fished fish varied from 1 to 3, and minimum and maximum of length in them were 41mm and 175mm, respectively. The identified preys present at fish stomaches were: Ephemeropera, Diptera, Liponeura, Simolium, Hydropsyche, coleopteran, Trichoptera, Flying insect, Spawn, Odonata, Oligochaeta, Plecoptera. In order to identify differences related to feeding in different sizes, fish were divided to three classes. Consumption percent of Hydropsyche and Liponeura had significant difference between three classes but the percentage of consumption of Ephemeroptera, plecophera and Simolum did not show significant difference between these three classes. Reproduction season of this fish is in fall (autumn). The maximum of feeding intensity was in spring and minimum was in summer and autumn. Classes 1 and >1 year old had higher feeding intensity than other classes (classes 2 and 3 years old). In general, Plecoptera, Ephemeroptera and Simolium constituted primary preys, but subordinate preys were consisted of Liponeura, Hydropsyche, dipteral, Trichoprera and Oligochaeta and also Coleoptera, Oligochaeta, Odonatan, flying insects and spawn constituted casual preys for this fish. The highest amount of prey for station 1, 2, 3, 4 and 5 were Simolium, Ephemeroptera, Simolium, Simolium and Liponeura, respectively. In regard to glutting stomach index (GSI) the station 2 was the highest followed by station 1, that both of them were located on Se-Hezar river. Key words: Feeding, Brown trout, Glutting stomach index Introduction Tonekabon river located at west part of Mazandaran because of physicochemical properties and Benthic material have life diversity and this river is one of the most watery (Hig-dischange) river in southern part of Mazandaran sea. This river is consisted of Do-Hezar, Se-Hezar and Valamrod rivers and in addition to aqous animals, various species of fish belonging to Salmoidae, Cyprinidae and Angailidae families live in it. Brown trout Salmo Trutta Fario is one of most important species in Tonekabon river that inhabits in interface ( where these two river connect each other) part of these river is considered as a native fish due to physicochemical properties and ecological condition [3]. This species have economical value and specially is one of the most popular for sportsman for angling [4, 8]. This thesis is on effort to identify feeding regim of this species in Tonekabon river. As we know. Feeding is one of the most important necessities of an organism. First order necessities of an organism (growth, development and reproduction) altogether conduct with consumed energy from food entered to body all of other energy-required processes in fish body accompolish with food consumption [10]. In aquaculture, fish feeding is of high importance, that everyone in encounter this issue in fishery industry for solving related issues. At present research on studying fish distribution of fish species [2, 9]. Designing of a logical ultimization method of commercial fish reserves is impossible without knowing a way that fish search its food resources and also without knowing the connection between the fish and other consumer of that food and the connection between predators [1, 6]. Understanding the type and composition of food organisms consumed by other competitors, amount and way of food consumption and linkage of feeding with time. Place and condition and some of other factors allow researches to achive a complete and comprehensive perspective of the life of studied 252

253 organisms [5]. Information and results from this investigation can be used to a better understanding of ecological condition of brown trout in the Tonekabon river. MATERIAL AND METHODS First Do-Hezar and Se-Hezar rivers in Tonekabon were divided to 5 stations and then fishing was conducted and these stations were investigated. Fishing was conduct using an electroshock instrument with power 1.7 KM with direct current (DC) and voltage V. Immediately after fishing, the fish were measured in regard to biometry properties, and then with cutting gullet(in throat)and cutting gut in rectum part the digestion apparatus was taken out of body and fixed in 70% alcohol. The following information were collected and recorded in sampling process. Total length, fork length, standard length, fish weight, stomach weight, gender determination, gonad weight, age determination, measuring of gut length. The fixed stomatchs were taken out from alcohol and rinsed with water and then placed in petridishes. The stomach was opened with and swallowed preys were identified carefully (Nafisi 1992). The type and number of prey and also percentage of prey groups recorded. The weight of stomach contents was also measured sexual maturity index was calculated from following formula as: Sexual maturity index = ((gonad weight/(body weight-entrails weight))*100 The relative length of gut, i. e gut length to body length ration, was calculated. Also GSI (Guttled stomach index) was calculated from following formula (Hynes 1970): GSI=stomach contents weight/body weight Results The average percentage of preys fed by brown trout during perfect period is as below: The frequency of primary, subordinate and casual preys for brown trout was calculated from the below formula: F p =N p *100/N 1 F p : prey frequency N p : number of N stomach than has P prey N 1 : number of investigated guttled stomach That, if F p has a value above 50 thus that prey is considered as primary prey, but if this value is between the prey is considered as subordinate prey and values below 10 are considered as casual preys. Results from this investigation were analyzed using variance analysis test. The amount of sexual maturity index in various seasons in male and female fish was calculated that following table shows it. Relative length of gut (RLG) in each of studied specimens was less than one that show the carnivore nature of this fish. Guttled stomach index in males and females was compared in different seasons as it has been shown in table 14. The maximum and minimum of guttled stomach index in males was in spring and autumn, respectively. Also, the maximum and minimum of guttled stomach index in females was in spring and summer, respectively. Discussion In order to better analysis of fish based on their age, fish were divided to three classes: Class1: fish bellow one year old and one year old Class2: two years old fish Class3: three years old fish Variance analysis test showed a significant difference between different classes for consumption of hydropsyche, but this test did not show significant difference between different 253

254 classes for consumption percentage of ephemeroptera. The high sexual maturity index in summer confirms that the spawning season in this fish is from mid-september to autumn. The mean of RLG in different classes was: Class one=0. 32, class two=0. 33, class three=0. 35 The maximum of guttled stomach index is in spring and the minimum of this index occurs in autumn and winter that these results are similar with Fasaic and Debeljal (1986) on brown trout in bager lake and lepenica river [7]. Also the reason of decreased feeding in summer and autumn (especially summer) compared to winter could be a high sexual maturity index in these seasons (summer and autumn). Results from feeding intensity between three classes 2 and 3. These finding confirm that brown trout in early stages of age feed more than later stages. The weight of stomach contents in smallest fish and larger classes have significant difference at 1% level, but the numbers of organisms in this level have not any significant differences. This confirms that brown trout catch larger prey if the prey size is increased. Also it was found that the frequency of consumed organisms during different seasons based on presence is changeable and this confirms that brown trout feed on most frequent and most wellknown prey. Presences of spawn in one of the samples also verify the selection factor based on presence of prey. Furthermore consumption of flying insects by brown trout in summer show that: first, this fish take some of its food (prey) at water level and second, feeding partially varies with season and presence of food(prey)because these land-living insects are scarce in other seasons [3, 8]. Table 1. average percentage of preys fed by brown trout during perfect period. percentage Prey Primary prey Simolium Primary prey Ephemeroptera Subordinate prey Liponeura Primary prey Plecoptera Subordinate prey 9.08 Hydropsyche Subordinate prey 1.58 Diptera Casual prey 0.78 Flying insecte Casual prey 0.73 Cleoptera Subordinate prey 0.53 Trichoptera Casual prey 0.30 Oligochaeta Casual prey 0.27 Odonata Casual prey 0.14 Spawn Table 2. the amount of sexual maturity index. winter autumn summer spring Sexual maturity index Male Female Average Table 3. Guttled stomach(gsi)index in males and females in different seasons. Winter autumn summer spring GSI male Female 254

255 References 1. Alp, A., Kara, C. and Buyukcapar, H. m, Age, growth and diet composition of the Resident Brown Trout, Salmo trutta macrostigma Dumeril 1858, in firniz stream of the River Ceyhan, Turkey. Turk. J. vel. Anem. Sci. 29: Bud, I. L. and Vladau, V. V., The geographic isolation impact on evolation of some morphophysiological features in the brown trout (Salmo trutta fario Linnaeus). AACL Bioflux, 1: Demir, o., Gumus, E., kucuk, F., Gunlu, A. and Kepenek., Some repreactive features of brown trout (Trout, Salmo trutta macrostigma Dumeril 1858) and its larval development under culture condition. Pak. Vet. Journal, 30(4): Fochetti, R., Argano, R. AND Tierno De Figueroa, J, M., Feeding ecology of various ageclasses of brown trout in River Nera, Central Itally. Belg. j. zool. 138(2): Kara, C., Alp, A., Gurlek, M. E., Morphological variation of the trouts (Salmo trutta and salmo platycephalus) in the rivers of Ceyhan, Seyhan and Euphrates, Turkey. Turkish journal Fisheries and Aquatic Sciences, 11: Nafisi, Mahmoud, The hand book of identification of invertebrate in running waters, project of bachelor, Tehran University, under supervision of Mohamadreza Ahmadi. 7. Ride ditmare, Fish and fishery, translated by Vosoghi G. and Ahmadi M., Markaz-e- Daneshgahi publication, pp Vosoghi, gholamhosein and Mostajir Behzad., Freshwater fish, Tehran University publication. 9. Sajadi, Masoud, The investigation of feeding regime in stizostedion luciaperca, M. S. thesis, Tehran University, under supervision Dr. Mohamad Reza Ahmadi. 10. Saidi, Ali asghar., Tonekabon River, fisheries Research centre, Mazandaran province. 255

256 INTERACTION BETWEEN FISH SPOILAGE BACTERIA AND PATHOGEN Yersinia enterocolitica IN SEA BREAM FILLETS AND MODEL SUBSTRATES Christodoulou C-E.P., Parlapani F.F, Boziaris I.S. 1 Department of Ichthyology and Aquatic Environment, School of Agricultural Science, University of Thessaly, Fitokou, 38446, Volos, Greece Abstract The population changes of total viable counts and spoilage microorganisms, such as Pseudomonas spp., H 2 S producing bacteria (Shewanella), Enterobacteriaceae and Lactic Acid Bacteria was investigated in sea bream fillets stored at 5 μ C under aerobic conditions. Σheir interaction with Yersinia enterocolitica was also investigated in a model fish substrate (sea bream juice agar) in mono- and cocultures. In sea bream fillets Pseudomonas spp., reached populations as high as (8-9 logarithmic cycles). In model fish substrate Pseudomonas spp. reached the higher population and exhibited the highest growth rates in monoculture. The results in co-culture showed that Pseudomonas spp. dominated against the other microorganisms. Lower populations observed for the pathogen microorganism Yersinia enterocolitica. However, the specific growth rate and the maximum population density of Yersinia enterocolitica were higher in co-cultures compared to monocultures, showing that the co-culture with the spoilage microorganisms favors its growth. Key words: Bacteria interaction, spoilage, specific spoilage organism, Yersinia enterocolitica, sea bream *Corresponding author: Christodoulou Christos-Elpidoforos (xelpsf@hotmail.com) ΑΛΛΖΛΔΠΗΓΡΑΖ ΑΛΛΟΗΟΓΧΝΧΝ ΜΗΚΡΟΟΡΓΑΝΗΜΧΝ ΗΥΘΤΧΝ ΚΑΗ ΣΟΤ ΠΑΘΟΓΟΝΟΤ Yersinia enterocolitica Δ ΦΗΛΔΣΑ ΣΗΠΟΤΡΑ ΚΑΗ ΜΟΝΣΔΛΟ ΤΠΟΣΡΧΜΑ Υξηζηνδνχινπ Υ-Δ.Π., Παξιαπάλε Φ.Φ., Μπνδηάξεο Η.. 1 Σιήια Γεςπμκίαξ Ηπεομθμβίαξ & Τδάηζκμο Πενζαάθθμκημξ, πμθή Γεςπμκζηχκ Δπζζηδιχκ, Πακεπζζηήιζμ Θεζζαθίαξ, μδυξ Φοηυημο, 38446, Βυθμξ, Δθθάδα. Πεξίιεςε Ζ παναημθμφεδζδ ηςκ πθδεοζιζαηχκ ιεηααμθχκ ηδξ μθζηήξ ιζηνμαζαηήξ πθςνίδαξ ηαζ ηςκ αθθμζςβυκςκ ιζηνμμνβακζζιχκ ηςκ ζπεφςκ [Pseudomonas spp., ααηηδνίςκ πμο πανάβμοκ οδνυεεζμ (Shewanella), Enterobacteriaceae ηαζ μλοβαθαηηζηχκ ααηηδνίςκ] ιεθεηήεδηακ ζε θζθέηα ηζζπμφναξ ζημοξ 5 μ C οπυ αενυαζεξ ζοκεήηεξ. Δπζπθέςκ δ αθθδθεπίδναζδ ημοξ ιε ημ ροπνυηνμθμ παεμβυκμ ιζηνμμνβακζζιυ Yersinia enterocolitica ιεθεηήεδηακ ζε ιμκμηαθθζένβεζεξ ηαζ ζοβηαθθζένβεζεξ ζε ιμκηέθμ οπυζηνςια, ημ μπμία απμηεθμφκηακ απυ γςιυ ηζζπμφναξ ηαζ άβαν. ηα θζθέηα, μ ιζηνμμνβακζζιυξ πμο έθηαζε ζε ιεβαθφηενμοξ θμβανίειμοξ ηδξ ηάλδξ 8 ιε 9 log(cfu/g) ήηακ ηα Pseudomonas spp. ηαζ απμηέθεζε ημκ επζηναηέζηενμ αθθμζςβυκμ ιζηνμμνβακζζιυ. ηα ιμκηέθα οπμζηνχιαηα, ανπζηά ζηζξ ιμκμηαθθζένβεζεξ ηα Pseudomonas spp., πανά ημ βεβμκυξ πςξ δεκ είπε ημ ιεβαθφηενμ εζδζηυ νοειυ αφλδζδξ, δ ηεθζηή ημο πθδεοζιζαηή ζοβηέκηνςζδ ήηακ ιεβαθφηενδ απυ υθμοξ ημοξ άθθμοξ ιζηνμμνβακζζιμφξ. ηζξ ζοβηαθθζένβεζεξ θάκδηε υηζ ηα Pseudomonas spp., εοκμήεδηε απυ ηζξ αθθδθεπζδνάζεζξ ηαζ ήηακ μ ιζηνμμνβακζζιυξ πμο επζηνάηδζε έκακηζ ηςκ άθθςκ, εκχ μ παεμβυκμξ ιζηνμμνβακζζιυξ Yersinia enterocolitica ζε υθεξ ηζξ πενζπηχζεζξ είπε ημκ παιδθυηενμ πθδεοζιυ. Χζηυζμ μ εζδζηυξ νοειυξ αφλδζδξ ηαζ δ ηεθζηή πθδεοζιζαηή ζοβηέκηνςζδ ηδξ Y.enterocolitica πήνακ ιεβαθφηενεξ ηζιέξ, ζε ζφβηνζζδ ιε ηζξ ηζιέξ υηακ ακαπηφπεδηε ζε ιμκμηαθθζένβεζα ηαζ θάκδηε κα εοκμείηαζ απυ ηδκ ζοκφπανλδ ιε ημοξ αθθμζςβυκμοξ ιζηνμμνβακζζιμφξ ηςκ ζπεφςκ. Λέμεηο θιεηδηά: βαθηεξηαθή αιιειεπίδξαζε, αιινίσζε, εηδηθνί αιινησγόλνη κηθξννξγαληζκνί, Yersinia enterocolitica, ηζηπνύξα *οββναθέαξ επζημζκςκίαξ: Υνζζημδμφθμο Υνήζημξ- Δθπζδμθυνμξ ( xelpsf@hotmail.com) 256

257 1. Δηζαγσγή Ο ηονζυηενμξ πανάβμκηαξ αθθμίςζδξ ηςκ ηνμθίιςκ, αθθά ηαζ πζμ ζοβηεηνζιέκα ηςκ κςπχκ αθζεοηζηχκ πνμσυκηςκ, είκαζ δ ακάπηολδ ηςκ αθθμζςβυκςκ ιζηνμμνβακζζιχκ. Ζ ακάπηολδ ηςκ ιζηνμμνβακζζιχκ οπμααειίγεζ ηονίςξ ηα μνβακμθδπηζηά παναηηδνζζηζηά θυβς ηζξ παναβςβήξ ιεηααμθζηχκ μζ μπμίμζ ηαεζζημφκ ηνυθζια αηαηάθθδθα πνμξ ηαηακάθςζδ (Huis in t Veld 1996, Gram & Dalgaard 2002). ηα αθζεοηζηά πνμσυκηα μζ ιζηνμμνβακζζιμί μζ μπμίμζ έπμοκ ηδκ ζηακυηδηα κα επζαζχκμοκ ηαζ κα ακαπηφζζμκηαζ ζε ιεβάθμοξ πθδεοζιμφξ ηαζ μζ μπμίμζ είκαζ δ ηφνζα αζηία απυννζρδξ ηςκ ζοβηεηνζιέκςκ ηνμθίιςκ, μκμιάγμκηαζ εζδζημί αθθμζςβυκμζ ιζηνμμνβακζζιμί (ΔΑΜ). Καεμνζζηζηυ νυθμ ζηδκ ακάπηολδ ηςκ ΔΑΜ παίγμοκ μζ ζοκεήηεξ απμεήηεοζδξ ημο πνμσυκημξ (Gram & Dalgaard 2002). Σα ηνυθζια είκαζ πζεακυκ κα επζιμθοκεμφκ ηαζ ιε παεμβυκμοξ ιζηνμμνβακζζιμφξ. Ζ Y.enterocolitica είκαζ έκα Gram ανκδηζηυ, πνμαζνεηζηά ακαενυαζμ ααηηήνζμ ανηεηά δζαδεδμιέκμ ααηηήνζμ ζηδ θφζδ ηαζ ζηα οδάηζκα μζημζοζηήιαηα, ηαζ θυβς ημο ροπνυηνμθμο παναηηήνα έπεζ παναηηδνζζηεί ςξ έκα δοκαιζηά ακαπηοζζυιεκμ παεμβυκμ ααηηήνζμ ζηα ηνυθζια ηαζ ζηα αθζεοηζηά πνμσυκηα (Davies et al., 2001). Ζ ζοιπενζθμνά ηςκ παεμβυκςκ ιζηνμμνβακζζιχκ ελανηάηαζ απυ δζάθμνμοξ εκδμβεκείξ (pζ, a w, ηηθ) ηαζ ελςβεκείξ πανάβμκηεξ (εενιμηναζία, ζφζηαζδ αηιυζθαζναξ) αθθά ηαζ απυ ημκ ακηαβςκζζιυ ηαζ αθθδθεπίδναζδ ιε ημοξ οπυθμζπμοξ ιζηνμμνβακζζιμφξ ημο ηνμθίιμο (Jay, 1997). ημπυξ ηδξ ζοβηεηνζιέκδξ ενβαζίαξ ήηακ δ ιεθέηδ ηδξ ζοιπενζθμνάξ ηδξ Y.enterocolitica πανμοζία ηςκ αθθμζμβχκςκ ιζηνμμνβακζζιχκ ηςκ αθζεοηζηχκ πνμσυκηςκ. 2. Τιηθά θαη Μέζνδνη Σα θζθέηα ηζζπμφναξ πνμιδεεφηδηακ απυ ηδκ ΓΗΑ ΑΔ. Σα ιμκηέθα οπμζηνχιαηα απυ γςιυ ηζζπμφναξ ηαζ άβαν πνμεημζιάζεδηακ ιεηά απυ ηνμπμπμίδζδ ηδξ ιεευδμο ηαηά Dalgaard (1995). Οζ ιζηνμμνβακζζιμί πμο πνδζζιμπμζήεδηακ βζα ημκ εκμθεαθιζζιυ ηςκ ιμκηέθςκ οπμζηνςιάηςκ είηε ζε ιμκμηαθθζένβεζεξ ή ζοβηαθθζένβεζεξ πνμέηορακ απυ ακακεςιέκεξ ηαθθζένβεζεξ ιίβιαημξ ιζηνμμνβακζζιχκ ιεηαλφ ηςκ μπμίςκ ήηακ ηα Pseudomonas spp. (Pseudomonas fluorescens, Pseudomonas fragi, Pseudomonas vranovensis, Pseudomonas migulae), μλοβαθαηηζηά ααηηήνζα (Carnobacterium maltaromaticum, Lactobacillus fuchuensis, Carnobacterium divergens), Shewanella putrefaciens ηαζ Y.enterocolitica (Y.enterocolitica CITY 650, Y.enterocolitica CITY 844) Ακά ηαηηά πνμκζηά δζαζηήιαηα θαιαάκμκηακ 10g θζθέημο ηζζπμφναξ ή 1g ιμκηέθμο οπμζηνχιαημξ εζξ ηνζπθμφκ ηαζ μιμβεκμπμζμφκηακ ιε δεηαπθάζζα πμζυηδηα απμζηεζνςιέκμο Maximum Recovery Diluent-MRD- 0,1% w/v πεπηυκδ ηαζ 0,85% w/v NaCl). ηδ ζοκέπεζα ιε ηδ ιέεμδμ ηςκ δζαδμπζηχκ αναζχζεςκ ιεηαθενυηακ 1ml δείβιαημξ ζε ζςθδκάηζα πμο πενζείπακ 9ml απμζηεζνςιέκμο MRD. Μεηά ηζξ δζαδμπζηέξ αναζχζεζξ πναβιαημπμζμφκηακ επίζηνςζδ ή εκζςιάηςζδ ηςκ ηνοαθίςκ βζα ηδκ ηαηαιέηνδζδ ηςκ ιζηνμμνβακζζιχκ. Οζ ιζηνμμνβακζζιμί πμο ιεθεηήεδηακ ηαζ ηαηαιεηνήεδηακ μζ πθδεοζιζαηέξ ιεηααμθέξ ημοξ, ήηακ μζ αηυθμοεμζ: Pseudomonas spp. ζε GSP Agar (Pseudomonas Aeromonas Agar), επχαζδ ηςκ ηνοαθίςκ ζημοξ 25 C βζα 1 διένα ηαζ ηαηαιέηνδζδ ηςκ ηυηηζκςκ απμζηζχκ. Βαηηήνζα πμο πανάβμοκ οδνυεεζμ (Shewanella) ζε Iron Agar, επχαζδ ηςκ ηνοαθίςκ ζημοξ 25 C βζα 2-3 διένεξ ηαζ ηαηαιέηνδζδ ηςκ ιαφνςκ απμζηζχκ. Ολοβαθαηηζηά ααηηήνζα ζε MRS Agar (Mann Rogosa Sharpe agar), επχαζδ ζε εενιμηναζία 25 C βζα 3-4 διένεξ. Enterobacteriaceae ζε VRBGA (Violet Red Bile Glucose Agar), επχαζδ ζε εενιμηναζία 37 C βζα 1 διένα. Οθζηή Μζηνμαζαηή Υθςνίδα ζε TSA (Tryptone Soy Agar), επχαζδ ηςκ ηνοαθίςκ ζημοξ 25 C βζα 2 διένεξ. Ζ Y.enterocolitica ζηα ιμκηέθα οπμζηνχιαηα απανζειήεδηε ζε VRBGA ιεηά απυ επχαζδ ζε εενιμηναζία 37 C βζα 1 διένα. Οζ ηζκδηζηέξ πανάιεηνμζ οπμθμβίζηδηακ ιεηά απυ πνμζανιμβή ηςκ πθδεοζιζαηχκ ιεηααμθχκ ιε ημ ιμκηέθμ ημο Baranyi (Baranyi & Roberts 1994). 3. Απνηειέζκαηα Απυ ηα απμηεθέζιαηα ηδξ ακάπηολδξ ηςκ αθθμζμβυκςκ ιζηνμμνβακζζιχκ ζηα θζθέηα ηζζπμφναξ πνμέηορε πςξ ηα Pseudomonas spp. είκαζ μ ηονζυηενμξ αθθμζςβυκμξ ιζηνμμνβακζζιυξ ηαεχξ ανέεδηε κα ακαπηφζζεηαζ ζε ιεβαθφηενμοξ πθδεοζιμφξ απ υθμοξ ημοξ οπυθμζπμοξ αθθμζςβυκμοξ ιζηνμμνβακζζιμφξ (Γνάθδια 1). Ο εζδζηυξ νοειυξ αφλδζδξ ηςκ Pseudomonas ήηακ 0,029±0,002 h -1, ηαεχξ επίζδξ οπμθμβίζηδηε πςξ είπε ιία θάζδ πνμζανιμβήξ ηδξ ηάλδξ ηςκ 14,910±0,000 h (Πίκαηαξ 1). 257

258 Γξάθεκα 1. Απεηθφληζε ηεο κεηαβνιήο ησλ πιεζπζκψλ ησλ αιινησγφλσλ κηθξννξγαληζκψλ ζε θηιέην ηζηπνχξαο, ζπληεξεκέλν ζηνπο 5 ν C ζε ζπλζήθεο αέξα. Σν εθάζηνηε ζεκείν απνηειεί ην κέζν φξν ηξηψλ επαλαιήςεσλ. Πίλαθαο 1. Παξνπζίαζε θηλεηηθψλ παξακέηξσλ ησλ κηθξννξγαληζκψλ ζηα θηιέηα ηζηπνχξαο. Μζηνμμνβακζζιμί Δζδζηυξ Ροειυξ Αφλδζδξ (h-1) Φάζδ πνμζανιμβήξ (h) Ανπζηυξ πθδεοζιυξ (logcfu/g) Σεθζηυξ πθδεοζιυξ (logcfu/g) OMX 0,035 ±0,001 4,590 ±0,017 9,330± 0,078 Pseudomonas spp. 0,029 ±0,002 14,910±0,000 5,550± 0,210 9,210±0,000 Enterobacteriaceae 0,048 ±0,003 41,580 ±0,594 3,250± 0,096 7,080 ±0,044 μλοβαθαηηζηά ααηηήνζα 0,020 ±0,000 1,710± 0,047 < 5,56 Shewanella spp. 0,027 ±0,001 3,230± 0,068 7,480± 0,045 ημ ιμκηέθμ οπυζηνςια, ζηζξ ιμκμηαθθζένβεζεξ ηςκ ιζηνμμνβακζζιχκ πνμέηορε πςξ υπςξ ηαζ ζηα θζθέηα έηζζ ηαζ εδχ μ ηονζυηενμξ αθθμζςβυκμξ ιζηνμμνβακζζιυξ είκαζ ηα Pseudomonas spp. (Γνάθδια 2α). Αλζμζδιείςημ είκαζ ημ βεβμκυξ πςξ πανά ημ υηζ ηα Pseudomonas spp. ζηζξ ιμκμηαθθζένβεζεξ είπε ηζξ ιεβαθφηενεξ πθδεοζιζαηέξ ζοβηεκηνχζεζξ, δεκ πανμοζίαζε ημ ιεβαθφηενμ νοειυ αφλδζδξ (Πίκαηαξ 2) ηδ ζοβηαθθζένβεζα ηςκ ηνζχκ αθθμζςβυκςκ ιζηνμμνβακζζιχκ ιαγί ιε ημ παεμβυκμ, δζαπζζηχεδηε πςξ, ηδ ιεβαθφηενδ ηεθζηή ζοβηέκηνςζδ πανμοζίαζε ηα Pseudomonas spp., εκχ δ Y.enterocolitica πανμοζίαζε ηδ παιδθυηενδ ηεθζηή ζοβηέκηνςζδ (Γνάθδια 2α). Γζαπζζηχεδηε πςξ μ εζδζηυξ νοειυξ αφλδζδξ, αθθά ηαζ μ ηεθζηυξ ιζηνμαζαηυξ πθδεοζιυξ ημο παεμβυκμο ιζηνμμνβακζζιμφ Y.enterocolitica ήηακ ιεβαθφηενμξ απυ ημκ ακηίζημζπμ ηδξ ιμκμηαθθζένβεζαξ ημο, βεβμκυξ πμο ιανηονά πςξ εοκμήεδηε απυ ηδκ αθθδθεπίδναζδ ιε ημοξ αθθμζςβυκμοξ ιζηνμμνβακζζιμφξ ηςκ ζπεφςκ, πανυθμ αοηά πανμοζίαζε ηζξ παιδθυηενεξ πθδεοζιζαηέξ ζοβηεκηνχζεζξ (Πίκαηαξ 2). 4. πδήηεζε ηα θζθέηα ηζζπμφναξ, μ ηφνζμξ αθθμζςβυκμξ ιζηνμμνβακζζιυξ ήηακ ημ Pseudomonas spp., ημ μπμίμ ένπεηαζ ζε ζοιθςκία ιε πνμδβμφιεκεξ ιεθέηεξ ζπεηζηέξ ιε ηα αθζεφιαηα ηδξ Μεζμβείμο πμο απμεδηεφμκηαζ οπυ ρφλδ ζε αενυαζεξ ζοκεήηεξ (Koutsoumanis & Nychas 1999, Parlapani et al. 2013). Καηά ηδκ ακάθοζδ ηαζ ηδ ιεθέηδ ηςκ απμηεθεζιάηςκ ζηα ιμκηέθα οπμζηνχιαηα, δζαπζζηχεδηε πςξ ζηα δείβιαηα ηα μπμία ήηακ ζε ιμκμηαθθζένβεζα ηα Pseudomonas spp. είπε ηζξ ιεβαθφηενεξ πθδεοζιζαηέξ ιεηααμθέξ. Καηά ηδ ζοβηαθθζένβεζα υθςκ ηςκ αθθμζςβυκςκ ηαζ ημο παεμβυκμο ιζηνμμνβακζζιμφ ιαγί, θάκδηε πςξ ηαζ ζε εηείκδ ηδκ πενίπηςζδ ηα Pseudomonas spp. απμηέθεζε ημκ ηονίανπμ ιζηνμμνβακζζιυ. Κάηζ ηέημζμ επζαεααζχκεηαζ ηαζ απυ ηδκ αζαθζμβναθία, ηαεχξ ζε ιεθέηδ πμο πναβιαημπμζήεδηε απυ ηδ Gram et al. (2002) ακαθένεηαζ πςξ υηακ ακαπηοπεμφκ ζε ζοβηαθθζένβεζα ηα Pseudomonas spp. ηαζ ημ Shewanella putrefaciens, ηα Pseudomonas spp. έπεζ ηδλ ζηακυηδηα κα δεζιεφεζ ζίδδνμ ηαζ κα ακαζηέθθεζ ηδκ ακάπηολδ ημο 258

259 S.putrefaciens. Ο παεμβυκμξ ιζηνμμνβακζζιυξ Y.enterocolitica, πανμοζίαζε ηζξ παιδθυηενεξ πθδεοζιζαηέξ ηζιέξ, βεβμκυξ πμο επζαεααζχκεηαζ ηαζ απυ άθθεξ ιεθέηεξ (Douglas et al. 1991,Vermeiren et al. 2006). (α) (β) Γξάθεκα 2. Γξαθηθή απεηθφληζε ηεο κεηαβνιήο ησλ πιεζπζκψλ ησλ Pseudomonas spp., Y. enterocolitica, νμπγαιαθηηθψλ βαθηεξίσλ (LAB) θαη Shewanella, ζε κνλνθαιιηέξγεηα (α) θαη ζε ζπγθαιιηέξγεηα (β), ζε κνληέιν ππφζηξσκα, ζηνπο 5 ν C ζε ζπλζήθεο αέξα. Σν εθάζηνηε ζεκείν απνηειεί ην κέζν φξν ηξηψλ επαλαιήςεσλ. Πίλαθαο 2. Παξνπζίαζε ησλ θηλεηηθψλ παξακέηξσλ ησλ κηθξννξγαληζκψλ ζην κνληέιν ππφζηξσκα. Δζδζηυξ Μζηνμμνβακζζιμί Ροειυξ Αφλδζδξ (h -1 ) Φάζδ πνμζανιμβήξ (h) Ανπζηυξ πθδεοζιυξ (logcfu/g) Σεθζηυξ πθδεοζιυξ (logcfu/g) ιμκμηαθθζένβεζεξ Pseudomonas spp. 0,049±0,001 9,960 ±0,758 3,940±0,080 9,270±0,023 Yersinia enterocolitica 0,031±0,001 0,0 2,149±0,023 <7,42 Shewanella putrefaciens 0,051±0,001 32,027±1,151 3,410±0,054 8,440±0,138 μλοβαθαηηζηά ααηηήνζα 0,046±0,001 0,0 3,650±0,071 8,220±0,114 ζοβηαθθζένβεζα Pseudomonas spp. 0,048±0,003 0,0 3,430±0,267 9,550±0,

260 Yersinia enterocolitica 0,035±0,001 11,710±0,000 3,110±0,067 7,940±0,029 μλοβαθαηηζηά ααηηήνζα 0,039±0,002 43,870±7,340 3,510±0,023 <9,32 Shewanella putrefaciens 0,034±0,006 68,720±1,530 3,620±0,531 <8,52 Βηβιηνγξαθία Baranyi, J., Roberts, T.A. (1994). A dynamic approach to predicting bacterial growth in food. International Journal of Food Microbiology. 23, Dalgaard P. (1995). Qualitative and quantitative characterization of spoilage bacteria from packed fish. International Journal of Food Microbiology, 26, Davies A.R., Capell C., Jehanno D., Nychas G.J.E., Kirby R.M. (2001). Incidence of foodborne pathogens on European fish. Food Control, 12, Douglas L.M., Schmidt R.H. (1991). Physiological evaluation of stimulated growth of Listeria monocytogenes by Pseudomonas species in milk. Canadian Journal of Microbiology, 37, Gram L., Dalgaard P. (2002). Fish spoilage bacteria problems and solutions. Current Opinion in Biotechnology, 13, Gram L., Ravn L., Rasch M., Bruhn J.B., Christensen A.B., Givskov M. (2002). Food spoilage interactions between food spoilage bacteria. International Journal of Food Microbiology, 78, Jay J.M. (1997). Do background microorganisms play a role in the safety of fresh foods? Trends in Food Science and Technology 8, Huis in t Veld J.H.J. (1996). Microbial and biochemical spoilage of foods: an overview. International Journal of Food Microbiology, 33, Koutsoumanis K., Nychas G-J.E. (1999). Chemical and Sensory Changes Associated with Microbial Flora of Mediterranean Boque (Boops boops) Stored Aerobically at 0, 3, 7, and 10 C. Applied and Environmental Microbiology, 65, Parlapani F.F. Meziti A., Kormas K.Ar., Boziaris I.S. (2013). Indigenous and spoilage microbiota on farmed sea bream stored in ice indentified by phenotypic and 16S rrna gene analysis. Food Microbiology 33, Vermeiren L., Devlieghere F., Vandekinderen I., Debevere J. (2006). The interaction of the nonbacteriocinogenic Lactobacillus sakei 10A and lactocin S producing Lactobacillus sakei 148 towards Listeria monocytogenes on a model cooked ham. Food Microbiology, 23,

261 ORAL PRESENTATIONS IN GREEK PRELIMINARY RESULTS ON AGE AND GROWTH OF COMMON PANDORA (Pagellus erythrinus) IN THE SOUTHERN AEGEAN SEA Lampri P-N. *, Bekas P., Dogrammatzi A., Mytilineou Ch. Hellenic Centre for Marine Research, Institute of Biological Resources and inland Waters, Anavyssos, Attiki, Greece Abstract The aim of the present study was the evaluation of age and growth parameters in common pandora (Pagellus erythrinus) in the Southern Aegean Sea. In total, 189 individuals were studied. Total length (TL) ranged from 63 to 488 mm. The length-weight relationship was investigated and showed that the species is characterized by slightly negative allometry (b=2.96). Ages were estimated by counting the annual rings on otoliths, with specimens ranging in age from 0+ to 14 years (11 age classes). The exponential growth model von Bertalanffy was fitted to the observed TL, as well as to the mean backcalculated length values of each age class. The parameters of growth were estimated to be: TL =545.8, k=0.098 year -1, t 0 = years and TL =719.8, k= year -1, t 0 = years, respectively. The estimates of the phi-prime Φ for the Southern Aegean Sea were found to be close to the estimates of other studies and especially, to those studies conducted in the West Mediterranean and Eastern Atlantic. Keywords: Pagellus erythrinus, otoliths, length weight relationship, growth parameters, age * Corresponding author: Lampri Paraskevi Niki (lampri@hcmr.gr) ΠΡΟΚΑΣΑΡΚΣΗΚΑ ΑΠΟΣΔΛΔΜΑΣΑ ΑΠΟ ΣΖ ΜΔΛΔΣΖ ΣΖ ΖΛΗΚΗΑ ΚΑΗ ΑΤΞΖΖ ΣΟΤ ΛΤΘΡΗΝΗΟΤ (Pagellus erythrinus) ΣΟ ΝΟΣΗΟ ΑΗΓΑΗΟ ΠΔΛΑΓΟ Λάκπξε Π-Ν. *, Μπέθαο Π., Νηνγξακκαηδή Α., Μπηηιελαίνπ Υ. Δθθδκζηυ Κέκηνμ Θαθάζζζςκ Δνεοκχκ, Ηκζηζημφημ Θαθάζζζςκ Βζμθμβζηχκ Πυνςκ ηαζ Δζςηενζηχκ Τδάηςκ, Ακάαοζζμξ Αηηζηή Πεξίιεςε ημπυξ ηδξ πανμφζαξ ενβαζίαξ ήηακ δ δζενεφκδζδ ηδξ δθζηίαξ ηαζ ηςκ παναιέηνςκ αφλδζδξ ζημ θοενίκζ (Pagellus erythrinus) ζηδκ πενζμπή ημο Νυηζμο Αζβαίμο. Δλεηάζηδηακ ζοκμθζηά 189 άημια. Σμ μθζηυ ιήημξ (TL) ηςκ αηυιςκ ηοιάκεδηε απυ 63 έςξ 488 mm. Ζ ζπέζδ αάνμοξ ιήημοξ πμο ελεηάζηδηε, έδεζλε υηζ ημ θοενίκζ πανμοζζάγεζ ζπεηζηά ιζηνή ανκδηζηή αθθμιεηνία (b=2,96). Απυ ηδκ ακάβκςζδ ηςκ εηδζίςκ δαηηοθίςκ πνμζδζμνίζηδηακ ζοκμθζηά 11 δθζηζαηέξ ηθάζεζξ (ιέβζζηδ δθζηία 14 εηχκ). Σμ εηεεηζηυ ιμκηέθμ αφλδζδξ Von Bertalanffy εθανιυζηδηε βζα ηα παναηδνμφιεκα ηαζ ηα ιέζα ακαδνμιζηά ιήηδ ηδξ ηάεε δθζηίαξ. Οζ πανάιεηνμζ αφλδζδξ οπμθμβίζηδηακ ςξ ελήξ: TL =545,8, k=0.098 year -1, t 0 =-1,802 years ηαζ TL =719,8, k= year -1, t 0 =-1,718 years, ακηζζημίπςξ. Οζ ηζιέξ ημο ζοκηεθεζηή μθμηθήνςζδξ ηδξ αφλδζδξ Φ βζα ημκ Νυηζμ Αζβαίμ ανέεδηακ πανυιμζεξ ιε αοηέξ άθθςκ ιεθεηχκ, ζδζαίηενα ιε ηζξ ηζιέξ πμο οπμθμβίζηδηακ ζε Γοηζηή Μεζυβεζμ ηαζ Ακαημθζηυ Αηθακηζηυ. Λέλεζξ ηθεζδζά: Pagellus erythrinus, ςηυθζεμζ, ζπέζδ αάνμοξ-ιήημοξ, πανάιεηνμζ αφλδζδξ, δθζηία * οββναθέαξ επζημζκςκίαξ: Λάιπνδ Παναζηεοή Νίηδ (lampri@hcmr.gr) 1.Δηζαγσγή Ζ ιεθέηδ ηςκ αζμθμβζηχκ παναηηδνζζηζηχκ ηςκ ειπμνζηχκ αεκεμπεθαβζηχκ ρανζχκ ζοιαάθθεζ ζηδκ ζςζηυηενδ εηιεηάθθεοζδ ηςκ απμεειάηςκ ημοξ ηαζ ζηδκ εέζπζζδ απμδμηζηυηενςκ 261

262 υχνότητα (Ν) HydroMedit 2014, November 13-15, Volos, Greece δζαπεζνζζηζηχκ ιέηνςκ βζα ηδκ πνμζηαζία ημοξ (Caddy 1993). οβηεηνζιέκα, δ εηηίιδζδ ηδξ δθζηίαξ ηςκ εζδχκ ηαζ δ πενζβναθή ηςκ πνμηφπςκ αφλδζήξ ημοξ είκαζ απαναίηδηα ζημζπεία βζα ηδκ ηαθφηενδ δζαπείνζζδ ηςκ απμεειάηςκ ημοξ. Σμ θοενίκζ (Pagellus erythrinus) απμηεθεί έκα ζδιακηζηυ αεκεμπεθαβζηυ είδμξ ειπμνζηήξ αλίαξ ιε εονεία βεςβναθζηή ελάπθςζδ απυ ηδ Μαφνδ Θάθαζζα, ζε υθδ ηδ Μεζυβεζμ ηαζ ζηα ακαημθζηά πανάθζα ημο Αηθακηζημφ ςηεακμφ (Fischer et al. 1987). Ο ζημπυξ ηδξ πανμφζαξ ένεοκαξ ήηακ δ ιεθέηδ ηδξ ζπέζδξ ιήημοξ-αάνμοξ ηαζ δ εηηίιδζδ ηδξ δθζηίαξ ηαζ ηςκ παναιέηνςκ αφλδζδξ ημο θοενζκζμφ ζημ Νυηζμ Αζβαίμ Πέθαβμξ. 2. Τιηθά θαη Μέζνδνη Σα δείβιαηα πμο πνδζζιμπμζήεδηακ βζα ηδκ ηαηά ιήημξ ζφκεεζδ ημο θοενζκζμφ ααζίζηδηακ ζηα ζημζπεία ειπμνζηήξ αθζείαξ ημο «Δεκζημφ Πνμβνάιιαημξ οθθμβήξ Αθζεοηζηχκ Γεδμιέκςκ 2013», εκχ μζ οπυθμζπεξ ακαθφζεζξ ζηδνίπεδηακ ζηδ αζμθμβζηή δεζβιαημθδρία ημο ίδζμο πνμβνάιιαημξ. οκμθζηά, ζοθθέπεδηακ 189 άημια θοενζκζμφ απυ δζάθμνα αθζεοηζηά ενβαθεία (ιδπακυηναηα, παναβάδζ, ιακςιέκα ηαζ απθάδζα) ηδκ πενίμδμ Οηηςανίμο-Γεηειανίμο 2013, ζημ Νυηζμ Αζβαίμ πέθαβμξ. ε υθα ηα άημια ιεηνήεδηε ημ μθζηυ ιήημξ (TL) ζε mm, γοβίζηδηε ημ μθζηυ αάνμξ (W) ζε g ηαζ πνμζδζμνίζηδηε ημ θφθμ ηαζ ημ ζηάδζμ βεκκδηζηήξ ςνζιυηδηαξ ζφιθςκα ιε ηδκ ηθίιαηα Nikolsky (1963). Απυ ηάεε άημιμ αθαζνέεδηακ μζ ςηυθζεμζ ηαζ αθμφ ηαεανίζηδηακ, θςημβναθήεδηε δ ελςηενζηή ημοξ πθεονά. Οζ θςημβναθίεξ ηςκ ανζζηενχκ ςημθίεςκ πνδζζιμπμζήεδηακ βζα ηδκ ακάβκςζδ δθζηίαξ απυ ηνεζξ δζαθμνεηζημφξ ενεοκδηέξ. Ζ ακάβκςζδ ηδξ δθζηίαξ (t) ααζίζηδηε ζημκ πνμζδζμνζζιυ ηςκ εηδζίςκ δαηηοθίςκ ηςκ ςημθίεςκ, δδθαδή ηςκ αδζαθακχκ γςκχκ πμο ακηζζημζπμφκ ζηζξ πενζυδμοξ ανβήξ αφλδζδξ ημο είδμοξ. ε ηάεε ςηυθζεμ ιεηνήεδηε δ αηηίκα ημο (R) ηαζ μζ αηηίκεξ ηςκ επζιένμοξ εηδζίςκ δαηηοθίςκ (R 1,R 2 R n ). Δπεζδή παναηδνήεδηε ζδιακηζηή επζηνάηδζδ ηςκ εδθοηχκ αηυιςκ ζηα δείβιαηα, μζ ακαθφζεζξ έβζκακ ηαζ βζα ηα δφμ θφθα ιαγί. Ζ απεζηυκζζδ ηδξ ηαηά ιήημοξ ζφκεεζδξ έβζκε ζε ηθάζεζξ ιήημοξ 10 mm TL. Ζ ζπέζδ αάνμοξ ιήημοξ ζημ είδμξ πενζβνάθδηε απυ ημ ιμκηέθμ W=aL b. Δλεηάγμκηαξ ηδ ζπέζδ ιήημξ ρανζμφ μθζηή αηηίκα ςημθίεμο, οπμθμβίζηδηακ μζ ιέζεξ ακαδνμιζηέξ ηζιέξ μθζημφ ιήημοξ ακά δθζηία. Οζ πανάιεηνμζ αφλδζδξ ζημ θοενίκζ οπμθμβίζηδηακ ιε αάζδ ηδκ ελίζςζδ von Bertalanffy L=L (1-e -k(t-to) ) (Bertalanffy 1938) πνδζζιμπμζχκηαξ: 1) ηα παναηδνδιέκα ιήηδ ιε ηζξ ακηίζημζπεξ δθζηίεξ ημοξ ηαζ 2) ηα ιέζα ακαδνμιζηά ιήηδ ηδξ ηάεε δθζηίαξ. Γζα κα ζοβηνζεμφκ μζ πανάιεηνμζ αφλδζδξ πμο πνμέηορακ απυ ηδκ ελίζςζδ Von Bertalanffy, οπμθμβίζηδηε μ ζοκηεθεζηήξ μθμηθήνςζδξ ηδξ αφλδζδξ Φ απυ ηδ ζπέζδ: Φ = log k + 2 log L ιεηαηνέπμκηαξ ημ TL απυ mm ζε cm (Pauli & Munro 1984). 3. Απνηειέζκαηα Ζ ζοκμθζηή ηαηά ιήημξ ζφκεεζδ ημο θοενζκζμφ ζημ Νυηζμ Αζβαίμ πανμοζζάγεηαζ ζημ πήια 1. Σμ εφνμξ ηζιχκ ημο μθζημφ ιήημοξ ηοιάκεδηε απυ 63 έςξ 488 mm, ιε ημ ιεβαθφηενμ πμζμζηυ αηυιςκ κα ηαηακέιεηαζ ιεηαλφ ηςκ ηθάζεςκ mm Κλάςεισ μήκουσ (mm) ρήκα 1: πλνιηθή θαηά κήθνο ζχλζεζε ηνπ ιπζξηληνχ (Pagellus erythrinus) ζην Νφηην Αηγαίν πέιαγνο. Ζ ζπέζδ αάνμοξ ιήημοξ ηςκ αηυιςκ ημο θοενζκζμφ πενζβνάθεηαζ απυ ημ ιμκηέθμ εηεεηζηήξ αφλδζδξ W= *TL , (R 2 = , N=189) (πήια 2). 262

263 W (g) HydroMedit 2014, November 13-15, Volos, Greece TL (mm) ρέζε 2 : ρέζε βάξνπο κήθνπο ηνπ ιπζξηληνχ (Pagellus erythrinus) ζην Νφηην Αηγαίν πέιαγνο. οκμθζηά μ πνμζδζμνζζιυξ ηςκ δαηηοθίςκ ηαζ δ ακάβκςζδ ηδξ δθζηίαξ ήηακ δοκαηή ζε 185 ςηυθζεμοξ. Ακαβκςνίζηδηακ 11 δθζηζαηέξ ηθάζεζξ ζημ θοενίκζ ιε ηδκ δθζηία κα ηοιαίκεηαζ απυ 0+ έςξ 14 πνυκζα. Καευηζ δε ανέεδηακ άημια δθζηίαξ πνμκχκ, μζ πανάιεηνμζ αφλδζδξ οπμθμβίζηδηακ θαιαάκμκηαξ οπυρδ ηζξ δθζηίεξ 0 9 ή 0 14 πνμκχκ, ηυζμ βζα ηα παναηδνμφιεκα ιήηδ υζμ ηαζ βζα ηα ιέζα ακαδνμιζηά. Οζ πανάιεηνμζ αφλδζδξ ιε αάζδ ημ ιμκηέθμ von Bertalanffy, ηαεχξ ηαζ μζ ηζιέξ ημο ζοκηεθεζηή Φ πανμοζζάγμκηαζ ζημκ Πίκαηα 1. Πίλαθαο 1: Παξάκεηξνη αχμεζεο κε βάζε ην κνληέιν von Bertalanffy θαη ηηκέο Φ γηα ην ιπζξίλη (Pagellus erythrinus) ζην Nφηην Αηγαίν πέιαγνο. Ζθζηία Μέεμδμξ L (mm) k (year -1 t 0 ) R 2 Φ (πνυκζα) (year) Παναηδνμφιεκα ιήηδ Ακάδνμιμξ οπμθμβζζιυξ ιήημοξ ,8 0,098-1,802 95,14 2, ,5 0,159-1,392 95,47 2, ,8 0,0583-1,718 98,12 2, ,0 0,220-0,295 99,91 2,45 4. πδήηεζε Σα απμηεθέζιαηα ηδξ ζπέζδξ αάνμοξ ιήημοξ έδεζλακ ιζα εθαθνχξ ανκδηζηή αθθμιεηνζηή αφλδζδ (b<3) ζημ θοενίκζ ημο Νμηίμο Αζβαίμο, οπμδδθχκμκηαξ ιεβαθφηενδ αφλδζδ ηαηά ιήημξ απυ υηζ ηαηά αάνμξ. Ζ ανκδηζηή αοηή αθθμιεηνία ένπεηαζ ζε ζοιθςκία ηαζ ιε άθθεξ ιεθέηεξ πμο πναβιαημπμζήεδηακ ζηδκ πενζμπή ημο Αζβαίμο ηαζ ηδξ Μεζμβείμο, πανυθμ πμο ημ εφνμξ παναηδνμφιεκςκ ιδηχκ ήηακ ανηεηά πενζμνζζιέκμ (Chasan et al. 2011, Metin et al. 2011). Πανυιμζα ηζιή βζα ημκ ζοκηεθεζηή b, ιε αοηή ηδξ πανμφζαξ ενβαζίαξ, ανήηακ μζ Metin et al. (2011) ζημκ Κυθπμ ηδξ ιφνκδξ. Ακηζεέηςξ, ζε ιεθέηεξ πμο πναβιαημπμίδζακ μζ Pajuelo & Lorenzo (1998) ζηα Κακάνζα κδζζά ηαζ δ Μοηζθδκαίμο (1989) ζημκ Δοαμσηυ ηυθπμ, ιε πζμ ιεβάθμ εφνμξ παναηδνμφιεκςκ ιδηχκ, ανέεδηε ζζμιεηνζηή αφλδζδ βζα ημ είδμξ, ακ ηαζ μζ ηζιέξ ημο ζοκηεθεζηή b πθδζζάγμοκ ανηεηά ηδκ εονεεείζα ηζιή ηδξ πανμφζαξ ιεθέηδξ. Πίλαθαο 2: Παξάκεηξνη ηεο ζρέζεο βάξνπο-κήθνπο (W=aL b ) απφ άιιεο κειέηεο. οββναθείξ Πενζμπή N Δφνμξ L (mm) a b Chasan et al Metin et al Pajuelo & Lorenzo 1998 Mytilineou 1989 Παβαζδηζηυξ Κυθπμξ Κυθπμξ ιφνκδξ Κακάνζα Νδζζά Δοαμσηυξ ,0382 2, ,0143 2, , , * 0, ,04 263

264 Κυθπμξ * διείςζδ: Σμ L οπμθμβίζηδηε πνδζζιμπμζχκηαξ ημ ιεζμοναίμ ιήημξ ρανζμφ (FL) ζηδκ ζπέζδ αάνμοξ-ιήημοξ. ηδκ πανμφζα ένεοκα, πμο αθμνά δείβιαηα θοενζκζμφ απυ ημ Νυηζμ Αζβαίμ Πέθαβμξ, ακαβκςνίζηδηακ 11 δθζηζαηέξ ηθάζεζξ ιε ηδ ιέβζζηδ δθζηία κα εηηζιάηαζ ζηα 14 πνυκζα, θυβς ηδξ πανμοζίαξ εκυξ ιεβάθμο αηυιμο ιε ιήημξ 488mm TL. Πανυιμζα απμηεθέζιαηα έπμοκ ανεεεί βζα ημ θοενίκζ ημο Δοαμσημφ ηυθπμο, υπμο δ Μοηζθδκαίμο (1989) ακαθένεζ υηζ ανήηε 12 δθζηζαηέξ μιάδεξ ιε ιέβζζημ ηα 11 πνυκζα ζε άημια ιε ιήημξ απυ 42 έςξ 430 mm TL. ε άθθεξ ιεθέηεξ υιςξ πμο αθμνμφκ ηδκ πενζμπή ηδξ Μεζμβείμο ηαζ υπμο ημ εφνμξ ιδηχκ πμο ελεηάζηδηε ήηακ πενζμνζζιέκμ, ηαοημπμζήεδηακ θζβυηενεξ δθζηζαηέξ ηθάζεζξ. οβηεηνζιέκα, ζημκ Παβαζδηζηυ ηυθπμ ακαβκςνίζηδηακ 9 δθζηζαηέξ ηθάζεζξ ιε ιέβζζηδ δθζηία ηα 8 πνυκζα (Chasan et al. 2011), ζημκ ηυθπμ ηδξ ιφνκδξ 11 δθζηζαηέξ ηθάζεζξ ιε ιέβζζημ ηα 10 πνυκζα (Metin et al. 2011) ηαζ ζημ Κνδηζηυ πέθαβμξ, φζηενα απυ ακάβκςζδ ηςκ θεπζχκ, 8 δθζηζαηέξ μιάδεξ ιε ιέβζζηδ δθζηία ηα 7 πνυκζα (Somarakis & Machias 2002). Απυ ένεοκεξ ζηδκ πενζμπή ημο Ακαη. Αηθακηζημφ, ζηα ιεκ Κακάνζα κδζζά ακαβκςνίζηδηακ 11 δθζηζαηέξ ηθάζεζξ ιε ιέβζζηδ δθζηία ηα 10 πνυκζα (Pajuelo & Lorenzo 1998), εκχ ζηδ εαθάζζζα πενζμπή κυηζα ηδξ Πμνημβαθίαξ δ ιέβζζηδ δθζηία ημο θοενζκζμφ ανέεδηε 21 πνυκζα (Coelho et al. 2010). Σα απμηεθέζιαηα ηςκ ενεοκχκ αοηχκ, ηα μπμία ααζίζηδηακ ζε άημια ιε πανυιμζμ εφνμξ ιδηχκ ιε ηδξ πανμφζαξ ένεοκαξ, πανμοζίαζακ ζοιθςκία ιε ηα πνμακαθενεέκηα απμηεθέζιαηα ιαξ. Οζ ελζζχζεζξ von Bertalanffy πμο εθανιυζηδηακ βζα ηα παναηδνμφιεκα ηαζ ηα ακαδνμιζηά ιήηδ, πνδζζιμπμζχκηαξ ηα άημια πμο ακήηακ ζηζξ δθζηίεξ 0+ έςξ 9 πνμκχκ, έδςζακ αζοιπηςηζηυ ιήημξ πμο ειπίπηεζ ιέζα ζημ εφνμξ ηζιχκ πμο έπμοκ ανεεεί ζε άθθεξ ένεοκεξ ζηδ Μεζυβεζμ ηαζ ζημκ Ακαημθζηυ Αηθακηζηυ βζα ηδκ αφλδζδ ημο θοενζκζμφ (Πίκαηαξ 3). Λαιαάκμκηαξ υιςξ οπυρδ ιαξ ηαζ ηδκ δθζηία ηςκ 14 εηχκ, εηπνμζςπμφιεκδ απυ έκα ιμκαδζηυ άημιμ, πνμηφπημοκ αζοιπηςηζηά ιήηδ ιε ανηεηά ιεβάθεξ ηζιέξ ζοβηνζηζηά ιε ηζξ πνμακαθενεείζεξ ηαζ ακηίζημζπμζ παιδθμί νοειμί αφλδζδξ (k), υπςξ εα ακαιεκυηακ. Δίκαζ πνμθακέξ υηζ ημ ιμκαδζηυ αοηυ ιεβάθμ άημιμ ζοκεζζθένεζ ζδιακηζηά ζηδκ δζεφνοκζδ ημο δθζηζαημφ εφνμοξ ηαζ ημο ιέβζζημο ιήημοξ ημο είδμοξ ζηδκ πενζμπή ημο Νμηίμο Αζβαίμο, αθθά ηαζ ηδξ Μεζμβείμο ηαζ ημο Αηθακηζημφ. Πίλαθαο 3: Παξάκεηξνη αχμεζεο ηεο εμίζσζεο Von Bertallanffy (k θαη L ) θαη ηηκέο Φ απφ άιιεο εξγαζίεο. Μέεμδμξ οββναθείξ Πενζμπή L k Φ ακάβκςζδξ Chasan et al., 2011 Χηυθζεμζ Παβαζδηζηυξ Κυθπμξ 345 0,13 2,19 Somarakis and Machias, 2002 Λέπζα Κνήηδ 242 * 0,32 2,27 Mytilineou, 1989 Χηυθζεμζ Δοαμσηυξ Κυθπμξ 482 * 0,06 2,16 Papaconstantinou et al., 1988 Λέπζα Ηυκζμ Πέθαβμξ 326 * 0,18 2,28 Metin et al., 2011 Χηυθζεμζ Κυθπμξ ιφνκδξ 307 0,17 2,19 Livadas, 1989 Χηυθζεμζ Κφπνμξ 300 0,20 2,26 Girardin, 1981 Λέπζα Κυθπμξ ηδξ Λοχκ 405 0,24 2,60 Girardin and Quignard, 1985 Andaloro and Giarritta, 1985 Λέπζα Κυθπμξ ηδξ Λοχκ 345 0,33 2,59 Χηυθζεμζ ζηεθία 367 0,16 2,33 264

265 Coelho et al., 2010 Χηυθζεμζ Νυηζα Πμνημβαθία 471 0,08 2,27 Pajuelo and Lorenzo, 1998 Χηυθζεμζ Κακάνζα Νδζζά 417 0,21 2,55 * διείςζδ: Σμ L οπμθμβίζηδηε πνδζζιμπμζχκηαξ ημ ιεζμοναίμ ιήημξ ρανζμφ (FL) ζηδκ ζπέζδ αάνμοξ-ιήημοξ. Οζ ηζιέξ ημο ζοκηεθεζηή Φ βζα ηα παναηδνμφιεκα ηαζ ηα ακαδνμιζηά ιήηδ ήηακ πανυιμζεξ ιε ηζξ ηζιέξ απυ άθθεξ ιεθέηεξ βζα ημ θοενίκζ. Ο ζοκηεθεζηήξ Φ ζημ Νυηζμ Αζβαίμ πανμοζίαζε ανηεηά ορδθέξ ηζιέξ πμο πθδζζάγμοκ πενζζζυηενμ ηζξ ακηίζημζπεξ ηζιέξ πμο οπμθμβίζηδηακ ζηδ Γοηζηή Μεζυβεζμ (Girardin 1981; Girardin & Quignard 1985) ηαζ ζημ Ακαη. Αηθακηζηυ (Pajuelo & Lorenzo 1998; Coelho et al. 2010). Ζ πανμφζα ενβαζία πανέπεζ κέεξ ζδιακηζηέξ πθδνμθμνίεξ ζπεηζηέξ ιε ηδκ εηηίιδζδ δθζηίαξ ηαζ ηςκ παναιέηνςκ αφλδζδξ ημοξ θοενζκζμφ ζηδκ πενζμπή ημο Νμηίμο Αζβαίμο, ζημπεφμκηαξ ζηδκ μοζζαζηζηυηενδ ηαηακυδζδ ηδξ αζμθμβίαξ ημο είδμοξ. Πεναζηένς υιςξ ένεοκεξ, μζ μπμίεξ εα ζηδνίγμκηαζ ζε δεζβιαημθδρίεξ ηαε υθδ ηδ δζάνηεζα ημο έημοξ, είκαζ απαναίηδηεξ βζα κα εηηζιδεμφκ ζςζηά ηα απμεέιαηα ημο είδμοξ ζηδκ εονφηενδ πενζμπή, αθθά ηαζ βζα κα εκημπζζημφκ πζεακέξ αθθαβέξ ζηζξ παναιέηνμοξ αφλδζδξ ιε ηδκ πάνμδμ ηςκ πνυκςκ ςξ απμηέθεζια ηδξ ηθζιαηζηήξ αθθαβήξ ηαζ ηδξ ακενχπζκδξ δναζηδνζυηδηαξ. Βηβιηνγξαθηθέο αλαθνξέο Andaloro, F., & Giarritta, P. S. (1985). Contribution to the knowledge of the age, growth and feeding of pandora, Pagellus erythrinus (L. 1758) in the Sicilian Channel. 336, pp Bertalanffy, L. v. (1938). A quantitative theory of organic growth. Human Biology (10), Caddy, J. F. (1993). Some future perspectives for assessment and management of Mediterranean fisheries. Scientia Marina (57), Chasan, E., Golomazou, E., Neofitou, C., Aifanti, S., & Kallianiotis, A. (2011). Preliminary results of biology and population parameters of Common Pandora (Pagellus erythrinus L.1758) in Pagasitikos Gulf. 4th International Symposium "Hydrobiology - Fisheries", (ζζ ). Volos. Coelho, R., Bentes, L., Correia, C., Gonçalves, J. M., Lino, P. G., & Monteiro, P. (2010). Life history of the common pandora, Pagellus erythrinus (Linnaeus, 1758) (Actinopterygii: Sparidae) from southern Portugal. Brazilian Journal of Oceanography, 58 (3), Fischer, W., Schneider, M., & Bauchot, M. L. (1987). Fishes FAO d' identification des especesmediterranee et Mer Noire. FAO. Girardin, M. (1981). Pagellus erythrinus (L., 1758) et Boops boops (L., 1758) (Pisces, Sparidae) du Golfe du Lion. Ecobiologie. Prises commerciales et modeles de gestion. Ph. D. thesis. University of Languedoc, France, p.295. Girardin, M., & Quignard, J. P. (1985). Croissance de Pagellus erythrinus (Pisces: TeÂleÂosteÂens Sparidae) dans le Golfe du Lion. Cybium, 9 (4), Livadas, R. J. (1989). A study of the biology and population dynamics of pandora (Pagellus erythrinus L., 1758), Family Sparidae, in the Seas of Cyprus. 412, Metin, G., Ilkyaz, A. T., Soukan, O., & Kinacigil, H. T. (2011). Biological characteristics of the common pandora, Pagellus erythrinus (Linnaeus, 1758), in the central Aegean Sea. Turkish Journal of Zoology, 35 (3), Mytilineou, C. (1989). Données biologiques sur le pageot, Pagelus erythrinus, des côtes orientales de la Grèce centrale. FAO Fish. Rep., 412, Nikolsky, G. v. (1963) Academic. The ecology of fishes., 352. Pajuelo, J. G., & Lorenzo, J. M. (1998). Population biology of the common pandora Pagellus erythrinus (Pisces: Sparidae) off the Canary Islands. Fisheries Research, 36, Papaconstantinou, C., Mytilineou, C., & T., P. (1988). Aspects of the life history and fishery of red pandora, Pagellus erythrinus (Sparidae) off Western Greece. Cybium, 12 (4), Somarakis, S., & Machias, A. (2002). Age, growth, and bathymetric distribution of red pandora (Pagellus erythrinus) on the Cretan shelf (eastern Mediterranean). Journal of the Marine Biological Association of the United Kingdom, 82,

266 AGE ESTIMATION OF RED MULLET (Mullus barbatus) IN THE EASTERN MEDITTERANEAN SEA Chatzispyrou A 1*., Anastasopoulou A 1., Mytilineou Ch 1., Bekas P 1., Kallianiotis A 2. 1 Hellenic Centre for Marine Research, Institute of Marine Biological Resources and Inland Waters, 46.7 km Athens Sounio ave., P.O. Box 712, Anavyssos, 19013, Attiki, Greece 2 Fisheries Research Institute, 64007, N. Peramos, Kavala, Greece Abstract In the present study, length-weight relationship and growth parameters of red mullet were studied from samples collected in the Aegean and Ionian Seas. Six and seven age groups were recorded in the Aegean and the Ionian Sea, respectively. Length-weight relationship was positive allometric in both areas. Fish length and otolith radius linear relationship was used for the estimation of mean back calculated lengths per age class. Von Bertallanfy growth parameters were calculated for observed and back-calculated lengths per age class. Φ values were similar in all cases. Differences were found in length-weight relationship and growth parameters between the study areas. Key words: Mullus barbatus, age, growth, otoliths *Corresponding author: Archontia Cahtzispyrou (a.chatzispyrou@hcmr.gr) ΔΚΣΗΜΖΖ ΣΖ ΑΤΞΖΖ ΣΖ ΚΟΤΣΟΜΟΤΡΑ (Mullus barbatus) ΣΟ ΑΗΓΑΗΟ ΚΑΗ ΣΟ ΗΟΝΗΟ ΠΔΛΑΓΟ Υαηδεζπχξνπ Α 1.*, Αλαζηαζνπνχινπ Α 1., Μπηηιελαίνπ Υ 1., Μπέθαο Π 1., Καιιηαληψηεο Α 2. 1 Δθθδκζηυ Κέκηνμ Θαθαζζίςκ Δνεοκχκ, Ηκζηζημφημ Θαθάζζζςκ Βζμθμβζηχκ Πυνςκ ηαζ Δζςηενζηχκ Τδάηςκ, 46,7 πι. Αεδκχκ-μοκίμο Σ.Θ. 712, Ακάαοζζμξ, 19013, Αηηζηή 2 Ηκζηζημφημ Αθζεοηζηχκ Δνεοκχκ, 64007, Ν. Πέναιμξ, Κααάθα Πεξίιεςε ηδκ πανμφζα ενβαζία δ ζοζπέηζζδ αάνμοξ-ιήημοξ ηαζ μζ πανάιεηνμζ αφλδζδξ ελεηάζηδηακ βζα ηδκ ημοηζμιμφνα ημο Αζβαίμο ηαζ Ημκίμο Πεθάβμοξ. Έλζ δθζηζαηέξ μιάδεξ πνμζδζμνίζηδηακ ζημ Αζβαίμ ηαζ επηά ζημ Ηυκζμ Πέθαβμξ. Ζ ζπέζδ αάνμοξ-ιήημοξ ανέεδηε εεηζηά αθθμιεηνζηή ηαζ ζηζξ δομ πενζμπέξ. Ζ βναιιζηή ζοζπέηζζδ ιεηαλφ ιήημοξ ρανζμφ ηαζ αηηίκαξ ςημθίεμο πνδζζιμπμζήεδηε βζα ημκ οπμθμβζζιυ ηςκ ακαδνμιζηχκ ιδηχκ ακά δθζηία. Οζ πανάιεηνμζ αφλδζδξ εηηζιήεδηακ ιε αάζδ ημ ιμκηέθμ Von Bertallanfy, ηυζμ βζα ηα παναηδνμφιεκα υζμ ηαζ βζα ηα ιέζα ακαδνμιζηά ιήηδ ακά δθζηία ηαζ μζ ηζιέξ ημο ζοκηεθεζηή Φ ήηακ ζε υθεξ ηζξ πενζπηχζεζξ πανυιμζεξ. Γζαθμνέξ παναηδνήεδηακ ζηδ ζπέζδ αάνμοξ-ιήημοξ ηαζ ζηζξ παναιέηνμοξ αφλδζδξ ακάιεζα ζηζξ δομ πενζμπέξ. Λέξειρ κλειδιά: Mullus barbatus, πξνζδηνξηκόο ειηθίαο, αύμεζε, σηόιηζνη *οββναθέαξ επζημζκςκίαξ: Ανπμκηία Υαηγδζπφνμο (a.chatzispyrou@hcmr.gr) 1. Δηζαγσγή Ζ εηηίιδζδ ηδξ δθζηίαξ ζηα ράνζα είκαζ έκα ααζζηυ ζημζπείμ βζα ηδ ιεθέηδ ηδξ αζμθμβίαξ ηαζ δοκαιζηήξ ηςκ πθδεοζιχκ ημοξ. Ζ ημοηζμιμφνα (Mullus barbatus) είκαζ έκα απυ ηα ζπμοδαζυηενα ειπμνζηά αεκεμπεθαβζηά είδδ ηςκ εθθδκζηχκ εαθαζζχκ, αθθά ηαζ μθυηθδνδξ ηδξ Μεζμβείμο (Tserpes et al., 2002; Ozbilgin et al., 2004). Πνμδβμφιεκεξ ιεθέηεξ ημο είδμοξ έπμοκ ακαδείλεζ πθδνμθμνίεξ ζπεηζηά ιε ηδ αζμθμβία ηαζ αθζεία ηδξ ημοηζμιμφναξ ζηδ Μεζυβεζμ (π.π. Cherif et al. 2007, Sieli et al. 2011, Aydin & Karadurmus 2013). ηδκ Δθθάδα έπμοκ βίκεζ ενβαζίεξ βζα ηδκ 266

267 ημοηζμιμφνα πμο αθμνμφκ ζηδκ ακαπαναβςβή (Anastasopoulou & Saborido-Rey, 2011), ηδ δζαηνμθή (Vassilopoulou & Papaconstantinou, 1993), ηδ ζπέζδ ιήημοξ-αάνμοξ ηαζ ηδκ αφλδζδ (Papaconstantinou et al. 1981, Vassilopoulou & Papaconstantinou 1992, Vrantzas et al. 1992, Moutopoulos & Stergiou, 2002, Κάνθμο-Ρήβα ηαζ ζοκ. 2007, Σζάιδξ ηαζ ζοκ. 2006) ηαζ εκδζζιυηδηα (Vassilopoulou & Papaconstantinou 1992, Vrantzas et al. 1992). Ζ πανμφζα ενβαζία απμηεθεί ιζα πνμηαηανηηζηή ιεθέηδ ηδξ ηαηά ιήημξ ηαζ ηαηά αάνμξ αφλδζδξ ηδξ ημοηζμιμφναξ ζημ Αζβαίμ ηαζ ζημ Ηυκζμ Πέθαβμξ, ηαζ ηδ πζεακή φπανλδ δζαθμνχκ ιεηαλφ ηςκ οπυ ιεθέηδ πενζμπχκ. 2. Τιηθά θαη Μέζνδνη Γζα ηδκ ηαηά ιήημξ ζφκεεζδ ηδξ ημοηζμιμφναξ πνδζζιμπμζήεδηακ ηα ζημζπεία ειπμνζηήξ αθζείαξ, ηα μπμία ζοβηεκηνχεδηακ ηαηά ηδ δζάνηεζα ημο Δεκζημφ Πνμβνάιιαημξ οθθμβήξ Αθζεοηζηχκ Γεδμιέκςκ (2013), ζημ Αζβαίμ ηαζ ημ Ηυκζμ Πέθαβμξ. Οζ οπυθμζπεξ ακαθφζεζξ ζηδνίπεδηακ ζηα δεδμιέκα απυ ηδ αζμθμβζηή δεζβιαημθδρία ημο ίδζμο πνμβνάιιαημξ βζα ηδκ πενίμδμ Ημοθίμο-Γεηειανίμο 2013 ζημ Αζβαίμ ηαζ Μαΐμο-Γεηειανίμο 2013 ζημ Ηυκζμ. ε ηάεε ράνζ ηαηαβνάθδηακ ημ μθζηυ ιήημξ (TL), ημ αάνμξ (W), ημ θφθμ ηαζ ημ ζηάδζμ βεκκδηζηήξ ςνζιυηδηαξ ιαηνμζημπζηά. Οζ ςηυθζεμζ ηςκ ρανζχκ ζοθθέπεδηακ, ηαεανίζηδηακ ηαζ θςημβναθήεδηακ βζα ηδκ ακάβκςζδ ηδξ δθζηίαξ (t), δ μπμία ααζίζηδηε ζημκ ανζζηενυ ςηυθζεμ ηαζ έβζκε απυ 3 δζαθμνεηζημφξ έιπεζνμοξ ενεοκδηέξ ιε φζηδια Ακάθοζδξ Φδθζαηήξ Δζηυκαξ (Image - Pro Plus). Υνδζζιμπμζήεδηακ ιυκμ μζ ςηυθζεμζ πμο ήηακ εοακάβκςζημζ ηαζ βζα ημοξ μπμίμοξ οπήνλε ζοιθςκία ηαζ ηςκ ηνζχκ ενεοκδηχκ. Γζα ηδκ εηηίιδζδ ηδξ δθζηίαξ έβζκε ηαηαιέηνδζδ ηςκ εηήζζςκ δαηηοθίςκ ηαζ δ 1 δ Ημοκίμο εεςνήεδηε ςξ διενμιδκία βέκκδζδξ βζα υθα ηα οπυ ελέηαζδ άημια. Έηζζ, βζα ηδκ απυδμζδ ηδξ δθζηίαξ ηςκ ρανζχκ οπμθμβίζηδηε μ ανζειυξ ηςκ εηήζζςκ δαηηοθίςκ ηαζ μ πνυκμξ απυ ηδκ διενμιδκία βέκκδζδξ ιέπνζ ηδκ διενμιδκία ζφθθδρήξ ημοξ. Δπίζδξ, ιεηνήεδηε δ αηηίκα (R) ηάεε ςηυθζεμο ηαεχξ ηαζ δ αηηίκα ηάεε εηήζζμο δαηηοθίμο. H ηαηά ιήημξ ζφκεεζδ ηδξ ημοηζμιμφναξ οπμθμβίζηδηε ζε ηθάζεζξ 10mm. Οζ πανάιεηνμζ ηδξ ζπέζδξ αάνμοξ (W) - ιήημοξ ρανζμφ (TL) εηηζιήεδηακ ιε αάζδ ημ εηεεηζηυ ιμκηέθμ W = atl b, εκχ ηδξ ζπέζδξ ιήημοξ ρανζμφ-αηηίκαξ ςημθίεμο ιε αάζδ ημ βναιιζηυ ιμκηέθμ TL = a+br, ηα μπμία πανμοζίαζακ ημ ηαθφηενμ ζοκηεθεζηή ζοζπέηζζδξ. Ο οπμθμβζζιυξ ηςκ ιέζςκ ακαδνμιζηχκ ιδηχκ ακά δθζηία ααζίζηδηε ζηδ ιέζδ αηηίκα ηάεε εηήζζμο δαηηοθίμο ηαζ ζηδ ζπέζδ TL-R. Οζ ζοκηεθεζηέξ ηςκ ζπέζεςκ αάνμοξ-ιήημοξ ηαζ ιήημοξ-αηηίκαξ ςημθίεμο ιεηαλφ ηςκ δομ πενζμπχκ εθέβπεδηακ ζηαηζζηζηά ιε ηδ πνήζδ ημο πνμβνάιιαημξ Statgraphics. Γζα ηδ ιεθέηδ ηδξ αφλδζδξ, πνδζζιμπμζήεδηε ημ εηεεηζηυ ιμκηέθμ Von Bertalanffy L = L (1-e -k(t-to) ) ιε ιδ βναιιζηή ζοζπέηζζδ παίνκμκηαξ ζακ δεδμιέκα α) ηα παναηδνμφιεκα ιήηδ ηαζ ηζξ ακηίζημζπεξ δθζηίεξ ημοξ ηαζ α) ηα ιέζα ακαδνμιζηά ιήηδ ακά δθζηία. Οζ πανάιεηνμζ αφλδζδξ βζα ηα παναηδνμφιεκα ηαζ ηα ακάδνμια ιήηδ ιεηαλφ ηςκ δομ πενζμπχκ εθέβπεδηακ ιε t-test. Ο ζοκηεθεζηήξ μθμηθήνςζδξ ηδξ αφλδζδξ Φ (Φ = log k + 2 log L ) ελεηάζηδηε ιε αάζδ ηζξ παναιέηνμοξ αφλδζδξ ηδξ πανμφζαξ ενβαζίαξ ηαζ ζοβηνίεδηε ιε αοηυκ απυ άθθεξ ένεοκεξ. Γζα ημκ οπμθμβζζιυ ημο ζοκηεθεζηή Φ δ ηζιή ημο L εηθνάζηδηε ζε cm. 3. Απνηειέζκαηα Σα ιήηδ ηςκ ρανζχκ πμο αθζεφηδηακ ζημ Αζβαίμ Πέθαβμξ ηοιάκεδηακ απυ 70 ιέπνζ 310 mm. Σα ιεβαθφηενα πμζμζηά (73%) ανέεδηακ ζηζξ ηθάζεζξ mm. ημ Ηυκζμ Πέθαβμξ ηα ιήηδ ηδξ ημοηζμιμφναξ ηοιάκεδηακ ιεηαλφ 50 ηαζ 310 mm ιε ιεβαθφηενμ πμζμζηυ ζηζξ ηθάζεζξ ιήημοξ ιεηαλφ mm (63%). Ο πνμζδζμνζζιυξ ηδξ δθζηίαξ ηδξ ημοηζμιμφναξ ζημ Αζβαίμ Πέθαβμξ πναβιαημπμζήεδηε ζε 210 ράνζα, ιήημοξ 94 έςξ 227 mm. Πνμζδζμνίζηδηακ 6 δθζηζαηέξ ηθάζεζξ απυ 0+ έςξ 5+. ημ Ηυκζμ δ ακάβκςζδ πναβιαημπμζήεδηε ζε 130 ςηυθζεμοξ ιήημοξ mm, υπμο πνμζδζμνίζηδηακ 7 δθζηζαηέξ ηθάζεζξ, απυ 0+ έςξ 6+. Σα ιμκηέθα ηδξ ζοζπέηζζδξ αάνμοξ-ιήημοξ βζα ηζξ δφμ πενζμπέξ ένεοκαξ, ηα μπμία πνμέηορακ απυ ηδκ ελέηαζδ ηςκ αηυιςκ βζα ηα μπμία ιεθεηήεδηε ηαζ δ δθζηία, πανμοζζάγμκηαζ ζημ πήια 1. Ζ ηαηά αάνμξ αφλδζδ ηδξ ημοηζμιμφναξ ζημ Αζβαίμ ηαζ ημ Ηυκζμ Πέθαβμξ πανμοζίαζε εεηζηή αθθμιεηνία (b>3,0), βεβμκυξ πμο δδθχκεζ ιεβαθφηενδ αφλδζδ ηαηά αάνμξ ηςκ ρανζχκ ζε ζπέζδ ιε ημ ιήημξ ημοξ. Σα ιμκηέθα ζοζπέηζζδξ αάνμοξ-ιήημοξ ηδξ ημοηζμιμφναξ δζέθενακ ηαζ ςξ πνμξ ηδ ηθήζδ ηαζ ςξ πνμξ ηδ ημιή ηςκ βναιιχκ παθζκδνυιδζδξ (p<0.0001) ακάιεζα ζηζξ δομ πενζμπέξ ιεθέηδξ. 267

268 W HydroMedit 2014, November 13-15, Volos, Greece WA = TL R² = 99.39, N=123 WI = TL R² = 98.57, N= ΑΗΓΑΗΟ ΗΟΝΗΟ TL ρήκα 1. ρέζε βάξνπο-κήθνπο ηεο θνπηζνκνχξαο ζην Αηγαίν (Α) θαη Ηφλην (Η) Πέιαγνο Ζ ζοζπέηζζδ ιήημοξ ρανζμφ ιε αηηίκα ςημθίεμο έδςζε ηζξ παναηάης ζπέζεζξ: Αζβαίμ: TL = *R, N=202, R 2 =90,70 Ηυκζμ: TL = *R, N=127, R 2 =91,57 Ζ ζφβηνζζδ ηςκ βναιιχκ παθζκδνυιδζδξ βζα ηζξ δομ πενζμπέξ δεκ έδεζλε ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ (p=0,95 βζα ηζξ ημιέξ, p= 0,47 βζα ηζξ ηθήζεζξ). Οζ πανάιεηνμζ αφλδζδξ ιε αάζδ ημ ιμκηέθμ Von Bertalanffy, δδθαδή ημ αζοιπηςηζηυ ιήημξ (L ), δ εεςνδηζηή δθζηία ζημ ιήημξ ιδδέκ (t 0 ) ηαζ μ νοειυξ αφλδζδξ (k), βζα ηα παναηδνμφιεκα ηαζ ηα ακαδνμιζηά ιήηδ, πανμοζζάγμκηαζ ζημκ Πίκαηα 1. Πίλαθαο 1. Παξάκεηξνη αχμεζεο ηεο θνπηζνκνχξαο ζηηο δχν πεξηνρέο κειέηεο κε βάζε ην κνληέιν Von Bertalanffy ( ± ηππηθφ ζθάικα) Παναηδνμφιεκα ιήηδ Παναηδνμφιεκα ιήηδ Μέζα ακαδνμιζηά ιήηδ Μέζα ακαδνμιζηά ιήηδ Πενζμπ ή ΑΗΓΑΗ Ο L (mm) k t 0 R 2 N Φ 326,79(± 38,8) ΗΟΝΗΟ 295,62(± 19,2) ΑΗΓΑΗ Ο 244,161(± 13,9) ΗΟΝΗΟ 308,898(± 20,4) 0,17(±0,04 ) 0,20(±0,03 ) 0,34(±0,06 ) 0,20(±0,03 ) -1,78(±0,28) 91,55-1,74(±0,22) 95, ,26 2,25-0,47(±0,18) 99,80 5 2,30-0,94(±0,19) 99,85 6 2,28 ηαηζζηζηά ζδιακηζηέξ δζαθμνέξ ιεηαλφ ηςκ παναιέηνςκ αφλδζδξ ηυζμ βζα ηα παναηδνμφιεκα υζμ ηαζ βζα ηα ακαδνμιζηά ιήηδ, ανέεδηακ ιεηαλφ ηςκ δομ πενζμπχκ (p<0,0001), πανυθα αοηά μζ ηζιέξ πμο οπμθμβίζηδηακ βζα ημκ ζοκηεθεζηή Φ ιε αάζδ ηζξ παναιέηνμοξ αφλδζδξ ήηακ πανυιμζεξ ιεηαλφ ηςκ δομ πενζμπχκ, ηαζ βζα ηα παναηδνμφιεκα αθθά ηαζ βζα ηα ακαδνμιζηά ιήηδ (Πίκαηαξ 1). 4. πδήηεζε Οζ εηηζιχιεκεξ δθζηίεξ ζηδκ πανμφζα ενβαζία δζαθένμοκ ιεηαλφ Αζβαίμο ηαζ Ημκίμο Πεθάβμοξ ηαηά ιζα δθζηζαηή ηθάζδ, μθεζθυιεκδ ζηδκ πανμοζία εκυξ ιυκμ αηυιμο, δθζηίαξ έλζ εηχκ ηαζ ιήημοξ TL=228mm, ζημ Ηυκζμ Πέθαβμξ. Δπζπθέμκ δθζηίεξ απυ αοηέξ πμο ακαβκςνίζηδηακ ζηδκ πανμφζα ιεθέηδ ακαιέκμκηαζ βζα ηδκ ημοηζμιμφνα, δεδμιέκμο υηζ δ ηαηά ιήημξ ζφκεεζδ ημο είδμοξ 268

269 οββναθείξ Aydin & Karadurmus 2013 Vassilopoulou & Papaconstantinou 1992 πενζείπε ιεβαθφηενα άημια απυ αοηά πμο ελεηάζηδηακ βζα ηδκ εηηίιδζδ ηδξ δθζηίαξ ηαζ ζηζξ δομ πενζμπέξ ένεοκαξ. Σα απμηεθέζιαηα ηδξ πανμφζαξ ενβαζίαξ ζπεηζηά ιε ηδκ ζοζπέηζζδ αάνμοξ-ιήημοξ ηδξ ημοηζμιμφναξ έδεζλακ εεηζηά αθθμιεηνζηή αφλδζδ ημ μπμίμ έπεζ παναηδνδεεί ηαζ ζε πνμδβμφιεκεξ ιεθέηεξ βζα ηζξ ίδζεξ πενζμπέξ ένεοκαξ υπςξ ηαζ ζε άθθα ιένδ ηδξ Μεζμβείμο (Πίκαηαξ 2). Ζ ζπέζδ αάνμοξ-ιήημοξ ανέεδηε κα δζαθένεζ ιεηαλφ Αζβαίμο ηαζ Ημκίμο Πεθάβμοξ. Ακηζεέηςξ, μζ Σζάιδξ ηαζ ζοκ. (2006) δεκ ανήηακ δζαθμνέξ ιεηαλφ ηςκ πενζμπχκ. Πίλαθαο 2. Παξάκεηξνο b ηεο ζρέζεο βάξνπο-κήθνπο απφ δηάθνξεο κειέηεο. οββναθείξ Πενζμπή b Πανμφζα ιεθέηδ Αζβαίμ 3,14(±0,03) Πανμφζα ιεθέηδ Ηυκζμ 3,42(±0,04) Vassilopoulou & Papaconstantinou 1992 Αζβαίμ 3,18(±0,04) Σζάιδξ ηαζ ζοκ ανςκζηυξ 3,22 Σζάιδξ ηαζ ζοκ Ν.Α. Ηυκζμ 3,18 Cherif et al Σοκδζία 3,10 Aydin & Karadurmus 2013 Ακ. Μαφνδ Θάθαζζα 3,03 Οζ ηζιέξ ηςκ παναιέηνςκ αφλδζδξ ηαζ ημο ζοκηεθεζηή Φ ηδξ πανμφζαξ ενβαζίαξ ήηακ ημκηά ιε αοηέξ πμο έπμοκ ανεεεί βζα ημ είδμξ ζε πνμδβμφιεκεξ ιεθέηεξ ζε δζάθμνεξ πενζμπέξ ηδξ Μεζμβείμο (Πίκαηαξ 3: δίκεηαζ ημ ηοπζηυ ζθάθια υπμο έπεζ ζοιπενζθδθεεί). Ανηεηά ορδθέξ ήηακ μζ ηζιέξ ημο k ηαζ ημο Φ πμο ανήηακ μζ Ozbilgin et al. (2004) ζημκ ηυθπμ ηδξ ιφνκδξ ηαζ μζ Vrantzas et al (1992) ζημ ανςκζηυ ηυθπμ (Πίκαηαξ 3). Οζ ιζηνυηενεξ ηζιέξ k ηαζ Φ ανέεδηε ζηδκ Ακ. Μαφνδ Θάθαζζα ζφιθςκα ιε ημοξ Aydin & Karadurmus (2013). Πίλαθαο 3. Παξάκεηξνη αχμεζεο (L θαη k) θαη ζπληειεζηέο Φ ηεο θνπηζνκνχξαο απφ πξνεγνχκελεο κειέηεο. Μέεμδμξ ακάβκςζδξ Χηυθζεμζ Χηυθζεμζ εδθοηχκ Χηυθζεμζ ανζεκζηχκ Πενζμπή L (cm) N k Φ Ακ. Μαφνδ Θάθαζζα Αζβαίμ Αζβαίμ 27, ,14 2,02 25,5* 22,7* Vrantzas et al 1992 Χηυθζεμζ ανςκζηυξ 23,5? 0,51 2,45 Ozbilgin et al Χηυθζεμζ ιφνκδ, Αζβαίμ 24,3? 0,56 2,52 Σζάιδξ ηαζ ζοκ Χηυθζεμζ ανςκζηυξ 27,9(± 1,69) 214 0,17(±0,02) 2,09 Σζάιδξ ηαζ ζοκ Χηυθζεμζ Ν.Α. Ηυκζμ 29,5(± 2,04) 250 0,15(±0,02) 2,12 Sieli et al Χηυθζεμζ εδθοηχκ ζηεθία 22,1(± 1,15) 595 0,38(±0,09) 2, ,21 0,25 2,14 2,11 *Οζ ηζιέξ αθμνμφκ ημ ιεζμοναίμ ιήημξ ηςκ ρανζχκ Οζ δζαθμνέξ αοηέξ ζηδκ αφλδζδ πμο παναηδνμφκηαζ βζα ηδκ ημοηζμιμφνα ακάιεζα ζηζξ δζάθμνεξ ιεθέηεξ ιπμνεί κα απμδμεμφκ ζηζξ δζαθμνεηζηέξ πενζααθθμκηζηέξ ζοκεήηεξ ηδξ ηάεε πενζμπήξ ένεοκαξ, αθθά ηαζ ζε δζαθμνέξ ζηδ ζφκεεζδ ηςκ οπυ ελέηαζδ δεζβιάηςκ, δζαθμνέξ ζηδ ιεεμδμθμβία ακάβκςζδξ ηαζ ενιδκείαξ ηςκ εηήζζςκ δαηηοθίςκ ηαεχξ ηαζ ζε αθθαβέξ ζημοξ πθδεοζιμφξ θυβς ηθζιαηζηήξ αθθαβήξ. Γεδμιέκμο υηζ δ πανμφζα ιεθέηδ είκαζ ιζα πνμηαηανηηζηή ενβαζία ζε ζπέζδ ιε ηδκ αφλδζδ ηδξ ημοηζμιμφναξ, πεναζηένς ένεοκα πμο εα ζηδνίγεηαζ ζε δεζβιαημθδρίεξ απυ υθεξ ηζξ επμπέξ ημο έημοξ, ιε επανηή ανζειυ ηαζ απυ ηα δομ θφθα, ηαζ εα ηαθφπηεζ υθμ ημ εφνμξ ιδηχκ ηςκ πθδεοζιχκ ημο είδμοξ, εα δχζμοκ ιζα πζμ μθμηθδνςιέκδ εζηυκα βζα ηδκ αφλδζδ ηδξ ημοηζμιμφναξ, ζημζπείμ απαναίηδημ βζα ηδκ δζαπείνζζδ ηςκ απμεειάηςκ ηδξ. 269

270 Βηβιηνγξαθία Aydin M., Karadurmus U. (2013). An investigation on age, growth, and biological characteristics of red mullet (Mullus barbatus ponticus, Essipov, 1927) in the Eastern Black Sea. Iranian Journal of Fisheries Science. 12(2), Anastasopoulou K., Saborido-Rey F. (2011). Reproductive ecology of Mullus barbatus in E. Mediterranean Sea.Conference Fish reproduction and Fisheries. Vigo, Spain (16-20 May). Cherif M., Zarrad R., Gharbi H., Missaoui H., Jarboui O. (2007). Some biological parameters of the red mullet Mullus barbatus L., 1758, from the Gulf of Tunis. ACTA ADRIAT. 48(2), Κάνθμο-Ρήβα Κ., Ακαζημπμφθμο Η., Καθαβηζά Μ. (2007). Δπίδναζδ ηςκ παναιέηνςκ αφλδζδξ ηαζ εκδζζιυηδηαξ ζηδκ εηηίιδζδ ηδξ ηαηάζηαζδξ ημο απμεέιαημξ ηδξ ημοηζμιμφναξ. 13 μ Πακεθθήκζμ οκέδνζμ Ηπεομθυβςκ, Μοηζθήκδ. Ozbilgin H., Tosunoglu Z., Bilecenoglou M., Tokac A. (2004). Population parameters of Mullus barbatus in Izmir Bay (Aegean Sea), using length frequency analysis. J.Appl.Ichthyol. 20, Sieli G., Badalucco C., Di Stefano G., Rizzo P., D Anna G., Fiorentino F. (2011). Biology of red mullet Mullus barbatus (L., 1758), in the Gulf of Castellammare (NW Sicily, Mediterranean Sea) subject to a trawling ban. J.Appl.Ichthyolo. 27, Σζάιδξ Δ., Μοηζθδκαίμο Υ., Κααααδάξ. (2006???). φβηνζζδ αζμθμβζηχκ παναηηδνζζηζηχκ ηδξ ημοηζμιμφναξ (Mullus barbatus L., 1758) ζηζξ εηθμνηχζεζξ ιδπακυηναηαξ ημο ανςκζημφ Κυθπμο ηαζ ημο Ν.Α. Ημκίμο Πεθάβμοξ. 8 μ Πακεθθήκζμ οιπυζζμ Χηεακμβναθίαξ & Αθζείαξ. Tserpes G., Fiorentino F., Levi D., Cau A., Murenu M., Zamboni A.D.A., Papaconstantinou C. (2002). Distribution of Mullus barbatus and M.surmuletus (Osteichthyes: Perciformes) in the Mediterranean continental shelf: implications for management. Sci. Mar. 66 (Suppl. 2), Moutopoulos D.K., Stergiou K.I. (2002). Length-weight and length length relationships of fish species form the Aegean Sea (Greece). J.Appl.Ichthyol. 18, Vassilopoulou V., Papaconstantinou C. (1993). Feeding habits of red mullet (Mullus barbatus) in a gulf in Western Greece. Fisheries Research 16, Vassilopoulou V., Papaconstantinou C. (1992). Aspects of the biology and dynamics of red mullet (Mullus barbatus) in the Aegean Sea. FAO Fish. Rep. 477, Vrantzas N., Kalagia M., Karlou C. (1992). Age, growth and state of stock of red mullet (Mullus barbatus L., 1758) in the Saronikos gulf of Greece. FAO Fisheries Report No 477, Papaconstantinou C., Tsimenidis N., Daoulas Ch Age, growth and reproduction of red mullet (Mullus barbatus L., 1758) in the gulfs of Saronikos and Thermaikos. THALASSOGRAPHICA. Vol. 4, No. 1,

271 PRELIMINARY STUDY OF JUVENILE PICAREL, Spicara smaris (Linnaeus 1758), GROWTH FROM OTOLITH MICROSTRUCTURE Denaxa M. 1, Bekas P. 1, Tziertzidis D. 2, Mytilineou Ch. 1 1 Institute of Marine Biological Resources and Inland Waters, Hellenic Center for Marine Research, 46.7 km Athens-Sounio av., Anavyssos, 19013, Attiki, Greece 2 Department of Environmental Technologists, T.E.I. Ionion Islands, Panagoula, 29100, Zakynthos, Greece Abstract In this work, the results from the study of the otolith microstructure in picarel (Spicara smaris) are presented. In total, 30 otoliths from individuals with a total length (TL) ranging from 50 to 163 mm, collected during the biological sampling of DCF national program in Argosaronikos Gulf, were examined. The otoliths were embedded in epoxic resin. After grinding and polishing them, the thin readable sections of otoliths were photographed in optical microscope and then, the daily rings were counted with the use of an Image analysis software. The daily readings ranged from 119 to 536 days. The S-curve model was the most adequate to describe the length - age relationship, based on the R 2 value, the parameters of the model were found to be a=5.435 and b= The annual rings seem to be formed between January and April. The annual rings were present on otoliths of specimens with TL greater than 123 mm. The area that corresponded to the annuli was consisted of daily rings having very narrow distances between them. Keywords: Spicara smaris, Aegean Sea, otoliths, microstructure, daily rings Coresponding author: Denaxa Maria (denaxam@hcmr.gr) ΠΡΟΚΑΣΑΡΚΣΗΚΖ ΜΔΛΔΣΖ ΣΖ ΑΤΞΖΖ ΝΔΑΡΧΝ ΑΣΟΜΧΝ ΜΑΡΗΓΑ, Spicara smaris (LINNAEUS 1758), ΜΔΧ ΣΖ ΔΞΔΣΑΖ ΣΖ ΜΗΚΡΟΓΟΜΖ ΣΧΝ ΧΣΟΛΗΘΧΝ Γελαμά Μ. 1*, Μπέθαο Π. 1, Σδηεξηδίδεο Γ. 1, Μπηηιελαίνπ Υ. 1 1 Ηκζηζημφημ Θαθαζζίςκ Βζμθμβζηχκ Πυνςκ ηαζ Δζςηενζηχκ Τδάηςκ, Δθθδκζηυ Κέκηνμ Θαθαζζίςκ Δνεοκχκ, 46.7 πθι. Αεδκχκ-μοκίμο, Ακάαοζζμξ Αηηζηή, Δθθάδα 2 Σιήια Σεπκμθυβςκ Πενζαάθθμκημξ, Σ.Δ.Η. Ημκίςκ Νήζςκ, Πακαβμφθα, Εάηοκεμξ, Δθθάδα Πεξίιεςε ηδκ πανμφζα ενβαζία πανμοζζάγμκηαζ ηα απμηεθέζιαηα ηδξ ελέηαζδξ ηδξ ιζηνμδμιήξ ημο ςημθίεμο ηδξ ιανίδαξ (Spicara smaris L.). Χηυθζεμζ απυ 30 άημια ιανίδαξ ιε εφνμξ μθζημφ ιήημοξ απυ 50 mm έςξ 163 mm πνμενπυιεκα απυ ηδ αζμθμβζηή δεζβιαημθδρία ημο ΔΠΑΓ ζημκ Ανβμζανςκζηυ ηυθπμ, εβηθείζεδηακ ζε επμλζηή νδηίκδ ηαζ ηαηυπζκ ηνζρίιαημξ ηαζ θείακζδξ πνμέηορακ θεπηέξ ηάεεηεξ ημιέξ μζ μπμίεξ θςημβναθήεδηακ ιε μπηζηυ ιζηνμζηυπζμ ηαζ ακαβκχζηδηακ ιε ηδ πνήζδ θμβζζιζημφ επελενβαζίαξ εζηυκςκ. Ζ ακάβκςζδ ηαζ ηαηαιέηνδζδ ηςκ διενδζίςκ αολδηζηχκ δαηηοθίςκ έδεζλε δαηηοθίμοξ πμο ακηζζημζπμφζακ ζε 119 έςξ 536 διένεξ. Σμ ζζβιμεζδέξ ιμκηέθμ (S-Curve) επζθέπεδηε βζα ηδ ζπέζδ ιήημοξ-δθζηίαξ ιε α = 5,435 ηαζ α = -175,916 ςξ αοηυ πμο έδςζε ημ ηαθφηενμ R 2. Ο εηήζζμξ δαηηφθζμξ, πμο ηαοημπμζήεδηε ςξ ιζα πενζμπή ιε διενήζζμοξ δαηηοθίμοξ πμθφ ιζηνμφ πάπμοξ, παναηδνήεδηε ζε άημια ιε μθζηυ ιήημξ υπζ ιζηνυηενμ απυ 123 mm ηαζ μ ζπδιαηζζιυξ ημο θαίκεηαζ κα βίκεηαζ ιεηαλφ Ηακμοανίμο ηαζ Απνζθίμο. Λέμεηο θιεηδηά: Spicara smaris, Αγαίν Πέιαγνο, σηόιηζνη, κηθξνδνκή, εκεξήζηνη δαθηύιηνη. *οββναθέαξ επζημζκςκίαξ: Γεκαλά Μανία (denaxam@hcmr.gr) 1. Δηζαγσγή Ζ ιεθέηδ ηδξ ιζηνμδμιήξ ηςκ ςημθίεςκ ακαπηφπεδηε ζηζξ ανπέξ ηδξ δεηαεηίαξ ημο 70 ηαζ ζήιενα πνδζζιμπμζείηαζ εονέςξ ζε πθδεχνα ιεθεηχκ ηςκ πνχηςκ ζηαδίςκ γςήξ, δθζηίαξ, 271

272 ακάπηολδξ, ζηναημθυβδζδξ, ιεηακάζηεοζδξ, εκδζζιυηδηαξ ηαζ δμιήξ ηςκ πθδεοζιχκ (Morales-Nin, 1992, Stevenson and Campana 1992). Ζ ιανίδα Spicara smaris L. είκαζ είδμξ ημζκυ ζηδ Μεζυβεζμ, ζημκ Δφλεζκμ Πυκημ ηαζ ζηζξ ακαημθζηέξ αηηέξ ημο Αηθακηζημφ. Υαναηηδνίγεηαζ απυ πνςηυβοκμ ενιαθνμδζηζζιυ, ηαζ ειθακίγεζ θοθεηζηυ δζιμνθζζιυ ηαηά ηδκ ακαπαναβςβζηή πενίμδμ (Whitehead et al. 1986). Έπεζ ιεβάθδ μζημκμιζηή αλία βζα ηδκ Δθθάδα δεδμιέκμο μηζ δ παναβςβή ιανίδαξ ακηζπνμζςπεφεζ ηοιαίκεηαζ απυ 4,5 έςξ 6% ηδξ ζοκμθζηήξ παναβςβήξ αθζεοιάηςκ ηδξ πχναξ ηα ηεθεοηαία 25 πνυκζα (Kavadas, et al, 2013). φιθςκα ιε ηδκ Δθθδκζηή ηαηζζηζηή Ανπή, ιέπνζ ηαζ ημ 2010, μζ εηθμνηχζεζξ ηδξ αζκηγυηναηαξ απμηεθμφζακ ημ 48.60% ηδξ ζοκμθζηήξ παναβςβήξ ηδξ ιανίδαξ, ηαζ αημθμοεμφζακ ηα δίπηοα (21.06%), μζ ιδπακυηναηεξ (20.22%), ηαζ ηα βνζβνί (10.06%). ημ πανεθευκ έπμοκ βίκεζ ιεθέηεξ βζα ηδκ δθζηία ηαζ ηδκ αφλδζδ ημο είδμοξ (Tsangridis & Filippousis, 1991, 1992, Dulcic, et al. 2003), ααζζζιέκεξ ηονίςξ ζηδκ ενιδκεία ζπδιαηζζιμφ ηςκ εηδζίςκ δαηηοθίςκ ζηδ ιαηνμδμιή ηςκ ςημθίεςκ. Μέπνζ ζήιενα, δεκ οπάνπμοκ δδιμζζεοιέκεξ ενβαζίεξ πμο κα ααζίγμκηαζ ζηδκ ακάβκςζδ ηςκ διενδζίςκ δαηηοθίςκ ηαζ ζηδκ ιζηνμδμιή ηςκ ςημθίεςκ ηδξ ιανίδαξ. ημπυξ ηδξ πανμφζαξ ενβαζίαξ είκαζ κα ζοιαάθθεζ ζηδκ ιεθέηδ ηδξ αφλδζδξ ηαηά ηα πνχηα ζηάδζα ημο ηφηθμο γςήξ ηδξ ιανίδαξ ιέζς ηδξ ελέηαζδξ ηδξ ιζηνμδμιήξ ηςκ ςημθίεςκ. 2. Τιηθά θαη Μέζνδνη Γζα ηδκ πανμφζα ενβαζία πνδζζιμπμζήεδηακ 30 ςηυθζεμζ απυ άημια ιανίδαξ ιε εφνμξ μθζημφ ιήημοξ (TL) ιεηαλφ 50 ηαζ 163 mm, ηα μπμία πνμήθεακ απυ ηδ αζμθμβζηή δεζβιαημθδρία ζε ιδπακυηναηα ηαζ βνζ-βνζ ημο «Δεκζημφ Πνμβνάιιαημξ οθθμβήξ Αθζεοηζηχκ Γεδμιέκςκ» ζημκ Ανβμζανςκζηυ Κυθπμ απυ ημκ Οηηχανζμ 2013 ιέπνζ ημκ Μάζμ Απυ ηα άημια αοηά αθαζνέεδηακ μζ ςηυθζεμζ (sagittae), ηαεανίζηδηακ, θςημβναθήεδηε δ ελςηενζηή ημοξ πθεονά ηαζ εβηθείζηδηακ μζ δελζμί ςηυθζεμζ ζε εήηεξ εβηθεζζιμφ απυ ζζθζηυκδ, δζαζηάζεςκ 14 x 6 x 4 mm, ιε ηδκ πνήζδ επμλζηήξ νδηίκδξ. Έπεζηα απυ ηδκ πάνμδμ 24 ςνχκ, ηα δμηίιζα ημπμεεηήεδηακ πάκς ζε ακηζηεζιεκμθυνμοξ πθάηεξ ηαζ ζηαεενμπμζήεδηακ ιε πνήζδ εενιμπθαζηζηήξ νδηίκδξ. Δκ ζοκεπεία, ιε ηδκ πνήζδ ηνμπμφ θείακζδξ, ημ ηάεε δμηίιζμ ηνίθηδηε δζαδμπζηά ιε θφθθα ηνζρίιαημξ ιεβέεμοξ 800P, 1600P ηαζ 2400P. Γζα ημ ηεθζηυ ζηάδζμ θείακζδξ ηαζ ηδκ ειθάκζζδ ηςκ διενήζζςκ αολδηζηχκ δαηηοθίςκ πνδζζιμπμζήεδηακ δζαδμπζηά θεζακηζηά θφθθα δζαθμνεηζημφ δζαιεηνήιαημξ ηυηημο (40, 24, 1ιm). Σμ επίπεδμ θείακζδξ εθεβπυηακ δζανηχξ ιε ηδκ πνήζδ μπηζημφ ιζηνμζημπίμο βζα κα απμθεοπεεί ημ εκδεπυιεκμ οπεναμθζηήξ θείακζδξ ηαζ ηοπυκ απχθεζαξ πθδνμθμνίαξ ζε επζιένμοξ ηιήιαηα ημο ςημθίεμο. Χξ απμηέθεζια ηδξ ακςηένς δζαδζηαζίαξ πνμέηορακ θεπηέξ ηάεεηεξ ημιέξ πάπμοξ 0,2 έςξ 0,4 mm μζ μπμίεξ θςημβναθήεδηακ ιε ηδκ πνήζδ μπηζημφ ιζηνμζημπίμο (Olympus BX41) ιε ιεβέκεοζδ 20Υ ηαζ 40Υ, πνμηεζιέκμο κα βίκεζ ηαηαιέηνδζδ ηςκ διενδζίςκ αολδηζηχκ δαηηοθίςκ (Δζηυκα 1). Γζα ηδ θήρδ ηςκ ρδθζαηχκ θςημβναθζχκ, πνδζζιμπμζήεδηακ αζκηεμηάιενεξ ακαθμβζηήξ εζηυκαξ, Ζ/Τ, ιεηαηνμπέαξ ακαθμβζηήξ ζε ρδθζαηή εζηυκα ηαζ ημ θμβζζιζηυ πνμβνάιιαημξ ακάθοζδξ ρδθζαηχκ εζηυκςκ Image Pro Plus 4,5 Γζα ηδκ ενιδκεία ηαζ ακάθοζδ ηςκ δαηηοθίςκ πνδζζιμπμζήεδηακ δδιμζζεοιέκα ζηδ δζεεκή αζαθζμβναθία πνςηυημθθα (Morales-Nin 1992, Campana & Jones 1992). Γζα ηδ ζπέζδ ιήημοξ ζχιαημξ-δθζηίαξ επζθέπεδηε ημ ιμκηέθμ S- curve πμο πανμοζίαζε ηδκ ηαθφηενδ ζοζπέηζζδ (R 2 =86,5) ημ μπμίμ εηθνάγεηαζ ςξ αημθμφεςξ: TL=exp(a+b/D), υπμο TL είκαζ ημ μθζηυ ιήημξ, α είκαζ μ ζοκηεθεζηήξ παθζκδνυιδζδξ, α δ ηθίζδ ηαζ D μ ανζειυξ ηςκ ιεηνδεέκηςκ διενχκ. Ζ ακαβκχνζζδ ημο εηήζζμο δαηηοθίμο ζηδκ ιζηνμδμιή ααζίζηδηε ζηδκ πανμοζία πμθθχκ διενδζίςκ δαηηοθίςκ ιζηνμφ πάπμοξ. Δπίζδξ ζοβηνίεδηε δ απυζηαζή ημοξ απυ ηδκ πενζθένεζα ημο ςημθίεμο ζηζξ εζηυκεξ ηςκ ημιχκ ηαζ ζηζξ εζηυκεξ μθυηθδνμο ημο ςημθίεμο. 3. Απνηειέζκαηα Ο ανζειυξ ηςκ διενδζίςκ δαηηοθίςκ πμο ηαηαιεηνήεδηακ ζημ ζφκμθμ ηςκ δεζβιάηςκ πμο ιεθεηήεδηακ ηοιαίκμκηακ απυ 119 (ζε άημιμ μθζημφ ιήημοξ TL=50mm) έςξ 536 (ζε άημιμ μθζημφ ιήημοξ ιήημξ TL= 163mm) (Πίκαηαξ 1). Ζ εθανιμβή ημο ιμκηέθμο S-Curve ιεηαλφ ημο ιήημοξ ηαζ ημο ανζειμφ ηςκ διενδζίςκ δαηηοθίςκ ηδξ ιανίδαξ πανμοζζάγεηαζ ζημ πήια 1. Οζ ζοκηεθεζηέξ ημο ιμκηέθμο ήηακ α = 5,435 ηαζ α = -175,916. Ζ πενζμπή πμο εεςνήεδηε υηζ ακηζπνμζςπεφεζ ημκ πνχημ εηήζζμ δαηηφθζμ, πενζμπή ιε διενήζζμοξ δαηηφθζμοξ ιζηνμφ πάπμοξ, ήηακ ειθακήξ ζηζξ εζηυκεξ εκκέα ημιχκ ςημθίεςκ, δ δε απυζηαζδ ηδξ πενζμπήξ αοηήξ απυ ηδκ πενζθένεζα ημο ςημθίεμο, ζοκέπζπηε ιε αοηήκ πμο ιεηνήεδηε βζα ημοξ εηήζζμοξ δαηηοθίμοξ ζηζξ εζηυκεξ ηδξ ιαηνμδμιήξ ηςκ ςημθίεςκ (Δζηυκεξ 2, 3). Ζ ιέζδ απυζηαζδ ιεηαλφ ηςκ διενδζίςκ δαηηοθίςκ ζηδκ πενζμπή ημο πνχημο εηδζίμο δαηηοθίμο ήηακ ιζηνυηενδ (1,777±0,0337) απυ αοηή ζηζξ εηαηένςεεκ αοημφ πενζμπέξ (2,913±0,081) (Δζηυκα 4). 272

273 TL HydroMedit 2014, November 13-15, Volos, Greece Πίλαθαο 1. Μήθε ησλ αηφκσλ καξίδαο κε ηνλ αξηζκφ ησλ εκεξψλ πνπ αλαγλψζζεθαλ ζηνπο σηνιίζνπο ηνπο θαη ηελ παξνπζία εηήζηνπ δαθηπιίνπ. ΣL(mm) Αν. Ζιεν. Γαηηφθζμξ Μήκαξ ζπδιαηζζιμφ ΣL(mm) Αν. Ζιεν. Γαηηφθζμξ Μήκαξ ζπδιαηζζιμφ ΥΗ ΥΗ ΥΗ ΥΗ ΥΗ ΥΗ ΥΗ ΥΗ ΥΗ ΥΗ ΥΗ ΥΗ ΥΗ ΝΑΗ 2μξ-3μξ ΥΗ ΝΑΗ 2μξ-3μξ ΥΗ ΝΑΗ 1μξ-2μξ ΥΗ ΝΑΗ 3μξ-4μξ ΥΗ ΝΑΗ 2μξ-4μξ ΥΗ ΝΑΗ 2μξ-3μξ ΥΗ 153* 314 ΝΑΗ 1μξ-2μξ ΥΗ ΝΑΗ 2μξ-3μξ ΥΗ 163* 536 ΝΑΗ 1μξ-2μξ *ειθάκζζδ δφμ πενζμπχκ ιε ποηκμφξ διενήζζμοξ δαηηφθζμοξ Ο πνχημξ εηήζζμξ δαηηφθζμξ θάκδηε κα ζπδιαηίγεηαζ ιεηά απυ 180 (εθάπζζημ) έςξ 372 (ιέβζζημ) διενδζίμοξ δαηηοθίμοξ, μζ μπμίμζ ακηζζημζπμφκ ιε αάζδ ημ ιμκηέθμ S-Curve ζε μθζηυ ιήημξ 86,3 ηαζ 142,9 mm ακηζζημίπςξ. Ο ζπδιαηζζιυξ ημο θαίκεηαζ κα βίκεηαζ ιεηαλφ Ηακμοανίμο ηαζ Απνζθίμο, υπςξ ανέεδηε απυ ηδκ ακηίζηνμθδ ιέηνδζδ ηςκ διενδζίςκ δαηηοθίςκ απυ ηδκ διενμιδκία ζφθθδρδξ. Με αάζδ ημ ιμκηέθμ, άημια πμο έπμοκ ζπδιαηίζεζ 365 διενήζζμοξ δαηηοθίμοξ, δδθ. έπμοκ ζοιπθδνχζεζ έκα διενμθμβζαηυ έημξ, ακηζζημζπμφκ ζε μθζηυ ιήημξ 141,7 mm. Σα άημια ιε μθζηυ ιήημξ 153 mm ηαζ 163 mm, ειθάκζζακ δφμ πενζμπέξ ιε ποηκμφξ διενδζίμοξ δαηηοθίμοξ, μζ μπμίεξ εεςνήεδηε υηζ ακηζζημζπμφκ ζε δφμ εηδζίμοξ δαηηοθίμοξ DAYS ρήκα 1. Γξαθηθή παξάζηαζε ηεο ζρέζεο κήθνπο ζψκαηνο-ειηθίαο ηεο καξίδαο ζηνλ Αξγνζαξσληθφ θφιπν. 273

274 Δηθφλα 1. Μηθξνθσηνγξαθία επί κέξνπο ηκήκαηνο ηεο ηνκήο σηνιίζνπ Μαξίδαο. (κεγέζπλζε 20x). Δηθφλα 2. Σνκή σηνιίζνπ καξίδαο κε κεγέζπλζε 4x. Γηαθξίλεηαη ε πεξηνρή ηνπ εηήζηνπ δαθηπιίνπ θαη ε απφζηαζή ηνπ απφ ηελ πεξηθέξεηα. Δηθφλα 3. Φσηνγξαθία νιφθιεξνπ ηνπ σηφιηζνπ (12.5x) ηνπ νπνίνπ ηελ ηνκή βιέπνπκε ζηελ Δηθφλα 2. Γηαθξίλεηαη ν εηήζηνο δαθηχιηνο θαη ε απφζηαζή ηνπ απφ ηελ πεξηθέξεηα, ίζε κε απηή ηεο ηνκήο. Σν ζεκείν πνπ θαίλεηαη ε κέηξεζε είλαη θαη ην ζεκείν ηνκήο ηνπ σηνιίζνπ. Δηθφλα 4. Σκήκα ηνκήο σηνιίζνπ καξίδαο (κεγέζπλζε 20x). ην δεμηφ κέξνο δηαθξίλνληαη κηθξφηεξεο απνζηάζεηο κεηαμχ ησλ εκεξεζίσλ δαθηπιίσλ πνπ ζεσξήζεθε φηη αληηπξνζσπεχνπλ ηελ πεξηνρή ζρεκαηηζκνχ ηνπ εηήζηνπ δαθηπιίνπ. 4. πδήηεζε Σα απμηεθέζιαηα ηδξ πανμφζαξ ενβαζίαξ απμηεθμφκ έκδεζλδ υηζ δ ιανίδα είκαζ είδμξ ηαπείαξ αφλδζδξ. Σα ιήηδ ζπδιαηζζιμφ ημο πνχημο εηήζζμο δαηηοθίμο είκαζ ιεβαθφηενα απυ αοηά πμο έπμοκ δδιμζζεοηεί ζε άθθεξ ενβαζίεξ. Οζ Vidalis & Tsimenidis (1996) ανήηακ κα ζπδιαηίγεηαζ ζηα 81 mm ιεζμοναίμο ιήημοξ, μζ Dulcic et al. (2003) ζηα 63mm μθζημφ ιήημοξ μζ Osman & Abdel Barr (2007) ζηα 104 mm μθζημφ ιήημζοξ. Οζ Tsangridis & Filippousis, (1991, 1992) ανήηακ ζηα 139 mm ιέζμο μθζημφ ιήημοξ, ημκ πνχημ εηήζζμ δαηηφθζμ ηαζ ζηα 159 mm ημκ δεφηενμ εηήζζμ δαηηφθζμ, ιεηνήζεζξ πμο πνμζεββίγμοκ ηαζ εκζζπφμοκ ηα απμηεθέζιαηα ηδξ πανμφζαξ ενβαζίαξ. Οζ δζαθμνέξ ιε ηζξ ηνεζξ πνχηεξ ιεθέηεξ ιπμνεί κα μθείθμκηαζ ζε δζαθμνεηζηή ακάβκςζδ ηςκ ςημθίεςκ, δεδμιέκμο υηζ οπάνπμοκ δφμ ιε ηνείξ δαηηφθζμζ πνζκ ημκ πνχημ εεςνμφιεκμ απυ ηδκ πανμφζα ενβαζία εηήζζμ δαηηφθζμ, μζ μπμίμζ υιςξ ιάθθμκ ακηζπνμζςπεφμοκ αθθαβέξ ημο ηφηθμο ηδξ γςήξ ηδξ ιανίδαξ (π.π. ιεηαιυνθςζδ, αθθαβή εκδζαζηήιαημξ, δζαηνμθήξ). Άθθμζ θυβμζ ζημοξ μπμίμοξ ιπμνεί κα μθείθμκηαζ αοηέξ μζ δζαθμνέξ είκαζ μζ πενζααθθμκηζημί πανάβμκηεξ ηδξ ηάεε πενζμπήξ ιεθέηδξ. Ο πνχημξ εηήζζμξ δαηηφθζμξ, ζφιθςκα ιε ηδκ πανμφζα ενβαζία, θαίκεηαζ κα ζπδιαηίγεηαζ ιεηαλφ Ηακμοανίμο ηαζ Απνζθίμο, εκχ μζ Vidalis & Tsimenidis (1996) ανίζημοκ κα ζπδιαηίγεηαζ ιεηαλφ Μανηίμο ηαζ Ημοθίμο. Σα απμηεθέζιαηα ηδξ πανμφζαξ ενβαζίαξ πνέπεζ κα επζαεααζςεμφκ ηαζ απυ ηδ ιεθέηδ ηδξ ιζηνμδμιήξ ηςκ ςημθίεςκ επί πθέμκ αηυιςκ. Ακ μζ εκδείλεζξ βζα ηδκ αφλδζδ ηαζ ηδκ δθζηία, πμο ιαξ πανέπμοκ ηα απμηεθέζιαηα ηδξ πανμφζαξ ενβαζίαξ επζαεααζςεμφκ, ηυηε εα έπμοιε ίζςξ ιία δζαθμνεηζηή εζηυκα ηδξ αζμθμβίαξ ηδξ ιανίδαξ, πμο εα ιαξ αμδεήζεζ ζηδκ πνμζπάεεζα εηηίιδζδξ ηαζ δζαπείνζζδξ ηςκ απμεειάηςκ ηδξ. Δπραξηζηίεο Οζ ζοββναθείξ εέθμοκ κα εηθνάζμοκ ηζξ εοπανζζηίεξ ημοξ ζηδκ Π.Ν. Λάιπνδ ηαζ ζημκ Ν. Ξεκηίδδ βζα ηδκ αμήεεζα πμο ημοξ πνμζέθενακ ζηδκ επζιέθεζα ημο ηεζιέκμο ηαζ ζηδκ επελενβαζία ηςκ εζηυκςκ. Βηβιηνγξαθία Campana, S.e., and C.M. Jones. (1992). Analysis of otolith microstructure data, p In D.K. Stevenson and S.E. Campana [ed.] Otolith microstructure examination and analysis. Can. Spec. Publ. Fish. Aquat. Sci

275 Dulcic, J., Pallaoro, A., Cetinic, P., Kraljevic, M., Soldo, A., Jardas, I. (2003), Age, growth and mortality of picarel, Spicara smaris L. (Pisces: Centracanthidae), from the eastern Adriatic (Croatian coast) J. Appl. Ichthyol Kavadas, S., Damalas, D., Tserpes, G., Georgakarakos, E., Papaconstantinou, C., Maravelias, C., IMAS-Fish - Integrated Management System to support the sustainability of Greek fisheries resources. A multidisciplinary web-based database management system: implementation, capabilities, utilization and future prospects for fisheries stakeholders. Mediterranean Marine Science 14(1): Morales-Nin, B. (1992). Determination of growth in bony fishes from otolith microstructure FAO Fisheries Technical Paper. No Rome, FAO.. 51p. Osman, A.M., Abdel Barr, M Biological studies of spicara smaris (teleostei Centracanthidae) in Egyptian mediterranean waters. Proceedings of the 8th International Conference on the Mediterranean Coastal Environment, MEDCOAST, vol 1 (2007), pp Tsangridis, A.; Filippousis, N., (1991). Use of length frequency data in the estimation of growth parameters of three Mediterranean fish species: bogue (Boops boops L.), picarel (Spicara smaris L.) and horse mackerel (Trachurus trachurus L.). Fish. Res. 12, Tsangridis, A.; Filippousis, N., (1992). Growthpattern of picarel Spicara smaris (L.) (Centracanthidae), a protognyous species. Cybium 3, Vidalis, K., (1994). Biology and population dynamics of the picarel (Spicara smaris, L. 1758) on the Cretan Continental Shelf. PhD Thesis, Department of Biology, University of Crete, Greece. 257 pp. (in Greek with English abstract). Vidalis, K.; Tsimenidis, N., (1996). Age determination and growth of picarel (Spicara smaris L.) from the Cretan continental shelf (Greece). Fish. Res. 28, Whitehead, P.J.P., Bauchot, M.-L., Hureau, J.-C., Nielsen, J. and Tortonese, E., (1986). Fishes of the North-Eastern Atlantic and the Mediterranean. Vol. II. UNESCO, Paris:

276 DOCUMENTARY APPEARANCE OF Tylosurus acus imperialis INDIVIDUALS IN THERMAIKOS GULF Imsiridou A.*, Minos G., Kokkokiris L. Department of Fisheries and Aquaculture Technology, Alexander Technological Educational Institute of Thessaloniki, P.O. BOX 157, GR-63200, Nea Moudania, Greece. ABSTRACT For the last five years, large quantities of needlefishes are caught in Thermaikos Gulf every summer. Anglers call them vasilozarganes because of their large size. Apart from the common genus Belone, three species of the genus Tylosurus have been also reported in the Mediterranean sea: the subspecies Tylosurus acus imperialis and two rare lessepsian immigrants, T. crocodilus and T. choram. The systematic analyses of the individuals caught in Thermaikos Gulf resulted to the identification of the genus Tylosurus, but species discrimination is difficult. The aim of the present work was the identification of the large sized individuals caught in Thermaikos Gulf. For this reason, the PCR and sequencing analysis of the mitochondrial 16S rrna gene was used, in parallel with the morphometric and meristic anlysis. The PCR product was 600 bp and the analyzed nucleotide sequence of the 16S rrna gene was 558 bp. All of the studied individuals revealed the same haplotype which revealed a 99% percentage of maximum identity with T. acus imperialis (as revealed in the BLAST engine). Results of the morphometric (indexes between body length and length of fins) and meristic (number of finrays) analysis, confirm and reinforce the existence of T. acus imperialis individuals. Key words: Tylosurus, 16S rrna gene, genetic identification, meristic analysis, morphometric analysis *Corresponding author: Imsiridou A.( imsiri@otenet.gr) ΣΔΚΜΖΡΗΧΜΔΝΖ ΔΜΦΑΝΗΖ ΣΟΤ YΠΟΔΗΓΟΤ Tylosurus acus imperialis ΣΟ ΘΔΡΜΑΨΚΟ ΚΟΛΠΟ Ηκζηξίδνπ Α.*, Μίλνο Γ., Κνθνθχξεο Λ. Σιήια Σεπκμθμβίαξ Αθζείαξ ηαζ Τδαημηαθθζενβεζχκ, Αθελάκδνεζμ Σεπκμθμβζηυ Δηπαζδεοηζηυ Ίδνοια Θεζζαθμκίηδξ, Σ.Θ , Νέα Μμοδακζά, Δθθάδα Πεξίιεςε Σα ηεθεοηαία πέκηε έηδ, ηάεε ηαθμηαίνζ ζημ Θενιασηυ ηυθπμ αθζεφμκηαζ ζε ιεβάθεξ πμζυηδηεξ γανβάκεξ, πμο μζ ρανάδεξ ηζξ απμηαθμφκ ααζζθμγανβάκεξ ελαζηίαξ ημο ιεβάθμο ιεβέεμοξ ημοξ. ηδ Μεζυβεζμ, εηηυξ απυ ηζξ ημζκέξ γανβάκεξ ημο βέκμοξ Belone, έπεζ ακαθενεεί ηαζ δ πανμοζία ηνζχκ εζδχκ ημο βέκμοξ Tylosurus: ημ οπμείδμξ Tylosurus acus imperialis ηαζ δφμ θεζερζακμί ιεηακάζηεξ ιε ζπάκζα ειθάκζζδ, ηα είδδ T. crocνdilus ηαζ T. choram. Απυ ηδ ιμνθμθμβζηή ελέηαζδ αηυιςκ πμο αθζεφηδηακ ζημ Θενιασηυ ηυθπμ πνμέηορε υηζ ακήημοκ ζημ βέκμξ Σylosurus, αθθά δ δζάηνζζδ ημο είδμοξ δεκ είκαζ εφημθδ. ηυπμξ ηδξ πανμφζαξ ενβαζίαξ ήηακ δ ηαοημπμίδζδ ηςκ ααζζθμγανβακχκ ημο Θενιασημφ ηυθπμο. Γζα ημ ζημπυ αοηυ, έβζκε πνήζδ ηδξ αθοζζδςηήξ ακηίδναζδξ πμθοιενάζδξ (PCR) ηαζ ηδξ ακάθοζδξ πνςημδζάηαλδξ ημο 16S rrna ιζημπμκδνζαημφ βμκζδίμο, εκχ πανάθθδθα 276

277 ακαθφεδηακ ιενζημί ιμνθμιεηνζημί (δείηηεξ ζςιαηζημφ ιήημοξ ηαζ ιήημοξ πηενοβίςκ) ηαζ ιενζζηζημί (ανζειυξ αηηίκςκ ηςκ πηενοβίςκ) παναηηήνεξ ηςκ δεζβιάηςκ. Σμ πνμσυκ ηδξ αθοζζδςηήξ ακηίδναζδξ πμθοιενάζδξ ήηακ πενίπμο 600 γεφβδ αάζεςκ ηαζ δ αημθμοεία ημο ιζημπμκδνζαημφ βμκζδίμο 16S rrna πμο ακαθφεδηε ήηακ 558 γεφβδ αάζεςκ. θα ηα άημια είπακ ημκ ίδζμ απθυηοπμ, μ μπμίμξ έδςζε έκα πμζμζηυ ιέβζζηδξ μιμζυηδηαξ 99% ιε ηo οπμείδoξ T. acus imperialis (ιδπακή ακαγήηδζδξ BLAST). Δπίζδξ, ηα απμηεθέζιαηα ηδξ ιμνθμιεηνζηήξ ηαζ ιενζζηζηήξ ακάθοζδξ επζαεααίςζακ ηαζ εκίζποζακ ηδκ φπανλδ αηυιςκ ημο οπμείδμοξ T. acus imperialis. Λέξειρ κλειδιά: Tylosurus, γνλίδην16s rrna, γελεηηθή ηαπηνπνίεζε, κεξηζηηθή αλάιπζε, κνξθνκεηξηθή αλάιπζε *οββναθέαξ επζημζκςκίαξ: Ηιζζνίδμο Ακαζηαζία 1. Δηζαγσγή Δηηυξ απυ ηζξ ημζκέξ γανβάκεξ ημο βέκμοξ Belone, ζηδ Μεζυβεζμ έπμοκ ακαθενεεί ηαζ ηνία είδδ ημο βέκμοξ Tylosurus: ημ είδμξ Tylosurus acus (Lacepède 1803) ηαζ δφμ θεζερζακμί ιεηακάζηεξ, ημ είδμξ Tylosurus crocνdilus (Péron & Lesueur 1821) ηαζ ημ είδμξ Tylosurus choram (Rüppell 1837) ιε πμθφ ζπάκζα ειθάκζζδ (Collete & Parin 1986, Sinis 2005). Tμ είδμξ T. acus ειθακίγεζ ζε δζάθμνεξ βεςβναθζηέξ πενζμπέξ οπμείδδ υπςξ ημ T. acus acus (Lacepède 1803) ζημ Γοηζηυ Αηθακηζηυ, ημ T. acus rafale (Collete & Parin 1970) ζημ Κυθπμ ηδξ Γμοζκέαξ, ημ T. acus melanotus (Bleeker 1850) ζημκ Ηκδζηυ ηαζ ζημ Γοηζηυ Δζνδκζηυ Χηεακυ, ημ T. acus pacificus (Steindachner 1876) ζημκ Ακαημθζηυ Δζνδκζηυ Χηεακυ ηαζ ημ T. acus imperialis (Rafinesque 1810) ζηδ Μεζυβεζμ. ηυπμξ ηδξ πανμφζαξ ενβαζίαξ είκαζ δ ηαοημπμίδζδ αηυιςκ ημο βέκμοξ Tylosurus, ηα μπμία αθζεφηδηακ ζημ Θενιασηυ ηυθπμ. Γζα ημ θυβμ αοηυ έβζκε βεκεηζηή ακάθοζδ ιε ηδ πνήζδ ηδξ αθοζζδςηήξ ακηίδναζδξ πμθοιενάζδξ (PCR) ηαζ ηδξ ακάθοζδξ πνςημδζάηαλδξ ημο ιζημπμκδνζαημφ βμκζδίμο ημ μπμίμ ηςδζημπμζεί βζα ημ 16S νζαμζςιζηυ RNA (16S rrna). Πανάθθδθα δζεκενβήεδηε ιμνθμιεηνζηή ηαζ ιενζζηζηή ακάθοζδ ηςκ δεζβιάηςκ. 2. Τιηθά θαη Μέζνδνη Αθζεφηδηακ 112 άημια ημο βέκμοξ Tylosurus (Δζηυκα 1) απυ επαββεθιαηίεξ ρανάδεξ ζηδ πενζμπή ημο Θενιασημφ ηυθπμο, απυ ημκ Ημφκζμ ημο 2013 έςξ ημκ Ημφκζμ ημο Πέκηε άημια δζαθμνεηζημφ θφθμο (ανζεκζηά/εδθοηά) ηαζ δζαθμνεηζηχκ ιεβεεχκ, ιεθεηήεδηακ ιε ηδκ ακάθοζδ πνςημδζάηαλδξ ημο 16S rrna βμκζδίμο. Δθήθεδ ιοσηυξ ζζηυξ απυ ηα δείβιαηα ηαζ αημθμφεδζε απμιυκςζδ μθζημφ DNA, ζφιθςκα ιε ημοξ Hillis et al. (1996). Έκα γεφβμξ παβηυζιζςκ εηηζκδηχκ πνδζζιμπμζήεδηε βζα ηδκ εκίζποζδ ημο 16S rrna βμκζδίμο (Palumbi 1996). Σμ ιείβια ακηίδναζδξ πενζείπε 100 ng DNA, 1 PCR buffer, 2,2 mm MgCl 2, 20 pmol απυ ηάεε εηηζκδηή, 0,25 mm απυ ηάεε κμοηθεμηίδζμ ηαζ 0,5U Taq polymerase. To πνυβναιια εκίζποζδξ είπε ςξ ελήξ: ανπζηή απμδζάηαλδ ζημοξ 94 C βζα 3 θεπηά, 31 ηφηθμζ (94 C βζα 50 s, 50 C βζα 50 s, 72 C βζα 50 s) ηαζ ιία ηεθζηή επζιήηοκζδ ζημοξ 72 o C βζα 5 θεπηά. H δθεηηνμθυνδζδ 3 ιl ημο πνμσυκημξ PCR έβζκε ζε 1 TBE buffer βζα 1 χνα, ζε ηάζδ 150 V. Ζ δθεηηνμθυνδζδ έβζκε ζε 1,5% πδηηή αβανυγδξ δ μπμία πενζείπε 0,5 ιg/ml ανςιζμφπμ αζείδζμ. Σα πνμσυκηα ηδξ εκίζποζδξ εθέβπεδηακ ιε οπενζχδδ αηηζκμαμθία (UV), θςημβναθήεδηακ ηαζ ζηάθεδηακ ζηδ VBC (Βζέκκδ, Αοζηνία), βζα ακάθοζδ πνςημδζάηαλδξ ιε ηδ πνήζδ ηαζ ηςκ δφμ εηηζκδηχκ. Οζ κμοηθεμηζδζηέξ αημθμοείεξ πμο πνμέηορακ εθέβπεδηακ μπηζηά, ιε αάζδ ημ πνςιαημβνάθδια πμο ακηζζημζπμφζε ζηδ ηάεε ιία. ηδ ζοκέπεζα ακαθφεδηακ ιε ηδ πνήζδ ηςκ παηέηςκ Clustal X (Thompson et al. 1997) ηαζ BioEdit (Hall 1999). Σέθμξ, δ μιμζυηδηά ημοξ ιε αημθμοείεξ άθθςκ εζδχκ ηδξ μζημβέκεζαξ Belonidae εθέβπεδηε ιε ηδ ιδπακή ακαγήηδζδξ BLAST ( 277

278 ημ ζφκμθμ ηςκ αηυιςκ έβζκε ιμνθμιεηνζηή ηαζ ιενζζηζηή ακάθοζδ ηαζ ηαηαβνάθδηακ δζάθμνα βκςνίζιαηα, υπςξ ή πανμοζία ή ιδ αναβπζαηχκ αηακεχκ ηαζ ηανίκαξ ζηδ αάζδ ημο μοναίμο ιίζπμο. οβηεηνζιέκα ζε ηάεε άημιμ ιεηνήεδηακ μ ανζειυξ ηςκ αηηίκςκ ζημ ναπζαίμ (D) ηαζ εδνζηυ (A) πηενφβζμ, ηαεχξ ηαζ ζηα εςναηζηά (P) ηαζ ημζθζαηά (V) πηενφβζα. Δπίζδξ, εθήθεδ ημ ιήημξ υθςκ ηςκ πηενοβίςκ απυ ηδ αάζδ ιέπνζ ηδκ άηνδ ημο. Σέθμξ, εηηζιήεδηακ μζ δείηηεξ (πδθίηα) ιεηαλφ ημο ζςιαηζημφ ιήημοξ (BL) ηαζ ημο ιήημοξ ημο εςναηζημφ (BL/P), ημζθζαημφ (BL/V), ναπζαίμο (BL/D) ηαζ εδνζημφ πηενοβίμο (BL/A), ηαεχξ ηαζ ημ πδθίημ ιεηαλφ ζςιαηζημφ ιήημοξ ηαζ ιήημοξ ηεθαθήξ (BL/HL). Δηθφλα 1. Μνξθνινγία αηφκνπ ηνπ ππνείδνπο Tylosurus acus imperialis πνπ αιηεχηεθε ζην Θεξκατθφ θφιπν. 3. Απνηειέζκαηα Σα πνμσυκηα ηδξ αθοζζδςηήξ ακηίδναζδξ πμθοιενάζδξ εθέβπεδηακ ιε ηδ αμήεεζα ημο ιμνζαημφ ιάνηονα 100 bp DNA ladder ηαζ ήηακ πενίπμο 600 γεφβδ αάζεςκ (Δζηυκα 2). Ζ αημθμοεία ημο ιζημπμκδνζαημφ βμκζδίμο 16S rrna πμο ακαθφεδηε ήηακ 558 γεφβδ αάζεςκ, βζα υθα ηα άημια πμο ιεθεηήεδηακ. θα ηα άημια Tylosurus απμηάθορακ ημκ ίδζμ απθυηοπμ μ μπμίμξ ηαηαηέεδηε ζηδ GenBank (accession number KF433075). Ο απθυηοπμξ αοηυξ εζζήπεδηε ζηδ ιδπακή ακαγήηδζδξ BLAST ηαζ έδςζε έκα πμζμζηυ ιέβζζηδξ μιμζυηδηαξ 99% ιε ηo οπμείδoξ Tylosurus acus imperialis (GeneBank AF , Banford et al. 2004). Σμ πμζμζηυ ιέβζζηδξ μιμζυηδηαξ ήηακ 96% ιε ημ είδμξ Tylosurus crocodilus (GeneBank AF , AF , AF , AF , Banford et al. 2004; GeneBank AF , AF , Lovejoy 2000) ηαζ 92% ιε ημ είδμξ Belone belone (GeneBank KJ , KJ , unpublished; GeneBank AF , Banford et al. 2004). Δηθφλα 2. Ζιεθηξνθφξεζε πεθηήο αγαξφδεο φπνπ θαίλνληαη ηα πξντφληα ελίζρπζεο ηνπ κηηνρνλδξηαθνχ γνληδίνπ 16S rrna κεγέζνπο 600 δεπγψλ βάζεσλ, γηα ηα άηνκα Tylosurus πνπ κειεηήζεθαλ. Ο κνξηαθφο κάξηπξαο πνπ ρξεζηκνπνηήζεθε ήηαλ ν 100 bp DNA ladder. ηα άημια πμο ιεθεηήεδηακ, ημ μθζηυ ιήημξ (TL) ηοιάκεδηε απυ 59,3 έςξ 111,6 cm. Οζ ηζιέξ ηςκ δεζηηχκ πμο εηηζιήεδηακ έπμοκ ςξ αημθμφεςξ: ημ πδθίημ BL/P ηοιάκεδηε απυ 8,3 έςξ 278

279 10,8, ημ πδθίημ BL/V ηοιάκεδηε απυ 10,9 έςξ 17,7, ημ πδθίημ BL/D ηοιάκεδηε απυ 10,5 έςξ 15,3, ημ πδθίημ BL/A ηοιάκεδηε απυ 9,3 έςξ 14,3 ηαζ ημ πδθίημ BL/HL ηοιάκεδηε απυ 2,0 έςξ 2,8. Δπίζδξ, ζημ ναπζαίμ πηενφβζμ ιεηνήεδηακ απυ 23 έςξ 26 αηηίκεξ (ζοκήεςξ 24) ηαζ ζημ εδνζηυ πηενφβζμ ιεηνήεδηακ απυ 21 έςξ 23 αηηίκεξ (ζοκήεςξ 22). 4. πδήηεζε Ακαθμνζηά ιε ημ βέκμξ Tylosurus, έπεζ ακαθενεεί ημ οπμείδμξ T. acus imperialis βεκζηά ζηδ Μεζυβεζμ (Bauchot 1987, Collete & Parin 1986) ηαζ εζδζηά ζηδκ πενζμπή ημο Αζβαίμο (Bauchot 1987, Akyol & Kara 2011, Türker Çakır & Zengin 2013). Τπάνπεζ ιζα ακαθμνά απυ ημ Βυνεζμ Αζβαίμ ημο είδμοξ T. crocνdilus (Sinis 2005), αθθά δζαηδνμφιε ιεβάθεξ επζθοθάλεζξ ηαεχξ δε ζοκμδεφεηαζ απυ βεκεηζηή ακάθοζδ ηαζ δ ηεηιδνίςζδ ιε ηδ πνήζδ ιενζζηζηχκ ηαζ ιμνθμιεηνζηχκ παναηηδνζζηζηχκ είκαζ εθθζπήξ ηαζ ακηζθαηζηή. Σμ είδμξ T. choram είκαζ θεζερζακυξ ιεηακάζηδξ πμο ειθακίζηδηε ζηδ Μεζυβεζμ, αθθά δεκ οπάνπμοκ ακαθμνέξ ζημ Αζβαίμ ηαζ πενζμνίγεηαζ πνμξ ημ πανυκ ζηδκ Νμηζμακαημθζηή Μεζυβεζμ (Bauchot 1987). Σα απμηεθέζιαηα ηδξ βεκεηζηήξ ακάθοζδξ δδθχκμοκ υηζ ηα άημια ημο βέκμοξ Tylosurus πμο αθζεφηδηακ ζημ Θενιασηυ Κυθπμ ακήημοκ ζημ οπμείδμξ T. acus imperialis. Σα απμηεθέζιαηα απυ ηδ βεκεηζηή ακάθοζδ ζοιθςκμφκ ηαζ ιε αοηά πμο πνμηφπημοκ απυ ηδ ιμνθμθμβζηή ακάθοζδ ηςκ αηυιςκ. Ακαθοηζηυηενα: Tα άημια ηδξ πανμφζαξ ιεθέηδξ δε είκαζ πζεακυ κα ακήημοκ ζηα είδδ Belone belone ηαζ Belone svetovidovi, ηαεχξ ηα ελεηαγυιεκα δείβιαηα δε δζέεεηακ αναβπζαηέξ άηακεεξ ηαζ έθενακ ιζα ιζηνή επζιήηδ ιαφνδ ηανίκα ζηδ αάζδ ημο μοναίμο ιίζπμο, παναηηδνζζηζηά βκςνίζιαηα ημο βέκμοξ Tylosurus. Δπίζδξ ηα άημια πμο ιεθεηήεδηακ ήηακ εοιεβέεδ, απυ 60 έςξ 106 εη. (SL), εκχ ηα άημια ημο είδμοξ B. belone ηοιαίκμκηαζ απυ 30 έςξ 60 εη. (SL) ηαζ θηάκμοκ ιέπνζ ηα 90 εη. (SL) ηαζ ηα άημια ημο είδμοξ B. svetovidovi είκαζ αηυιδ ιζηνυηενμο ιεβέεμοξ ηαεχξ δεκ λεπενκμφκ ηα 57 εη. (SL). Tα άημια ηδξ πανμφζαξ ιεθέηδξ δε είκαζ πζεακυ κα ακήημοκ ζημ είδμξ T. choram ηαεχξ ηα άημια αοημφ ημο είδμοξ δεκ λεπενκμφκ ηα 70 εη. SL, εκχ ηα δείβιαηα ιαξ θεάκμοκ ιέπνζ ημ ιήημξ ηςκ 106,3 εη. SL. ημ είδμξ T. choram ηα εςναηζηά ηαζ ημζθζαηά πηενφβζα είκαζ ζπεηζηά επζιήηδ, ηαζ ημ πδθίημ BL/P ηοιαίκεηαζ απυ 6,6 έςξ 8,3 εκχ ημ πδθίημ BL/V ηοιαίκεηαζ απυ 7,9 έςξ 10,6 (Collette 1984, Bauchot 1987). ηα δείβιαηα πμο ιεθεηήζαιε ημ πδθίημ BL/P ηοιαίκεηαζ απυ 8,3 έςξ 10,8 ηαζ ημ πδθίημ BL/V ηοιαίκεηαζ απυ 10,9 έςξ 17,7, ηζιέξ πανυιμζεξ ιε αοηέξ (BL/P = 8,0-12,4 ηαζ BL/V = 10,0-14) βζα ημ οπμείδμξ T. acus imperialis (Collette 1984, Bauchot 1987). Δπίζδξ, ζημ είδμξ T. choram ημ ναπζαίμ ηαζ ημ εδνζηυ πηενφβζμ είκαζ ζπεηζηά επζιήηδ ηαζ ζε ζπέζδ ιε ημ ιήημξ ημο ζχιαημξ (BL), ημ πδθίημ BL/D ηοιαίκεηαζ απυ 5,4 έςξ 10,6 ηαζ ημ πδθίημ BL/A ηοιαίκεηαζ απυ 5,5 έςξ 8. ηα δείβιαηα ιαξ, ημ πδθίημ BL/D ηοιαίκεηαζ απυ 10,5 έςξ 15,3 ηαζ ημ πδθίημ BL/A ηοιαίκεηαζ απυ 9,3 έςξ 14,3, ηζιέξ πανυιμζεξ (BL/D = 10,5-13,3 ηαζ BL/A = 9,7-11,7) ιε αοηέξ βζα ημ οπμείδμξ T. acus imperialis (Collette 1984, Bauchot 1987). Σέθμξ, ζημ είδμξ T. choram μζ αηηίκεξ ημο ναπζαίμο πηενοβίμο ηοιαίκμκηαζ απυ 19 έςξ 24 ηαζ ημο εδνζημφ απυ 19 έςξ 22. Ακηίεεηα, ζημ οπμείδμξ T. acus imperialis μζ αηηίκεξ ημο ναπζαίμο ηαζ ημο εδνζημφ πηενοβίμο είκαζ πενζζζυηενεξ (απυ 20 έςξ 26 ηαζ απυ 20 έςξ 24 ακηίζημζπα) (Tortonese 1970, Collette 1984, Collette & Parin 1986). ηα δείβιαηα ιαξ ιεηνήεδηακ απυ 23 έςξ 26 αηηίκεξ (ζοκήεςξ 24) ζημ ναπζαίμ πηενφβζμ ηαζ απυ 21 έςξ 23 (ζοκήεςξ 22) ζημ εδνζηυ πηενφβζμ, ηζιέξ πανυιμζεξ ιε αοηέξ πμο ακαθένμκηαζ βζα ημ οπμείδμξ T. acus imperialis. Tα δείβιαηα ιαξ δε είκαζ πζεακυ κα ακήημοκ ζημ είδμξ T. crocνdilus. Δίκαζ παναηηδνζζηζηυ υηζ ζημ ζοβηεηνζιέκμ είδμξ είκαζ ακεπηοβιέκμζ ηαζ μζ δφμ θμαμί ηδξ βμκάδαξ, ιε ηδ δελζά βμκάδα κα είκαζ πζμ επζιήηδξ απυ ηδκ ανζζηενή (Collette 1984). ηα δείβιαηα πμο ιεθεηήζαιε ήηακ ακεπηοβιέκμξ ιυκμ μ δελζυξ θμαυξ ηδξ βμκάδαξ ηαζ ζηα δφμ θφθα, παναηηδνζζηζηυ ημο οπμείδμοξ T. acus imperialis (Collette 1984, Bauchot 1987). Δπίζδξ, ζημ είδμξ T. crocνdilus μζ αηηίκεξ ημο ναπζαίμο πηενοβίμο ηοιαίκμκηαζ απυ 21 έςξ 23 ηαζ ημο εδνζημφ απυ 18 έςξ 22. ηα δείβιαηα ιαξ ιεηνήεδηακ απυ 23 έςξ 26 αηηίκεξ (ζοκήεςξ 24) ζημ ναπζαίμ πηενφβζμ ηαζ απυ 21 έςξ 23 (ζοκήεςξ 22) ζημ εδνζηυ, ηζιέξ πμο οπμδδθχκμοκ ημ οπμείδμξ T. acus imperialis. Σέθμξ, ηα δφμ είδδ δζαθένμοκ ηαζ ζηα πδθίηα BL/D, BL/A, BL/P ηαζ BL/V. ημ 279

280 είδμξ T. crocodilus, ημ πδθίημ BL/D ηοιαίκεηαζ απυ 5,4 έςξ 10,6 ηαζ ημ πδθίημ BL/A ηοιαίκεηαζ απυ 5,5 έςξ 8. Οζ ηζιέξ ηςκ δφμ πδθίηςκ ζηα δείβιαηά ιαξ (10,5 έςξ 15,3 βζα ημ BL/D ηαζ 9,3 έςξ 14,3 βζα ημ BL/A) είκαζ πμθφ ιεβαθφηενεξ απυ ηζξ πνμακαθενεείζεξ βζα ημ είδμξ T. crocodilus, ηαζ ακηζζημζπμφκ ζε αοηέξ πμο έπμοκ ακαθενεεί βζα ημ οπμείδμξ T. acus imperialis. Δπίζδξ, ζημ είδμξ T. crocodilus μζ ηζιέξ ηςκ πδθίηςκ BL/P (απυ 6,6 έςξ 8,3) ηαζ BL/V (απυ 7,3 έςξ 10,6) είκαζ πμθφ ιζηνυηενεξ απυ αοηέξ ζηα δείβιαηά ιαξ ηαζ μζ μπμίεξ ακηζζημζπμφκ ζε αοηέξ πμο έπμοκ ακαθενεεί βζα ημ οπμείδμξ T. acus imperialis (Collette 1984, Bauchot 1987). οιπεναζιαηζηά θμζπυκ, θαιαάκμκηαξ οπυρδ ηα απμηεθέζιαηα ηδξ βεκεηζηήξ ακάθοζδξ αθθά ηαζ αοηά ηδξ ακάθοζδξ ηςκ ιενζζηζηχκ ηαζ ιμνθμιεηνζηχκ βκςνζζιάηςκ, ηαηαθήβμοιε ζημ ζοιπέναζια ηδξ πανμοζίαξ ημο οπμείδμοξ T. acus imperialis ζημ Θενιασηυ Κυθπμ. Βηβιηνγξαθία Akyol O., Kara A. (2011). Occurrence of Tylosurus acus imperialis (Rafinesque, 1810) (Osteichthyes: Belonidae) in the northern Aegean Sea. Journal of Applied Ichthyology 27, Banford H.M., Bermingham E., Collette B.B. (2004). Molecular phylogenetics and biogeography of transisthmian and amphi-atlantic needlefishes (Belonidae: Strongylura and Tylosurus): perspectives on New World marine speciation. Molecular Phylogenetics and Evolution 31, Bauchot M.-L. (1987). Poissons osseux. In: ''Fiches FAO d'identification pour les besoins de la pêche. (rev. 1), Méditerranée et mer Noire. Zone de pêche 37. Vol. II.'', Fischer W., Bauchot M.L., Schneider M. (eds). Commission des Communautés Européennes and FAO Rome, p Collette B.B. (1984). Belonidae. In: ''FAO species identification sheets for fishery purposes. Western Indian Ocean; (Fishing Area 51)'', Fischer W., Bianchi G. (eds). Prepared and printed with the support of the Danish International Development Agency (DANIDA). Food and Agricultural Organization of the United Nations Rome, Vols 1-6, pag. var. Collette B.B., Parin N.V. (1986). Belonidae. In: ''Fishes of the north-eastern Atlantic and the Mediterranean'', Whitehead P.J.P., Bauchot M.-L., Hureau J.-C., Nielsen J., Tortonese E. (eds). UNESCO Paris, Vol. 2., p Hall T.A. (1999). BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symposium Series 41, Hillis D.M., Moritz C., Mable B.K. (1996). Molecular Systematics. Sunderland, MA: Sinauer & Associates Inc., pp Lovejoy N.R. (2000). Reinterpreting recapitulation: systematics of needlefishes and their allies (Teleostei: Beloniformes). Evolution 54(4), Palumbi S.R. (1996). Nucleic acids II: The polymerase chain reaction. In: "Molecular Systematics", Hillis D.M., Moritz C., Mable B.K. (eds). Sunderland, MA: Sinauer & Associates Inc., p Sinis A. (2005). First record of Tylosurus crocodilus (Péron & Lesueur 1821) (Pisces: Belonidae) in the Mediterranean (North Aegean Sea, Greece). Journal of Biological Research 4, Thompson J.D., Gibson T.J., Plewniak F., Jeanmougin F., Higgins D.G. (1997). The CLUSTAL X windows interface: Flexible strategies for multiple alignment aided by quality analysis tool. Nucleic Acids Research 25,

281 Tortonese E. (1970). Fauna d Italia. Osteichthyes. Vol X. Calderini. Bologna, Italy, pp. 636 Türker Çakır D., Zengin K. (2013). Occurrence of Tylosurus acus imperialis (Rafinesque, 1810) (Osteichthyes: Belonidae) in Edremit Bay (Northern Aegean Sea). Journal of Applied Ichthyology 29,

282 ESTIMATION OF AGE AND GROWTH OF EUROPEAN HAKE IN THE AEGEAN AND IONIAN SEA Pattoura P. 1 *, Lefkaditou E. 1, Mytilineou Ch. 1, Adamidou A 2., Dogrammatzi A. 1 1 Hellenic Centre for Marine Research, Institute of Marine Biological Resources and Inland Waters, 19013, Anavissos, Attica, Greece 2 Fisheries Research Institute, 64007, N. Peramos, Kavala, Greece ABSTRACT Age and growth of European hake (Merluccius merluccius) in the Aegean and Ionian Sea were studied within DCF Program in Length-frequency distribution, weight-length relationship and length-otolith radius relationship were examined. Age was estimated by means of annual rings. 7 age groups in the Aegean and 6 age groups in the Ionian Sea were identified for individuals with length ranging between mm and mm, respectively. Von Bertalanffy growth parameters (L, k, t 0 ) were calculated for both areas and found to be statistically different (p<0.001). Back-calculated lengths-at-age were resulted higher in Aegean than in Ionian Sea for all the age groups. Our results defend the fast growth hypothesis of hake in the Mediterranean. Key words: Merluccius merluccius, age, otolith, growth, Mediterranean *Corresponding author: Pattoura Photiana (photianap@hcmr.gr) ΜΔΛΔΣΖ ΣΖ ΖΛΗΚΗΑ ΚΑΗ ΑΤΞΖΖ ΣΟΤ ΔΤΡΧΠΑΗΚΟΤ ΜΠΑΚΑΛΗΑΡΟΤ ΣΟ ΑΗΓΑΗΟ ΚΑΗ ΗΟΝΗΟ ΠΔΛΑΓΟ Παηηνχξα Φ. 1 *, Λεπθαδίηνπ Δ. 1, Μπηηιελαίνπ Υ. 1, Αδακίδνπ Α. 2, Νηνγξακκαηδή Α 1. 1 Δθθδκζηυ Κέκηνμ Θαθάζζζςκ Δνεοκχκ, Ηκζηζημφημ Θαθάζζζςκ Βζμθμβζηχκ Πυνςκ ηαζ Δζςηενζηχκ Τδάηςκ, 19013, Ακάαοζζμξ, Αηηζηή, Δθθάδα 2 Ηκζηζημφημ Αθζεοηζηήξ Ένεοκαξ, 64007, Ν. Πέναιμξ, Κααάθα, Δθθάδα Πεξίιεςε Ζ ιεθέηδ ηδξ δθζηίαξ ηαζ αφλδζδξ ημο εονςπασημφ ιπαηαθζάνμο (Merluccius merluccius) ζημ Αζβαίμ ηαζ Ηυκζμ Πέθαβμξ, ααζίζηδηε ζε δείβιαηα απυ ημ Δεκζηυ Πνυβναιια οθθμβήξ Αθζεοηζηχκ Γεδμιέκςκ ημο Μεθεηήεδηακ δ ηαηά ιήημξ ζφκεεζδ, δ ζπέζδ αάνμοξ-ιήημοξ, δ ζπέζδ ιήημοξ ζχιαημξ-αηηίκαξ ςημθίεμο, δ δθζηία ιέζς ηδξ ακάβκςζδξ ηςκ εηδζίςκ δαηηοθίςκ ηαζ μζ πανάιεηνμζ αφλδζδξ. Γζα άημια ιε ιήημξ mm ηαζ mm πνμζδζμνίζηδηακ 7 δθζηζαηέξ ηθάζεζξ ζημ Αζβαίμ ηαζ 6 δθζηζαηέξ ηθάζεζξ ζημ Ηυκζμ, ακηίζημζπα. Γζα ηδ ιεθέηδ ηδξ αφλδζδξ οπμθμβίζηδηακ μζ πανάιεηνμζ (L, k, t 0 ) ημο εηεεηζημφ ιμκηέθμο von Bertalanffy ηαζ βζα ηζξ δφμ πενζμπέξ, μζ μπμίεξ ανέεδηακ κα δζαθένμοκ ζηαηζζηζηά ζδιακηζηά (p<0.001). Σα οπμθμβζζιέκα ιέζα ακαδνμιζηά ιήηδ ηάεε δθζηίαξ ήηακ ιεβαθφηενα ζημ Αζβαίμ απ υηζ ζημ Ηυκζμ βζα υθεξ ηζξ δθζηίεξ. Σα απμηεθέζιαηα ηδξ ενβαζίαξ εκζζπφμοκ ημ ιμκηέθμ βνήβμνδξ αφλδζδξ ημο ιπαηαθζάνμο ζηδ Μεζυβεζμ. Λέμεηο θιεηδηά: Merluccius merluccius, ειηθία, σηόιηζνο, αύμεζε, Μεζόγεηνο *οββναθέαξ επζημζκςκίαξ: Παηημφνα Φςηεζάκα (photianap@hcmr.gr) 1. Δηζαγσγή Ο εονςπασηυξ ιπαηαθζάνμξ Merluccius merluccius, είκαζ έκα εονέςξ δζαδεδμιέκμ είδμξ ζηδ Μεζυβεζμ ηαζ ημ κμηζμακαημθζηυ Αηθακηζηυ, πνςηανπζηήξ ζδιαζίαξ ηυζμ βζα ηα εαθάζζζα μζημζοζηήιαηα υζμ ηαζ βζα ηδκ αθζεία ζηζξ εκ θυβς πενζμπέξ. Ζ εκηαηζηή αθίεοζδ ημο ιπαηαθζάνμο απυ δζαθμνεηζηά αθζεοηζηά ενβαθεία ζηδ δοηζηή αθθά ηαζ ηδκ ακαημθζηή Μεζυβεζμ (Papaconstantinou & Stergiou 1995; Belcari et al. 2006) πνμηαθεί έκημκδ ακδζοπία βζα ηδκ ηαηάζηαζδ ηςκ απμεειάηςκ ημο είδμοξ, ηαεζζηχκηαξ αηυια ιεβαθφηενδ ηδκ ακάβηδ βζα ιεθέηδ ηςκ αζμθμβζηχκ παναιέηνςκ 282

283 Αφθονία (%) HydroMedit 2014, November 13-15, Volos, Greece υπςξ δ αφλδζδ ηαζ δ βεκκδηζηή ςνζιυηδηα (Morales-Nin et al. 2005). Πανά ηζξ πμθθέξ πνμζπάεεζεξ πμο έπμοκ βίκεζ εδχ ηαζ ανηεηά πνυκζα βζα κα εηηζιδεεί δ δθζηία ημο ιπαηαθζάνμο, δ ενιδκεία ηςκ πνμηφπςκ ιαηνμδμιήξ ηςκ ςημθίεςκ ημο είκαζ αιθζθεβυιεκδ ηαζ ααέααζδ υζμκ αθμνά ηδκ αλζμπζζηία ημο πνμζδζμνζζιμφ ηδξ δθζηίαξ (Piñeiro et al. 2007; ICES 2010). Ακηζηείιεκμ ηδξ πανμφζαξ ενβαζίαξ είκαζ δ ιεθέηδ ηδξ ζπέζδξ αάνμοξ-ιήημοξ, ηδξ δθζηίαξ ηαζ ηδξ αφλδζδξ ημο ιπαηαθζάνμο ζημ Αζβαίμ ηαζ Ηυκζμ Πέθαβμξ, ζφιθςκα ιε ηζξ μδδβίεξ πμο δυεδηακ βζα ηδ αεθηίςζδ ηδξ ακάβκςζδξ ηδξ δθζηίαξ ημο ιπαηαθζάνμο απυ δζεεκή επζζηδιμκζηή μιάδα, θαιαάκμκηαξ οπυρδ ηα απμηεθέζιαηα εηηίιδζδξ ηδξ δθζηίαξ ζε άημια πμο ζοιιεηείπακ ζε πεζνάιαηα ιανηανίζιαημξ (ICES 2010). 2. Τιηθά θαη κέζνδνη Γζα ηδκ ηαηά ιήημξ ζφκεεζδ ημο είδμοξ πνδζζιμπμζήεδηακ ηα ιήηδ πμο ηαηαβνάθδηακ επί ζηαθχκ επαββεθιαηζηήξ αθζείαξ ηαηά ηδκ πενίμδμ Ημφθζμξ-Γεηέιανζμξ 2013 ζημ Αζβαίμ ηαζ ημ Ηυκζμ Πέθαβμξ, ζηα πθαίζζα ημο Δεκζημφ Πνμβνάιιαημξ οθθμβήξ Αθζεοηζηχκ Γεδμιέκςκ Οζ οπυθμζπεξ ακαθφζεζξ ζηδνίπεδηακ ζηα δείβιαηα ιπαηαθζάνμο πμο ζοθθέπεδηακ βζα ημ ίδζμ πνυβναιια, απυ ηα αθζεφιαηα δζαθυνςκ αθζεοηζηχκ ενβαθείςκ (ιδπακυηναηα, απθάδζα, ιακςιέκα ηαζ ιακςιέκα-απθάδζα). Γζα ηάεε άημιμ ηαηαβνάθδηε ημ μθζηυ ιήημξ (TL) ζε mm, ημ μθζηυ αάνμξ (W) ζε g, ημ θφθμ, ημ ζηάδζμ βεκκδηζηήξ ςνζιυηδηαξ ηαζ αθαζνέεδηακ μζ ςηυθζεμζ. Γζα ηδκ εηηίιδζδ ηδξ δθζηίαξ, επζθέπεδηακ μζ δελζμί ςηυθζεμζ απυ 294 άημια (TL: mm) αθζεοιέκα ζημ Αζβαίμ ηαζ 145 άημια (TL: mm) αθζεοιέκα ζημ Ηυκζμ. O πνμζδζμνζζιυξ ηςκ «εηδζίςκ» δαηηοθίςκ, πναβιαημπμζήεδηε εεςνχκηαξ υηζ ζηδ ιαηνμδμιή ημο ςημθίεμο παναηδνμφκηαζ 2 δζαθακείξ δαηηφθζμζ ακά έημξ, ζφιθςκα ιε ηζξ μδδβίεξ ηδξ μιάδαξ ενβαζίαξ ημο ICES (2010), έκαξ απυ ημοξ μπμίμοξ ζπδιαηίγεηαζ ηαηά ηδκ πενίμδμ παιδθήξ εενιμηναζίαξ ηδξ εάθαζζαξ (εηήζζμξ), εκχ μ άθθμξ ηαηά ηδκ πενίμδμ παιδθήξ αθεμκίαξ ηδξ ηνμθήξ πμο παναηδνείηαζ ημ θεζκυπςνμ. Ζ δθζηία εηηζιήεδηε απυ δφμ δζαθμνεηζημφξ ενεοκδηέξ πμο ήηακ ελμζηεζςιέκμζ ιε ηδ ιεθέηδ ηδξ δθζηίαξ ημο ιπαηαθζάνμο, ιε ηεθζηή επζθμβή ηςκ δθζηζχκ βζα ηζξ μπμίεξ οπήνπε ζοιθςκία, πνμηεζιέκμο κα αεθηζςεεί δ ακηζηεζιεκζηυηδηα ηδξ εηηίιδζδξ. ε ηάεε ςηυθζεμ ιεηνήεδηακ ιε ηδ αμήεεζα ημο θμβζζιζημφ Image Pro-Plus, μζ απμζηάζεζξ (αηηίκεξ) ηδξ πενζιέηνμο ηαζ ημο ηάεε εηήζζμο δαηηοθίμο απυ ημκ πονήκα. Με αάζδ αοηέξ ηζξ ιεηνήζεζξ οπμθμβίζηδηακ μζ ιέζεξ ηζιέξ μθζημφ ιήημοξ πμο ακηζζημζπμφκ ζε ηάεε εηήζζμ δαηηφθζμ, αημθμοεχηαξ ηδ ιέεμδμ ημο ακάδνμιμο οπμθμβζζιμφ ιήημοξ (back-calculation) ηαζ δ ζπέζδ ιήημοξ ζχιαημξ αηηίκαξ ςημθίεμο. Ο οπμθμβζζιυξ ηςκ παναιέηνςκ ημο εηεεηζημφ ιμκηέθμο von Bertalanffy L=L (1-e -k(t-to) ) ααζίζηδηε ζηζξ δθζηίεξ (t) ηαζ α) ζηα παναηδνμφιεκα μθζηά ιήηδ ηαζ α) ζηζξ ηζιέξ ιέζμο ακαδνμιζημφ ιήημοξ βζα ηάεε εηήζζμ δαηηφθζμ ηςκ ςημθίεςκ. Γζα ηδκ απεζηυκζζδ ηδξ ηαηά ιήημξ ζφκεεζδξ ημο είδμοξ μζ ιεηνήζεζξ ηςκ μθζηχκ ιδηχκ ηαηακειήεδηακ ζε ηθάζεζξ ιήημοξ 20 mm. Ζ ζπέζδ αάνμοξ-ιήημοξ ααζίζηδηε ζημ εηεεηζηυ ιμκηέθμ W=aTL b πνδζζιμπμζχκηαξ ηα δεδμιέκα απυ 129 άημια βζα ημ Αζβαίμ ηαζ απυ 140 άημια βζα ημ Ηυκζμ. θεξ μζ ακαθφζεζξ έβζκακ λεπςνζζηά βζα ηάεε πενζμπή ιεθέηδξ. Οζ ζοκηεθεζηέξ ηςκ ζπέζεςκ αάνμοξ-ιήημοξ ηαζ μζ πανάιεηνμζ αφλδζδξ ζοβηνίεδηακ ακάιεζα ζηζξ δφμ πενζμπέξ ιεθέηδξ. Γζα ηδ ζφβηνζζδ ηςκ παναιέηνςκ L ηαζ k ιε αοηέξ πμο εηηζιήεδηακ απυ πνμδβμφιεκεξ ενβαζίεξ, πνδζζιμπμζήεδηε μ ζοκηεθεζηήξ μθμηθήνςζδξ ηδξ αφλδζδξ Φ = logk + 2log L (Pauly & Munro 1984). 3. Απνηειέζκαηα Ζ ηαηά ιήημξ ζφκεεζδ ημο ιπαηαθζάνμο ζημ Αζβαίμ ηαζ Ηυκζμ ηοιάκεδηε ιεηαλφ mm ηαζ mm, ακηίζημζπα. Σμ εφνμξ ιήημοξ πμο παναηδνήεδηε βζα ημ ιεβαθφηενμ ιένμξ ηςκ αηυιςκ ηαζ ζηζξ δφμ πενζμπέξ ηοιάκεδηε ιεηαλφ mm (πήια 1) % 15.00% 10.00% 5.00% 0.00% Κλάςεισ μήκουσ (mm) ρήκα 1. Καηά κήθνο ζχλζεζε ηνπ επξσπατθνχ κπαθαιηάξνπ Merluccius merluccius ζην Αηγαίν θαη Ηφλην Πέιαγνο (Δζληθφ Πξφγξακκα πιινγήο Αιηεπηηθψλ Γεδνκέλσλ 2013) Αιγαίο Ιόνιο 283

284 Ζ αφλδζδ ημο αάνμοξ ιε ημ μθζηυ ιήημξ ημο ιπαηαθζάνμο ζημ Αζβαίμ πενζβνάθεηαζ απυ ημ ιμκηέθμ W= TL , (R 2 =0.9975, N=129) εκχ βζα ημκ ιπαηαθζάνμ ημο Ημκίμο απυ ημ ιμκηέθμ W= TL , (R 2 =0.9968, N=140). Ζ ζφβηνζζδ ηςκ ζπέζεςκ ηςκ δφμ πενζμπχκ έδεζλε υηζ δεκ οπάνπεζ ζηαηζζηζηά ζδιακηζηή δζαθμνά ιεηαλφ ηςκ ημιχκ (p=0.07) ηαζ ηςκ ηθίζεςκ ημοξ (p=0.24) ηαζ βζ αοηυ ημ θυβμ οπμθμβίζηδηε ιζα ημζκή ζοζπέηζζδ W= TL , (R 2 =0.9971, N=265). ημ Αζβαίμ Πέθαβμξ εηηζιήεδηακ 7 δθζηζαηέξ μιάδεξ απυ 0+ έςξ 6+ (0.5 έςξ 6.9 έηδ) εκχ ζημ Ηυκζμ 6 δθζηζαηέξ μιάδεξ απυ 0+ έςξ 5+ (0.9 έςξ 5.9 έηδ). Ζ ζπέζδ ιήημοξ ζχιαημξ-αηηίκαξ ςημθίεμο (TL=aR b ) βζα ημ Αζβαίμ ήηακ TL=43.17R 1.11 (R 2 =99.05, Ν=290) εκχ βζα ημ Ηυκζμ TL=42.08R 1.11 (R 2 =98.87, Ν=144). Ζ ζφβηνζζδ ηςκ βναιιχκ παθζκδνυιδζδξ ηςκ δφμ πενζμπχκ έδεζλε υηζ μζ δφμ εοεείεξ δε δζαθένμοκ ζδιακηζηά μφηε ςξ πνμξ ηζξ ημιέξ (p=0.19) μφηε ςξ πνμξ ηζξ ηθίζεζξ (p=0.84) ηαζ βζ αοηυ οπμθμβίζηδηε ιζα ημζκή ζοζπέηζζδ TL=42.93R 1.10 (R 2 =99.00, Ν=435). Οζ ηζιέξ ηςκ ιέζςκ ακαδνμιζηχκ ιδηχκ πμο οπμθμβίζηδηακ βζα ηάεε εηήζζμ δαηηφθζμ ηςκ ςημθίεςκ απυ ηα δείβιαηα Αζβαίμο ηαζ Ημκίμο πεθάβμοξ πανμοζζάγμκηαζ ζημκ Πίκαηα 1. Οζ ηζιέξ αοηέξ ήηακ ιεβαθφηενεξ βζα ηα άημια ημο Αζβαίμο απ υηζ ημο Ημκίμο. Πίλαθαο 1. Μέζα αλαδξνκηθά κήθε (TL, mm) θάζε ειηθίαο γηα ηνλ επξσπατθφ κπαθαιηάξν (Merluccius merluccius) ζην Αηγαίν θαη Ηφλην Πέιαγνο Ακαδνμιζηά ιήηδ Ζθζηία Αζβαίμ Ηυκζμ Οζ πανάιεηνμζ αφλδζδξ ημο ιμκηέθμο von Bertalanffy οπμθμβίζηδηακ ιε αάζδ ηα παναηδνμφιεκα ιήηδ ηαζ ηζξ ιέζεξ ηζιέξ ηςκ ακαδνμιζηχκ ιδηχκ ακά δθζηία (Πίκαηαξ 2) ηαζ ανέεδηε κα δζαθένμοκ ιεηαλφ ηςκ δφμ πενζμπχκ (p<0.001) ηυζμ βζα ηα παναηδνμφιεκα υζμ ηαζ βζα ηα ακαδνμιζηά ιήηδ. Οζ ηζιέξ Φ ήηακ ζε υθεξ ηζξ πενζπηχζεζξ πανυιμζεξ. Πίλαθαο 2. Παξάκεηξνη αχμεζεο θαη ηηκέο Φ γηα ην κνληέιν von Bertalanffy γηα ην Αηγαίν θαη ην Ηφλην Πενζμπή L (mm) k t 0 N R 2 Φ Αζβαίμ - παναηδνμφιεκα ιήηδ Αζβαίμ - ακαδνμιζηά ιήηδ Ηυκζμ - παναηδνμφιεκα ιήηδ Ηυκζμ - ακαδνμιζηά ιήηδ πδήηεζε Σμ ιεβαθφηενμ πμζμζηυ ηςκ αθζεοεέκηςκ αηυιςκ ζημ Αζβαίμ ηαζ ημ Ηυκζμ είπε εφνμξ ιδηχκ mm. ημκ ηυθπμ ηδξ ιφνκδξ παναηδνήεδηε πανυιμζμ ιέβζζημ μθζηυ ιήημξ (320 mm) ιεηαλφ ηςκ ηθάζεςκ πμο πανμοζίαγακ ορδθυηενδ αθεμκία, εκχ ηα άημια ιε ιήημξ ηάης απυ 260 mm ήηακ ζπάκζα (Uçkun et al. 2006). Ζ αφλδζδ ηαηά αάνμξ ημο ιπαηαθζάνμο παναηηδνίγεηαζ απυ εεηζηή αθθμιεηνία (b>3), οπμδεζηκφμκηαξ υηζ ημ αάνμξ ηςκ αηυιςκ αολάκεηαζ ιε ιεβαθφηενμ νοειυ απ υηζ ημ ιήημξ ζημ Αζβαίμ ηαζ ημ Ηυκζμ πέθαβμξ. Σα απμηεθέζιαηα ηδξ πανμφζαξ ενβαζίαξ ζοιθςκμφκ ιε ηα απμηεθέζιαηα ηςκ Μμοηυπμοθμο ηαζ ηενβίμο (2002) μζ μπμίμζ ιεθέηδζακ 152 άημια ιπαηαθζάνμο απυ ημ Αζβαίμ ιε μθζηυ ιήημξ απυ mm ηαεχξ επίζδξ ηαζ ιε αοηά ηςκ Özaydin ηαζ Taskavak (2006) πμο οπμθυβζζακ ηδκ ηζιή ημο b=3.15 ελεηάγμκηαξ 501 άημια ζημκ ηυθπμ ηδξ ιφνκδξ ιε ιήηδ mm. Οζ Γεςνβίμο ηαζ Καπίνδξ (2009) ακαθένμοκ πςξ ζηδκ πενίπηςζδ ημο ιπαηαθζάνμο ημο Παβαζδηζημφ ηυθπμο, δ ζπέζδ πμο πενζβνάθεζ ηζξ δφμ παναιέηνμοξ είκαζ δ ζζμιεηνία, ηάηζ πμο ζζπφεζ ηαζ ζηδκ πενίπηςζδ δζαπςνζζιμφ ηςκ δφμ θφθςκ, ζφιθςκα ιε ημοξ ζοββναθείξ. Σα πενζζζυηενα απυ ηα άημια ηςκ δεζβιάηςκ απυ ημ Αζβαίμ ηαζ ημ Ηυκζμ ακήηακ ζηζξ δθζηζαηέξ ηθάζεζξ 0+ έςξ 2+. Σα άημια ηςκ ιεβαθφηενςκ δθζηζαηχκ ηθάζεςκ (4+ ηαζ άκς) ήηακ εθάπζζηα, βεβμκυξ πμο ζπεηίγεηαζ αθεκυξ ιε ηα μθζηά ιήηδ ηςκ αηυιςκ ζηα δείβιαηα πμο ζοθθέπεδηακ απυ ημ Αζβαίμ ηαζ ημ Ηυκζμ ηαζ αθεηένμο ιε ηα δζαθμνεηζηά ηνζηήνζα πμο 284

285 αημθμοεήεδηακ βζα ημκ πνμζδζμνζζιυ ηςκ «πεζιενζκχκ» δαηηοθίςκ. Ακαηνέπμκηαξ ζηδκ οπάνπμοζα αζαθζμβναθία βζα ηδκ δθζηία ηαζ ηδκ αφλδζδ ημο εονςπασημφ ιπαηαθζάνμο, παναηδνεί ηακείξ ηδκ αζοιθςκία πμο οπάνπεζ ζηδκ ενιδκεία ηςκ πνμηφπςκ ηςκ "εηδζίςκ" δαηηοθίςκ ηαζ ηαηά ζοκέπεζα ζηζξ εηηζιήζεζξ ημο ιήημοξ ακά δθζηία (Piñeiro & Sainza 2003). Δζδζηυηενα βζα ηδ Μεζυβεζμ, ζε ιπαηαθζάνμοξ απυ ηδ αυνεζα Σοννδκζηή εάθαζζα ακαθένμκηαζ 14 δθζηζαηέξ ηθάζεζξ ιε ιέβζζηδ δθζηία ηα 13 έηδ βζα έκα άημιμ ιε μθζηυ ιήημξ 910 mm (Ligas et al. 2011). Οζ πανάιεηνμζ αφλδζδξ πμο πνμζδζμνίζηδηακ ζηδκ εκ θυβς ενβαζία πθδζζάγμοκ ηδκ ηζιή L πμο οπμθμβίζηδηε βζα ημ δείβια ιπαηαθζάνμο απυ ημ Αζβαίμ εκχ δ ηζιή ημο k είκαζ ανηεηά ιζηνυηενδ, πθδζζέζηενδ ζ αοηή πμο εηηζιήεδηε βζα ημοξ ιπαηαθζάνμοξ ημο Ημκίμο (Πίκαηαξ 3). Σμ ίδζμ ζζπφεζ ηαζ βζα ημ δείβια ιπαηαθζάνμο πμο ιεθεηήεδηε ζημκ ηυθπμ ηδξ ιφνκδξ (Uçkun et al. 2006) ιε πμθφ ιζηνυ αοηή ηδ θμνά νοειυ αφλδζδξ (Πίκαηαξ 3). Ζ ιεβαθφηενδ ηζιή ημο k πμο εηηζιήεδηε ζηδκ πανμφζα ενβαζία βζα ημ Αζβαίμ ζπεηίγεηαζ ιε ημ υηζ ημ δείβια πμο ελεηάζηδηε πενζθάιαακε εθάπζζηα άημια ιε μθζηυ ιήημξ άκς ηςκ 400 mm εκχ ζηα δείβιαηα πμο ακαθφεδηακ ζηζξ πνμακαθενεείζεξ ενβαζίεξ ζοιιεηείπακ ανηεηά ιεβάθα άημια, ηα μπμία ζοκεζζθένμοκ ζηδ ιείςζδ ημο ιέζμο νοειμφ αφλδζδξ. Σζιή k ακάθμβδ ιε αοηή πμο εηηζιήεδηε βζα ημ Αζβαίμ, οπμθμβίζηδηε απυ ημοξ García-Rodríguez ηαζ Esteban (2002) βζα ημ ιπαηαθζάνμ ζηδ δοηζηή Μεζυβεζμ ιε ακάθοζδ ηςκ ηαηά ιήημξ ζοκεέζεςκ ηςκ εηθμνηχζεςκ ζε ζοκδοαζιυ ιε ακάβκςζδ ςημθίεςκ, εεςνχκηαξ υπςξ ηαζ ζηδκ πανμφζα ιεθέηδ, υηζ ζημοξ ςημθίεμοξ ημο ιπαηαθζάνμο ζπδιαηίγμκηαζ 2 δαηηφθζμζ ακά έημξ. Πανάβμκηεξ υπςξ μ ζπδιαηζζιυξ ρεοδμ-δαηηοθίςκ ηαζ δ παναηεηαιέκδ ακαπαναβςβζηή πενίμδμξ ζοκεζζθένμοκ ζηζξ δζαθςκίεξ πμο ειθακίγμκηαζ ηαηά ηδκ ακάβκςζδ ηςκ ςημθίεςκ (Casey & Pereiro 1995). Σα ιέζα ακαδνμιζηά ιήηδ ηάεε δθζηίαξ πμο οπμθμβίζηδηακ ζηδκ πανμφζα ενβαζία, είκαζ ανηεηά ιεβαθφηενα απυ ηα ακηίζημζπα πμο πνμζδζμνίζηδηακ απυ ημοξ Ligas et al. (2011). Οζ ίδζμζ ζοββναθείξ ακαθένμοκ πςξ δ εηηίιδζδ ηδξ δθζηίαξ ηαζ ηα ηνζηήνζα πμο πνδζζιμπμζμφκηαζ βζ αοηήκ, επζηνέπμοκ ηδκ ακάβκςζδ ηςκ δαηηοθίςκ ζε ςημθίεμοξ αηυιςκ ιέπνζ 500 mm, εκχ πένακ αοημφ ημο ιήημοξ δ δζαδζηαζία ακάβκςζδξ βίκεηαζ αδφκαηδ θυβς ηςκ πμθθχκ ρεοδμ-δαηηοθίςκ ηαζ ηδξ ιείςζδξ ημο πάπμοξ ηςκ εηδζίςκ δαηηοθίςκ. Πίλαθαο 3. Παξάκεηξνη αχμεζεο θαη ηηκέο Φ γηα ην κνληέιν von Bertalanffy, απφ δηαθνξεηηθέο εξγαζίεο οββναθείξ L (mm) k Φ' García-Rodríguez ηαζ Esteban, 2002 Piñeiro ηαζ Sainza, 2003 Uçkun et al., Ligas et al., Ο δείηηδξ Φ' παίνκεζ πανυιμζεξ ηζιέξ βζα ημοξ ιπαηαθζάνμοξ απυ Αζβαίμ ηαζ Ηυκζμ υηακ οπμθμβίγεηαζ απυ ημ ιμκηέθμ von Bertalanffy ιε αάζδ είηε ηζξ παναηδνμφιεκεξ ηζιέξ μθζημφ ιήημοξ είηε αοηέξ πμο εηηζιήεδηακ ιε ακάδνμιμ οπμθμβζζιυ (Πίκαηαξ 2). Οζ ηζιέξ ημο Φ' πμο έπμοκ οπμθμβζζηεί ζε πνμδβμφιεκεξ ενβαζίεξ ιε αάζδ ηδκ ακάβκςζδ ςημθίεςκ ή ηδκ ακάθοζδ πενζμδζηχκ ηαηά ιήημξ ζοκεέζεςκ ηςκ πθδεοζιχκ ημο ιπαηαθζάνμο είκαζ ζπεηζηά ιζηνυηενεξ, ιε ιμκαδζηή ελαίνεζδ ηδκ ορδθυηενδ ηζιή πμο εηηζιήεδηε απυ ημοξ García-Rodríguez ηαζ Esteban (2002). Αλίγεζ κα ζδιεζςεεί υηζ ορδθέξ ηζιέξ ηςκ παναιέηνςκ ηδξ ελζζςζδξ von Bertalanffy (L =899 mm, k=0.36 ηαζ Φ'=3.46) οπμθμβίζηδηακ ηαζ ζηδκ πενίπηςζδ εηηίιδζδξ ηδξ δθζηίαξ αηυιςκ ηςκ μπμίςκ μζ ςηυθζεμζ είπακ οπμζηεί πδιζηυ ιανηάνζζια ιε μλοηεηναηοηθίκδ, εέημκηαξ ζε αιθζζαήηδζδ ηα ηνζηήνζα πμο είπακ δζαηοπςεεί πνμδβμοιέκςξ βζα ηδκ ενιδκεία ηδξ ιαηνμδμιήξ ηςκ ςημθίεςκ ημο ιπαηαθζάνμο (de Pontual et al. 2006; Piñeiro et al. 2007). Ακάθμβα ζοιπενάζιαηα πνμέηορακ ιεηά απυ ζοιααηζηυ ιανηάνζζια ιπαηαθζάνμο ζημκ ηυθπμ ηςκ Λευκηςκ ηαζ εηηίιδζδ ημο νοειμφ αφλδζδξ ημο ηαηά ημ πνμκζηυ δζάζηδια ιεηαλφ ιανηανίζιαημξ ηαζ επακαζφθθδρδξ (Mellon-Duvall et al. 2010). Βηβιηνγξαθία Belcari P., Ligas A., Viva C. (2006). Age determination and growth of juveniles of the European hake, Merluccius merluccius (L., 1758), in the northern Tyrrhenian Sea (NW Mediterranean). Fisheries Research 78, Casey J., Pereiro J. (1995). European hake (M. merluccius) in the North-east Atlantic. In: Hake: Biology, Fisheries and Markets,J. Alheit and T. Pitcher (eds). London: Chapman & Hall; p García-Rodríguez M., Esteban A. (2002). How fast does hake grow? A study on the Mediterranean hake 285

286 (Merluccius merluccius L.) comparing whole otoliths readings and length frequency distributions data. Scientia Marina 66, Georgiou K.A., Kapiris K. (2009). Preliminary study on the age and growth of the hake s (Merluccius merluccius) population in Pagasitikos Gulf. Proceedings of the 9 th Symposium on Oceanography and Fisheries, vol. 2 (2009), pp ICES (2010). Report of the Workshop on Age estimation of European hake (WKAEH), 9-13 November 2009, Vigo, Spain. ICES CM 2009/ACOM: pp. Ligas A., Pierattini C., Viva C., Bertolini D., Belcari P. (2011). Age estimation and growth of European hake Merluccius merluccius (Linnaeus, 1758), in the northern Tyrrhenian sea. Atti Soc. tosc. Sci. nat., Mem., Serie B, 118 pagg. 9-14, figg. 3, tabb. 4; doi: /ASTSN.M Mellon-Duval C., de Pontual H., Métral L., Quemener L. (2010). Growth of European hake (Merluccius merluccius) in the Gulf of Lions based on conventional tagging. ICES Journal of Marine Science 67, Morales-Nin B., Bjelland R.M., Moksness E. (2005). Otolith microstructure of a hatchery reared European hake (Merluccius merluccius). Fisheries Research 74, Moutopoulos D. K., Stergiou K. I. (2002). Length weight and length length relationships of fish species from the Aegean Sea (Greece). Journal of Applied Ichthyology 18, Özaydin O., Taşkavak E. (2006). Length-weight relationships for 47 fish species from Izmir Bay (eastern Aegean Sea, Turkey). Acta Adriatica 47, Papaconstantinou C., Stergiou K. (1995). Biology and fisheries of hake Merluccius merluccius L., 1758, in the eastern Mediterranean. In: Hake: Biology, Fisheries and Markets,J. Alheit and T. Pitcher (eds). London: Chapman & Hall, p Pauly D., Munro J.L (1984). Once more the comparison of growth in fish and invertebrates. ICLARM Fishbyte 2.21 pp. Piñeiro C., and Sainza M. (2003). Age estimation, growth and maturity of the European hake (Merluccius merluccius Linnaeus, 1758) from Iberian Atlantic waters. ICES Journal of Marine Science 60, Piñeiro C., Rey J., de Pontual H., Goñi R. (2007). Tag and recapture of European hake (Merluccius merluccius L.) off the Northwest Iberian Peninsula: First results support fast growth hypothesis. Fisheries Research 88, Pontual H., Groisonb A.L., Piñeiro C., Bertignac M. (2006). Evidence of underestimation of European hake growth in the Bay of Biscay, and its relationship with bias in the agreed method of age estimation. ICES Journal of Marine Science 63, Uçkun D., Taşkavak E., Toǧulga M. (2006). A preliminary study on otolith-total length relationship of the common hake (Merluccius merluccius L., 1758) in Izmir Bay, Aegean Sea. Pakistan Journal of Biological Sciences 9,

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288 ORAL PRESENTATIONS IN ENGLISH ESTIMATES OF THE ECONOMIC IMPACTS OF SEA LEVEL RISE ON PAROS AND NAXOS ISLANDS (CYCLADES ARCHIPELAGO GREECE) Klaoudatos D. Kokkali A. Conides A. Institute of Marine Biological Resources Hellenic Center for Marine Research 46.7 km Athens-Sounion, Anavyssos Attikis, Greece Abstract The effects of climate change are numerous and diverse, often interlinked, causing severe impacts on the economic and physical environment of the affected areas. Freshwater shortage and sea level rise are highlighted as the priority risks of climate change in Mediterranean coastal region. This study seeks to illustrate at a local level the impact that sea level rise may generate on the coastal communities of Cyclades Islands in Greece in terms of value of lost land due to sea level rise. After developing three different scenarios of sea level rise by and 1 m in tandem with the use of Geographic Information System (GIS) as a mapping tool the percentage of inundated area at different islands was illustrated and the respective economic cost was calculated. Results revealed that in the most possible case scenario of sea level rise by 0.6 m the total land loss value for the whole Cyclades complex reaches 4 billion (close to 2.2% GDP) with Naxos island being the most vulnerable. Further research needs to take into consideration additional factors related to the impact assessment of sea level rise in Cyclades in order to produce more robust results. The study was performed for all Cyclades Islands (24 inhabited islands in total) from which Paros and Naxos islands were selected as the most important in terms of economy. Keywords: Paros Island Naxos Island Cyclades sea level rise climate change Corresponding Author: Dimitris Klaoudatos (dklaoudatos@yahoo.com) 1. Introduction Over the recent decades CO 2 emissions have considerably increased due to the intense use of fossil fuels in industry being a prime factor responsible for global warming and global climate changes. The latest Reports of the World Meteorological Organization (WMO) and the United Nations Programme for the Environment (UNEP) indicate that between 1980 and 2005 the world ambient temperature had increased between 1 and 1.5 C (Melloul and Collin 2009). One of the most critical issues arisen from the ongoing global warming is the expected sea level rise and thus focus has been put on the future sea level trends which inextricably affect coastal areas and islands. According to the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4; IPCC 2007a) for water at 15 C, an increase by 1 C in a water column of 1000 m would heighten the water column by 16 cm while the estimated global mean sea level rise will be between 18 and 59 cm by the 288

289 2090s. Nevertheless sea level rise and its expected impacts are not uniform around the globe since there are many factors that influence the rates of sea level changes such as eustatic glacio-hydroisostatic and tectonic factors (Lambeck et al. 2004). Recent scenarios for 2100 (IPCC 2001ab) and sea-level measurements (Church and White 2006) suggest an acceleration in sea-level rise. This enhances the importance of a new simulation of the impact of rising sea level on the shoreline position. Low lying coastal areas and their populations are primarily affected by sea level rise consequences as more than 40% of the world s population (more than 2.8 billion people) live within 100 km of the coast (IOC/UNESCO IMO FAO UNDP 2011). Taking into consideration the conversion of natural coastal landscapes to anthropogenic uses due to continuous population growth in coastal areas the impacts of sea level rise aggravate the cost both in natural and economic resources of these areas. The assessment of the vulnerability of coastal resources to the impacts of sea level rise is delineated into both natural (natural system vulnerability) and socio-economic environment (socioeconomic system vulnerability; Travers et al. 2010). The prerequisite of the socioeconomic vulnerability analysis relies on the efficient knowledge about natural response system to sea level rise (Travers et al. 2010). Adaptation to these phenomena is mainly translated into cost assessment rather than cost-benefit assessment (CBA) as decision makers are not for supporting inaction but making optimal actions that would ensure the safety of the area at risk (European Commission 2009). The rates of sea level change in Mediterranean are a controversial issue. Carillo et al. (2012) stated that the characteristics of Mediterranean Sea as a semi-closed basin connected to the Atlantic Ocean only through the Strait of Gibraltar allow for differing from the global sea level trends. Applying statistical techniques on satellite data Tsimplis et al. (2009) estimated an increase of sea level trend about 0.63 mm year-1 for the period using tide gauge data whereas in another study by Tsimplis and Baker (2000) identified an increase at a rate of mm year-1 before 1960 and a decrease at a rate of -1.3 mm/year between 1960 and As Travers et al. (2010) reported in Adriatic and Aegean Seas the raise of average temperature will be greater than in Levantine basin raising the elevation rate in the eastern part of Mediterranean basin at rate of +5 and +15 mm/year compared to less than +5 mm/year in the western part. The Aegean Sea is considered to be the most exposed area of the Mediterranean Sea to sea level rise due to high water temperatures (Paulopoulos et al. 2002). The impacts of sea level rise will be particularly strong on the majority of the Mediterranean coastal areas as they housed 36% (EUROSTAT 2011) of the EU coastal regions population in 2009 with a trend to increase by 1.4% in 2025 (Goudert and Larid 2011) causing floods land loss salinisation of groundwater and destruction of built property and infrastructure (Devoy 2007). Given the large and growing concentration of population and economic activity in the coastal zone as well as the importance of coastal ecosystems the potential impacts of sea-level change have evoked widespread concern for more than two decades (Barth and Titus 1984; Milliman et al. 1989; Warrick et al. 1993). The present study focuses on the Paros and Naxos Islands (belonging to the Cyclades Archipelago Greece). The main aim of this study was to assess and visualize the percentage of the inundation area after developing three different scenarios of sea level rise in the study area using GIS as a tool. Valuation is based on the national figures for the values of urban and non-urban land for taxation purposes. The objective of this paper is to identify the hotspots (areas of high risk) and estimate the economic loss of land for each sea level rise scenario.. 2. Materials and Methods Study area Cyclades (Fig. 1) is a complex of islands located in the central Aegean Sea (Greece; (Fig 1). The natural environment of Cyclades is very rich as it hosts a great variety of ecosystems which although they have limited size they host significant ecological features and protected areas that are included in the NATURA 2000 Network. The main economic activities are include agriculture, mining, fishing, small-scale-industry and tourism. Tourism has long played an important role in the 289

290 economic development of Cyclades characterizing them as one of the most significant tourism destinations in Greece. Figure 1. Map of the study area (with re the islands of Paros and Naxos) Naxos Island is the largest island in Cyclades with an area of 429 km² and a population (census of 2001) and a density of 42 inhabitants/km². Paros Island is also one of the largest islands of the Cyclades complex with an area of km² a population of 6058 (census 2001) and a density of 70 inhabitants/km². Both islands have significant mountainous terrain of m but also extensive coastal plains with beautiful beaches with clear waters suitable for swimming and other water-related activities. This combination makes these islands (also others in the region of Cyclades) as a very attractive tourism destination. Data analysis The analysis involves a two-step procedure. Initially we employed GIS software to superimpose critical elements directly impacted by sea level rise including surface elevations in relation to mean sea level and urban areas polygons adjacent to sea. Data were provided by the Hellenic Military Geographical Service and after applying interpolation techniques (Topo to Raster) elevation datasets were converted from polyline to raster format with a user-defined pixel size to 5 m. Three different scenarios of sea level rise were developed illustrating the inundated areas after a sea level rise of 0.3 m (scenario 1), 0.6 m (scenario 2) and 1 m (Scenario 3) respectively. Basic statistics were computed for model results to determine total land area inundated at each different case. Geological formations were not taken into consideration as they will be considered at a future study. At the second phase of the analysis we estimated the economic impact resulting from sea level rise at each different scenario on islands. We calculated the economic loss according to the economic value of land (urban and non-urban) as they were been provided by Ministry of Finance and Economics Tables of land value for taxation purposes. 3. Results The basic results on land loss due to sea level rise are summarised in Table

291 Table 1. Land loss per island and per scenario of sea level rise ISLAND Total lost area (m 2 ) Percentage of island area (%) 0.3 m 0.6 m 1 m 0.3 m 0.6 m 1 m Naxos Paros Antiparos) (with The results on economics losses due to land losses are summarised in Table 2. The most affected urban areas are located in the island of Naxos where land inundation ranges between m² and m² with a respective cost between and Paros is the second most inundated island among the Cyclades region. Table 2. Economic loss for each island due to inundation of urban area ISLAND Lost urban area (m 2 ) Value ( ) 0.3 m 0.6 m 1 m 0.3 m 0.6 m 1 m Naxos Paros(with Antiparos) The results on economic losses due to land losses of non-urban areas are summarised in Table 3. Table 3. Economic loss for island due to inundation of non-urban area ISLAND Lost non-urban-area (m 2 ) Value ( ) 0.3 m 0.6 m 1 m 0.3 m 0.6 m 1 m Naxos Paros(with Antiparos) Table 3 indicates that the islands of Naxos and Paros have the highest economic loss from the inundation of non-urban areas due to sea level rise 291

292 4. Discussion Sea-level change is one of the observed consequences of global warming and future sea-level rise is inevitable in a warming world with the rates and geographical patterns of this rise remaining uncertain (IPCC 2007a). Within coastal zones these climate-related changes can be expected to have a range of impacts. Rising sea levels will increase the flood-risk and erosion along the coast but may also impact freshwater availability or result in an accelerated loss of coastal eco-systems. A key element in assessing these issues is the development of sea-level rise scenarios (or plausible futures). Climate experts emphasise the importance of adapting to these potential effects of climate change by developing and implementing coastal protection and adaptation strategies. Coastal environment managers are increasingly concerned by the current rise in sea level and its possible acceleration during the 21st century in relation to climate warming (IPCC 2001ab). This phenomenon coincides with an unprecedented socio-economic development of the coastal fringe. In coming decades ongoing global warming will augment the probability of climate change. This may trigger alteration in sea level rise magnitude and rate as well as increase the impact of enhancing factors as shown in ongoing global sea level rise as well as instances in sudden sea level rise situations over recent years. Human use of the coast increased dramatically in the last century and it seems that this trend will continue in the future (Nicholls et al. 2008ab). Coastal population growth in many low-lying areas has led to the conversion of natural coastal landscapes to land for agricultural aquaculture industrial and residential uses (Valiela 2006). The attractiveness of the coast has resulted in rapid expansion of economic activity but has also degraded coastal ecosystems. Floods pose serious threats to coastal areas around the world; they cause great financial losses in property and infrastructure and affect many millions of people (Dasgupta et al. 2009; Nicholls 2004; Nicholls et al. 2008b). Paros (with Antiparos) are located in the center of Cyclades Island complex with and 1215 inhabitants in Both islands are among the most affected regions by sea level rise as the total economic loss ranges from (best case scenario) to (worst case scenario; Table 4). Paros and Antiparos are highly visited islands with Antiparos to be a low-lying small island attracting high-income tourists and expensive tourism investments during the last years in contrast with Paros which is a traditional tourism destination mainly attracting mass tourism. Antiparos will lose 2.1% of the total island area after applying the second sea level rise scenario of 0.6 m while Paros is less affected with 0.8% land loss (Fig.2). Fig.2. Land losses (red) per sea level rise scenario (0.3 m 0.6 m 1 m) of Paros Island Naxos is a large island with (2011) inhabitants with imposing mountainous volumes and strong winds. The topography of the island is a representative example of the Aegean topography characterised by hills and mountains covered by bushes and very limited flat fields. It is considered as the most fertile island of Cyclades. Naxos is the most vulnerable island relative to the others; since it risks losing a higher percentage of land (1.06%) for sea level rise of 0.60 m (Fig.3). Moreover it faces the most severe economic cost as for the most possible scenario of sea level rise 0.6 m the economic 292

293 cost accounts for Based on the above measurements, Klidos is the most affected urban area as 15.54% of the land is inundated. The western part of Naxos is susceptible to future sea level rise and especially the southern part of Naxos capital which also includes the airport. Fig.2. Land losses (red) per sea level rise scenario (0.3 m 0.6 m 1 m) of Naxos Island. 5. Conclusion The main effect of sea level rise is the loss of valuable (in many cases) land. At the same time though this land may also produce added value when it is exploited for other reasons except habitation. For example, a part of the coastline which is important for tourism exhibits both a urban value and a touristic value. The present paper, due to the lack of credible data on the uses of the coastline provides estimates on the building value of the land losses in the target area. However, we this estimates as important because they provide a baseline estimate of the losses which, if the added value for the exploitation of these lands is added, is expected to be higher. References Barth M.C., Titus J.G., (1984). Greenhouse effect and sea level rise: A challenge for this generation, Van Nostrand Reinhold, New York Carillo A., Sannino G., Artale V., Rutti P.M., Calmanti S., Dell Aquila A., (2012). Steric sea level rise over the Mediterranean Sea: present climate and scenario simulations. Climate Dynamics 39 (9-10), , Coudert E., Larid M., (2006). IMAGINE : un ensemble de méthodes et d outils pour contribuer à la gestion intégrée des zones côtières en Méditerranée, Vertigo - la revue électronique en sciences de l environnement, Dossier : Les littoraux et la gestion intégrée des zones côtières, 7 (3). ( 17 September 2012). Dasgupta S., Laplante B., Meisner C., Wheeler D., Yan J., (2009). The impact of sea level rise on developing countries: a comparative analysis. Climatic Change 93, Devoy R.J.N., (2008). Coastal Vulnerability and the Implications of Sea-Level Rise for Ireland. Journal of Coastal Research, 24 (2), EUROSTAT, (2011). Coastal regions. In: European Commission (ed) Eurostat regional year book Luxembourg: Publications Office of the European Union, Belgium. IOC/UNESCO, IMO, FAO, UNDP, (2011) A Blueprint for Ocean and Coastal Sustainability. IOC/UNESCO, Paris. IPCC, (2001a). Climate change 2001: impacts, adaptations and vulnerability. In: McCarthy JJ, Canziani OF, Leary NA, Dokken DJ, White KS (eds) Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge. IPCC, (2007a). Climate Change 2007: impacts, adaptation and vulnerability. Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge. 293

294 IPCC, (2001b). Climate change 2001: impacts, adaptation and vulnerability. Contribution of the working group to the 3rd assessment report of the intergovernmental Panel of Climate Change. World Meteorological Organization, Genève. 124 pp. Lambeck K., Anzidei M., Antonioli F., Benini A., Esposito A., (2004). Sea level in Roman time in the Central Mediterranean and implications for recent change. Earth and Planetary Science Letters 224, Melloul A, Collin M (2009). Key natural and anthropogenic parameters enhancing the effect of sea level rise: The case of Israel s Mediterranean coast. Ocean & Coastal Management 52: Milliman J.D., Broadus J.M., Gable F., (1989). Environmental and economic implications of rising sea level and subsiding deltas: The Nile and Bengal examples. Ambio 18: Nicholls R.J. (2004). Coastal flooding and wetland loss in the 21st century: changes under the SRES climate and socio-economic scenarios. Global Environmental Changes 14: Nicholls RJ, Hanson S, Herweijer C. Patmore N., Hallegatte S., Corfee-Morlot J., Chateau J., Muir- Wood R. (2008a). Ranking port cities with high exposure and vulnerability to climate extremes: exposure estimates. OECD environment working papers No. 1, ENV/WKP(2007). OECD, Paris, France. Nicholls R.J., Tol R.S.J., Vafeidis A.T. (2008b) Global estimates of the impact of a collapse of the West Antarctic ice sheet: an application of FUND. Climatic Changes 91, Paulopoulos K, Chalkias C, Karimbalis E, (2002). Potential impact of sea level rise on Mykonos, Delos, Rinia islands, In: 6th Pan-Hellenic Geographical Conference (Volume III), Thessaloniki, 3-6 October 2002, p Travers A., Elrick C., Kay R., (2010). Background Paper: Climate Change in Coastal Zones of the Mediterranean. Priority Actions Programme, Mediterranean Regional Activity Centre (PAP/RAC), Coastal Zone Management Pty Ltd, Claremont, Australia. Tsimplis M.N., Baker T.F., (2000) Sea level drop in the Mediterranean Sea: An indicator of deepwater salinity and temperature changes? Geophysical Research Letters 12, Tsimplis M.N., Marcos M., Colin J., Somot S., Pascual A., Shaw A.G.P., (2009). Sea level variability in the Mediterranean Sea during the 1990s on the basis of two 2D and one 3d model. Journal of Marine Systems 78 (1), Valiela I., (2006) Global coastal change. Wiley-Blackwell, London. Warrick RA, Barrow EM, Wigley TML (1993). Climate and sea level change: Observations, projections, implications. Cambridge University Press, Cambridge. 294

295 INVESTIGATION OF THE FACTORS AFFECTING FARMED FISH CONSUMPTION Kaimakoudi E 1*., Polymeros K 1., Papamichalopoulos A 1., Batzios Ch. 2 1 Department of Agriculture Ichthyology and Aquatic Environment, School of Agriculture Sciences, University of Thessaly, Fytoko str., , Volos, Greece 2 Lab. of Animal Production Economics, School of Veterinary Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, University campus, Thessaloniki, Greece ABSTRACT This study investigates the major factors that affect consumption in farmed fish. Using data from an in-person field survey, the categorical regression analysis was employed in order to detect the most significant factors which affect the consumption of farmed fish. The analysis identified that consumer preference and price are the most significant factors that determines consumption frequency in farmed fish. Socioeconomic factors are also playing a significant role regarding the consumption of farmed fish. Therefore, this study facilitates the development of consumer profile that could provide the basis of consumer-focused strategies aiming to improve consumer performance in the sector. Keywords: Consumer s behavior, Categorical Regression with optimal scaling, farmed fish. *Corresponding author: Kaimakoudi Eleni (ekaimakoudi@hotmail.com) 1. Introduction Fish have always been considered as an important part of human diet and they have long been recognized as a health-promoting food for human nutrition. Globally, fish provides about 4.3 billion people with almost 15% of their average per capita intake of animal protein, with the global annual per capita consumption of fish to stand at around 18.6kg, having doubled since the 1960s (FAO 2012). Particularly, aquaculture is considered as the fastest growing primary production sector, representing an annual growth rate of nearly 7% over the past decades. Furthermore, it is positioned to overtake capture fisheries as a source of food fish (FAO 2009). Greece s share in E.U.-28 in terms of value in aquaculture is 12.59%, dominating the third position (CFP 2014). However, the Greek fisheries sector operates in the context of an increasingly marketbased economy, characterized by rapid changes in market and ultimate consumer demands. Particularly, consumer expectations are good quality products derived from healthy animals raised in a healthy environment, to be natural, fresh tasting and nutritious (Kennedy et al. 2004). Particularly, a critical driver of consumer perceptions towards food quality and acceptance is better taste and nutrition (Cardello et al. 2007). Consumer perception is a key concept in order to better understand various aspects of consumer behaviour (Maciel et al. 2013). Additionally, the prediction of consumer behaviour is strongly affected by consumer attitude (Phillips et al., 2013). Previous studies have shown that although consumer attitudes towards production procedure have a minor impact of buying behaviour, they can be regarded as a potential that can be taken into consideration by creative marketing and product development (Grunert 2006). Furthermore, the system of production, traceability and quality control are of increased consumers interest (Peniak et al. 2007). Particularly, consumers interest in health, longevity and food safety is the key driver in fish consumption (Maciel et al. 2013). In the seafood market, consumers use experiences combined with a reliance on retailers reputation and knowledge in order to simulate information about credence 295

296 characteristics (Anderson 1995). According to previous studies, consumers claim to pay more attention to fish resources state, the visual aspects of the product, fish origin, prices, product form, and to the freshness when they purchase fish (Brecard et al. 2009). The present study aims to establish which factors are most important in the consumption of farmed fish. Therefore, the objective of the study is to detect the consumers perceived attitudes towards farmed fish and to analyse possible relationships between consumer characteristics and marketing aspects of these products. This consumer segmentation could potentially identify both policy and marketing improvements aiming to deliver an improved consumer value (Macharia et al. 2013). 2. Materials and Methods The study was carried out in the capital of Greece, in Athens. The questionnaire used was simple and consisted of twelve questions divided into two sections. The first section consisted of seven questions covering consumers preferences and attitudes towards farmed fish, namely, consumption preference: Q 1, respondents choice criteria: Q 2, such as price, quality, flavour, and availability, points of purchase: Q 3 (fish shops, fish mongers, super market), packaging importance: Q 4, as well as product form: Q 5 (fresh, frozen, raw, scaled), processed kinds preferences: Q 6 (fillets, smoked, canned, salted), consumption frequency: Q 7 (none, once per month, twice per month, once per week, twice per week,). Questions in the survey tool employed a five-point Likert scale, ranging from (1) none to (5) very much. The second section collected general information regarding the principal socioeconomic characteristics of consumers, namely, monthly disposable income: Q 8, educational level: Q 9, householder s age: Q 10, gender: Q 11 and profession: Q 12. The data on the householder s age were divided into five groups: a) 18 25, b) 26 35, c) 36 50, d) and e) >65 years old. The monthly disposable income data were divided into five groups: a) <700, b) c) , d) and e) >2.500 EURO. Furthermore, with respect to householder s profession, data was split into six groups: a) private employees, b) public employees, c) freelance, d) agriculturists, e) students and f) unemployed. Finally, the householder s educational level was categorized as elementary, secondary or higher education. The questionnaire was pre-tested on a sample of fourteen respondents selected by convenience to obtain face validity (Batzios et al. 2003). The field research was initiated after the necessary modifications were made to the questionnaire. Field data was collected during March - April of 2012, employing personal interviews in the prefecture of Attiki. Due to the lack of a sampling frame based on more recent information, the snowballing procedure was chosen as the method of data collection (Patton, 1990). In snowball sampling, population elements are deliberately selected for three reasons: (1) they can meet the needs of the research, (2) they are representative of the population of interest, and (3) they can offer researchers the information they need. In all, 154 valid questionnaires were collected with this method. The reliability of the information source was assessed by emphasising the identification of appropriate individuals from whom to elicit the requisite information and the willingness of these individuals to participate in the study. The respondents were considered appropriate if they were responsible for making the household s purchasing decisions. Thus, the respondents answers applied to their field of responsibility and provided reliable and accurate information. In order to identify potential relationships between the variables of the questionnaire, the method of categorical regression was chosen, known as regression with optimal scaling. The latter is a method designed to maximise the relationship between the predictor and an outcome variable by adjusting their scales (Cleophas 2013). It actually scales simultaneously nominal, ordinal and numerical variables. Therefore, the prediction of the dependent variable is provided for any combination of the 296

297 independent variables (Shrestha 2009). The variables categories are quantified aiming to maximise the R 2 regression coefficient between the dependent variable and the group of independent variables. One major advantage of categorical regression is that the sample size need not necessarily be large (Shrestha 2009). Additionally, it is particularly beneficial with lack of homogeneity in the scales of the variables (Cleophas 2013). Furthermore, in order to test model s colinearity, the Pratt s measures of relative importance and tolerance were used. Low levels of tolerance indicate low variable s contribution to the estimation of the model and can cause computational problems (Batzios et al. 2005). 3. Results The statistical indices, calculated for the overall evaluation and validity of the applied categorical regression model, resulted in relatively good values of multiple R and statistically significant F value of the ANOVA test (level of significance: α=0.001). More specifically, the coefficient of multiple determination was This means that approximately 74% of the dependent variable s variance is explained by the independent variables in the model. Table 1 presents the most important results of the methodology applied, regarding the consumption frequency of farmed fish. The estimated categorical regression model showed that the beta coefficient of each of the independent variables was in accordance with the presence of the remaining independent variables. Σhe deletion of an independent variable from the regression model, together with the presence of the remaining independent variables, reduces the predictability of the model. Consumption preference, processed kinds preferences: smoked, purchase point: Super markets and price were the independent variables with the highest significant beta coefficients in the model and the largest importance to the predictability of the model (23.4%, 17.3%, 10.9% and 10.7%, respectively). Education and product form: scaled exhibited lower importance to the predictability of the above model (10% and 8.4%, respectively). Cumulatively, these predictor variables exhibited the 80.7% of the total importance. The tolerance values of the regression model were very high indicating lack of multicollinearity (Table 1). Table 1. Categorical regression model for farmed fish (Standardized coefficients, relative importance and tolerance values) Independent variables Standardized coefficients F value Relative importance Tolerance Beta Standard error Sex Age Education Profession

298 Income Consumption Preference Price Flavour Purchase point: Super markets Purchase Fishmongers point: Packaging importance Product form: Fresh Product form: Scaled Processed kinds preferences: Canned Processed kinds preferences: Smoked Dependent variable: Consumption frequency of farmed fish 4. Discussion In this study, a categorical regression analysis was implemented in an effort to identify the effect of basic classification variables of consumers socio-economic status and marketing aspects regarding the consumption frequency of farmed fish. Results reveal that the main factors that were detected to be the most important determinants of consumption frequency in farmed fish were consumer preference, price, purchase point: supermarkets and processed kinds preferences: smoked. Particularly, according to Table 1, the positive and significant effect of consumer preference and price indicates that they are a prerequisite for improving the level of consumption frequency in farmed fish and thus consumer performance in the sector. In this respect, higher levels of consumer performance could be supported by the implementation of specific marketing strategies which focalized in meeting consumer demand in conjunction with the implementation of competitive prices. This supports findings from previous and recent studies that although noted a prejudice against conventional farmed fish among Greek consumers, urban consumers seems to have overcome this habit (Batzios et al. 2003; Peniak et al. 2013). Furthermore, the same result holds for the purchase point: supermarkets, which reflects the preference purchase point for farmed fish. This indicates that supermarkets are important and significant purchase points for farmed fish, contributing in higher levels of consumption and thus in improving consumer performance. Previous studies have also provided evidence that there is a general trend of purchase preference of farmed fish from supermarkets (Kaimakoudi et al. 2013). Additionally, product form: scaled and education exhibited lower importance to the predictability of the categorical regression model. Particularly, from the beta coefficients of these independent 298

299 variables, it is concluded that the impact of those variables to consumption frequency is positive. This indicates that the product form: scaled is important and significant product form of farmed fish, contributing in higher levels of consumption and thus in improving consumer performance. Moreover, younger consumers and with a relatively higher educational level, exhibit higher farmed fish consumption s levels. These support findings from previous and recent studies (Batzios et al. 2005; Polymeros et al. 2014) where younger consumers and with a relatively higher educational level exhibit higher sensitivity on marketing aspects of farmed fish. Potentially, they are usually better informed about marketing issues. Thus, in order to improve product s communication and consequently, increase the demand of farmed fish, the adoption of a marketing strategy aiming to boost awareness and to promote the consumption of aquaculture products, could reinforce the image of the sector as a whole. This is in accordance with previous studies where it is clearly stated that the lack of awareness regarding aquaculture s risks and benefits has caused an image problem within the European public (Schlag & Ystgaard, 2013). Additionally, as it has been demonstrated by previous studies, consumers with the highest use of all information sources about fish, demonstrated the highest intention and consequently consumption of fish (Peniak et al. 2007). Consequently, information programmes regarding aquaculture products safety and quality attributes should potentially be introduced, aiming at enhanced publicity for the Greek aquaculture sector in general and thus could contribute in guiltlessness of the whole sector. Thus, as it has been proposed by recent studies, a focus towards consumers education in relation to health benefits of fish consumption could provide a more efficient communication strategy (Maciel et al. 2013). The study served to identify the specific marketing aspects and socio-economic characteristics of farmed fish market. Therefore, the identification of this target market facilitates the adoption of a suitable marketing mix for the firms involved in the aquaculture industry. The adoption of this marketing mix serves to meet the requirements of the market more effectively. These results show that a market segmentation strategy is probably needed so that aquaculture production could take advantage of the significant potential for improving the demand in the near future. For this reason, it is essential to consider potential marketing strategies designed to enhance awareness and facilitate communication about the product. Therefore, a marketing strategy aiming to increase public awareness could improve the customer value of the product, improving the image of aquaculture products in the Greek market. In conclusion, certain limitations should be acknowledged. Due to the snowballing procedure used in this study, the collection of data with the questionnaire depended on the single-informant approach. As a result, the findings should be interpreted with caution, even though single informants provide information as reliable as that furnished by multiple informants. In addition, this study was limited at local level. Potentially, gathered information by different sample areas could provide important and specific information for designing targeted promotional campaigns. Therefore, generalisations of these findings to markedly different contexts should be made cautiously in view of the competitive and market differences that most likely exist between different areas and countries. However, it may provide an opportunity for further research regarding the proposed model of farmed fish consumption. Possible research avenues may pertain to a more detailed investigation of the factors affecting farmed fish consumption under the implementation of other statistical analyses such as cluster analysis, providing the critical comparison between them by confirming or rejecting the results derived. References Anderson J. (1995). Purchase Behaviour, Food Safety, and Quality Control in Seafood and Aquaculture Marketing: Discussion American Journal of Agricultural Economics 77 (5),

300 Batzios Ch., Angelidis P., Moutopoulos D., Anastasiadou Ch., Chrisopolitou V. (2003). Consumer Attitude towards Shellfish in the Greek Market: A Pilot Study. Mediterranean Marine Science 4, Batzios Ch., Moutopoulos D., Arabatzis G., Siardos G. (2005). Understanding Consumer s Attitude on Fish Quality and Marketing Aspects in the Greek Fish Market. Agricultural Economic Review 6 (1), Brécard, D., Hlaimi, B., Lucas, S., Perraudeau, Y. and Salladarré, F. (2009). Determinants of demand for green products: An application to eco-label demand for fish in Europe. Ecological Economics 69, Cardello A., Schutz H., Lesher L. (2007). Consumer perceptions of foods processed by innovative and emerging technologies: A conjoint analytic study. Innovative Food Science and Emerging Technologies 8, Cleophas Ton J. (2013). Optimal Scaling, A Wonderful Method for Analysing Clinical Trials with Imperfect Data. Open Journal of Mathematical Modeling 1(1), 7-20 CFP (2014). Common Fisheries Policy, Facts and Figures, 2014 edition FAO (2009). The State of World Fisheries and Aquaculture, Food and Agriculture Organization of the United Nations, Rome, p. FAO (2012). The State of World Fisheries and Aquaculture. Food and Agriculture Organization of the United Nations, Rome. Grunert K. (2006). Future trends and consumer lifestyles with regard to meat consumption. Meat Science 74, Kaimakoudi E., Polymeros K., Shinaraki M., Batzios Ch. (2013). Consumers attitudes towards fisheries products. Procedia Technology 8, Kennedy O.B., Stewart-Knox B.J., Mitchell P.C., Thurnham D.I. (2004). "Consumer perceptions of poultry meat: a qualitative analysis", Nutrition & Food Science 34 (3), Macharia J., Collins R., Sun T. (2013). Value-based consumer segmentation: the key to sustainable agri food chains. British Food Journal 115 (9), Maciel E., Savay-da-Silva L., Vasconcelos J., Sonati J., Galvao J., Lima L., Oetterer M. (2013). Relationship between the price of fish and its quality attributes: a study within a community at the University of Sao Paolo, Brazil. Food Science and Technology 33 (3), Patton Q.M. (1990). Qualitative evaluation and research methods, Sage, California Phillips, W., Asperin, A. and Wolfe, K. (2013). Investigating the effect of country image and subjective knowledge on attitudes and behaviours: U.S. Upper Midwesterners intentions to consume Korean Food and visit Korea. International Journal of Hospitality Management 32, Pieniak Z., Verbeke W., Scholderer J., Brunso K., Olsen S. (2007). European consumers use of and trust in information sources about fish. Food Quality and Preference 18, Pieniak Z., Vanhonacker F., Verbeke W. (2013). Consumer knowledge and use of information about fish and aquaculture. Food Policy 40, Polymeros K., Kaimakoudi E., Schinaraki M., Batzios Ch. (2014). Analysing consumers perceived differences in wild and farmed fish. British Food Journal. In press Schlag A.,Ystgaard K. (2013). Europeans and aquaculture: perceived differences between wild and farmed fish. British Food Journal 115 (2), Shrestha Lal Srijan. (2009). Categorical Regression Models with Optimal Scaling for Predicting Indoor Air Pollution Concentrations inside Kitchens in Nepalese Households. Nepal Journal of Science and Technology 10,

301 ASSESSING THE EFFICIENCY OF BOTTOM TRAWLERS AND SMALL- SCALE FISHING VESSELS IN GREECE Pinello D.* 1, Liontakis, A. 2, Sintori, A. 2, Tzouramani I. 2, Polymeros K 1. 1 Department of Ichthyology and Aquatic Environment, University of Thessaly, Volos, Greece 2 Agricultural Economics and Policy Research Institute, ELGO, Demeter, Terma Alkamanos, P.C , Athens, Greece. Abstract This study explores the technical and scale efficiency of the small scale, coastal fisheries as well as bottom trawlers in Greece. The issue of efficiency is explored using an input oriented data envelopment analysis model. Moreover, the association of technical and scale efficiency scores with several characteristics of the vessel as well as characteristics of the skipper were also explored. Results indicate that small-scale vessels achieve a low average technical efficiency of 0.54 but much higher scale efficiency (0.80). The results of the analysis also indicate that in coastal fisheries, smaller vessels have the ability to better manage their resources. On the other hand, bottom trawlers achieve high scale but also technical efficiency scores. One important finding of the analysis is that in coastal fisheries, unlike trawlers, technical efficiency is positively correlated with the age and therefore the experience of the skipper. In a looser context, it can be said that small scale coastal fisheries mainly rely on skills, while bottom trawlers fisheries rely on science. Finally, this study suggests that there is room for improvement in the efficiency of mainly small scale vessels, which will allow for the achievement of the same level of output, but with reduced inputs. Key words: small scale fishery, bottom-trawlers, technical efficiency, scale efficiency, DEA *Corresponding author: Pinello Dario (dario.pinello@fao.org). 1. Introduction Fisheries is an important economic activity in Greece. According to the Greek Fleet Register, in 2012 the Greek fleet consists of 16,063 fishing vessels, with a combined gross tonnage of 79,678 GT and a total engine power of 462,429 kw. In particular, there were 13,918 fishing enterprises operating in Greece offering employment to 27,558 people. An important and unique characteristic of the Greek fishing fleet is that it consists mainly of small scale fishing vessels that exploit the extended Greek coastline. Thus, the fishery sector can be separated into two categories, namely small scale fisheries (coastal fisheries) and medium scale fisheries, mainly bottom trawlers and purse-seiners. From a socioeconomic point of view, the two categories have distinct characteristics. Small scale fishing vessels use polyvalent passive fishing gear and relay mainly on the work of the vessel owners. On the other hand, bottom trawlers and purse seiners are characterized by high operating costs, especially personnel costs. It is also important to emphasize that medium scale fisheries and in particular bottom trawlers appear to have high productivity and profitability. In the last decade, many studies explore efficiency in the European fishing fleet. Efficiency in fisheries is about achieving the best possible outcome with the available resources (fish stock and fishing inputs). Improvements in efficiency are desirable provided that a management structure exists that prevents biological and economic overexploitation. If not, increased efficiency or the ability to catch more fish for a given amount of fishing effort can be detrimental to sustainability (Grafton et al., 2006). Efficiency is strictly related with the concept of overcapacity. Overcapacity equals the difference between the maximum potential output that could be produced - given technology, desired resource conditions, and full and efficient utilization of capital stock, other fixed and variable input - and a desired optimum level of output (e.g. the maximum sustainable yield, or maximum economic yield) (Pascoe et al., 2003). Efficiency in fisheries is mainly explored in terms of the optimal combination of inputs to achieve a given level of output using Data Envelopment Analysis (DEA). DEA is a non-parametric approach of estimating efficiency. It was originally proposed by Charnes et al. (1978) and is based on Farrell s model (Farrell, 1957). By solving a linear programming problem, it allows us to estimate efficiency in multi-output situations without assuming an a priori functional form for frontier production (Coelli, 1996). Pascoe et al. (2001) analysed the technical efficiency of the Dutch beam trawl fleet over time. Lindebo et al. (2007) also investigated the efficiency of Danish North Sea trawlers. Pascoe and Coglan (2002) and Pascoe et al. (2004) utilized DEA in order to investigate the efficiency of the English Channel fisheries. Tingley et al. (2005) analyzed the technical efficiency for three fishing segments (netters, potters and mobiles) in the English Channel. Finally, Eggert (2001) 301

302 investigated the technical efficiency in the Swedish trawl fishery for Norway Lobster. In the Mediterranean region, Tsitsika and Maravelias (2008) and Tsitsika et al. (2009) investigated efficiency of the purse seiners in Greece while Fousekis and Klonaris (2002) studied efficiency in netters. In Sardinia, Madau et al. (2009) focused their analysis on the small-scale segment and Idda et al. (2009) studied the TE for the small trawlers. The present study explores the issue of efficiency of the Greek fishing fleet. The study focuses in both small scale vessel and bottom trawlers, which allows for comparisons and helps associate efficiency with specific characteristics of the two segment. For the purpose of the study, efficiency was considered using economic capacity analysis (Herrero and Pascoe, 2002; Lindebo et al., 2007), in which a data envelopment model (DEA) was used. Both the concepts of technical and scale efficiency were considered. 2. Material and Methods According to Kumbhakar and Lovell (2000), technical efficiency is defined as the ability of a decision-making unit (DMU) to obtain the maximum output from a given set of inputs (output orientation) or to produce an output using the lowest possible amount of inputs (input orientation). One way to do that is to measure a DMU's position relative to an efficient frontier, resulting in an efficiency score for this particular DMU. These efficiency scores will be bounded between zero and one, where a score of one indicates full efficiency. Therefore, efficiency measurement requires knowledge of the efficient production function. Technical efficiency and the factors determining it are of crucial importance in production theory. Technical efficiency of a DMU and the degree of use of variable inputs determine both output and capacity utilization. Determining those factors affecting technical efficiency allows stakeholders to take measures to limit or improve it (Grafton et al, 2006). In the fisheries context, there is a growing interest in the measurement of technical efficiency of different fishing fleets. This interest is twofold: to establish the underlying factors (e.g. Kirkley et al., 1998; Sharma and Leung, 1998), and to assess the effects of several socioeconomic variables. In the fisheries economics literature, output-oriented technical efficiency is usually applied, as the main aim is the estimation of capacity utilization, a concept which is basically output-oriented. Moreover, several authors based in output orientation, suggest that fishery managers may reduce technical efficiency by constraining the use of certain inputs (Kirkley et al., 1995; Pascoe et al., 2001), or alternatively, they may improve it by expanding these inputs or by taking measures that properly define the property rights of the fishery (Grafton et al, 2006). Although usually the efficiency analysis in fisheries investigates the capacity utilization (CU) of the fleet, we have indeed focused our study on the technical efficiency (TE) and the scale efficiency (SE), obtained by an input-oriented DEA. An input-orientated way of defining technical efficiency is the minimum amount of inputs required to produce a given level of output. In many fisheries, fishing vessels are not technically efficient because they use too many inputs, or are overcapitalized in the sense that a lower level of input (often measured in number of vessels) could be used to catch the same total harvest. Technical inefficiency may surface for many reasons, but a major cause is inputs controls that fail to prevent effort creep due to input substitution (Grafton et al, 2006). Input oriented technical and scale efficiency are particular meaningful in the case of the Greek small-scale and trawler fleets since the managerial scheme in force is mainly based on inputcontrol measures, including limited entry plans (licensing), open and closed areas and seasons, minimum length of species harvested and mesh size of nets (Fousekis and Klonaris, 2002). There are instead no limitations on the volume that can be landed per day or per year. The limits at the activity are therefore represented by the environmental conditions and by the input factors and the market conditions as well. The latter doesn t represent usually a constraint since the domestic market is characterized by an imbalance between demand and supply that lead the prices at a high level when compared to other European countries. From the end of the 1970s onwards, several techniques have been developed for efficiency analysis, based on the comparison of the output (input) of a group of DMUs. Methods to measure efficiency can be classified into two groups: non-parametric models (Data Envelopment Analysis - DEA) and parametric models, (Deterministic Frontier Analysis DFA and Stochastic Frontier Analysis - SFA). Apart from measuring efficiency, applications using DEA have been recommended by FAO (1998) from the late- 1990s onwards to measure also fishing capacity (e.g. Kirkley and Squires, 2002; Reid et al., 2003; Vestergaard et al., 2003; Pascoe et al., 2004). Data envelopment analysis developed by Charnes et. al. (1978). The production frontier constructed by DEA is deterministic, so any deviations from the frontier are related to inefficiency. The idea behind DEA is to use linear programming methods to construct a frontier around the data. 302

303 Efficiency is then measured relative to this frontier, where all deviations from the frontier are assigned to be inefficiency. Consider n DMUs producing m different output using h different inputs. Thus, Y is an mxn matrix of outputs and X is an hxn matrix of inputs. Both matrices contain data for all n DMUs. The Technical Efficiency (TE) measure can be formulated as follows: min ζ, subject to: -y i + Yθ 0 (1) ζx i Xθ 0 ι 0 and solved for each DMU in the sample. ζ, is DMU s index of technical efficiency, y i, and x i, represent the output and input of DMU i respectively and Yθ and Xθ are the efficient projections on the frontier. A measure of ζ i = 1 indicates that the DMU is completely technically efficient. Thus, 1 - ζ, measures how much DMU i's inputs can be proportionally reduced without any loss in output. Model (1) implies that all vessels are operating under constant returns to scale (CRS). However, the CRS assumption is only appropriate when all DMU s are operating at an optimal scale (i.e one corresponding to the flat portion of the LRAC curve) (Coelli et al., 2002). Several factors like imperfect competition and constraints on finance may cause a DMU not to operate at optimal scale. The use of the CRS specification when not all DMU s are operating at the optimal scale will result in measures of TE which are confounded by scale efficiencies (SE). Simply being technically efficient (producing on the production frontier) does not maximize overall productivity, but instead maximizes productivity only for a given input-output combination (Grafton et al, 2006). When the vessel is scale efficient it also produces at the optimal input-output combination. This means that the vessel operates under constant return to scale (CRS), and therefore one more unit of input-mix will effect in operating under decreasing return to scale. The use of the Variable Returns to Scale (VRS) specification will permit the calculation of TE devoid of these SE effects. Banker, Charnes and Cooper (1984) suggested an extension of the CRS DEA model to account for VRS situations. The modified DEA model that accounts for VRS is as follows: min ζ, Subject to: -y i + Yι 0 ζx i Xι 0 (2) NI ι = 1 ι 0 The new constraint is NI ι = 1 where NΗ is a nx1 vector of ones. This constraint makes the comparison of firms of similar size possible, by forming a convex hull of intersecting planes, so that the data is enveloped more tightly. The technical efficiency measures under VRS will always be at least as great as under the CRS assumption (Coelli et al., 2005). Scale efficiency can be calculated by conducting both a CRS and a VRS DEA upon the same data. If there is a difference in the two TE scores for a particular DMU, then this indicates that the DMU has scale inefficiency, and that the SE score is equal to the ratio of CRS TE score to VRS TE score. One shortcoming of this measure of scale efficiency is that the value does not indicate whether the DMU is operating in an area of increasing or decreasing returns to scale. This can be determined by running a modified DEA model where nonincreasing returns to scale (NIRS) are imposed. In this model, the NI θ = 1 restriction is substituted by NI ι 1, to provide: min ε, Subject to: -y i + Yι 0 ζx i Xι 0 (3) NI ι 1 ι 0 The nature of the scale inefficiencies (i.e. due to increasing or decreasing returns to scale) for a particular DMU can be determined by comparison of the NIRS TE score and the VRS TE score. If they are unequal then decreasing returns to scale exist for that DMU, while if they are equal, increasing returns to scale exist. 303

304 In this study, DEAP 2.1 software is used for the estimation of the efficiency scores. Moreover, to deal with slacks, we use the multi-stage method (Coelli, 1996). According to the author, the advantages of this method are that it identifies efficient projected points which have input and output mixes which are as similar as possible to those of the inefficient points, and that it is also invariant to units of measurement. After the estimation of the above efficiency measures, a second stage statistical analysis is performed to associate efficiency scores with several socio-economic variables. This set of variables includes among others, education and age of the skipper, owner contribution to the vessel, length of the vessel and gross cash flow. This analysis is performed with spearman correlation and Wilcoxon rank-sum test (Mann Whitney two-sample statistic). In order to perform the Mann-Witney test, vessels are divided in two groups according to a specific characteristic (binary variable). Then, the technical and the scale efficiency scores of the two groups are compared. The Mann-Whitney test is a non-parametric analog to the independent samples t-test that does not require the assumption that the dependent variable is normally distributed (Siegel and Castellan, 1988). As the distribution of the efficiency scores reveals, the assumption of normal distribution is not rational in this study. Data used in the analysis were collected through a sample survey using a well-structured socio-economic questionnaire. Face to face interviews with 283 fishermen were conducted, 249 of which were engaged in costal, small scale vessels with total length less than 12 meters and 34 in bottom trawlers, with vessel length over 18 meters 1. The variables used for the DEA analysis consist of one fixed input, which is the annual depreciation cost and 4 variable inputs, namely annual personnel cost, fuel cost, running cost and repair and maintenance cost. The output variable considered in the analysis is the annual revenues of the vessels. Energy costs refer to the annual cost of fuels for the engine while personnel costs refer to the total cost of paid labour plus any unpaid labour of the owner. Maintenance and repair costs refer to the annual costs of repairs for vessel, the engine as well as the fishing gear and running costs refer to all other operation cost (e.g. bait and hooks) including the cost of lubricants and the commercial costs (e.g. ice, boxes and packages). Other annual expenses of the vessels like dock expenses and book keeping costs, were also included in the running costs. Annual revenues of the vessels were determined through the value of the annual landings. Table 1 contains some descriptive statistics of the main variables used in the DEA analysis for both the small scale vessels and for trawlers. As far as the depreciation cost is concerned, it has been estimated according to the Perpetual Inventory Method (PIM methodology) (IREPA et al., 2006). PIM proposes to determine the aggregate value of the tangible capital goods used in the current year by aggregation of the value of all vintages (year classes). Such aggregation can be based either on historical, current or constant prices. Once the value of the capital goods in a given benchmark year has been determined, the capital value of each subsequent year is calculated by adding investments of that year (gross capital formation), revaluing the existing stock and subtracting value of capital goods taken out of operation. The annual depreciation cost is then calculated, using proper depreciation schedule. The assumed depreciation rates used for the different components of the vessel are 7% for hull, 25% for engine, 50% for electronics and 35% for other equipment. The service lives are 25 years for hull, 10 years for engine, 5 years for electronics, 7 years for other equipment. Table 1. Descriptive statistics of the input and output variables used in the analysis Variable Small scale vessels Bottom trawlers Input variables Mean value ( ) St. deviation Mean value ( ) St. deviation Personnel cost 9,068 6,498 81,243 44,842 Fuel cost 4,699 5, ,825 57,005 Running cost 3,268 5,194 70,983 46,019 1 The data used in the analysis is part of a larger data set collected in the framework of the Greek National Fisheries Data Collection Program 2013 (in application of the EC decision 93/2010). For the purpose of the analysis only data concerning small scale fishing vessels and bottom trawlers were used. 304

305 Repair and maintenance cost 2,112 2,268 20,229 12,854 Output variable Revenues 18,869 16, , ,570 As mentioned by Tinkley et al (2005), the use of revenue as the output measure is not ideal, as revenue is a function of prices as well as quantity. Consequently, price changes that affect the output measure independent of input use may be interpreted as changes in technical efficiency. This is particularly a problem for DEA, as there is the likelihood that price changes affecting all operators would enter the random error component when using SPF. Further, assuming fishers seek to maximise profit, a change in relative prices may result in a change in their fishing strategy. As a result, the function is not truly a production function and the efficiency scores may represent a combination of allocative as well as technical efficiency. However, the potential biases introduced into the analysis from using revenue as the output measure are not likely to be large. Squires (1987) and Sharma and Leung (1998) note that fishers base their fishing strategies on expected prices, the level of technology and resource abundance. However, price expectations are not always accurate, information on the variation in abundance of the stock across the fishery is generally not available, and catch composition is governed largely by fishing gear that is not perfectly species selective. Changing gears types is time consuming and usually needs to be done on shore rather than at sea. Hence, the ability of fishers to respond to changes in relative prices by varying their fishing activity is limited. Several recent studies (e.g. Holland and Sutinen, 2000) have suggested that fishing activity is largely influenced by habit, with only relatively minor changes in effort allocations in response to price in the short term. Furthermore, we consider that the Greek small-scale and bottom trawlers fisheries are operating in a situation of unbalance ratio between demand and supply, where cultural and economic factors generate a high demand for seafood products leading to constantly high prices, not significantly affected by the either landing volume or the season. Finally, the use of inputs (and outputs) values rather than quantities is very common in efficiency studies. As is recently proved by Portela (2013), and has been previously mentioned by Fare et al. (1990) and Banker et al. (2007), when the assumption that fishermen face equal input prices is hold, then values can be used in the place of quantities and still produce technical efficiency scores. 3. Results Small-scale vessels Table 2 provides the descriptive statistics of TE and SE scores for the small-scale vessels in Greece. It also reports the number of vessels that work under constant, increasing and decreasing returns to scale technology. On average, small-scale vessels have 0.54 TE scores and therefore, assuming that they are technically efficient, they can proportionally decrease their inputs by 46% and still produce the same amount of output. The standard deviation, the min and the max score of TE also reveal that the results are characterised by high heterogeneity. According to Figure 1, many vessels have very low efficiency, which suggests that there is room for improvement. On the other hand, the average scale efficiency score is much higher (0.80). Therefore, on average, small scale vessels operate close to the optimal scale of production. According to Table 2, the vast majority of the vessels (72.7%) operate at increasing returns to scale, while 18.1 % operates at decreasing returns to scale. This is a common finding in the relevant literature (e.g. Fousekis and Klonaris, 2003; Garcia Del Hoyo et al., 2004; Esmaeili, 2006). Table 2. Descriptive statistics of TE, SE and scale of operation for small scale vessels. Variable Mean Standard Deviation CV Min Max TE %.16 1 (34 vessels) SE %.20 1 (23 vessels) Scale of operation DMUs 305

306 Frequency Frequency HydroMedit 2014, November 13-15, Volos, Greece IRS 181 vessels (72.7%) CRS 23 vessels (9.2%) DRS 45 vessels (18.1%) te se Figure 1. Histograms of a) TE and b) SE scores of the small-scale vessels Table 3 provides the results of the Spearman correlation analysis among the efficiency scores and several other continuous variables. Moreover, Table 4 provides the results of the Mann-Witney test. These results suggest that the vessels with length less than 6 meters are more technically efficient. To some extent this can be explained by the high level of flexibility that characterizes small vessels. These vessels can easily adjust their cost determinants according to the seasonal or regional productivity of the harvesting. This can be done for example using alternative fishing gear or moving to a different fishing ground targeting different species or simply by decreasing the level of the activity and operating only during the (potentially) more productive days. A similar result was reported by Fousekis and Klonaris (2002), whose empirical results in the investigation of the Greek trammel netters indicate that larger vessels tend to be less technically efficient than smaller vessels. They also point out that the crew size plays an important role, since larger vessels need larger crew. Thus, a large crew size may reduce the ability of a skipper to adjust the level of other inputs (Fousekis and Klonaris, 2002). Furthermore, it is noteworthy that the small vessels are generally capable of achieving higher selling prices than big vessels. This can be explained by several factors, like the limited volume of landings, better marketing strategy, higher product quality, or, more likely, a combination of these factors. In any case these vessels normally set their selling strategy on direct sales, without any intermediate intervention. This seems to encourage fishermen to focus on the product quality, which leads to high selling prices. Table 3. Spearman correlations of TE and SE scores of the small-scale vessels with technical and socioeconomic variables TE SE Length -0.29** 0.23** Gt -0.28** 0.23** revenues 0.25** 0.68** Days at sea -0.10* 0.28** Unpaid labour to total labour -0.17** 0.15** ** 0.05 level of significance, * 0.10 level of significance Table 4. Variables that define groups with different TE scores in the small-scale fishing segment Variable that define groups Average TE Z score Result Length class 0-6 m m ** Small vessels have higher TE Level of education basic 0.56 advanced * Skippers with basic education perform better Vessels registered in East Yes ** Vessels in this region have lower TE 306

307 Macedonia & Thrace No 0.57 Vessels registered in South Aegean and Crete Yes 0.69 No ** Vessels in these regions have higher SE Young skipper (less than 40) Yes 0.50 No * Vessels whose skipper is very young have less TE *0.05 level of significance **0.10 level of significance Table 5. Variables that define groups with different TE scores in the small-scale fishing segment Variable that define groups Average SE Z score Result *0.05 level of significance **0.10 level of significance Length class 0-6 m m * Small vessels have higher SE The results also reveal that TE is lower when the vessel is managed by a skipper younger than 40 years of age. Moreover, the literacy level appears to have a weak negative effect on TE. One possible explanation may lie in the fact that in small scale vessels, the outcome of the fishing activity relies on the experience of the skipper rather than on his formal education or on the use of new technologies (commonly associated with younger skippers). Furthermore, the experience of the skipper plays a key role in the selection of the fishing gear, the fishing ground and the fishing day. These results are not always supported by similar studies. For example, Ali et al. (1996) mention that formal education is generally associated with increased efficiency as it broadens the producers minds and enables them to acquire and process relevant information. Moreover, according to Esmaeili (2006) younger skippers are more efficient than others. Finally, Fousekis and Klonaris (2002), exploring the efficiency of Greek netters, report that the good skipper is aged about 50, has a literacy level higher than the primary, and comes from a fishermen family. The analysis also detected that the vessels operating in the region of East Macedonia and Thrace score lower TE than the vessels operating in others regions. On the contrary, vessels operating in the Cyclades Islands and Crete have high TE scores. These regional differences in the TE scores can be explained by differences in the composition of the catch or differences in the extent of competition with the large scale vessels for the same fishing ground and/or the same markets. The fishing grounds in the Cyclades Islands and Crete are characterized by rocky bottoms, while in the region of East Macedonia and Thrace, sandy grounds are more common. Moreover a lower number of large scale vessels operate in the Cyclades Islands and Crete. The Spearman correlation analysis shows, as expected, that the vessels with smaller technical characteristics (LOA and GT) have higher TE. These vessels are capable of producing the same unit of output (revenues) with less input. There is also a positive correlation with the revenues generated by the vessel. The reason may lie on the ability of vessels with higher turnover and cash availability to invest on new and more efficient fishing gear. The number of days that the vessel spends at sea is negatively correlated with TE. This could be explained by a more rational fishing strategy (i.e. operation only under optimal conditions or a close proxy of them). Finally, a positive correlation was detected between the TE and the presence of the owner onboard the vessel. This factor was detected by the ratio of unpaid labour to total labour costs. In general, owner-operated vessels are considered more efficient than others (Esmaeili, 2006; Sharma and Leung, 1998). As far as scale efficiency scores are concerned, they are negatively correlated with the length and the capacity of the vessels, thus bigger vessels have lower SE scores than smaller vessels. This result is in line with what has already been mentioned about the TE; for the Greek small scale fleet it seems that the smaller the vessel the better the (overall) efficiency. A positive correlation was detected with the unpaid labour, that indicates the presence onboard of the owner. This results is in line with what detected for the TE. 307

308 Frequency Frequency HydroMedit 2014, November 13-15, Volos, Greece Bottom trawlers Table 6 provides the descriptive statistics of TE and SE scores for the Greek bottom trawlers. The table also reports the number of the vessels that operate under constant, increasing and decreasing returns to scale. On average, bottom trawlers TE scores are very high (0.83), indicating that, provided that they are technically efficient, fishermen can reduce their inputs by 17% and still produce the same amount of output. The descriptive statistics and the histogram (Figure 2) reveal that TE scores in the case of bottom trawlers are more tightly clustered around the average, than in the case of the smallscale vessels. As far as scale efficiency is concerned, it is on average equal to As expected, the 82% of the vessels operates under increasing returns to scale, which means that the main reason for scale inefficiencies is the sub-optimal size of the vessels. Table 6. Descriptive statistics of TE, SE and scale of operation of the bottom-trawlers Variable Mean Standard Deviation CV Min Max TE %.51 1 (13 vessels) SE %.31 1 (6 vessels) Scale of operation DMUs IRS 28 vessels (82.4%) CRS 4 vessels (17.6%) DRS 0 vessels Table 7 provides the results of the Spearman correlation analysis among the efficiency scores and several other characteristics of the vessels and their skippers. Moreover, Table 7 provides the results of the Mann-Whitney test. Unlike the small-scale vessels, the TE of bottom trawlers is not associated with any technical (LOA and GT) as well social (age and literacy level of the skipper) factor. This was expected since, unlike small-scale vessels, the majority of trawlers operate at a similar TE level. Furthermore, from a technical point of view, this segment is more homogenous, since all vessels use similar fishing gear and exhibit similar fishing behaviour. It is noteworthy that the gross cash flow per vessel is positively correlated with the TE. This could be explained by the higher cash availability which is associated to higher investments in fishing equipment and technology. As far as scale efficiency is concerned, the results indicate that, unlike small-scale vessels, the SE of trawlers is positively correlated with the technical characteristics of the vessels (LOA and GT). Thus, it is more likely that large vessels produce at the optimal input-output combination compare to smaller vessels. Finally, the SE is positively correlated with the gross cash flow. This correlation can be explained by the higher cash availability which leads to investment in better fishing equipment (gear and vessel) te se Figure 2. Histograms of TE and SE scores of bottom trawlers Table 6. Spearman correlations TE SE Length ** Gt * 308

309 revenues ** Days at sea Gross cash flow 0.51** 0.72* ** 0.05 level of significance, * 0.10 level of significance 4. Discussion In this analysis the technical and scale efficiency of the Greek fishing fleet was explored. The analysis focused on small scale, coastal fisheries as well as bottom trawlers, indicating similarities and differences among the two fleet segments. The issue of efficiency was explored using an input oriented data envelopment analysis model. The data used in the analysis were collected through a sample data survey and involve cost and revenue parameters. Four variable inputs were taken into consideration, namely, fuel cost, personnel cost, repair and maintenance cost and other running costs. Also, annual depreciation cost was used as a fixed input variable and annual revenues represent the output of the fishing activity. Additional information regarding the characteristics of the vessel (length and capacity) as well as characteristics of the skipper (age and education level) were also available and tested for correlation with the technical and scale efficiency. The results of the analysis indicate that small scale vessels achieve a small average technical efficiency of 0.54 but much higher scale efficiency (0.80). The results of the analysis also indicate that small vessels achieve higher technical and scale efficiency scores. This means that in coastal fisheries, smaller vessels have the ability to better manage their resources. On the other hand, the results of the analysis indicate that bottom trawlers achieve high scale but also technical efficiency scores. The bottom trawlers fleet segment is more homogenous, regarding the technical efficiency scores, regardless of the size of the vessel, though size is positively correlated with high scale efficiency scores. One important finding of the analysis is that technical efficiency is positively correlated with the age and therefore the experience of the skipper, though age is negatively correlated with scale efficiency. Education appears to have no effect on technical and scale efficiency of small scale vessels. As far as trawlers are concerned, the characteristics of the skipper have no effect on technical or scale efficiency. Overall, the results of the analysis suggest that in small scale fisheries, efficiency relies mainly on qualitative factors, like the experience of the skipper. On the other hand, the high efficiency scores of the bottom trawlers are the result of the improved technology these vessels utilize. For trawlers, qualitative factors, like the experience of the skipper, have no significant impact on efficiency. In a looser context, it can be said that small scale coastal fisheries rely on skills, while bottom trawlers fisheries rely on technology. Furthermore, the results of the analysis, suggest that there is room for improvement in the efficiency of mainly small scale vessels, which will allow for the achievement of the same level of output, but with reduced inputs. This can be achieved reducing the level of activity of the segment by decreasing the total number of operating vessels or decreasing the days at sea per vessel. The former proposal being more practical. On the other hands, the bottom trawl fleet seems to have a more balanced level of activity. Acknowledgements The research was funded by the Greek National Program of Data Collection for Fisheries Sector, Part Socio Economic Variables, through the study, The socioeconomic Survey of Greek Fisheries. The authors would like to thank Prof. K. Galanopoulos for his helpful and insightful comments. References Ali, F., Parikh, A., Shah, M. K. (1996). Measurement of economic efficiency using the behavioral and stochastic cost frontier approach. Journal of Policy Modelling, 18(3), Banker, R. D., Charnes, A., Cooper, W.W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), Banker, R., Chang, H., Natarajan, R. (2007). Estimating dea technical and allocative inefficiency using aggregate cost or revenue data. Journal of Productivity Analysis, 27: Charnes, A., Cooper, W.W., Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), Coelli T. (1996). A guide to DEAP Version 2.1: a Data Envelopment Analysis (computer) program. Department of Econometrics University of New England. CEPA Working Papers 96/

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312 SCIENTIFIC DIVING AND APPLICABLE LAW Longinidis P 1*., Skoufas G Faculté de Droit et Science Politique, Université Toulouse 1 Capitole, 2 rue Doyen Gabriel Marty, F Toulouse cedex 9, France 2. Department of Fisheries Technology and Aquacultures, Α.Σ.Δ.Η.Th., N. Miltiadi 1, 63200, Nea Moudania, Greece ABSTRACT Scientific diving is a valuable tool for collecting data, which are useful in a wide range of disciplines such as biology, archeology, geology, etc. For an effective and well-defined scientific diving and in order to avoid any kind of problems both practical and theoretical, a legal framework to regulate the characteristics of scientific diving is needed. Although recreational diving is now experiencing a significant growth in Greece, however, scientific diving is not recognized by the Greek legislation, only slightly, under legislation destined for other forms of diving. Key words: Scientific diving, legislation. * Corresponding author: Longinidis Panagiotis (longinidis@gmail.com) ΔΠΗΣΖΜΟΝΗΚΖ ΚΑΣΑΓΤΖ ΚΑΗ ΗΥΤΟΝ ΓΗΚΑΗΟ Λμββζκίδδξ Π.1*, ημφθαξ Γ2. 1.Faculté de Droit et Science Politique, Université Toulouse 1 Capitole, 2 rue Doyen Gabriel Marty, F Toulouse cedex 9, France 2.Σιήια Σεπκμθμβίαξ Αθζείαξ ηαζ Τδαημηαθθζενβεζχκ, Α.Σ.Δ.Η.Θ., Ν. Μζθηζάδδ 1, 63200, Νέα Μμοδακζά, Δθθάδα Πενίθδρδ Ζ επζζηδιμκζηή ηαηάδοζδ απμηεθεί έκα πμθφηζιμ ενβαθείμ βζα ηδ ζοθθμβή ηαζ ηδκ ηαηαβναθή δεδμιέκςκ, ηα μπμία είκαζ δοκαηυ κα αλζμπμζδεμφκ ζε έκα εονφ θάζια επζζηδιχκ υπςξ είκαζ δ Βζμθμβία, δ Ανπαζμθμβία, δ Γεςθμβία, η.ά. Γζα ιζα απμηεθεζιαηζηή ηαζ ζαθχξ μνζζιέκδ επζζηδιμκζηή ηαηάδοζδ ηαζ πνμηεζιέκμο κα απμθεοπεμφκ πάζδξ θφζεςξ πνμαθήιαηα ηυζμ ζε πναηηζηυ (αθ. ζπέζεζξ ιε δζμίηδζδ) υζμ ηαζ ζε εεςνδηζηυ επίπεδμ, ηαείζηαηαζ αοηυιαηα ακαβηαία δ φπανλδ εκυξ κμιμεεηζημφ πθαζζίμο πμο κα νοειίγεζ ηα παναηηδνζζηζηά ηδξ επζζηδιμκζηήξ ηαηάδοζδξ. Ακ ηαζ δ ηαηάδοζδ ακαροπήξ πθέμκ βκςνίγεζ ιία ζδιακηζηή ακάπηολδ ζηδκ Δθθάδα, εκημφημζξ δ επζζηδιμκζηή ηαηάδοζδ δεκ ακαβκςνίγεηαζ άιεζα απυ ηδκ εθθδκζηή κμιμεεζία, πανά ιυκμ απμζπαζιαηζηά, ζηα πθαίζζα κμιμεεηδιάηςκ πνμμνζζιέκςκ βζα άθθεξ ιμνθέξ ηαηάδοζδξ. Λέλεζξ Κθεζδζά: Δπζζηδιμκζηή ηαηάδοζδ, κμιμεεζία. *οββναθέαξ επζημζκςκίαξ: Λμββζκίδδξ Πακαβζχηδξ (longinidis@gmail.com) 1. Δηζαγσγή Ζ επζζηδιμκζηή ηαηάδοζδ (βαθθζηά plongée scientifique, αββθζηά scientific diving) απμηεθεί εηείκμ ημ είδμξ ηδξ εθεφεενδξ ηαηάδοζδξ πμο πναβιαημπμζείηαζ απυ αίηζα ηαεανά επζζηδιμκζηχκ ακαγδηήζεςκ ηαζ είκαζ δοκαηυ κα επζπεζνδεεί είηε αημιζηά, είηε απυ ζφκμθμ δοηχκ, ιε ηδ πνήζδ ή υπζ επζζηδιμκζηχκ μνβάκςκ ηαζ αμδεδιάηςκ (American Academy of Underwater Sciences, 2013). ημπυξ ηδξ είκαζ δ παναημθμφεδζδ ηαζ ζοθθμβή επζζηδιμκζηχκ ηαζ ιυκμκ εονδιάηςκ, ηα μπμία ζοκδέμκηαζ άιεζα ιε ημκ οπμεαθάζζζμ ηυζιμ ηαζ είκαζ δοκαηυ κα απμηηδεμφκ ηονίςξ ιε αοηυκ ημκ ηνυπμ ηδξ ηαηάδοζδξ. Ονίγεηαζ δε ςξ πςνζζηυξ ηφπμξ ηαηάδοζδξ ηαεχξ δε δφκαηαζ κα πενζθδθεεί ζε άθθμοξ ηφπμοξ αοηυκμιδξ ηαηάδοζδξ υπςξ ηδκ ηαηάδοζδ ακαροπήξ, ηδκ επαββεθιαηζηή ηαηάδοζδ ή ηδκ ηαηάδοζδ βζα θυβμοξ πμο επζαάθθεζ δ αζθάθεζα ή ιία έηηαηηδ ακάβηδ (ΦΔΚ 273α'/2005. Νυιμξ 3409 ). Δίκαζ δε παναηηδνζζηζηυ υηζ, δ επζζηδιμκζηή ηαηάδοζδ είκαζ δοκαηυ κα ειπενζέπεζ ηαζ άθθμοξ ηφπμοξ αημιζηήξ ηαηάδοζδξ ηαεχξ είκαζ πμθοδζάζηαηδ ηαζ αθμνά ζε ιία ζεζνά ηθάδςκ υπςξ δ αζμθμβία, δ ανπαζμθμβία, δ θοζζηή ςηεακμβναθία, δ πδιζηή ςηεακμβναθία ηαζ δ βεςθμβία ηαζ είκαζ δοκαηυ κα απαζηεί ηαζ εζδζηέξ βκχζεζξ, αοηέξ ηδξ ηαηάδοζδξ ηαη' επάββεθια (CMAS (xi), 2000),. Ζ παναπάκς εκκμζμθμβζηή πνμζέββζζδ ηδξ επζζηδιμκζηήξ ηαηάδοζδξ ηνίκεηαζ ακαβηαία ζημκ ααειυ πμο πνυηεζηαζ κα δζενεοκδεεί ημ εβπχνζμ κμιζηυ πθαίζζμ ζε ζοκάνηδζδ ιε ηδ δζεεκή οθζζηάιεκδ ηαηάζηαζδ (Sayer et al., 2008). 312

313 2. Τιηθά θαη Μέζνδνη Ζ πανμφζα επζζηδιμκζηή ιεθέηδ απμηεθεί ιία αζαθζμβναθζηή ακαζηυπδζδ ημο κμιμεεηζημφ πθαζζίμο πμο δζέπεζ ηδκ αοηυκμιδ ηαηάδοζδ ηαζ ηδκ εθανιμβή ηδξ ζηδκ επζζηδιμκζηή ένεοκα. Ζ ιεεμδμθμβζηή πνμζέββζζδ ημο εέιαημξ ααζίγεηαζ ζε δζαηνζημφξ ημιείξ δζενεφκδζδξ. Καηανπήκ ζηδκ εεκζηή κμιμεεζία, ηαζ ζε δεφηενμ πνυκμ ζηδκ εονςπασηή ηαζ δζεεκή κμιμεεζία. Γζα ηδ δζενεφκδζδ ηδξ εεκζηή κμιμεεζίαξ, πνδζζιμπμζήεδηε ηαηά αάζδ δ δθεηηνμκζηή ζεθίδα ημο Δεκζημφ Σοπμβναθείμο ( Ο ηνυπμξ πανμοζίαζδξ ηςκ απμηεθεζιάηςκ αημθμοεεί ηδ ιεεμδμθμβία δζενεφκδζδξ. 3. Απνηειέζκαηα-πδήηεζε 3.1. Ηζρχνλ εζληθφ δίθαην χληαγκα Ζ ζοκηαβιαηζηή εειεθίςζδ ηδξ εθεφεενδξ ηαηάδοζδξ ηαζ ηδξ επζζηδιμκζηήξ ηαηάδοζδξ ςξ ηιήια αοηήξ εδνάγεηαζ ζημ άνενμ 5 ημο οκηάβιαημξ, ημ μπμίμ ακαδεζηκφεζ ηδκ εθεφεενδ ακάπηολδ ηδξ πνμζςπζηυηδηαξ ημο ηαεεκυξ, υηακ αοηή δεκ πνμζαάθεζ ηα δζηαζχιαηα ηςκ άθθςκ, εκχ επζπθέμκ εθανιυγεηαζ εζδζηά βζα ηδκ επζζηδιμκζηή ηαηάδοζδ ημ άνενμ 16, ημ μπμίμ οπμπνεχκεζ ηδκ Πμθζηεία κα πνμάβεζ ηδκ επζζηήιδ ηαζ ηδκ ένεοκα, μζ μπμίεξ ιε ηδ ζεζνά ημοξ είκαζ εθεφεενεξ βζα ημοξ πμθίηεξ ηαζ παίνμοκ ημκ ζεααζιυ ηαζ ηδκ πνμχεδζή ημοξ απυ ημ ηνάημξ. Άθθςζηε, δ επζζηδιμκζηή ηαηάδοζδ ζοκδέεηαζ άιεζα ιε ημ άνενμ 22, ημ μπμίμ εέηεζ ςξ ααζζηυ εειέθζμ ηςκ αημιζηχκ δζηαζςιάηςκ ηδκ πνμζηαζία απυ ημ Κνάημξ ηδξ ενβαζίαξ ηαζ ηδκ οπμπνέςζδ ημο ηεθεοηαίμο κα ιενζικά βζα ηδ δδιζμονβία ηςκ ηαηάθθδθςκ ζοκεδηχκ απαζπυθδζδξ ηςκ πμθζηχκ. Σμ φκηαβια θμζπυκ, ημ μπμίμ ηαηζζπφεζ υθςκ ηςκ οπμθμίπςκ ααειίδςκ εεζιμεεηδιέκςκ κυιςκ ηαζ άθθςκ κμιμεεηδιάηςκ, δείπκεζ ζαθχξ ηδκ εφκμζά ημο πνμξ ηδ δδιζμονβία εκυξ ζοιπαβμφξ κμιμεεηήιαημξ, ημ μπμίμ εα πνέπεζ κα νοειίγεζ ηα γδηήιαηα ηδξ αοηυκμιδξ ηαηάδοζδξ ηαζ πζμ ζοβηεηνζιέκα ηδξ επζζηδιμκζηήξ ηαηάδοζδξ Νφκνη Μία πνχηδ ένεοκα ηςκ εεζπζζιέκςκ εθθδκζηχκ κυιςκ ζπεηζηά ιε ηζξ ηαηαδφζεζξ ιπμνεί εφημθα κα ηαηαθήλεζ ζηδ δζαπίζηςζδ υηζ δ επζζηδιμκζηή ηαηάδοζδ, ςξ ηιήια ηδξ αοηυκμιδξ ηαηάδοζδξ, μοδέπμηε έςξ ηχνα δεκ απαζπυθδζε ημκ Έθθδκα κμιμεέηδ, πανυθμ ημ εκδζαθένμκ πμο πανμοζζάγεζ ημ γήηδια ζε εονςπασηυ ηαζ παβηυζιζμ επίπεδμ. Χζηυζμ, εα πνέπεζ κα ενεοκδεεί δ ζπεηζηή κμιμεεζία πενί αοηυκμιςκ ηαηαδφζεςκ, δ μπμία mutatis mutandis δφκαηαζ κα εθανιμζηεί ζηδκ πενίπηςζδ ηδξ επζζηδιμκζηήξ ηαηάδοζδξ, πμο μζ δφμ αοηέξ ηαοηίγμκηαζ ή ζοκακηζμφκηαζ. Ζ αοηυκμιδ ηαηάδοζδ (scuba diving) θαίκεηαζ κα ακηζιεηςπίγεηαζ πνχηδ θμνά απυ ημκ Έθθδκα κμιμεέηδ ιε ηδκ οπ'ανζει /9/1994 Τπμονβζηή απυθαζδ ημο Τπμονβμφ Διπμνζηή Ναοηζθίαξ (ΦΔΚ 858/1994), δ μπμία αθμνά ζηδκ έβηνζζδ ημο Γεκζημφ Κακμκζζιμφ Λζιέκα, ανζει. 5 ηαζ ζημκ μπμίμ νδηχξ μνίγεηαζ ςξ εναζζηέπκδξ πηοπζμφπμξ αοημδφηδξ, «απηόο πνπ έρεη εξαζηηερληθό πηπρίν απηνδύηε από Διιεληθό ή αλαγλσξηζκέλν αιινδαπό θέληξν εθκάζεζεο ππνβξύρηαο θνιύκβεζεο κε απηόλνκε θαηαδπηηθή ζπζθεπή παξνρήο αέξα». Δφημθα, θμζπυκ, ακηζθαιαάκεηαζ ηάπμζμξ υηζ ακαθυβςξ, ημ εκ θυβς οπ'ανζει. 2 3 άνενμ ηδξ πνμηείιεκδξ Τπμονβζηήξ απυθαζδξ, εθανιυγεηαζ ηαζ ζηδκ πενίπηςζδ ημο επζζηδιμκζημφ δφηδ. Απαναίηδηδ, θμζπυκ, πνμτπυεεζδ πνμηεζιέκμο κα εεςνδεεί επζζηήιςκ δφηδξ μ εναζζηέπκδξ δφηδξ είκαζ δ απυηηδζδ απυ ημκ αοημδφηδ εκυξ πηοπίμο ζηακμφ κα επζηνέπεζ ηδκ ηαηάδοζδ. ημ πθαίζζμ πμο δ επζζηδιμκζηή ηαηάδοζδ ζοκδέεηαζ ζοπκά ιε ηδκ εηηέθεζδ εκυξ επαββέθιαημξ ή ηδ ιενζηή άζηδζδ αοημφ, δ εέζπζζδ ηδξ επαββεθιαηζηήξ ηαηάδοζδξ ιε ηδκ έβηνζζδ ημο Γεκζημφ Κακμκζζιμφ Λζιέκα αν. 10 (ΦΔΚ 978/1995) εα ιπμνμφζε κα ηφπεζ εθανιμβήξ ηαζ ζηδκ πενίπηςζδ ηδξ επζζηδιμκζηήξ ηαηάδοζδξ, εθυζμκ αοηή πναβιαημπμζείηαζ ζοπκά απυ επαββεθιαηίεξ επζζηήιμκεξ ηαζ ζημπεφεζ ζηδκ άζηδζδ ηςκ επαββεθιαηζηχκ ημοξ οπμπνεχζεςκ. Χζηυζμ, ιζα ζε αάεμξ ακάβκςζδ ηδξ εκ θυβς Τπμονβζηήξ απυθαζδξ, ιαξ απμιαηνφκεζ απυ ημκ επζδζςηυιεκμ βζα ειάξ ζημπυ ιζαξ ηαζ ζηδκ πανάβναθμ 1 ημο άνενμο 2 ανζειμφκηαζ απμηθεζζηζηά μζ ενβαζίεξ ημο επαββεθιαηία δφηδ: «Κάζε εξγαζία, πνπ δηελεξγείηαη θάησ από ηελ επηθάλεηα ηεο ζάιαζζαο, όπσο επηζεώξεζε, επηζθεπή, αλέιθπζε, δηάιπζε πινίνπ, πθαινθαζαξηζκόο ή άιιεο ζπλαθείο εξγαζίεο θαη ζρεηίδεηαη κε ηα πινία ή ηα πισηά λαππεγήκαηα θαζώο θαη κε ηελ εθηέιεζε ιηκεληθώλ ή άιισλ ππνβξύρησλ έξγσλ». Πανάθθδθα, δ πανάβναθμξ 5 ημο ίδζμο άνενμο ένπεηαζ κα αεααζχζεζ ημκ απμηθεζζιυ ημο επζζηήιμκα δφηδ απυ ημκ δφηδ πμο ηαηαδφεηαζ βζα ηδκ άζηδζδ επαββέθιαημξ, μνίγμκηαξ ημκ ηεθεοηαίμ ςξ «ηνλ εξγαδόκελν θαη' επάγγεικα θάησ από ηελ επηθάλεηα ηνπ λεξνύ θαη πθηζηακέλνπ πηέζεηο ίζεο ή κεγαιύηεξεο ηεο αηκνζθαηξηθήο, κε νπνηνπδήπνηε ηύπνπ θαηαδπηηθή ζπζθεπή, απηόλνκε ή εμαξηώκελε από ηελ επηθάλεηα, κέζα ζηα πιαίζηα ησλ πεξηνξηζκώλ ηνπ παξόληνο θαη ηνπο λόκνπο ηεο ηέρλεο θαη ηεο επηζηήκεο». Ο επζζηήιςκ δφηδξ δεκ ενβάγεηαζ ηάης απυ ηδκ επζθάκεζα ημο κενμφ, πανά δ ηαηάδοζδ δφκαηαζ - υπζ οπμπνεςηζηά - κα ζοιπθδνχκεζ ηδκ επζζηδιμκζηή ημο ένεοκα, πςνίξ αοηή κα απμηεθεί ηδκ ηφνζα επαββεθιαηζηή ημο αζπμθία. Δπζπθέμκ, εκχ βζα ηδκ επαββεθιαηζηή ηαηάδοζδ πνμαθέπεηαζ 313

314 δ δζαδζηαζία απυηηδζδ άδεζαξ ηαηάδοζδξ απυ ηδ Λζιεκζηή Ανπή, δεκ έπεζ πνμαθεθεεί δ απυηηδζδ ακηίζημζπδξ άδεζαξ βζα ημκ επζζηήιμκα δφηδ ιε απμηέθεζια αοηυξ κα αμοηάεζ ζε κμιζηυ ηεκυ ηαζ ζε απμοζία κμιζηήξ ηάθορδξ. Χζηυζμ, ζπμοδαίμ γήηδια ηδξ εκ θυβς Τπμονβζηήξ απυθαζδξ πμο εα ιπμνμφζε εκ δοκάιεζ κα απμηεθέζεζ ιεβάθμ ειπυδζμ ζηδκ επζζηδιμκζηή ηαηάδοζδ ηαζ ζοκδβμνεί ζηδκ ακαβηαζυηδηα εζδζηήξ κμιμεεηζηήξ νφειζζδξ ηδξ επζζηδιμκζηήξ ηαηάδοζδξ απμηεθεί ημ άνενμ 11, ημ μπμίμ πνμαθέπεζ ηδ πμνήβδζδ εζδζηήξ άδεζαξ ηαηάδοζδξ απυ ηδ Λζιεκζηή Ανπή ζηδκ επαββεθιαηζηή ηαηάδοζδ, δ απμοζία ηδξ μπμίαξ, ηαεζζηά πανάκμιδ ηδκ αοηυκμιδ ηαηάδοζδ βζα επαββεθιαηζημφξ θυβμοξ. Ζ ζπμοδαζυηενδ ελέθζλδ ζημ δίηαζμ πενί ηαηαδφζεςκ επήθεε ιε ημκ οπ ανζει. 3409/2005 κυιμ (ΦΔΚ 273.4/11/2005), μ μπμίμξ ζημ άνενμ 3, μνίγεζ ημκ μνβακζζιυ πζζημπμίδζδξ αοημδοηχκ, ζοκδέμκηάξ ημκ ιε ημοξ δφηεξ ακαροπήξ ηαζ ηδκ ακηίζημζπδ εηπαίδεοζδ ηδκ μπμία αοημί μθείθμοκ κα θάαμοκ, πνζκ πζζημπμζδεμφκ. Με ιία δζαζηαθηζηή ενιδκεία ημο πανυκημξ κμιμεεηήιαημξ ηαζ εθθείρεζ εζδζηήξ κμιμεεζίαξ βζα ηδκ επζζηδιμκζηή ηαηάδοζδ, δφκαηαζ μ επζζηήιςκ δφηδξ κα οπαπεεί ζηδκ ηαηδβμνία ημο πνμξ ακαροπή δφηδ, ηαεχξ αοηυξ ζίβμονα δεκ πναβιαημπμζεί ηζξ ενβαζίεξ υπςξ απανζειμφκηαζ ζηδκ οπ ανζει /20/95 (ΦΔΚ 978/1995) Τπμονβζηή απυθαζδ. Χζηυζμ, ιία ηέημζα ενιδκεία είκαζ πζεακυ κα ηαηαζηναηδβήζεζ ημκ επζδζςηυιεκμ ζημπυ ημο εκ θυβς κυιμο, μ μπμίμξ ίζςξ ακηζιεηχπζγε κμιζηά δζαθμνεηζηά ημκ επζζηήιμκα δφηδ ζε ζπέζδ ιε ημκ δφηδ πνμξ ακαροπή. φιθςκα θμζπυκ ιε ημκ εκ θυβς κυιμ, αηυια ηαζ ακ εεςνδεεί αιθζζαδημφιεκδ δ ελ επαβςβήξ οπαβςβή ημο επζζηήιμκα δφηδ ζηδκ ηαηδβμνία ημο δφηδ ακαροπήξ, εεςνείηαζ αέααζδ δ ακάθμβδ εθανιμβή ζηδκ επζζηδιμκζηή ηαηάδοζδ ημο άνενμο 11 1 ημο εκ θυβς κυιμο, ημ μπμίμ απαβμνεφεζ ηζξ ηαηαδφζεζξ πάνζκ ακαροπήξ ιε ακαπκεοζηζηέξ ζοζηεοέξ ή άθθα οπμεαθάζζζα ιέζα α) ζε πνμζδζμνζζιέκεξ απυ ηζξ ανιυδζεξ οπδνεζίεξ ημο Τπμονβείμο πμθζηζζιμφ εαθάζζζεξ πενζμπέξ εκαθίςκ ανπαζμθμβζηχκ πχνςκ ζφιθςκα ιε ηα μνζγυιεκα ζηα άνενα 12 ηαζ 15 ημο κ. 3028/2002 ηαζ α) ζε ζοβηεηνζιέκα μζημθμβζηά εοαίζεδηα εαθάζζζα μζημζοζηήιαηα ζφιθςκα ιε ημοξ κυιμοξ 1650/1986, 3044/2002 ηαζ ηδκ Κ.Τ.Α /3028/1998. πςξ πνμηφπηεζ απυ ηδκ ανίειδζδ υθςκ ηςκ πενζπηχζεςκ απαβυνεοζδξ ηαηάδοζδξ πνμξ ακαροπή, αοηή επζαάθθεηαζ θυβς δζαζθάθζζδξ ζοθθμβζηχκ (πενζαάθθμκ, ανπαζμθμβζηή αλία) ή αημιζηχκ (αζθάθεζα) εκκυιςκ αβαεχκ, ηα μπμία είκαζ πζεακυκ κα εζπημφκ ηαηά ηδ δζαδζηαζία ηδξ οπμανφπζαξ ημθφιαδζδξ. Πνυηεζηαζ θμζπυκ βζα έκκμια αβαεά ηςκ μπμίςκ δ ζπμοδαζυηδηα είκαζ ανηεηή χζηε κα πενζμνίζεζ ημ κμιζηά ηαημπονςιέκμ δζηαίςια ηδξ αοηυκμιδξ ηαηάδοζδξ ηαζ δδ αοηήξ πνμξ ακαροπή. Ακαθμβζηά, εα ιπμνμφζε ηάπμζμξ κα επζηαθεζηεί υηζ ημ ίδζμ ζζπφεζ ηαζ βζα ηδκ επζζηδιμκζηή ηαηάδοζδ, δ μπμία δε εα ιπμνμφζε κα ηαηζζπφζεζ ηςκ εκκυιςκ δζηαζςιάηςκ ή αβαεχκ πμο πνμζηαηεφμκηαζ ιε ηζξ δζαηάλεζξ πενί ελαζνέζεςξ ηδξ ηαηάδοζδξ πνμξ ακαροπή ζε υθδ ηδκ επζηνάηεζα. Χζηυζμ, ζηδκ πενίπηςζδ αοηή, έπμοιε ηδκ ελήξ παναδμλυηδηα, άιεζα ζοκδεδειέκδ ιε ηδκ επζζηδιμκζηή ηαηάδοζδ, δ μπμία δζαθμνμπμζείηαζ ςξ πνμξ ημ ηίκδηνμ ημο δφηδ απυ ηδκ ηαηάδοζδ πνμξ ακαροπή: δ επζζηδιμκζηή ηαηάδοζδ ζοκδέεηαζ ζοπκά ιε πχνμοξ βζα ημοξ μπμίμοξ πνμαθέπεηαζ απαβυνεοζδ ηαηάδοζδξ ηαηά ημ άνενμ 11 ημο κ. 3409/2005. Καζ ζε αοηήκ ηδκ πενίπηςζδ, απμδεζηκφεηαζ πενίηνακα ημ κμιζηυ ηεκυ ζηδκ ακηζιεηχπζζδ ημο επζζηήιμκα δφηδ, μ μπμίμξ ειπμδίγεηαζ ζηδκ μθμηθήνςζδ ηδξ ένεοκαξ ημο υζμ ημ πεδίμ ένεοκάξ ημο είκαζ απνμζπέθαζημ ζε επίπεδμ πνμζέββζζδξ, δδθαδή ημο απαβμνεφεηαζ κα ηαηαδοεεί ζε εηείκμκ ημ πχνμ. Δλαίνεζδ ζηδκ ςξ άκς πνμαθδιαηζηή νφειζζδ, απμηεθεί ημ άνενμ 16 ημο ίδζμο κυιμο, υπμο ακαθένεηαζ ζηζξ ενεοκδηζηέξ ηαηαδφζεζξ ςξ ελαζνεηέεξ ημο πανυκημξ κυιμο, εθυζμκ αοηέξ πναβιαημπμζμφκηαζ απυ ημ Δθθδκζηυ Κέκηνμ Θαθαζζίςκ Δνεοκχκ (ΔΛ. ΚΔ. Θ. Δ.). Αοηή είκαζ ιία απυ ηζξ δφμ πενζπηχζεζξ νφειζζδξ επζζηδιμκζηήξ ή ηαθφηενα ενεοκδηζηήξ ηαηάδοζδξ, μζ μπμίεξ νοειίγμκηαζ ιε ζαθήκεζα απυ ημκ κυιμ, ηαεχξ ζδζαίηενμ εκδζαθένμκ έπεζ ηαζ δ δεφηενδ νφειζζδ ημο άνενμο 13 πενί «Πεξηνρώλ Οξγαλσκέλεο Αλάπηπμεο Καηαδπηηθνύ Πάξθνπ», ζηζξ μπμίεξ είκαζ δοκαηή δ ηαηάδοζδ βζα επζζηδιμκζηή ένεοκα, πςνίξ υιςξ κα μνίγεηαζ πμζμξ κμιζιμπμζείηαζ κα πναβιαημπμζεί ηδκ ένεοκα. Γοζηοπχξ, παναηδνείηαζ ηαζ εδχ δ αζοκέπεζα ημο κμιμεέηδ ηαεχξ εκχ πνμαθέπεηαζ δ δοκαηυηδηα έζης ηαζ ιενζηήξ πςνζηά επζζηδιμκζηήξ ένεοκαξ, πενζμνζζιέκδξ ιυκμ ζε γχκεξ Π. Ο. Α. Κ. Π., δεκ οπάνπεζ ηαιία πνυαθερδ βζα ημ οπμηείιεκμ πμο εα ιπμνμφζε κα πναβιαημπμζήζεζ ηδκ επζζηδιμκζηή ένεοκα. Σέθμξ, εκδζαθένμκ πανμοζζάγεζ δ ηαη'άνενμκ 9 2 πνυαθερδ βζα πμνήβδζδ πηοπίμο ηαηάδοζδξ εναζζηεπκχκ ηαηαδοηχκ, αθθά ζημ ααειυ πμο αοηυ πμνδβείηαζ ζφιθςκα ιε ηα Δεκζηά Πνυηοπα Καηαδφζεςκ Ακαροπήξ (Δ. Π. Κ. Α.) ηαζ ημ ζφκμθμ ηςκ κμιμεεηδιάηςκ αθμνά ζηζξ ηαηαδφζεζξ ακαροπήξ, είκαζ άζημπμ ηαζ κμιζηά έςθμ κα πνμζπαεήζεζ ηάπμζμξ κα εκηάλεζ ημκ επζζηήιμκα δφηδ ζε αοηή ηδ δζαδζηαζία απυηηδζδξ πηοπίμο ηαηάδοζδξ. Μάθθμκ, μ επζζηήιςκ ηαηαδφηδξ εκηάζζεηαζ υπςξ πνμακαθένεδηε ζημκ εναζζηέπκδ πηοπζμφπμ ηαηαδφηδ υπςξ μνίγεηαζ ιε ηδκ οπ'ανζει /9/1994 Τπμονβζηή απυθαζδ ημο Τπμονβμφ Διπμνζηή Ναοηζθίαξ (ΦΔΚ 858/1994). 314

315 3.2. Δπξσπατθφ θαη Γηεζλέο δίθαην Δπξσπατθά δεδνκέλα θαη Γηεζλή δεδνκέλα ε επίπεδμ Δονςπασηήξ Έκςζδξ, δ επζζηδιμκζηή ηαηάδοζδ ακηζιεηςπίγεηαζ ηάεε θμνά απυ ηδκ εεκζηή κμιμεεζία ηςκ ηναηχκ - ιεθχκ, ηάεε έκα απυ ηα μπμία μνίγεζ ζηδκ εεκζηή ημο κμιμεεζία ηζξ πνμτπμεέζεζξ ηαζ ημοξ υνμοξ πναβιαημπμίδζδξ επζζηδιμκζηχκ ηαηαδφζεςκ, πςνίξ ςζηυζμ αοημί κα ηαοηίγμκηαζ ιεηαλφ ηςκ ηναηχκ - ιεθχκ. Αοηυ πναηηζηά ζδιαίκεζ υηζ, δ απυηθζζδ ζημκ μνζζιυ ηδξ επζζηδιμκζηήξ ηαηάδοζδξ απυ ηνάημξ - ιέθμξ ζε ηνάημξ - ιέθμξ δφκαηαζ κα είκαζ παμηζηή, υπςξ ζηζξ πενζπηχζεζξ ηδξ Γαθθίαξ ηαζ ηδξ Δθθάδαξ υπμο ζηδκ πνχηδ μνίγεηαζ ζαθχξ δ επζζηδιμκζηή ηαηάδοζδ ιαγί ιε ηδκ ηαηάδοζδ ηαη' επάββεθια απυ ημ δζάηαβια ιε ανζει /11 Ηακμοανίμο 2011, εκχ ημ εθθδκζηυ δίηαζμ δε ιενίικδζε έςξ ζήιενα κα εεζπίζεζ έκα ζοβηεηνζιέκμ κμιζηυ πθαίζζμ βζα ηδκ επζζηδιμκζηή ηαηάδοζδ. Λυβς ηδξ ζπμοδαζυηδηαξ υιςξ ηδξ επζζηδιμκζηήξ ηαηάδοζδξ, δ μπμία ζπεηίγεηαζ ιε ιία ζεζνά επαββεθιάηςκ ζε δζάθμνμοξ ημιείξ ένεοκαξ ηαζ ακάπηολδξ, υπςξ ηδκ ανπαζμθμβία, ηζξ θοζζηέξ επζζηήιεξ, ηζξ πενζααθθμκηζηέξ ηαζ αζμθμβζηέξ επζζηήιεξ, δ Δονςπασηή Έκςζδ δε εα ιπμνμφζε κα αβκμήζεζ ηδ ζοκδνμιή ηδξ επζζηδιμκζηήξ ηαηάδοζδξ ζημ πεδίμ ηδξ ένεοκαξ, ιε απμηέθεζια ενιδκεοηζηά κα οπαπεεί δ επζζηδιμκζηή ηαηάδοζδ ζηδκ πνμζπάεεζα ηδξ Δ.Δ. βζα ηδ δδιζμονβία εκυξ εονςπασημφ πχνμο ζημκ ημιέα ηδξ ένεοκαξ (Ακαημίκςζδ ηδξ Δπζηνμπήξ (2000) 6 ηεθζηυ ηδξ 18/1/2000). Ο πχνμξ αοηυξ εα δζεοημθφκεζ ηδ ζοκμπή ηςκ ηναηχκ - ιεθχκ ζημκ ημιέα ηδξ ένεοκαξ, ιε ακηαθθαβή πθδνμθμνζχκ ηαζ ενεοκδηχκ ιεηαλφ ηναηχκ - ιεθχκ ηαεχξ ηαζ ηδ ζφβηθζζδ ηςκ εεκζηχκ ημοξ δζηαίςκ ζημκ ημιέα ηδξ ένεοκαξ ή αηυια ηαθφηενα ηδ δδιζμονβία εκζαίμο θμνέα ένεοκαξ ζημκ εονςπασηυ πχνμ πμο εα ελαθακίζεζ πνμαθήιαηα πμο πνμηφπημοκ απυ ηδ δζαθμνεηζηή κμιμεεζία ζηα ηνάηδ ιέθδ ηαζ αθμνμφκ ζηδκ πενίπηςζή ιαξ ηαζ ηδκ ηαημπφνςζδ ηδξ επανημφξ εηπαίδεοζδξ εκυξ επζζηήιμκα δφηδ πμο πμζηίθεζ απυ πχνα ζε πχνα. Χζηυζμ 33 πχνεξ, ιεηαλφ αοηχκ ηαζ δ Δθθάδα, δεζιεφηδηακ κα δμοθέρμοκ πνμηεζιέκμο κα επζηφπμοκ ηδ δδιζμονβία εκυξ εονςπασημφ πχνμο ένεοκαξ, μ μπμίμξ πενζθαιαάκεζ ηαζ ηδκ μιμβεκμπμίδζδ ηςκ υνςκ ηαζ ηςκ ηνζηδνίςκ πναβιαημπμίδζδξ ιίαξ επζζηδιμκζηήξ ηαηάδοζδξ. Ζ ακάβηδ αοηή πενί εκυξ ημζκμφ μνζζιμφ ηδξ επζζηδιμκζηήξ ηαηάδοζδξ ζε επίπεδμ Δ.Δ. μδήβδζε ημ 2000 έκα ζχια Δονςπαίςκ ενεοκδηχκ πμο ζοκήεζγακ κα ηαηαδφμκηαζ βζα επζζηδιμκζημφξ θυβμοξ κα δχζμοκ ημκ μνζζιυ δφμ εονςπασηχκ πνμηφπςκ επζζηδιμκζηήξ ηαηάδοζδξ: α) εονςπασηυξ επζζηδιμκζηυξ δφηδξ ηαζ α) πνμπςνδιέκμξ επζζηδιμκζηυξ δφηδξ (European Scientific Diver (ESD)), and Advanced European Scientific Diver (AESD) (Sayer et al. 2008). Ζ επυιεκδ ελέθζλδ βζα ηδκ επζζηδιμκζηή ηαηάδοζδ ζε εονςπασηυ επίπεδμ ήνεε ημ 2007 ιε ηδ δδιζμονβία ηδξ Δονςπασηήξ Δπζηνμπήξ Δπζζηδιμκζηήξ Καηάδοζδξ, δ μπμία ιε έδνα ημ Bremerhaven ηδξ Γενιακίαξ έεεζε ςξ ζηυπμ ηδ αεθηίςζδ ηδξ οπμεαθάζζζαξ ένεοκαξ ζηδκ Δονχπδ, ηδκ πνμχεδζδ ηδξ αζθαθμφξ επζζηδιμκζηήξ ηαηάδοζδξ ζημκ εονςπασηυ πχνμ ηαεχξ ηαζ ηδκ εκεάννοκζδ ηδξ δζεεκμφξ ηζκδηζηυηδηαξ πνμξ ηδκ εονςπασηή ημζκυηδηα επζζηδιμκζηήξ ηαηάδοζδξ ιε ηδκ πνμχεδζδ ηςκ δφμ ςξ άκς ακαθενμιέκςκ πνμηφπςκ επζζηδιμκζηήξ ηαηάδοζδξ. ε επίπεδμ δζεεκμφξ δζηαίμο, πένακ ηδ ακμιμζμβέκεζαξ πμο μφηςξ ή άθθςξ παναηδνείηαζ ιεηαλφ ηςκ εεκζηχκ κμιμεεζζχκ ηςκ δζαθυνςκ ηναηχκ, έπμοκ οπάνλεζ πνμζπάεεζεξ απυ δζάθμνμοξ δζεεκείξ θμνείξ πνμηεζιέκμο κα ηεεμφκ ζοβηεηνζιέκα πνυηοπα, μνζζιμί ηαζ πνμτπμεέζεζξ ζημκ ημιέα ηδξ επζζηδιμκζηήξ ηαηάδοζδξ. Σμκ ζδιακηζηυηενμ νυθμ ζημ πεδίμ ηςκ ηαηαδφζεςκ ηαζ δδ ηςκ επζζηδιμκζηχκ έπεζ παίλεζ δ Παβηυζιζα οκμιμζπμκδία Τπμανφπζςκ Γναζηδνζμηήηςκ (CMAS - Confédération Mondiale des Activités Subaquatiques) δ μπμία, ζημ πθαίζζμ ηδξ αιμζααίαξ ακαβκχνζζδξ επζζηδιυκςκ δοηχκ ζε παβηυζιζμ επίπεδμ, έεεζε ηα ηνζηήνζα βζα ηδκ πζζημπμίδζδ ηεζζάνςκ ηαηδβμνζχκ επζζηδιυκςκ δοηχκ: ανπζηά ημοξ Δπζζηήιμκεξ Γφηεξ (CSD) ηαζ ημοξ Πνμπςνδιέκμοξ Δπζζηήιμκεξ Γφηεξ (CASD), μζ μπμίμζ πνμτπμεέημοκ ηάπμζμ εθάπζζημ ημζκά ακαβκςνζζιέκμ επίπεδμ εηπαίδεοζδξ, χζηε κα ιπμνμφκ κα δζαηζκμφκηαζ απυ ηνάημξ ζε ηνάημξ πςνίξ πνμαθήιαηα ακαβκχνζζδξ. Δπζπθέμκ, δ CMAS πνμαθέπεζ ηαζ δφμ αηυια ζηάδζα επζζηδιυκςκ δοηχκ αοηά ημο Δηπαζδεοηή επζζηδιμκζηήξ ηαηάδοζδξ ηαζ ημο Πζζημπμζδιέκμο Δηπαζδεοηή επζζηδιμκζηήξ ηαηάδοζδξ. Δίκαζ ζδιακηζηυ κα ζδιεζςεεί υηζ, δ επζζηδιμκζηή ηαηάδοζδ εκηάζζεηαζ ζφιθςκα ιε ηδκ CMAS ζηδκ επαββεθιαηζηή ηαηάδοζδ, βεβμκυξ πμο δεκ οζμεεηήεδηε απυ ηδκ εθθδκζηή κμιμεεζία. ηδκ ηαηάδοζδ ενβαζίαξ, ηαζ εζδζηυηενα ζηδκ επζζηδιμκζηή ηαηάδοζδ ζδζαίηενα ζδιακηζηυξ είκαζ μ νυθμξ ημο diving officer ή αθθζχξ ιε ιζα ιδ δυηζιδ ιεηάθναζδ πνυηεζηαζ βζα ημκ οπεφεοκμ ηαηαδφζεςκ. Πνυηεζηαζ βζα έκακ ζδζαίηενα ζδιακηζηυ νυθμ πμο επζαθέπεζ ηζξ ηαηαδφζεζξ (π.π. αζθάθεζα, δζελαβςβή ένβμο η.ά.) ζημ πθαίζζμ εκυξ πακεπζζηδιίμο, ενεοκδηζημφ ζηαειμφ, επζζηδιμκζημφ πνμβνάιιαημξ ή ηάπμζαξ άθθδξ δναζηδνζυηδηαξ. Ο μνζζιυξ ηαζ μ ζοβηεηνζιέκμξ νυθμξ δίκεηαζ ζηα εβπεζνίδζα ηδξ CMAS (CMAS (xi) (2000)), αθθά ηαζ ζημ εβπεζνίδζμ ηςκ Πνμηφπςκ βζα ηδκ Δπζζηδιμκζηή Καηάδοζδ, ηδξ Αιενζηακζηήξ Αηαδδιίαξ Τπμανοπίςκ Δπζζηδιχκ (American Academy of Underwater Sciences, 2013). Αλίγεζ κα οπμβναιιζζηεί υηζ, πανά ηδ ζδιακηζηυηδηα ημο νυθμο ημο επυπηδ ηαηαδφζεςκ, ηυζμ ζε πακεπζζηδιζαηέξ ζπμθέξ, υζμ ηαζ ηναηζημφξ θμνείξ ηαζ ζκζηζημφηα, δεκ οπάνπεζ εεζιμεέηδζδ ζηδκ εθθδκζηή κμιμεεζία. Ηδζαίηενμ εκδζαθένμκ πανμοζζάγεζ 315

316 υηζ, μ εεζιυξ δεκ οθίζηαηαζ ζηα μνβακμβνάιιαηα ηςκ Φμνέςκ Γζαπείνζζδξ ηςκ δφμ Δεκζηχκ Θαθάζζζςκ Πάνηςκ Εαηφκεμο ηαζ πμνάδςκ. φιθςκα ιε ημ εβπεζνίδζμ ηδξ CMAS (CMAS xi, 2000), δ επζζηδιμκζηή ηαηάδοζδ ανίζηεζ πεδία εθανιμβήξ ζε πακεπζζηήιζα, ενεοκδηζημφξ ζηαειμφξ πακεπζζηδιίςκ, ηεπκζηά ημθθέβζα, ηναηζηέξ οπδνεζίεξ ηαζ ενβαζηήνζα, κμζμημιεία, εεκζηά πάνηα ηαζ ιμοζεία, Μιδ ηενδμζημπζηέξ μνβακχζεζξ ημζκήξ ςθεθείαξ. Ζ εονεία εθανιμβή ηδξ εέζδξ ιε ηα ζοβηεηνζιέκα πνμζυκηα, ηαεζζηά επζηαηηζηή ηδ εεζιμεέηδζδ ημο νυθμο ημο δφηδ επυπηδ (diving officer), εζδζηυηενα υηακ θεζημονβμφκ ηαηαδοηζηέξ μιάδεξ ηάης απυ ημ πθαίζζμ πακεπζζηδιζαηχκ ζδνοιάηςκ ή ζκζηζημφηςκ. Δηηυξ υιςξ απυ ηδκ επζζηδιμκζηή ηαηάδοζδ ζε επαββεθιαηζηυ επίπεδμ, οπάνπεζ ηαζ ιία άθθδ πνμζέββζζδ ηδξ επζζηδιμκζηήξ ηαηάδοζδξ, αοηήξ ζε εναζζηεπκζηυ επίπεδμ. Ζ ζδιακηζηυηενδ δνάζδ ςξ πνμξ αοηυ ημ επίπεδμ έπεζ βίκεζ απυ ηδκ CMAS, δ μπμία έπεζ πενζθάαεζ ιζα ζεζνά ηαηαδοηζηχκ εζδζημηήηςκ βζα ημοξ εναζζηέπκεξ δφηεξ, υπςξ αοηέξ πανμοζζάγμκηαζ ζημ ηεπκζηυ εβπεζνίδζμ Nonprofessional CMAS Scientific Specialty Courses (SSC). Ζ αοηυκμιδ ηαηάδοζδ ακαροπήξ απμηεθεί έκακ ζδιακηζηυ άλμκα δνάζδξ ζημοξ ημιείξ ηδξ πενζααθθμκηζηήξ εοαζζεδημπμίδζδξ ηαζ εηπαίδεοζδξ. Πανάθθδθα υιςξ, εα ιπμνμφζε κα απμηεθέζεζ ηαζ έκα πμθφ ζδιακηζηυ ιέζμ ζηδκ οπδνεζία ηδξ εηθαΐηεοζδξ ηδξ επζζηήιδξ ηαζ ζηδ δζάδμζδ ηδξ επζζηδιμκζηήξ βκχζδξ. Κάης απυ αοηυ ημ πνίζια, μ ηαηαδοηζηυξ μνβακζζιυξ CMAS (απυ ηα πνχηα ηαηαδοηζηά υνβακα) πνμζθένεζ έκα ζδιακηζηυ ηαηαδοηζηυ πνυβναιια εηπαίδεοζδξ ζφιθςκα ιε ημοξ παναηάης άλμκεξ (2014): Underwater Geology Course (UGC) (CMAS(ii) 2014), Underwater Archaeology Course (UAC),(CMAS(iii) 2014), Ocean Discover Course (ODC) (CMAS(iv) 2014), Marine Biology Course (MBC) (CMAS(v) 2014), Freshwater Biology Course (FBC) (CMAS(vi) 2014), Advanced Underwater Geology Course (AUGC) (CMAS(vii) 2014), Advanced Underwater Archaeology Course (AUAC) (CMAS(viii) 2014), Advanced Marine Biology Course (AMBC) (CMAS(ix) 2014), Advanced Freshwater Biology Course (AFBC) (CMAS(x) 2014). Ζ δζαδζηαζίαξ ηδξ εηπαίδεοζδξ εναζζηεπκχκ δοηχκ ζε ενεοκδηζηά πεδία, υπςξ ηα παναπάκς, πανμοζζάγεζ ζδζαίηενμ εκδζαθένμκ, αθμφ εηηυξ ημο υηζ δ ζοβηεηνζιέκδ μιάδα δοηχκ θαιαάκεζ εηθασηεοιέκδ επζζηδιμκζηή βκχζδ, εα ιπμνμφζε κα θεζημονβήζεζ ηαζ επζημονζηά ζε ενεοκδηζηά επζζηδιμκζηά πνμβνάιιαηα ΓΔΝΗΚΑ ΤΜΠΔΡΑΜΑ Πνμηφπηεζ, θμζπυκ, ιε ζαθήκεζα υηζ δ εθθδκζηή κμιζηή πναβιαηζηυηδηα ιμζάγεζ κα ιδκ ακαβκςνίγεζ ζπεδυκ ηαευθμο ηδ δοκαηυηδηα ηδξ επζζηδιμκζηήξ ηαηάδοζδξ, αθμφ ιε εθάπζζηεξ ελαζνέζεζξ, δεκ έπεζ κα επζδείλεζ έκα άνηζμ ηαζ μθμηθδνςιέκμ κμιμεέηδια, ζηακυ κα απαθθάλεζ υζμοξ πναβιαημπμζμφκ επζζηδιμκζηέξ ηαηαδφζεζξ ζηα κενά ηδξ πχναξ ιαξ απυ ημκ ηίκδοκμ ηδξ ζφθθδρδξ ηαζ ηςκ εκ βέκεζ πμζκζηχκ ηαζ δζμζηδηζηχκ ηονχζεςκ. Ζ εθθδκζηή πμθζηεία ηαζ δδ μ Έθθδκαξ κμιμεέηδξ μθείθμοκ κα εκανιμκζζημφκ ιε ηα πνμπςνδιέκα εονςπασηά δεδμιέκα, πνμηεζιέκμο κα δζεοημθοκεεί δ ιεηαθμνά ηςκ εονςπασηχκ πνμηφπςκ ζηδκ εθθδκζηή πναβιαηζηυηδηα ηαζ κα μνζζημφκ ιε ζαθήκεζα μζ πνμτπμεέζεζξ ηεηιδνίςζδξ ηαζ ακαβκχνζζδξ ηδξ επζζηδιμκζηήξ ηαηάδοζδξ, ιε ζημπυ ηδκ αζθάθεζα ηυζμ ηςκ ίδζςκ ηςκ δοηχκ υζμ ηαζ ηςκ παναβυιεκςκ επζζηδιμκζηχκ δεδμιέκςκ απυ αοημφξ. Βηβιηνγξαθία ΦΔΚ 858α /1994. Γεκζηυξ Κακμκζζιυξ Λζιέκα, αν. 5. ζεθ Δεκζηυ Σοπμβναθείμ. ΦΔΚ 978α'/1995. Γεκζηυ Κακμκζζιυ Λζιέκα, αν. 10. ζεθ Δεκζηυ Σοπμβναθείμ. ΦΔΚ 273α'/2005. Νυιμξ 3409: Καηαδφζεζξ ακαροπήξ ηαζ άθθεξ δζαηάλεζξ. ζεθ Δεκζηυ Σοπμβναθείμ. ΦΔΚ 449α /2006. Τπμονβζηή απυθαζδ Τπμονβείμο Ναοηζθίαξ, Καεμνζζιυξ υνςκ ηαζ πνμτπμεέζεςκ βζα ηδκ έηδμζδ Άδεζαξ Πανμπέα Καηαδοηζηχκ Τπδνεζζχκ Ακαροπήξ δζαδζηαζίεξ εθέβπμο απαβμνεφζεζξ άζηδζδξ ηδξ δναζηδνζυηδηαξ. ζεθ American Academy of Underwater Sciences (2013). Standards for Scientific Diving. pp CMAS(i), Scientific Committee (2014). Non-professional CMAS Scientific Specialty Courses (SSC), Administrative text. pp CMAS(ii), Scientific Committee (2014). Underwater Geology Course (UGC). pp CMAS(iii), Scientific Committee (2014). Underwater Archaeology Course (UAC). pp CMAS(iv), Scientific Committee (2014). Ocean Discover Course (ODC). pp CMAS(v), Scientific Committee (2014). Marine Biology Course (MBC). pp CMAS(vi), Scientific Committee (2014). Freshwater Biology Course (FBC). pp CMAS(vii), Scientific Committee (2014). Advanced Underwater Geology Course (AUGC). pp CMAS(viii), Scientific Committee (2014). Advanced Underwater Archaeology Course (AUAC). pp CMAS(ix), Scientific Committee (2014). Advanced Marine Biology Course (AMBC). pp CMAS(x), Scientific Committee (2014). Advanced Freshwater Biology Course (AFBC). pp

317 CMAS (xi) (2000), Scientific Diver, Advanced Scientific Diver, Scientific Diving Instructor, Scientific Diving Confirmed Instructor, Editor: Dr Alain Norro CMAS CS secretary, pp Sayer M.D.J., Fischer P., Feral J.P. (2008). Scientific Diving in Europe: Integration, Representation and Promotion In: Brueggeman P, Pollock NW, eds. Diving for Science 2008.Proceedings of the American Academy of Underwater Sciences 27th Symposium. Dauphin Island, AL: AAUS; pp

318 FRESHWATER HABITATS AND FISHING ACTIVITIES IN THE BURIGANGA RIVER, DHAKA, BANGLADESH Md. Muzammel Hossain¹*, Mohammad Abdul Baki¹ ¹Department of Zoology, Jagannath University, Dhaka-1100, Bangladesh. Abstract The Buriganga River has served as the central artery to economic life in Dhaka city for centuries. But Buriganga River is the most polluted river in Bangladesh. During the study period (December 2012 to November 2013), we directly observed freshwater habitats and fishing activities by boat-base survey from china-bangladesh Friendship Bridge ( '' E and ''N) to Amin bazar Bridge ( ''E and ''N) in the Buriganga River. Freshwater habitats were observed at babu bazar, kamrangichar, kholamora ghat and shadar ghat throughout the year in the River. Different types of fishes, fishing gears and crafts were observed and fish samples were collected directly from fishermen during fishing time to confirm identification. A total of 32 species were recorded from three gears in the river. Maximum numbers of plastic jar, Current Jal (gill net) and Veshal Jal (lift net) were operated in October and August 2013 in the river. Different ages of men, women, and children were fishing within flood vegetation by different sizes of plastic jars and small nets where maximum numbers of Heteropneustes fossilis, Mastacembelus armatus, Mastacembelus pancalus, Colisa fasciata and Glossogobius giuris were recorded at Kamrangichar in the river. Water transparency level was high in July 2013 in the Buriganga River. Key words: Freshwater, Fishing activities, Fish, Gear, Buriganga River. *Corresponding author: Md.Muzammel Hossain (muzammel3@gmail.com) 1. Introduction Bangladesh is known to be a riverine country with more than 700 rivers, most of which are fed by the Ganges and Brahmaputra rivers that shapes the biodiversity within the country (Banglapedia 2004) and Freshwater biodiversity is a major contributor to the economy through is provision to many ecosystem goods and services. Fresh air, clean water, nutrients for plant and animal growth and crop pollination are just some of the ecosystem services that nature provides. Dissolved oxygen is obviously essential for the metabolism of all aquatic organisms that possess aerobic respiratory biochemistry (Wetzel 1975, Trivedy 1988). Buriganga fishes and freshwater habitat can be occupying significant position in the socio-economic of Dhaka cities by providing the population not only the nutrition but also income and employment opportunities with healthy environment. Arguably, fishes form the most important wetland product at a global scale, and are often referred to as a rich food for poor people (WorldFish Center 2005). A number of studies indicated that the major causes of declining fish catch from floodplains are the increased fishing pressure and habitat destruction (Siddique, 1990; Hoggarth et al., 1999; Tsai and Ali, 1987; de Graff et al., 2001). Due to irrational fishing practices, environmental aberrations like reduction in water volume, increased sedimentation, water abstraction, and pollution over the years this diversity is on a decline and few species have been lost from the freshwater ecosystem of river Buriganga. As a consequence, they are often used as bio indicator for the assessment of water quality, river network connectivity or flow regime (Chovance et al. 2003). Today the fish diversity and associated habitats management is a great challenge (Dudgeon et al. 2006). The river is a fresh water habitat and is located in the humid tropical region with seasonal variation in temperature and rainfall patterns. About 94% of all freshwater fisheries occur in developing countries (FAO, 2007). It was estimated that the global values of ecosystem goods (e.g. fish as food and fresh water to drink), ecosystem regulation (e.g. creation of climate and rain through the hydrological cycle), ecosystem support (e.g. nutrient recycling), and cultural considerations (e.g. recreation), yields a value measured in trillions of dollars (Reid et al., 2013). Today, fishing remains the largest extractive use of wildlife in the world. In 2010, the annual capture, combining both wild capture and aquaculture, was 149 million tonnes (FAO, 2012).Human activities and annual environmental effects e.g. dry season and damping continue to cause considerable damage to the natural production of freshwater ecosystem. The Buriganga River is an important part of Dhaka City s urban landscape, ecology, and economy. Early settlements developed, concentrating on the riverbank; it had been sources of domestic water supply, groundwater recharge and recreation and fishing sites, and served as major transportation route and flood control and drainage outlet. It has also been used for agricultural, sanitary, and industrial purposes. According to Dhaka WASA experts, 60% of the 318

319 city s sewerage is dumped into the river. Urban/township storm run-off carries various pollutants washed off from the streets, roof-tops various types of land covers directly into the river water which are being threatening the natural aquatic environment (Rahman & Chowdhury 1999).However, Fishes from Buriganga are going to be extinct due to water pollution. Finally, it is intended that this paper serve as a baseline for studying future changes of the fish faunal composition in the area. 2. Material and Methods Study area: Buriganga River is located the south-western periphery of Dhaka City which is most polluted river in the world. The study area was started from china-bangladesh Friendship Bridge ( '' E and ''N) to Amin bazar Bridge ( ''E and ''N) in the River. Sampling period & tools: The studies were carried out from the December 2012 to November 2013 in Buriganga River. Sampling were done two days per month with the help of traditional fishing gears Plastic Jars, lift nets and gill nets locally known as Plastic bati, Veshal Jal and Current Jal. Active gears and water transparency level were used as measurement tools. Study was usually made between mornings to afternoon by boat base survey. Observation & Identification: The fish species were identified up to species level following the standard procedures lain in the literature. Also habitat identified on seasonal base. Habitats, fish and fishing gears were directly observed by boat, randomly counted active fishing gears throughout the year and fish samples were collected from fisherman during fishing time to confirm identification. A rope attached with sacchidise was sent to the water until it was just disappeared under water, and at that time the value of the length of the rope was taken to measure the transparency. 3. Results During the study period we have found polluted water, freshwater habitats on seasonal base and fishing activities from china-bangladesh Friendship Bridge to Aminbazar Bridge in the Buriganga River. Especially four month (August to November 2013) maximum fishing effort and freshwater habitats were observed at babu bazar, kamrangichar, kholamora ghat in the Buriganga River. A total of 32 species were recorded from three gears (Table 1) within 56 species of inventory study in the Buriganga River and heavy blackish or dark black habitat directly observed with minimum number of fishes in the month of February, March, April and May. Maximum water transparencies (figure 1) were recorded in July 2013 and minimum in April & May 2013 which was indicated quality of habitat in the Buriganga River. 319

320 Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec Number of plastic jar water transparency level (inch) HydroMedit 2014, November 13-15, Volos, Greece transparency 5 0 Time Figure 1. Habitat observetion during study period in the Buriganga River Plastic jar Time Figure 2. Fishing effort with plastic jar in bank of the Buriganga River 320

321 Number of gear Number of gear HydroMedit 2014, November 13-15, Volos, Greece Veshal Jal Time Figure 3. Fishing effort with Veshal Jal in the Buriganga River Current Jal Time Figure 4. Fishing effort with Current Jal in the Buriganga River Family Species Name Local Name V C P Habitat Abundance Notopteridae Notopterus notopterus Foli y FW + Cyprinidae Puntius sophore Punti y y y FW ++++ Cyprinidae Puntius ticto Tit Punti y y FW ++ Cyprinidae Puntius chola Punti/ Chalapunti y y FW +++ Cyprinidae Puntius conchonius Taka Punti y y FW + Cyprinidae Labeo rohita Rui/ Rohit y y y FW ++++ Cyprinidae Amblypharyngodon mola Mola y FW + Cyprinidae Labeo calbasu Kalibaus y y FW ++ Cyprinidae Labeo gonius Goni/Ghainna y FW + Cyprinidae Catla catla Catla y y FW ++ Cyprinidae Cirrhinus cirrhosus Mirka y FW ++ Cyprinidae Hypophthalmichthys molitrix Silver Carp y FW + Cyprinidae Cirrhinus reba Tatkini/Bata y y FW ++ Anabantidae Anabas testudineus Koi/Corvu y FW + Siluridae Wallago attu Boal y FW + Gobidae Glossogobius giuris Bele/Bailla y y y FW ++++ Ambassidae Pseudambassis baculis Chanda y FW + Osphronemidae Colisa fasciata Khalisha y y y PW, FW +++ Osphronemidae Colisa lalia Lal Khalisha y FW + Osphronemidae Ctenops nobilis Napit Khailsha y y PW, FW ++++ Bagridae Mystus tengara Bujuri y y y PW, FW ++ Channidae Channa punctatus Taki/Lati y y y PW, FW ++++ Channidae Channa striatus Shol/ Shoul y FW ++ Clupeidae Gudusia chapra Chapila y y FW +++ Clupeidae Tenualosa ilisha Ilish/Ilsha y FW + 321

322 Mastacembelidae Mastacembelus armatus Sal Baim y y y FW +++ Mastacembelidae Mastacembelus pancalus Guchi Baim y y y FW ++++ Mastacembelidae Macrognathus aculeatus Tara Baim y y FW +++ Heteropneustidae Heteropneustes fossilis Shing/Shingi y y PW, FW ++++ Cobitidae Botia dario Rani y FW + Cobitidae Botia lohachata Rani y FW + Cobitidae Lepidocephalichthys guntea Gutum y FW + Different ages of man, women, children had been fishing within flood vegetation by different size of plastic jar, small net at kamrangichar in the river buriganga. At Kamrangichar, 20 to 30 persons together were fishing in a habitat having length of 20ft to 30ft at the bank of the river. Maximum numbers of Channa punctatus, Mastacembelus pancalus, Mastacembelus armatus, Colisa fasciata, Heteropneustes fossilis and Glossogobius giuris were recorded by different size of plastic jar, small net at kamrangichar in bank of the river. Maximum numbers of plastic jar (figure 2) have operated for fishing in the river in October Also observed different types of fishing gear have operated in the river such as Cast Net, Lift Net, Current Net, Seine Net, Boat lift net with engine, Fixed beg net and Push Net. Maximum numbers of Veshal Jal (lift net) (figure 3) were observed in August when water transparency was high in the river. Maximum numbers of current jal (gill net) (figure 4) were observed in October during fishing activities in the river. Channa punctatus, Colisa fasciata, Ctenops nobilis, Mystus tengara, Heteropneustes fossilis were found in both habitat in the river. Table 1. List of recorded fishes of three gears in the Buriganga River, Dhaka Note: FW= Freshwater; PW= Polluted water; + = Less, ++= Much, +++ = Very Much, ++++= More. y= Present, V= Veshal Jal, C= Current Jal, P = Plastic jar. 4. Discussion Open river habitats were the most preferred habitat for fishes inhabited in the tropical rivers (Sarkar et al. 2010; Lobb and Orth 1991; Aadland 1993; Arunachalam 2000). Fish communities in riverine ecosystem typically follow a pattern of increasing species richness, diversity and abundance from upstream to downstream (Welcomme, 1985, Bayley and Li, 1994, Granado, 2000). We can observe maximum 46% fish species diversity in the lift net (Veshal Jal) and minimum 19% in the plastic Jar during fishing time in river (figure 5). Colisa fasciata, Ctenops nobilis, Mystus tengara, Channa punctatus and Heteropneustes fossilis were found in both habitats. Abundance were more of Labeo rohita, Glossogobius giuris, Ctenops nobilis, Channa punctatus, Mastacembelus pancalus and Puntius sophore in the Veshal Jal. Furthermore, total 32 fish population were recorded from three gears the Buriganga River during study period but habitat has threatened due to several reasons including habitat loss, siltation in river basins, over-exploitation and indiscriminate killing of juvenile fish as a result of unregulated fishing pressure, water pollution caused by industrial and domestic wastes, and destruction of breeding and nursery grounds because of flood control. Aquarium fishes of Botia Dario, Botia lohachata were found in the Buriganga River which is economically important in fisheries sector. We can observe low species richness at shadarghat site in the Buriganga River due to water pollution. Climate change also poses threats to freshwater species and habitats. Labeo rohita, Puntius sophore, Glossogobius giuris, Colisa fasciata, Mystus tengara, Channa punctatus, Mastacembelus armatus, Mastacembelus pancalus were found in three gears of during fishing time in the river. 19% 35% 46% Veshal Jal Current Jal Plastic Jar Figure 5. Percentages of species diversity under three gears in the Buriganga River Sreekantha and Ramachandra (2005) recorded the low fish richness due to degradation of breeding ground from Linganamakk reservoir on Sharavathi River, India. According to Bunn and Arthington (2002) many types of river ecosystem have been lost and populations of many riverine species have 322

323 become highly fragmented due to human intervention. In Bangladesh, Indonesia and the Philippines freshwater fishes comprise 50% of animal protein intake, while in Thailand and Vietnam its share is 40%. It is the major and often the only source of animal protein for low income families (Briones et al., 2004). But the main threats to freshwater habitat degradation in the Buriganga River caused by infrastructure development and land conversion, water pollution, flow modification, overharvesting and overexploitation. Figure 6. Polluted water habitat at kamrangichar and shadarghat in the Buriganga River in the Dry Season Figure 7. Freshwater habitat with fishing activities at kamrangichar in the Buriganga River in the Rainy Season. Poor people and professional fisherman are engaged in part-time and full time fishing in monsoon period due to moderately improved water quality but reduced water flow in the river has resulted in a severe depletion of fisheries and also loss of healthy environment and aquatic resources. Most examples the fish diversity and habitats in the Buriganga River is getting threatened by water habitat loss. Ecological changes to the fish habitat indicating the need of immediate comprehensive studies regarding to the biology of fish, aquatic habitat, protection of aquatic ecosystems and conservation of fish species. Acknowledgements The author extends his thanks to the many fisherman and local people in the survey area for their sincere cooperation. This research work was funded by Jagannath University Grant for Research Work The authors would like to thank all the students of the Department of Zoology, Jagannath University, Dhaka who helped during the field survey. Reference Aadland LP (1993) Stream habitat types: their fish assemblages and relationship to flow. North Am J Fish Manag 13: Arunachalam M (2000) Assemblage structure of stream fishes in the Western Ghats (India). Hydrobiologia 430:1 31 Banglapedia. (2004). National Encyclopedia of Bangladesh, Asiatic Society of Bangladesh, 1st edn. February Dhaka, Bangladesh. Available from URL: Bayley P, Li H (1994) Riverine fisheries. In: Calow P, Petts GE (eds) The river handbook: hydrological and ecological principles. Blackwell, Boston, pp Bunn SE, Arthington AH (2002) Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environ Manag 30: Briones M., Dey M.M. and Ahmed, M The future for fish in the food and livelihoods of the poor in Asia. WorldFish Center Quarterly. 27(3-4):

324 Chovance A, Hoffer R, Schiemer F (2003) Fish as bioindicators. In:Market BA, Breure AM, Zechmeiser HG (eds) Bioindicatos and biomonitors, pp Dudgeon, D., Arthington, A.H., Gessner, M.O., Kawabata, Z., Knowler, D., Lévêque, C., Naiman, R.J., Prieur-Richard, A.-H., Soto, D., Stiassny, M.L.J. and Sullivan, C.A. (2006). Freshwater biodiversity: importance, threats, status and conservation challenges. Biological Reviews 81: de Graff, G.J., Born, A.F., Uddin, A.K.M. and Martin, F., (2001). Floods, fish and fishermen. Eight years experience with floodplain fisheries in Bangladsh. University Press Ltd., Dhaka, 174 pp. FAO. (2007). The state of world Aquaculture and Fisheries Food and Agriculture Organization of the United Nations. Fisheries and Aquaculture Department. Rome, Italy. FAO. (2012). The State of World Fisheries and Aquaculture Food and Agriculture Organization of the United Nations. Fisheries and Aquaculture Department. Rome, Italy. Granado C (2000) Ecologa de communidades el paradigma de los pecces de agua dulce. Universidad de Sevilla Secretariado de Publicaciones, Sevilla Hoggarth, D.D., Cowan, V.J., Halls, A.S., Aeron-Thomas, M.A., McGregor, J.A., Garaway, C.A., Payne, A.I. and Welcomme, R.L. (1999). Management guidelines for Asian floodplain river fisheries, FAO Fisheries Technical Paper 384/2, Rome, 117 pp. Lobb MD, Orth DJ (1991) Habitat use by an assemblage of fish in a large warm water stream. Trans Am Fish Soc 120: Rahman, M.M. and Chowdhury, M.B.R Isolation of bacterial pathogen causing on ulcer disease in farmed carp fishes of Mymensingh. Bangladesh. J. Fish., 19: Reid, G. McG., Contreras MacBeath, T. and Csatadi, K Global challenges in freshwater fish conservation related to public aquariums and the aquarium industry. International Zoo Yearbook 47 (1): Sarkar UK, Gupta BK, Lakra WS (2010) Biodiversity, ecohydrology, threat status and conservation priority of freshwater fishes of River Gomti, a tributary of River Ganga (India). Environmen-talist 30:3 17 Sreekantha KV, Ramachandra TV (2005) Fish diversity in Linganamakki Reservoir, Sharavathi River. Ecol Environ Conserv 11: Siddiqui, H.M., (1990). Flood control and drainage development: Physical environmental issues. In: A.A. Rahman, S. Huq and G.R. Conway (Eds.), Environmental aspects of surface water systems of Bangladesh. Dhaka University Press Ltd., Dhaka: Trivedy, R.K. (1988). Studies on the biological characteristics of the river Krishna in Maharashtra with reference to human activity and population. Technical reports submitted to Dept. of Environment, Ministry of Environment, Forest and Wildlife, New Delhi. Tsai, C. & Ali, L. (1987). The Changes in Fish Community and Major Carp Population in Beels in the Sylhet-Mymensingh Basin, Bangladesh. Indian Journal of Fisheries, 34(1), Welcomme RL (1985) River fisheries. FAO Fish Tech Pap 262:1 318 Wetzel, R.G., (1975). Limnology, W.B. Saunders Company, Philadelphia, USA PP.743. WorldFish Center. (2005). Fish and Food Security in Africa. The WorldFish Center, Penang, Malaysia 324

325 ANALYSIS OF VISITORS WILLINGNESS TO PAY CONCERNING A COASTAL RECREATIONAL SITE IN CENTRAL GREECE Ekonomou G. 1*, Neofitou C. 1, Matsiori S. 1 1 Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Fytokou St., Nea Ionia, 38446, Prefecture of Magnisia, Volos, Greece. ABSTRACT Coastal sites and marine environments are considered popular natural settings for developing tourism policies. Recreational beach sites play an essential role for human s well being. The purpose of this study was to define variables that significantly affect visitors willingness-to-pay concerning improvements in the provision of nature-based tourism policies and products. The contingent valuation method was applied on a hypothetical market scenario. The empirical results showed that visitors willingness-to-pay is positively influenced by income, education level, overall satisfaction gained. In addition, respondents willingness-to-pay disposition was found to be negatively affected by overcrowded and not organized beach sites. The research findings have management implications so as to advance thorough management plans in view of enhancing sustainable resource allocation practices and fostering preferred destination places that meet consumer needs and wants. Keywords: needs, wants, management, quality *Corresponding author: Ekonomou George (oikongeorge@gmail.com) 1. Introduction Tourism is a rapid growing industry which directly incorporates human beings, natural resources, marketing and management approaches as well as environmental ethics and economy theory (supply and demand). By its definition coastal tourism is based on a unique resource combination at the interface of land and sea offering diverse amenities while it includes a wide range of activities that take place in coastal waters and zones (UNEP, 2009). Supportively, effective environmental coastal management ought to consider tourism development as an integral part of the whole process. It is widely known that coastal areas represent natural settings that attract many visitors with different needs wants and expectations. The benefits obtained from these areas are still underestimated because of the difficulty in expressing the importance of their ecological functions in monetary terms (Brenner et al. 2010). In the same wavelength, sustainable management strategies for coastal tourism and recreation are based on a thorough assessment of their value within the relevant policy context (Ghermandi & Nunes, 2013). Environmental valuation studies offer information which policy makers and managers require to manage the coastal environment (Beharry-Borg & Scarpa 2010). As the field of coastal tourism continues to develop, the need for identifying factors that affect visitors Willingness to Pay (WTP) when visiting a destination remains a crucial issue in meeting their demands and satisfying their needs. As a result, if we want to increase the benefits (recreation value) of a coast we must improve the quality of environmental status and recreation services (Halkos & Matsiori, 2011). The purpose of this study was to define visitors WTP for improving environmental quality by establishing sustainable tourism products to a coastal recreational site in prefecture of Fhtiotida as a function of contingent valuation method in view of making effective decisions for sustainable resource allocation and tourism accomplishments. 325

326 2. Materials and Methods A contingent valuation survey was carried out to 1433 randomly selected beach visitors of the coastal zone in interest in Prefecture of Fthiotida. The cluster sampling technique was used since no sampling frames were available for beach users. The population was divided into non overlapping populations called clusters (Zelin & Stubbs 2005). Cluster sampling is a random sampling technique in which a cluster represents the sampling unit (Ahmed 2009). In this method, the total population is divided into clusters. Then a sample of the clusters is selected. As a result, the analysis was conducted on a population of clusters, n=33 days, since each day of the research was deemed as a cluster. The population within a cluster should be as heterogeneous as possible. In cluster sampling only the selected clusters are studied. On site face-to-face interviews were conducted. Respondents were asked if they were willing-to-pay so as to advance and improve the quality of the tourism experience and protect the natural ecosystem from unstructured tourism policies. The hypothetical market contained a proposed tourism product that promotes dive and fishing tourism, experience-based water activities, coastal events and coastal ecotourism as the core destination attributes in view of advancing conservation concepts and environmental knowledge avoiding environmental degradation. Such components will result in water quality improvement, biodiversity conservation and effective environmental management. Stated WTP responses were checked for determining variables that affect users WTP. A pilot survey was conducted to provide feedback concerning the range of the amount used in the questionnaires and determine bid values. According to the results derived from the pilot survey the range of the amount was 5( ) to 50 ( ). Binary logistic regression was implemented since the dependent variable (WTP) was dichotomous. Binary logistic regression estimates the probability that a characteristic is present given the values of other independent variables of any type (categorical or not). The mean WTP was calculated by using the following formula suggested by Hanemann (1984) and Ekstrand & Loomis (1998): (2.1) 1 *ln(1 Bo MeanWTP e ) / b / 1 In the formula (2.1), 1 is the bid coefficient in absolute value and Bo is the sum of the estimated constant plus the product of the other independent variables times their respective means for each respondent. 3. Results In the survey 933 participants stated a positive WTP answer while 390 respondents expressed a clear no answer (not protest votes) (Table 1). The classification results (Table 2) showed that 89.3% of the answers were correctly classified as a result of the binary logistic method. In the analysis, from those who answered No in the WTP question 110 answers were identified as protest votes and, consequently, were excluded from the analysis (Hanley et al. 2006). Protest votes were highly related with the answer that the government should pay for establishing new tourism practices in view of improving the quality of the provided tourism experience (52 answers). In the sample of the 1323 individuals the mean years of education were almost 16 and the mean monthly income was almost ( ). 326

327 Table 1. Percentage of Yes and No answers in the survey sample Frequency Percentage Valid Percentage Cumulative Percentage NO YES Total Table 2. Classification table of observed and predicted answers derived from binary logistic regression Predicted Observed Willingness-to-pay NO YES Percentage correct (%) NO ,2 YES ,7 Overall Percentage (%) 89,3 Judging from the results of the binary logistic regression (Table 3) all coefficient signs were in the expected direction and were statistically significant given a 95% confidence interval. The BID amount coefficient had a negative sign indicated that respondents were unwilling to pay for bigger amounts. This means that the higher the bid amount the lower the likelihood (probability) of the respondent to pay the amount. Respondents education level (EDUVAR) had a significant positive impact on the likelihood of accepting to pay for coastal improvement in terms of tourism development. In the same sense, individuals that were well educated were found to be more familiar with terms such as coastal resource uses, environmental management and knowledge seeking through experience based marine tourism. The WTP is higher if the respondents income is higher (INCVAR). Visitors that are economically robust do not hesitate to spend money for well organized beach sites where sustainable forms of tourism and viable marine policies dominate the efforts for wise coastal resource exploitation. Moreover, the results showed that the more satisfied the visitor (SATISVAR), the more willing to pay for sustainable coastal tourism accomplishments. Respondents acknowledged the potential of the coastal site in terms of quality improvement (IMPROVAR) and were found to be willing to pay more for coastal improvement and modern tourism products in terms of environmental quality. 327

328 Table 3. Results of binary logistic regression Β S.E. Wald df Sig. EXP(B) BID -0,232 0, , ,000 0,793 EDUVAR 0,098 0,043 5, ,023 1,102 INCVAR 0,001 0, , ,001 1,001 SATISVAR 1,548 0,271 32, ,000 4,702 CROWDBEACH -0,441 0,211 4, ,037 0,643 COASTALUSES -1,982 0,331 35, ,000 0,138 IMPROVAR 0,645 0,212 9, ,002 1,907 Constant 6,083 0,888 46, , ,418 The logical interpretation of the other negative signs of the coefficients generated by the logistic regression was that respondents showed a clear disposition to pay less for overcrowded beaches (CROWDBEACH) and for sites that unstructured and unplanned uses (COASTALUSES) dominate the tourism practices causing devastating effects on the coastal ecosystem. According to the formula (2.1) and the respective coefficients of the independent variables the mean WTP was calculated by using the following formula: (3.1) 1 MeanWTP 0,232 9,293 *ln(1 e ) The mean WTP was estimated at ( ) per person and the recreational value of the coastal zone in interest was estimated at 4,005,400 ( ). 4. Discussion Valuing the marine leisure and recreation industry can provide an argument for making sound decisions for effective coastal tourism policies, for sustainable use of areas with valuable marine biodiversity, natural beauty as well as establishing customer driven tourism products that meet visitors expectations and fulfil their needs and wants. Issues such as willingness-to-pay and estimation of recreational benefits have been overlooked in the current literature concerning beach sites in central Greece. To the best of our knowledge there is no other research concerning economic valuation methodologies in the study area..management and tourism planners may find the present research useful in determining factors that directly affect (positively or negatively) the consuming behaviour of vistors. Supportively, this research provides a platform on which local authorities may find margins for improvement as far as tourism facilities, quality of the coastal environment and implementation of eco-friendly tourism activities (e.g. dive or fishery tourism) are concerned in view of protecting and improving the natural settings. As a result, factors that explain to a large degree visitors willingness-to-pay will be determined. It is imperative need for managers to know for what reason and how tourists prefer or like to spend their money. By taking into account their needs and desires customer satisfaction will be achieved and word of mouth advertising will be experienced. As 328

329 a direct consequence the study area will become a preferred destination place which fulfils visitors expectations by providing them quality tourism products for various trends and tastes. It goes without saying that future research in the area will help to become more reactive and provide solid solutions for achieving high rates of performance since tourism market is dominated by volatile market conditions and tourists needs and wants vary from time to time. Specifically, in Greece, coastal areas represent 72% of total territory, 86% of population, 88% of employment in manufacture, 90% of tourist activities and 90% of energy consumption (OECD 2000). Another interesting point is that the robustness of many economies is broadly based on tourism development and sustainable exploitation of natural settings. The evolving profile of today s tourists and under the existing considerable economic pressure, value for money is a frequently used phrase as a marketing tool or mission statement which arises crucial issuues in terms of destination s competitiveness, arrivals, average spend and duration of stay. Perceiving what customers value most and the extent to which these valued attributes can be interpreted into applicable coastal tourism plans are important determining factors for achieving coherent strategic policies which offer a great challenge of placing tourism planners in the role of social change agents (Lew 2007). Data analysis is not only about testing of statistical hypothesis but also about thinking to update, deciding to upgrade, changing to recover and improving to proceed. One of the core objectives of coastal management is to maximize the social value of coastal zones as preferred tourism settings. Therefore, coastal resource valuations will shed light on the link between conservation and regional economic development as well as help adapt systems of national accounting to better reflect the value of ecosystem services and natural capital (Qadri 2001). Zoppi (2004) argues that the contingent valuation approach defines a ranking of the planning options based on the degree of consensus concerning the local communities while at the same time identifies a ranking of the criteria identified by the public administration to assess the planning, options based on the preferences of the local communities. Last but far from least, cooperation among various stakeholders of the tourism system and implementation of techniques in view of assigning values in coastal settings are salient elements in achieving sustainability as well as in creating growth and development to the region and host society. Bibliography Ahmed, S. (2009). Methods in sample surveys. Cluster sampling. John Hopkins Bloomberg. School of Public Health. Beharry-Borg N., Scarpa R. (2010). Valuing quality changes in Caribbean coastal waters for heterogeneous beach visitors. Ecologivcal Economics, 69, Brenner J., Jimenes J.A., Sarda R., Garola A. (2010). An assessment of the non market value of the ecosystem services provided by the Catalan coastal zone, Spain. Ocean & Coastal Management, 53, Ekstrand E.R., Loomis J. (1998). Incorporating respondent uncertainty when estimating willingness to pay for protecting cxritical habitat for threatened and endangered fish. Water Resource Research, 34, Ghermandi A., Nunes P.A.L.D. (2013). A global map of of coastal recreation values. Results from a spatially explicit meta-analysis. Ecological Economics, 86, Halkos G., Matsiori S. (2011). Economic valuation of coastal zone quality improvements. MPRA Paper No Munich Personal RePEcS Archieve. Hanemann W.,M. (1984). Welfare evaluations in contingent valuation experiments with discrete response data. American Agricultural Economics Association, 66, Hanley N., Wright R.E., Alvarez-Farizo B. (2006). Estimating the economic value of improvements in river ecology using choice experiments: an application to the water framework directive. Journal of Environmental Management, 78, Lew, A. (2007). Invited commentary: Tourism planning and traditional urban planning theory The planner as an agent of social change. Leisure/Loisir, 31,

330 OECD (2000). Environmental performance reviews. Greece, Paris, France. UNEP. (2009). Sustainable coastal tourism. An integrated planning and management approach. United Nations Environment Programme Qadri S.T. (2001). Natural Resources Management and the Environment. Asian Development Bank. Zelin A., Stubbs, R. (2005). Cluster sampling: A false economy? International Journal of Market Research, 47, Zoppi C. (2004). A contingent valuation-multicriteria analysis case study on the taxonomy of three planning scenarios for a coastal zone of Sardinia (Italy). ERSA conference papers ersa04p147. European Regional Science Association. 330

331 ORAL PRESENTATIONS IN GREEK AN INVESTIGATION OF THE COMPETITIVENESS OF GREEK GILT-HEAD SEA BREAM IN EU MARKET Oikonomou A.*, Polymeros K. Department of Ichthyology and Aquatic Environment, University of Thessaly, Nea Ionia Street Fytokou Magnesia, , Greece Abstract The main aim of this study is the investigation of the competitive position of exports of Greek gilthead sea bream (Sparus aurata) in the market of EU-27. The gilt-head sea bream is one of the main export products of Greece, especially in the EU-27 market, reinforcing exports and improving its Balance of Trade. Initially, the major importing countries-markets and the main competing countries, in terms of exports, were identified. Then, the competitive position and the evolution of the level of competitiveness of the Greek gilt-head sea bream in each of the major importing markets were evaluated. The study performed using the index of Revealed Export Competitive Advantage (RXCA) and Import Share (IS), in the Greek market. Results revealed that the main importing markets of Greek gilt-head sea bream in the EU-27 are Italy, France, Portugal, Spain, Great Britain and Germany. In addition, an importing emerging market seems to be Romania, while the main competitive to Greek exports countries seem to be Spain, Turkey, France, Italy, Malta and Croatia. Finally, the assessment of the degree of penetration, using (IS) index, regarding sea-bream from the major competing countries revealed that Albania, Italy, Turkey, Cyprus, and Spain constitute the main suppliers. Keywords: fisheries and aquaculture product, gilt-head sea-bream, competitiveness, Greece, European Union * Corresponding author: Athina Oikonomou (aoikonom@mie.uth.gr) ΓΗΔΡΔΎΝΖΖ ΣΖ ΑΝΣΑΓΧΝΗΣΗΚΉ ΘΈΖ ΣΖ ΔΛΛΖΝΗΚΉ ΣΗΠΟΎΡΑ ΣΖΝ ΑΓΟΡΆ ΣΖ Δ.Δ. Οηθνλφκνπ Α.*, Πνιχκεξνο Κ. Σιήια Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ, Πακεπζζηήιζμ Θεζζαθίαξ, Οδυξ Φοηυημο, Νέα Ηςκία Μαβκδζίαξ, , Δθθάδα Πεξίιεςε Βαζζηυξ ζημπυξ ηδξ πανμφζαξ ενεοκδηζηήξ πνμζπάεεζαξ είκαζ δ δζενεφκδζδ ηδξ ακηαβςκζζηζηήξ εέζδξ ηςκ ελαβςβχκ ηδξ εθθδκζηήξ ηζζπμφναξ (Sparus aurata) ζηδκ αβμνά ηδξ Δ.Δ.-27. Ζ ηζζπμφνα απμηεθεί έκα απυ ηα ηονζυηενα ελαβςβζηά πνμσυκηα ηδξ Δθθάδαξ, ζδζαίηενα ζηδκ αβμνά ηδξ Δ.Δ., ζοιαάθθμκηαξ ζηδκ αφλδζδ ηςκ ελαβςβχκ ηαζ ζηδ αεθηίςζδ ημο ζζμγοβίμο ηςκ ειπμνζηχκ ζοκαθθαβχκ ηδξ. Ανπζηά, εκημπίζηδηακ μζ ηονζυηενεξ εζζαβςβζηέξ πχνεξ ηδξ ηζζπμφναξ, ηαεχξ ηαζ μζ ηονζυηενεξ ακηαβςκζζηζηέξ πχνεξ ζηδκ αβμνά ηδξ Δ.Δ.-27. Αημθμφεςξ, επζπεζνήεδηε δ δζενεφκδζδ ηδξ ακηαβςκζζηζηήξ εέζδξ ηαζ ηδξ ελέθζλδξ ημο ααειμφ ακηαβςκζζηζηυηδηαξ, ηδξ εθθδκζηήξ ηζζπμφναξ ζε ηάεε ιία απυ ηζξ ηονζυηενεξ εζζαβςβζηέξ αβμνέξ. Δπίζδξ, δζενεοκήεδηε δ ακηαβςκζζηζηή εέζδ ηςκ ηονζυηενςκ ακηαβςκζζηζηχκ πςνχκ βζα ηάεε ιία απυ ηζξ παναπάκς αβμνέξ. Ζ ακάθοζδ πναβιαημπμζήεδηε πνδζζιμπμζχκηαξ ημ δείηηδ ημο Απμηαθοπηυιεκμο Δλαβςβζημφ Ακηαβςκζζηζημφ Πθεμκεηηήιαημξ (Revealed Export Competitive Advantage, RΥCA) ηαζ ημ δείηηδ ιενζδίμο (Import Share, IS). Απυ ηα απμηεθέζιαηα ηδξ ένεοκαξ πνμέηορε υηζ, μζ ηονζυηενεξ 331

332 εζζαβςβζηέξ αβμνέξ ηδξ εθθδκζηήξ ηζζπμφναξ ζηδκ E.E.-27 είκαζ δ Ηηαθία, δ Γαθθία, δ Πμνημβαθία, δ Ηζπακία, ημ Ζκςιέκμ Βαζίθεζμ ηαζ δ Γενιακία. Δπίζδξ, ζδιακηζηά ακαδουιεκδ αβμνά δζαθαίκεηαζ υηζ απμηεθεί δ Ρμοιακία. Δκχ, μζ ηονζυηενεξ ακηαβςκζζηζηέξ πχνεξ ηδξ Δθθάδαξ είκαζ δ Ηζπακία, δ Σμονηία, δ Γαθθία, δ Ηηαθία, δ Μάθηα ηαζ δ Κνμαηία. Σέθμξ, αάζεζ ημο ααειμφ δζεζζδοηζηυηδηαξ (Import Share, IS) ηδξ ηζζπμφναξ ζηδκ αβμνά ηδξ Δθθάδαξ μζ ηονζυηενεξ ακηαβςκζζηζηέξ πχνεξ είκαζ δ Αθαακία, δ Ηηαθία, δ Σμονηία, δ Κφπνμξ ηαζ δ Ηζπακία. Λέμεηο θιεηδηά: Αθζεοηζηά πνμσυκηα ηαζ πνμσυκηα οδαημηαθθζένβεζαξ, ηζζπμφνα, ακηαβςκζζηζηυηδηα, Δθθάδα, Δονςπασηή Έκςζδ *οββναθέαξ επζημζκςκίαξ: Οζημκυιμο Αεδκά 1. Δηζαγσγή Ζ έκκμζα ηδξ ακηαβςκζζηζηυηδηαξ, ηα ηεθεοηαία πνυκζα, έπεζ πνδζζιμπμζδεεί εονέςξ ζηδκ μζημκμιζηή ένεοκα ηαζ ζηδκ μζημκμιζηή πμθζηζηή απυ δζαθμνεηζηέξ μπηζηέξ ζημπζέξ, αθθά παναηδνείηαζ ιζηνή ζοιθςκία ακαθμνζηά ιε ημκ μνζζιυ ηδξ. Ο ακηαβςκζζιυξ ςξ έκκμζα δεκ έπεζ κα ηάκεζ ιυκμ ιε ημκ ανζειυ ηςκ πςθδηχκ ζε ιζα ζοβηεηνζιέκδ αβμνά, αθθά ηαζ ημ ιενίδζμ ηδξ αβμνάξ πμο απμηηά μ ηαεέκαξ ζε έκακ ηθάδμ, ηδ δζαηδνδζζιυηδηα ημο ιενζδίμο αοημφ ηαζ ηδκ ηενδμθμνία ημο (Σζαηθάβηακμξ A., 2004). O ααειυξ ημο ακηαβςκζζιμφ ιζαξ επζπείνδζδξ ιέζα ζε ιία ζοβηεηνζιέκδ αβμνά ελανηάηαζ απυ ημοξ αηυθμοεμοξ πέκηε ααζζημφξ πανάβμκηεξ: α) απυ ημκ ανζειυ ηςκ κεμεζζενπυιεκςκ επζπεζνήζεςκ, α) ηδκ φπανλδ οπμηαηάζηαηςκ πνμσυκηςκ, β) ηδ δζαπναβιαηεοηζηή δφκαιδ ηςκ πνμιδεεοηχκ, δ) ηδ δζαπναβιαηεοηζηή δφκαιδ ηςκ αβμναζηχκ ηαζ ε) ημκ ακηαβςκζζιυ ιεηαλφ ηςκ οπανπμοζχκ επζπεζνήζεςκ ζηδκ αβμνά. O ακηαβςκζζιυξ είκαζ δοκαιζηυξ ηαζ ζοκεπχξ ελεθίζζεηαζ, ηαεχξ κέα πνμσυκηα, κέμζ ιέεμδμζ ιάνηεηζκβη, κέεξ δζαδζηαζίεξ παναβςβήξ ηαζ κέεξ αβμνέξ ειθακίγμκηαζ (Porter M., 1998). φιθςκα ιε ημοξ Kim D. and Marion B.W., (1997), μ ααειυξ ημο ακηαβςκζζιμφ ηςκ επζπεζνήζεςκ ζηδκ εβπχνζα αβμνά είκαζ εεηζηά ζοκδεδειέκμξ ιε ηδκ ζηακυηδηα ηςκ επζπεζνήζεςκ κα είκαζ ακηαβςκζζηζηέξ ζηζξ δζεεκείξ αβμνέξ, ηαεχξ δ έκημκδ εβπχνζα ακηαβςκζζηζηυηδηα απμηεθεί ημ πθέμκ ηαηάθθδθμ οπυααενμ βζα κα πνμεημζιάζεζ ηζξ επζπεζνήζεζξ, χζηε κα είκαζ ακηαβςκζζηζηέξ ηαζ αζχζζιεξ ζηδκ παβημζιζμπμζδιέκδ αβμνά. Βαζζηυξ ζημπυξ ηδξ πανμφζαξ ενβαζίαξ ήηακ δ δζενεφκδζδ ηδξ ακηαβςκζζηζηήξ εέζδξ ηςκ ελαβςβχκ ηδξ εθθδκζηήξ ηζζπμφναξ (Sparus aurata). Γζα ημ ζημπυ αοηυκ, εκημπίζηδηακ μζ ηονζυηενεξ εζζαβςβζηέξ πχνεξ ηδξ ηζζπμφναξ, ηαεχξ ηαζ μζ ηονζυηενεξ ακηαβςκζζηζηέξ πχνεξ - αβμνέξ ζηδκ αβμνά ηδξ Δ.Δ.-27 ηαζ οπμθμβίζεδηε μ δείηηδξ ημο Απμηαθοπηυιεκμο Δλαβςβζημφ Ακηαβςκζζηζημφ Πθεμκεηηήιαημξ (RΥCA), ζε ηάεε ιία απυ ηζξ ηονζυηενεξ εζζαβςβζηέξ πχνεξ ηδξ Δ.Δ.-27 ηδξ ηζζπμφναξ. ηδ ζοκέπεζα ηδξ ενβαζίαξ, βίκεηαζ ακάθοζδ ηςκ δεζηηχκ ακηαβςκζζηζηυηδηαξ ηαζ ηδξ ιεεμδμθμβίαξ πμο αημθμοεήεδηε ζηδκ ένεοκα ηαζ δ ηαηαβναθή ηςκ απμηεθεζιάηςκ ηδξ. 2. Τιηθά θαη Μέζνδνη φιθςκα ιε ηδ δζεεκή αζαθζμβναθία δζαθμνεηζημί δείηηεξ έπμοκ πνδζζιμπμζδεεί απυ πμθθμφξ ενεοκδηέξ βζα ηδ δζενεφκδζδ ημο ααειμφ ακηαβςκζζηζηυηδηαξ εεκζηχκ μζημκμιζχκ, αζμιδπακζχκ, επζπεζνήζεςκ ηαζ πνμσυκηςκ. ηδ ζοκέπεζα πανμοζζάγμκηαζ μζ πζμ ζδιακηζημί απυ αοημφξ: φιθςκα ιε ημοξ Balassa Β. (1965), Lee J. (1995), Havrila I. and Gunawardana P. (2003) ηαζ Polymeros et al. (2005), μ δείηηδξ ημο Απμηαθοπηυιεκμο οβηνζηζημφ Πθεμκεηηήιαημξ, RCA (Revealed Comparative Advantage), έπεζ πνδζζιμπμζδεεί βζα κα πενζβνάρεζ εάκ ιία πχνα πανμοζζάγεζ ή υπζ ζοβηνζηζηυ πθεμκέηηδια ζε έκακ ζοβηεηνζιέκμ ηθάδμ, ημιέα ή πνμσυκ ιέζα απυ ημ νυθμ ημο ειπμνίμο, πςνίξ υιςξ κα ακαθφεζ ηζξ ααζζηέξ πδβέξ αοημφ ημο ζοβηνζηζημφ πθεμκεηηήιαημξ. Ονίγεηαζ ςξ μ θυβμξ ημο ιενζδίμο ηςκ ελαβςβχκ εκυξ πνμσυκημξ ή εκυξ ηθάδμοημιέα ιζαξ πχναξ ζηδκ παβηυζιζα αβμνά πνμξ ημ ιενίδζμ ηςκ ζοκμθζηχκ ελαβςβχκ υθςκ ηςκ πνμσυκηςκ ή ηθάδςκ-ημιέςκ ηδξ πχναξ ζηδκ ίδζα αβμνά. Δπμιέκςξ, μ δείηηδξ RCA απμηοπχκεηαζ ςξ ελήξ: RCA ij = (x ij / X j ) / (x iw / X w ) 332

333 πμο, RCA ij είκαζ μ δείηηδξ ημο Απμηαθοπηυιεκμο οβηνζηζημφ Πθεμκεηηήιαημξ βζα έκα πνμσυκ ή ημιέα-ηθάδμ i ιζαξ πχναξ j, x ij μζ ελαβςβέξ ημο πνμσυκημξ ή ημιέα-ηθάδμο i ηδξ πχναξ j, X j μζ ζοκμθζηέξ ελαβςβέξ ηδξ πχναξ j, x iw μζ ελαβςβέξ ημο πνμσυκημξ ή ημιέα-ηθάδμο i παβημζιίςξ, X w ζοκμθζηέξ ελαβςβέξ παβημζιίςξ. Ακάθμβα ιε ηδκ ηζιή ημο δείηηδ, ιπμνμφιε κα ζοιπενάκμοιε εάκ ιία πχνα πανμοζζάγεζ ή υπζ ζοβηνζηζηυ πθεμκέηηδια ςξ πνμξ ιία ηαηδβμνία πνμσυκηςκ. Δπμιέκςξ, υηακ δ ηζιή ημο δείηηδ ημο Απμηαθοπηυιεκμο οβηνζηζημφ Πθεμκεηηήιαημξ είκαζ ιεβαθφηενδ ηδξ ιμκάδαξ, ηυηε δ οπυ ιεθέηδ ηαηδβμνία πνμσυκηςκ πανμοζζάγεζ ζοβηνζηζηυ πθεμκέηηδια, εκχ ακηίεεηα βζα ηζιέξ ιζηνυηενδξ ηδξ ιμκάδαξ πανμοζζάγεζ ζοβηνζηζηυ ιεζμκέηηδια (Havrila I. and Gunawardana P., 2003; Polymeros K. and Katrakilidis K., 2008). Σνμπμπμίδζδ ημο παναπάκς δείηηδ απμηεθεί μ δείηηδξ ημο Απμηαθοπηυιεκμο Δλαβςβζημφ Ακηαβςκζζηζημφ Πθεμκεηηήιαημξ, RΥCA (Revealed Export Competitive Advantage), πμο οπμθμβίγεζ ημ ακηαβςκζζηζηυ πθεμκέηηδια ιζαξ πχναξ βζα έκα ζοβηεηνζιέκμ πνμσυκ, υπζ ζηδκ παβηυζιζα αβμνά, αθθά ζε ιία ζοβηεηνζιέκδ αβμνά-ζηυπμ ηαζ εηθνάγεηαζ ςξ ελήξ: RXCA ij X ij / X ij / X ij / X ij i j ij πμο: Υ είκαζ μζ αλίεξ ηςκ ελαβςβχκ, i είκαζ μζ οπυ ιεθέηδ πχνεξ, j είκαζ ηα οπυ ιεθέηδ πνμσυκηα. Ζ πνμζέββζζδ αοηή δίκεζ ηδκ δοκαηυηδηα δζενεφκδζδξ ηδξ ακηαβςκζζηζηήξ εέζδξ ηςκ ελαβςβχκ ιζαξ πχναξ ζε ζοβηεηνζιέκεξ αβμνέξ, ηαεζζηχκηαξ δοκαηυκ, αθεκυξ ημκ εκημπζζιυ ηςκ ηονζυηενςκ εζζαβςβζηχκ αβμνχκ ηαζ αθεηένμο ηδκ ελέθζλδ ημο ααειμφ ηδξ ακηαβςκζζηζηυηδηαξ ζηζξ εκ θυβς αβμνέξ. Δπζπθέμκ, ιε ηδκ παναπάκς πνμζέββζζδ ηαείζηαηαζ εθζηηή δ δζαδζηαζία εκημπζζιμφ ηςκ ηονζυηενςκ ελαβςβζηχκ ακηαβςκζζηζηχκ πςνχκ ζηζξ εζζαβςβζηέξ αοηέξ αβμνέξ. ηακ δ ηζιή ημο δείηηδ RXCΑ είκαζ ιεβαθφηενδ ηδξ ιμκάδαξ, ηυηε δ οπυ ιεθέηδ πχνα πανμοζζάγεζ ακηαβςκζζηζηυ πθεμκέηηδια, ακηίεεηα βζα ηζιέξ ιζηνυηενδξ ηδξ ιμκάδαξ πανμοζζάγεζ ακηαβςκζζηζηυ ιεζμκέηηδια. φιθςκα ιε ημοξ Havrila ηαζ Gunawardana (2003) έκαξ άθθμξ ηνυπμξ δζενεφκδζδξ ημο ααειμφ ακηαβςκζζηζηυηδηαξ απμηεθεί δ πνδζζιμπμίδζδ ηςκ δεζηηχκ ημο ζοβηνζηζημφ πθεμκεηηήιαημξ ημο Vollrath, μζ μπμίμζ είκαζ μζ ελήξ: i) μ δείηηδξ ημο πεηζημφ Δλαβςβζημφ Πθεμκεηηήιαημξ, RXA (Relative Export Advantage Index), ii) μ δείηηδξ ημο πεηζημφ Δζζαβςβζημφ Πθεμκεηηήιαημξ, RMA (Relative Import Advantage Index), iii) o δείηηδξ ημο πεηζημφ Διπμνζημφ Πθεμκεηηήιαημξ, RTA (Relative Advantage Trade Index) ηαζ iv) o δείηηδξ ηδξ πεηζηήξ Ακηαβςκζζηζηυηδηαξ, RC (Relative Competitiveness Index). Οζ παναπάκς δείηηεξ ημο Vollrath απμηοπχκμκηαζ ςξ ελήξ: RXA ij = (X ij /X nj )/(X ir /X nr ) RMA ij = (M ij /M nj )/(M ir /M nr ) RTA ij = RXA ij - RMA ij RC ij = Ln(RXA ij ) - Ln(RMA ij ) πμο: Υ: είκαζ μζ ελαβςβέξ, Μ: είκαζ μζ εζζαβςβέξ, i: είκαζ ημ πνμσυκ, j: είκαζ δ πχνα, n: είκαζ ημ οπυθμζπμ ηςκ πνμσυκηςκ, r: ημ οπυθμζπμ ηςκ πςνχκ, Ln: μ θοζζηυξ θμβάνζειμξ. Οζ δφμ δείηηεξ RXA ηαζ RMA ιπμνμφκ κα πάνμοκ ηζιέξ απυ 0 έςξ άπεζνμ, εκχ μζ ηζιέξ ημο RTA είκαζ είηε εεηζηέξ, είηε ανκδηζηέξ. Δπμιέκςξ, υηακ μζ ηζιέξ ηςκ δεζηηχκ RXA ηαζ RMA είκαζ ιεβαθφηενεξ ηδξ ιμκάδαξ έπμοιε ηδκ ειθάκζζδ ζπεηζημφ ελαβςβζημφ ή εζζαβςβζημφ πθεμκεηηήιαημξ, ακηίζημζπα, εκχ υηακ είκαζ ιζηνυηενεξ ηδξ ιμκάδαξ έπμοιε ηδκ ειθάκζζδ ελαβςβζημφ ή εζζαβςβζημφ ιεζμκεηηήιαημξ. ζμκ αθμνά ηζξ ηζιέξ ημο δείηηδ RTA, υηακ αοηέξ είκαζ εεηζηέξ ηυηε έπμοιε ζπεηζηυ ειπμνζηυ πθεμκέηηδια, εκχ υηακ είκαζ ανκδηζηέξ έπμοιε ακηζζημίπςξ ιεζμκέηηδια (Havrila I. and Gunawardana P., 2003). Ζ ζπμοδαζυηδηα ηςκ δεζηηχκ ημο Vollrath έβηεζηαζ ζημ βεβμκυξ υηζ επζηνέπμοκ κα βίκεζ δζάηνζζδ εκυξ πνμσυκημξ/πχναξ ηαζ ηςκ οπμθμίπςκ πνμσυκηςκ/πςνχκ, απμθεφβμκηαξ έηζζ ηδ δζπθή ηαηαιέηνδζδ ζημ παβηυζιζμ ειπυνζμ (Havrila I. and Gunawardana P., 2003). 333

334 Ακηίζημζπα, μ δείηηδξ ημο Μενζδίμο Δζζαβςβχκ, IS i (Import Share) ελεηάγεζ ημ ιενίδζμ εζζαβςβχκ ιζαξ πχναξ i, ζε ζπέζδ ιε ηζξ παβηυζιζεξ εζζαβςβέξ βζα έκα ζοβηεηνζιέκμ πνμσυκ, ημιέα ή ηθάδμ, ηαζ εηθνάγεηαζ ςξ ελήξ: IS I / i i πμο: X είκαζ μζ εζζαβςβέξ ηαζ n είκαζ μζ δζάθμνεξ πχνεξ. Οζ ηζιέξ ημο παναπάκς δείηηδ ηοιαίκμκηαζ επίζδξ ιεηαλφ ημο 0 ηαζ ημο 1. Έηζζ, υηακ μ δείηηδξ παίνκεζ ηδκ ηζιή 0, ηυηε δ πχνα i δεκ έπεζ ηαευθμο εζζαβςβέξ βζα ημ οπυ ιεθέηδ πνμσυκ, εκχ υηακ παίνκεζ ηδ ιέβζζηδ ηζιή 1, ηυηε δ πχνα i είκαζ δ ιμκαδζηή εζζαβςβέαξ ημο ζοβηεηνζιέκμο πνμσυκημξ (Kim D. and Μarion B.W., 1997). ηδκ πανμφζα ενεοκδηζηή ενβαζία, μζ αλίεξ ηςκ εθθδκζηχκ ελαβςβχκ ηαζ εζζαβςβχκ ηδξ ηζζπμφναξ, αθθά ηαζ ηςκ οπυθμζπςκ πςνχκ ηδξ Δ.Δ.-27 ζηδ αβμνά ηδξ Δ.Δ.-27 πμο πνδζζιμπμζήεδηακ βζα ιζα ζεζνά εηχκ (απυ ημ 2000 έςξ ηαζ ημ 2013), πνμένπμκηαζ απυ ηδκ δθεηηνμκζηή δζεφεοκζδ ηδξ Eurostat ( Ζ ηζζπμφνα ακήηεζ ζηδ ηαηδβμνία ηςκ κςπχκ ρανζχκ ή ηςκ δζαηδνδιέκςκ ιε απθή ρφλδ ηαζ ζοβηεηνζιέκα ιε ημκ ηςδζηυ ηαζ απυ ημ Ανπζηά, εκημπίζηδηακ μζ ηονζυηενεξ εζζαβςβζηέξ πχνεξ-αβμνέξ ηδξ ηζζπμφναξ, ηαεχξ ηαζ μζ ηονζυηενεξ ακηαβςκζζηζηέξ πχνεξ ζηδκ αβμνά ηδξ Δ.Δ.-27. ηδ ζοκέπεζα, επζπεζνήεδηε δ δζενεφκδζδ ηδξ ακηαβςκζζηζηήξ εέζδξ ηαζ ηδξ ελέθζλδξ ημο ααειμφ ακηαβςκζζηζηυηδηαξ ηδξ εθθδκζηήξ ηζζπμφναξ, ζε ηάεε ιία απυ ηζξ ηονζυηενεξ εζζαβςβζηέξ αβμνέξ. Δπίζδξ, δζενεοκήεδηε δ ακηαβςκζζηζηή εέζδ ηςκ ηονζυηενςκ ακηαβςκζζηζηχκ πςνχκ ςξ πνμξ ηζξ εζζαβςβέξ αοημφ ημο πνμσυκημξ, απυ ηάεε ιία απυ ηζξ παναπάκς αβμνέξ. Ζ ιεθέηδ έβζκε πνδζζιμπμζχκηαξ ημ δείηηδ ημο Απμηαθοπηυιεκμο Δλαβςβζημφ Ακηαβςκζζηζημφ Πθεμκεηηήιαημξ (RΥCA), υπζ υιςξ ζε υθδ ηδκ αβμνά ηδξ Δ.Δ.-27, αθθά ζηζξ ηονζυηενεξ εζζαβςβζηέξ πχνεξ-αβμνέξ ηςκ ηναηχκ-ιεθχκ ηδξ Δ.Δ. ηδ ζοκέπεζα, πνδζζιμπμζχκηαξ ηδ ιαεδιαηζηή ζπέζδ αλίεξ πνμξ πμζυηδηεξ, ζοβηνίεδηακ ιεηαλφ ημοξ μζ ηζιέξ πχθδζδξ ηδξ ηζζπμφναξ ηςκ ακηαβςκζζηζηχκ πςνχκ, ζηζξ ηονζυηενεξ εζζαβςβζηέξ πχνεξ ηδξ Δ.Δ.-27. Pij = Vij / Qij πμο: P: δ ηζιή, V: μζ αλίεξ, Q: μζ πμζυηδηεξ, i: δ πχνα, j: ημ πνμσυκ Σέθμξ, πνδζζιμπμζήεδηε μ δείηηδξ ημο Μενζδίμο Δζζαβςβχκ, IS (Import Share), βζα κα εηηζιδεεί μ ααειυξ δζεζζδοηζηυηδηαξ ζηδκ αβμνά ηδξ Δθθάδαξ ηςκ ακηαβςκζζηζηχκ πςνχκ βζα ηδκ ηζζπμφνα. 3. Απνηειέζκαηα πδήηεζε φιθςκα ιε πνμδβμφιεκεξ ένεοκεξ, δ Δθθάδα ηαηέπεζ ζδιακηζηή εέζδ ζημ ειπυνζμ ηςκ αθζεοηζηχκ πνμσυκηςκ.. (Πμθφιενμξ, K., ηαζ ζοκ., 2005α: Πμθφιενμξ Κ., ηαζ ζοκ., 2005α: Polymeros K., et al., 2005). Ηδζαίηενα μζ ελαβςβέξ ηςκ πνμσυκηςκ οδαημηαθθζένβεζαξ ηδξ Δθθάδαξ δζαθαίκεηαζ υηζ ηονζανπμφκ ζε επίπεδμ Δ.Δ-27. (Polymeros ηαζ Katrakilidis, 2008: Λζυθζμο Μ., 2009: Λζυθζμο, Μ., Πμθφιενμξ, Κ. ηαζ Καηναηοθίδδξ, Κ., 2010: Kaimakoudi, E., et al., 2014) Ζ ηζζπμφνα ηαζ ημ θαανάηζ απμηεθμφκ ηα δφμ ηονζυηενα ελαβςβζηά πνμσυκηα οδαημηαθθζένβεζαξ ηδξ Δθθάδαξ ζηδκ αβμνά ηδξ Δ.Δ.-27, ζοιαάθθμκηαξ ζηδκ αφλδζδ ηςκ ελαβςβχκ ηαζ ζηδ ιείςζδ ημο ανκδηζημφ ειπμνζημφ ζζμγοβίμο. To 2008, δ αλία ηςκ ελαβςβχκ ηδξ ηζζπμφναξ έθεαζε πενίπμο ηα 138,25 εηαημιιφνζα εονχ. Δπίζδξ, έπεζ δζαπζζηςεεί υηζ απυ ηζξ επηά ηονζυηενεξ οπμηαηδβμνίεξ ηςκ εθθδκζηχκ αθζεοηζηχκ πνμσυκηςκ ηαζ ηςκ πνμσυκηςκ οδαημηαθθζένβεζαξ, δ οπμηαηδβμνία "302" (ράνζα κςπά ή δζαηδνδιέκα ιε απθή ρφλδ) ηαηαθαιαάκεζ ημ ιεβαθφηενμ ιενίδζμ ηςκ εθθδκζηχκ ελαβςβχκ ζηδκ αβμνά ηδξ Δ.Δ.-27, πανμοζζάγμκηαξ ζοβηνζηζηυ πθεμκέηηδια έκακηζ υθςκ ηςκ οπυθμζπςκ ζηδκ αβμνά ηδξ Δ.Δ.-27, ηαζ ηαεζζηχκηαξ έηζζ ηδ πχνα ιαξ απυ ηζξ ηονζυηενεξ πχνεξ πμο ζοιιεηέπμοκ ζηδκ εκ θυβς αβμνά. οβηεηνζιέκα, δ οπμηαηδβμνία "302", απυ πζθζάδεξ εονχ ημ 2000 έθεαζε ηζξ πζθζάδεξ εονχ ημ 2008, πανμοζζάγμκηαξ αφλδζδ ηαηά 22,79% (Καναβημφκδξ Υν., 2011: Karagounis, C. and Polymeros K., 2011: Καναβημφκδξ, Υ. ηαζ Πμθφιενμξ Κ., 2012) n j I j 334

335 ηδκ πανμφζα ένεοκα δζαπζζηχκεηαζ υηζ: Α) Oζ ηονζυηενεξ εζζαβςβζηέξ αβμνέξ ιεηαλφ ηςκ πςνχκ ηδξ Δ.Δ.-27 είκαζ δ Ηηαθία, δ Γαθθία, δ Πμνημβαθία, δ Ηζπακία, ημ Ζκςιέκμ Βαζίθεζμ ηαζ δ Γενιακία, ιε ακενπυιεκδ αβμνά ηδκ Ρμοιακία. Οζ πχνεξ αοηέξ απμηεθμφκ επίζδξ ημοξ ηονζυηενμοξ πνμμνζζιμφξ ηςκ εθθδκζηχκ ελαβςβχκ. Πανάθθδθα, μζ ακηαβςκζζηζηέξ πχνεξ ηδξ Δθθάδαξ ζηδκ αβμνά ηδξ Δ.Δ.-27, απυ υθεξ ηζξ πχνεξ παβημζιίςξ, βζα ηδκ ηεθεοηαία 5εηία, είκαζ δ Ηζπακία, δ Σμονηία, δ Γαθθία, δ Ηηαθία, δ Μάθηα ηαζ δ Κνμαηία. οβηεηνζιέκα, δ αβμνά ηδξ Ηηαιίαο απμηεθεί ηδκ ζδιακηζηυηενδ αβμνά βζα ηδκ εθθδκζηή ηζζπμφνα. φιθςκα ιε ηα ζημζπεία αλίαξ ηςκ εζζαβςβχκ ηδξ Ηηαθίαξ απυ ηζξ πχνεξ Δθθάδα, Ηζπακία, Γαθθία, Σμονηία, Μάθηα ηαζ Κνμαηία δζαπζζηχκεηαζ υηζ, δ εθθδκζηή ηζζπμφνα ηαηέπεζ απυ ημ 2000 έςξ ζήιενα ημ πνχημ ιεβαθφηενμ ιενίδζμ αβμνάξ ηαζ αημθμοεεί δ Μάθηα - πμο ηαηέπεζ ηαζ ημ ιεβαθφηενμ ακηαβςκζζηζηυ πθεμκέηηδια-, ζε ζπέζδ ιε ηζξ πνμακαθενεείζεξ ακηαβςκζζηζηέξ πχνεξ, ιε ηνίηδ ηδκ Σμονηία ηαζ κέα ακηαβςκίζηνζα πχνα ηδκ Κνμαηία ιεηά ημ Χζηυζμ, παναηδνείηαζ ζπεηζηή ηάιρδ ημο δείηηδ Απμηαθοπηυιεκμο Δλαβςβζημφ Ακηαβςκζζηζημφ Πθεμκεηηήιαημξ ηδξ Δθθάδαξ ιε πμζμζηυ ανκδηζηήξ ιεηααμθήξ -15,15% (Πίκαηαξ 1). Δπίζδξ, απυ ηα απμηεθέζιαηα οπμθμβζζιμφ ηςκ ηζιχκ ηδξ ηζζπμφναξ ηςκ ακηαβςκζζηζηχκ πςνχκ ζηδκ αβμνά ηδξ Ηηαθίαξ δζαπζζηχκεηαζ υηζ, ημ πνμσυκ ηδξ Σμονηίαξ ηαζ ηδξ Μάθηαξ ηαηά ιέζμ υνμ ειθακίγεζ ηζξ παιδθυηενεξ ηζιέξ, έκακηζ ηδξ Ηζπακίαξ ηαζ ηδξ Γαθθίαξ, ιε ηνίηδ πζμ θεδκή ηδκ ηζιή ηδξ εθθδκζηήξ ηζζπμφναξ ηαζ κέα ακηαβςκζζηζηή ηζιή αοηή ηδξ ηζζπμφναξ Κνμαηίαξ. Χζηυζμ, ηδκ ηεθεοηαία 6εηαία ζπεδυκ υθεξ μζ ηζιέξ ειθακίγμοκ ακμδζηή πμνεία. Γζα ηδκ αβμνά ηδξ Γαιιίαο, δζαπζζηχκεηαζ υηζ, δ εθθδκζηή ηζζπμφνα ηναηά ηδκ πνχηδ εέζδ ζε ιενίδζμ αλίαξ εζζαβςβχκ πμο ηαηείπε απυ ημ 2000 ιε δεφηενδ ηδκ ζζπακζηή, αθθά ιε ιζα ζηαεενά ηαεμδζηή πμνεία ημο δείηηδ ακηαβςκζζηζηυηδηαξ ηαζ ηςκ δφμ. ηδκ αβμνά ηδξ Πνξηνγαιίαο δ εθθδκζηή ηζζπμφνα είκαζ δεφηενδ ζε ιενίδζμ αλίαξ εζζαβςβχκ εκχ ζηδκ αβμνά ημο Ζλσκέλνπ Βαζίιεηνπ είκαζ πνχηδ. Καζ ζηζξ δφμ αβμνέξ δζαθαίκεηαζ ιζα ακάηαιρδ ηδξ ιεηααμθήξ ημο δείηηδ ακηαβςκζζηζηυηδηαξ ηδξ Δθθάδαξ ζε πμζμζηυ ημο 64%-67,69% ηδκ ηεθεοηαία 6εηία (Πίκαηεξ 2,3 ηαζ 4). Γζα ηδκ αβμνά ηδξ Ηζπαλίαο δζαπζζηχκεηαζ υηζ, εκχ δ εθθδκζηή ηζζπμφνα είκαζ πνχηδ ζε ιενίδζμ αλίαξ εζζαβςβχκ, μ εθθδκζηυξ δείηηδξ RXCA δζαηδνείηαζ ζηαεενά ζε δεφηενδ εέζδ ιεηά ηδκ Σμονηία, ιε ιία υιςξ ζδιακηζηή ακμδζηή ιεηααμθή ημο δείηηδ ηδξ Σμονηίαξ, ζε πμζμζηυ 12,66% ηδκ ηεθεοηαία 6εηία. (αθ. Πίκαηα 5). Γζα ηδκ αβμνά ηδξ Ρνπκαλίαο, πμο απμηεθεί ακαπηοζζυιεκδ αβμνά βζα ηδκ εθθδκζηή ηζζπμφνα, ηδκ ηεθεοηαία 6εηία, δζαπζζηχκεηαζ υηζ, δ εθθδκζηή ηζζπμφνα έπεζ ηενδίζεζ ηδκ πνχηδ εέζδ ηαζ αημθμοεεί δ Σμονηία (Πίκαηαξ 6). Ακαθμνζηά ιε ηζξ ηζιέξ ηδξ ηζζπμφναξ ηςκ ακηαβςκζζηζηχκ πςνχκ ηδκ ηεθεοηαία 6εηία, ζηζξ αβμνέξ Γαιιίαο, Πνξηνγαιίαο, Ηζπαλίαο δζαπζζηχκεηαζ υηζ, ημ πνμσυκ ηδξ Δθθάδαξ ηαζ ηδξ Σμονηίαξ ειθακίγεζ ηζξ παιδθυηενεξ ηζιέξ, ιε πζμ θεδκή ηδκ ηζζπμφνα ηδξ Σμονηίαξ (Πίκαηεξ 2,3 ηαζ 5), εκχ ζηδκ αβμνά ημο Ζλσκέλνπ Βαζηιείνπ δζαπζζηχκεηαζ υηζ ημ πνμσυκ ηδξ Δθθάδαξ ειθακίγεζ ηζξ παιδθυηενεξ ηζιέξ (Πίκαηαξ 4). ηδ Ρνπκαλία δζαπζζηχκεηαζ υηζ, ημ πνμσυκ ηδξ Δθθάδαξ ηαζ ηδξ Σμονηίαξ ειθακίγεζ ηζξ παιδθυηενεξ ηζιέξ, ιε ζπεηζηά ιζηνή δζαθμνά ιεηαλφ ημοξ ηαζ ηδκ ηζζπμφνα ηδξ Σμονηίαξ θίβμ πζμ θεδκή (Πίκαηαξ 6). Γζα ηδκ αβμνά ηδξ Γεξκαλίαο δζαπζζηχκεηαζ ιία ζδιακηζηή δζαθμνά έκακηζ ηςκ πνμακαθενεέκηςκ εζζαβςβζηχκ αβμνχκ. Ζ Δθθάδα ηαηέπεζ ηδκ πνχηδ εέζδ ζε ακηαβςκζζηζηυ πθεμκέηηδια ηαηά ιέζμ υνμ ηδκ ηεθεοηαία 6εηία. (Πίκαηαξ 7). Δπίζδξ, αάζεζ οπμθμβζζιμφ ηςκ ηζιχκ ηδξ ηζζπμφναξ ηςκ ακηαβςκζζηζηχκ πςνχκ ζηδκ αβμνά ηδξ Γενιακίαξ, δ Σμονηία ειθακίγεζ ηζξ παιδθυηενεξ ηζιέξ, ηδκ ηεθεοηαία 6εηία, ηαζ αημθμοεεί δ Δθθάδα, εκχ ιέπνζ ημ 2007 πζμ θεδκή ήηακ δ εθθδκζηή ηζζπμφνα. B) Χξ πνμξ ημ ααειυ δζεζζδοηζηυηδηαξ ζηδκ αβμνά ηδξ Διιάδαο ηδξ ηζζπμφναξ ηςκ ηονζυηενςκ ακηαβςκζζηζηχκ πςνχκ πμο είκαζ δ Αθαακία, δ Ηηαθία, δ Σμονηία, δ Κφπνμξ ηαζ δ Ηζπακία, ηδκ ηεθεοηαία 5εηία παναηδνείηαζ ιεβάθδ αφλδζδ ηςκ εζζαβςβχκ ηδξ Δθθάδαξ απυ Αθαακία ηαζ 335

336 αημθμοεμφκ δ Ηηαθία ηαζ Σμονηία ηαζ δ Κφπνμξ, εκχ ιέπνζ ημ 2008 δ πνχηδ πχνα ήηακ δ Ηηαθία ηαζ αημθμοεμφζακ δ Σμονηία ηαζ δ Ηζπακία. φιθςκα ιε ηα απμηεθέζιαηα εηηίιδζδξ ηςκ ζπεηζηχκ δεζηηχκ ζηδκ πανμφζα ενβαζία, δζαπζζηχκμοιε υηζ δ αβμνά ηδξ Δ.Δ.-27 είκαζ ζδζαίηενα απαζηδηζηή ηαζ ζοκεπχξ ελεθζζζυιεκδ, ακηαβςκζζηζηά. οκμρίγμκηαξ, εα θέβαιε υηζ δ εθθδκζηή ηζζπμφνα παναηηδνίγεηαζ απυ ζηακμπμζδηζηυ ααειυ ακηαβςκζζηζηυηδηαξ ζε ανηεηέξ απυ ηζξ οπυ ιεθέηδ εζζαβςβζηέξ αβμνέξ. ζμκ αθμνά ζηδκ ακάθοζδ ηςκ ακηαβςκζζηζηχκ - ελαβςβζηχκ πςνχκ, δ Σμονηία, ζοκζζηά ιζα ζμαανή απεζθή βζα ηζξ εθθδκζηέξ ελαβςβέξ ηζζπμφναξ. Ζ παιδθυηενδ ηζιή πμο ζοκήεςξ ζοκμδεφεζ ηδκ ημονηζηή ηζζπμφνα, δζαθαίκεηαζ υηζ απμηεθεί ημ ζδιακηζηυηενμ πανάβμκηα βζα ηδ ζοκεπή αεθηίςζδ ηδξ ακηαβςκζζηζηήξ εέζδξ ηδξ πχναξ αοηήξ έκακηζ ηςκ εθθδκζηχκ ελαβςβχκ. οκεπχξ, μζ εθθδκζηέξ ελαβςβέξ εα πνέπεζ κα πνμζακαημθζζημφκ ζε εκαθθαηηζηέξ ζηναηδβζηέξ, μζ μπμίεξ εα ζημπεφμοκ ζηδ αεθηίςζδ ηδξ ακηαβςκζζηζηυηδηαξ, πςνίξ κα εζηζάγμοκ ζηδκ ηζιή αοηή ηαε αοηή αθθά ζε δζαδζηαζίεξ πμο εα αεθηζχκμοκ ηδκ ηαηακαθςηζηή αλία, εηπθδνχκμκηαξ έηζζ ηαθφηενα ηζξ ζοκεπχξ ιεηαααθθυιεκεξ απαζηήζεζξ ηςκ εονςπαίςκ πεθαηχκ ημοξ. Χξ ηέημζεξ εα ιπμνμφζακ κα εεςνδεμφκ δ επελενβαζία ηαζ δ ιεηαπμίδζδ ηςκ αθζεοηζηχκ πνμσυκηςκ, δζαδζηαζίεξ πμο πνμζδίδμοκ ακηαβςκζζηζηυ πθεμκέηηδια, ζηζξ πχνεξ πμο ηζξ οζμεεημφκ. φιθςκα ιε ημοξ Πμθφιενμξ, K. ηαζ Αναακζημβζάκκδξ, Η.,2003, μ πνμζακαημθζζιυξ ζηδκ πεναζηένς ακάπηολδ ιεηαπμζδηζηχκ δναζηδνζμηήηςκ, δ αεθηίςζδ ηςκ θεζημονβζχκ ημο ιάνηεηζκβη βεκζηυηενα, ζε ζοκδοαζιυ ιε ηδκ εθανιμβή ζοζηδιάηςκ δζαζθάθζζδξ πμζυηδηαξ, απμηεθεί ηδ δοκαιζηυηενδ ακηίδναζδ, εκυρεζ ηςκ εονςπασηχκ ηαζ δζεεκχκ πνμηθήζεςκ. Λαιαάκμκηαξ οπυρδ επίζδξ, υηζ μ ημιέαξ ηδξ ζοθθεηηζηήξ αθζείαξ ακηζιεηςπίγεζ ηα ηεθεοηαία πνυκζα ημ μλφ πνυαθδια ηδξ οπεναθίεοζδξ, δ ακάπηολδ ηςκ οδαημηαθθζενβεζχκ ζοκζζηά έκα πμθφ ζμαανυ εέια βζα ηδκ ακάπηολδ, ηδξ υπμζαξ ιαξ μζημκμιίαξ αθθά ηαζ ηδ δζαζθάθζζδ ηδξ αεζθμνζηήξ δζαπείνζζδξ ημο οδάηζκμο πενζαάθθμκημξ. Βηβιηνγξαθία Λζυθζμο, Μ. (2009). Γζενεφκδζδ ηδξ ακηαβςκζζηζηυηδηαξ ηδξ εθθδκζηήξ ηζζπμφναξ ζηδκ αβμνά ηδξ Δονςπασηήξ Έκςζδξ. Μεηαπηοπζαηή δζαηνζαή. Σιήια Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ, Πακεπζζηήιζμ Θεζζαθίαξ, Βυθμξ, ζεθ Λζυθζμο, Μ., Πμθφιενμξ, Κ. ηαζ Καηναηοθίδδξ, Κ., (2010). ''H δοκαιζηή ηςκ εθθδκζηχκ ελαβςβχκ πνμσυκηςκ γςζηήξ πνμέθεοζδξ ζηδκ αβμνά ηδξ Δ.Δ''. Πναηηζηά 10μο Πακεθθδκίμο οκεδνίμο Αβνμηζηήξ Οζημκμιίαξ, Θεζζαθμκίηδ, Δηδυζεζξ Γνάθδια, ζεθ Καναβημφκδξ Υν. (2011). Οζ πνμμπηζηέξ ηςκ εθθδκζηχκ αθζεοηζηχκ πνμσυκηςκ ζηδκ αβμνά ηδξ Δονςπασηήξ Έκςζδξ. Μεηαπηοπζαηή δζαηνζαή, Σιήια Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ, Πακεπζζηήιζμο Θεζζαθίαξ, Βυθμξ, ζεθ. 39 Καναβημφκδξ, Υ. ηαζ Πμθφιενμξ Κ., (2012). ''Γζενεφκδζδ ηδξ ακηαβςκζζηζηυηδηαξ ηδξ εθθδκζηήξ ηζζπμφναξ ζηδκ αβμνά ηδξ Δονςπασηήξ Έκςζδξ''. Πναηηζηά 11μο Πακεθθδκίμο οκεδνίμο Αβνμηζηήξ Οζημκμιίαξ, Θεζζαθμκίηδ. Πμθφιενμξ, K. ηαζ Αναακζημβζάκκδξ, Η. (2003). ''Μεηαπμίδζδ-Γζαηίκδζδ ηαζ Διπμνία Αθζεοηζηχκ Πνμσυκηςκ''. Πναηηζηά 1μο Πακεθθδκίμο οκεδνίμο Τδνμαζμθμβίαξ Αθζείαξ, (Αθζείαοδαημηαθθζένβεζεξ ακηζηνμουιεκεξ ή πανάθθδθεξ δναζηδνζυηδηεξ. Πμθφιενμξ, K., Λμΐγμο, Δ. Καζ Σζαηζνίδμο, Δ. (2005). ''Δηηίιδζδ Γεζηηχκ Ακηαβςκζζηζηυηδηαξ ηςκ Δθθδκζηχκ Αθζεοηζηχκ Πνμσυκηςκ''. Πναηηζηά 8μο Πακεθθδκίμο οκεδνίμο Αβνμηζηήξ Οζημκμιίαξ, Δηδυζεζξ Αβνμηφπμξ α.ε., ζεθ Πμθφιενμξ, K., Σζαηζνίδμο, Δ. ηαζ Καηναηοθίδδξ, Κ., (2005). ''Δηηίιδζδ ηςκ Μενζδίςκ Αβμνάξ ηςκ Δθθδκζηχκ Δλαβςβχκ Αθζεοηζηχκ Πνμσυκηςκ ζηδκ Αβμνά ηδξ Δ.Δ.''. Πναηηζηά 2μο Πακεθθδκίμο οκεδνίμο Τδνμαζμθμβίαξ Αθζείαξ, (Πνμηθήζεζξ ηαζ Πνμμπηζηέξ ζημ Μάνηεηζκβη ηαζ ζηδκ Σεπκμθμβία ηςκ Ηπεοδνχκ). Δηδυζεζξ Δκηοπχζεζξ, ζεθ Σζαηθαβηάκμξ Α., (2004). Βαζζηέξ ανπέξ ημο Μάνηεηζκβη. Θεζζαθμκίηδ: Δηδυζεζξ Αδεθθχκ Κονζαηίδδ. Balassa B.,(1965). Trade liberalization and revealed comparative advantage. The Manchester School of Economic and Social Studies. 1,

337 HydroMedit 2014, November 13-15, Volos, Greece Havrila, I. and Gunawardana P. (2003). Analysing Comparative Advantage and Competitiveness: an Application to Australia s Textile and Clothing Industries. Australian Economic Papers, 42(1), Kaimakoudi, E., Polymeros K. and Batzios Ch., (2014). ''Investigating export performance of Balkan and Eastern European fisheries sector''elsevier, Procedia Economics and Finance. Reference: FINE576. DOI: /S (14) (2014), pp The Economies of Balkan and Eastern Europe Countries in the Changed World (EBEEC 2013). Karagounis, C. and Polymeros K., (2011). Investigating the competitiveness of Greek sea bass in the E.U. market. Proceedings of the 4th International Symposium on Hydrobiology and Fisheries, p Kim, D. and Marion, B. W. (1997). Domestic Market Structure and Performance in Global Markets: Theory and Empirical Evidence from U.S. Food Manufacturing Industries, Review of Industrial Organization 12: Lee, J. (1995). Comparative Advantage in Manufacturing as a Determinant of Industrialization: the Korean Case. World Development, 23(7): Polymeros K. and Κatrakilidis Κ. (2008). The Dynamic Characteristics of Competitiveness in the E.U Fish Market. The International Journal of Economic Issues, Volume 1, (1), pp Polymeros K., Mattas K. and E. Tsakiridou, (2005). Assessing the Competitiveness of E.U Mediterranean Fisheries and Aquaculture Industries. 95th Seminar of the European Association of Agricultural Economists (EAAE), The Economics of Aquaculture with Respect to Fisheries, Civitavecchia (Rome). Porter, M. (1998). The Competitive Advantage of Nations: with a new introduction. London: Macmillan Press, pp 11-15, 33-39, Δζζαβςβέξ ηαζ Δλαβςβέξ πνμσυκηςκ απυ ηαζ πνμξ ηδκ Δ.Δ.-27. (Πνυζααζδ Μάνηζμξ-Απνίθζμξ 2014). ΠΑΡΑΡΣΗΜΑ Πίνακασ 1. Δείκτησ RXCA ςτην αγορά τησ Ιταλίασ και τιμζσ τςιποφρασ ςτην Ιταλία ΔΕΙΚΣΗ RCXA ITAΛΙΑ TIME ΙΣΑΛΙΑ ΕΛΛΑΔΑ Ι ΠΑΝΙΑ ΓΑΛΛΙΑ ΣΟΤΡΚΙΑ ΟΛΛΑΝΔΙΑ ΚΡΟΑΣΙΑ ,88 0,28 0,18 0,46 0,01 0, ,37 0,35 0,19 0,31 0,01 0, ,38 0,41 0,17 0,49 0,01 0, ,41 0,40 0,15 0,83 0, ,26 0,28 0,19 0,85 0, ,48 0,29 0,19 1,48 0,01 1, ,78 0,26 0,23 1,09 0,11 1, ,17 0,30 0,16 1,83 0,06 0, ,42 0,33 0,22 2,14 0,08 0, ,18 0,38 0,26 2,31 0,04 1, ,92 0,29 0,22 3,47 0,15 1, ,67 0,29 0,25 3,04 0,22 0, ,60 0,33 0,20 2,77 0,19 1, ,90 0,28 0,23 2,95 0,13 1,13 MAX ,78 0,41 0,23 1,83 0,11 1,15 MIN ,88 0,26 0,15 0,31 0,01 0,20 ΜΟ ,33 0,33 0,19 1,07 0,06 0,67 ΜΕΤΑΒΟΛΗ % ,19 6,58-8,87 298,43 923,29 299,55 TYΠ. ΑΠΟΚΛΙΣΗ MAX MIN ΜΟ ΜΕΤΑΒΟΛΗ % TYΠ. ΑΠΟΚΛΙΣΗ ΜΑΛΣΑ 7,40 6,88 8,38 7,16 5,91 4,53 6,45 6,01 5,98 5,65 5,07 4,72 4,25 4,26 8,38 4,53 6,46-18,79 0,26 3,42 2,60 3,01 0,06 0,38 0,28 0,33 0,02 0,26 0,20 0,23 0,53 3,47 2,14 2,81 0,04 0,22 0,04 0,13 0,33 1,16 0,73 0,94 1,15 5,98 4,25 5,11-15,15-15,47 3,50 37,77 72,74 54,84-28,72 0,31 0,04 0,02 0,49 0,07 0,18 0,72 ΕΛΛΑΔΑ Ι ΠΑΝΙΑ ΓΑΛΛΙΑ ΣΟΤΡΚΙΑ ΟΛΛΑΝΔΙΑ ΚΡΟΑΣΙΑ ΜΑΛΣΑ ,51 8,99 4,76 4,12 5,06 3,91 3, ,70 7,99 5,89 3,56 4,73 3,27 2, ,64 8,30 6,99 3,28 4,30 3,47 2, ,69 8,85 6,98 3,37 3,31 4,10 3, ,31 8,94 6,55 4,45 4,21 4,25 5, ,25 7,39 6,45 3,64 7,77 4,53 4, ,30 7,73 7,18 3,58 6,73 4,37 4, ,03 7,88 8,41 3,44 7,35 4,85 4, ,37 8,69 8,67 2,84 7,09 4,53 3, ,76 9,55 7,16 3,18 6,89 4,30 3, ,30 10,51 9,32 3,74 7,67 4,49 4, ,02 10,27 9,06 4,69 8,28 4,97 4, ,18 10,77 9,06 3,53 6,71 4,61 4, ,13 11,11 10,54 3,86 6,02 4,71 4,23 MAX ,51 8,99 8,41 4,45 7,77 4,85 5,07 MIN ,64 7,39 4,76 3,28 3,31 3,27 2,62 ΜΟ ,07 8,19 6,59 3,86 5,54 4,06 3,85 ΜΕΤΑΒΟΛΗ % ,70-12,32 76,57-16,60 45,31 24,10 32,95 MAX MIN ΜΟ ΜΕΤΑΒΟΛΗ % ,02 3,37 4,19 11,11 8,69 9,90 10,54 7,16 8,85 4,69 2,84 3,76 8,28 6,02 7,15 4,97 4,30 4,63 4,86 3,26 4,06 22,40 27,91 21,59 35,96-15,10 3,84 30,05 Πίνακασ 2. Δείκτησ RXCA ςτην αγορά τησ Γαλλίασ και τιμζσ τςιποφρασ ςτην Γαλλία 337

338 ΔΕΙΚΣΗ RCXA ΓΑΛΛΙΑ TIME ΓΑΛΛΙΑ ΕΛΛΑΔΑ ΙΣΑΛΙΑ ΙΠΑΝΙΑ ΣΟΤΡΚΙΑ ΟΛΛΑΝΔΙΑ ΚΡΟΑΣΙΑ ΜΑΛΣΑ ΕΛΛΑΔΑ ΙΣΑΛΙΑ ΙΠΑΝΙΑ ΣΟΤΡΚΙΑ ΟΛΛΑΝΔΙΑ ΚΡΟΑΣΙΑ ΜΑΛΣΑ ,03 0,74 3,59-0, ,39 6,71 5,73-5, ,71 0,03 2,14-0, ,32 5,53 5,59-4, ,27 0,23 1,86 0,57 0, ,43 5,24 5,95 4,57 5, ,01 0,28 2,26-0, ,07 4,70 5,77-3, ,74 0,28 1,95-0, ,89 4,47 5,62-4, ,71 1,12 2,31-0, ,62 4,80 5,09-7, ,27 0,55 2,30-0, ,09 5,24 5,00-6, ,23 0,32 2,56-0, ,28 8,08 5,38-4, ,32 1,67 2,34 7,89 0, ,32 7,33 4,34 2,92 3, ,79 1,74 2,97-0, ,63 5,01 3,92-4, ,97 2,03 3,10 9,27 0, ,14 4,79 4,49 4,14 4, ,85 2,56 2,30-0, ,14 5,73 5,19-5, ,99 1,88 2,84 23,95 0, ,71 4,23 5,20-4,61-3, ,38 3,57 3,32 6,97 0, ,57 4,64 4,84 3,99 4, MAX ,03 1,12 3,59 0,57 0, MAX ,39 8,08 5,95 4,57 7, MIN ,23 0,03 1,86 0,57 0, MIN ,32 4,47 5,00 4,57 3, ΜΟ ,63 0,57 2,73 0,57 0, ΜΟ ,35 6,27 5,48 4,57 5, ΜΕΤΑΒΟΛΗ % ,79-56,99-28, , ΜΕΤΑΒΟΛΗ % ,50 20,48-6, , TYΠ. ΑΠΟΚΛΙΣΗ ,89 0,34 0,54-0,20 MAX ,97 3,57 3,32 23,95 0, MAX ,14 7,33 5,20 4,14 5,95 MIN ,99 1,67 2,30 6,97 0, MIN ,32 4,23 3,92 2,92 3, ΜΟ ,48 2,62 2,81 15,46 0, ΜΟ ,23 5,78 4,56 3,53 4,71 ΜΕΤΑΒΟΛΗ % ,08 113,41 41,77-11,68 229, TYΠ. ΑΠΟΚΛΙΣΗ ,10 0,72 0,41 8,01 0, ΜΕΤΑΒΟΛΗ % ,49-36,64 11,40 36,54 22, Πίνακασ 3. Δείκτησ RXCA ςτην αγορά τησ Πορτογαλίασ και τιμζσ τςιποφρασ ςτην Πορτογαλία ΔΕΙΚΣΗ RCXA ΠΟΡΣΟΓΑΛΙΑ TIME ΠΟΡΣΟΓΑΛΙΑ ΕΛΛΑΔΑ ΙΣΑΛΙΑ ΓΑΛΛΙΑ ΙΠΑΝΙΑ ΣΟΤΡΚΙΑ ΟΛΛΑΝΔΙΑ ΚΡΟΑΣΙΑ ΜΑΛΣΑ ΕΛΛΑΔΑ ΙΣΑΛΙΑ ΓΑΛΛΙΑ ΙΠΑΝΙΑ ΣΟΤΡΚΙΑ ΟΛΛΑΝΔΙΑ ΚΡΟΑΣΙΑ ΜΑΛΣΑ ,80 0,64-0, ,43 4,58-4, ,63-1,26 0, ,93-4,09 4, , , , , ,76-0,07 0, ,69-6,62 3, ,10-0,06 0, ,56-5,89 4, ,70 0,03 0,17 0, ,94 3,94 4,80 4,29-4, ,80 0,12 0,01 0, ,87 4,27 17,64 4, ,78-3,96 0, ,14-3,84 4, ,54-3,23 1, ,41-3,91 3, ,76-0,34 0,98 4, ,61-8,85 3,69 2, ,53-0,22 1, ,88-10,42 4, ,02-0,91 0,99 10, ,91-6,77 5,14 3, ,36-2,05 0,92 7, ,25-5,93 4,86 3, ,18 0,02 1,10 0,90 4,57-6, ,19 3,79 4,72 4,51 3,38-3,59 - MAX ,80 0,64 3,96 0, MAX ,56 4,58 17,64 4, MIN ,63 0,03 0,01 0, MIN ,62 3,94 3,84 3, ΜΟ ,21 0,33 1,99 0, ΜΟ ,09 4,26 10,74 4, ΜΕΤΑΒΟΛΗ % , , ΜΕΣΑΒΟΛΗ % , , TYΠ. ΑΠΟΚΛΙΣΗ ,99 0,33 1,56 0, MAX ,18 0,02 3,23 1,09 10, MAX ,91 3,79 10,42 5,14 3, MIN ,53 0,02 0,22 0,90 4, MIN ,41 3,79 3,91 3,69 2,91 - ΜΟ ,35 0,02 1,72 0,99 7, ΜΟ ,16 3,79 7,16 4,41 3,35 - ΜΕΤΑΒΟΛΗ % ΜΕΤΑΒΟΛΗ % , ,00-12, ,01-20,80 20,50 - TYΠ. ΑΠΟΚΛΙΣΗ ,63-1,15 0,07 2, Πίνακασ 4. Δείκτησ RXCA ςτην αγορά του Ηνωμζνου Βαςιλείου και τιμζσ τςιποφρασ ςτο Ηνωμζνο Βαςίλειο 338

339 ΔΕΙΚΣΗ RCXA ΑΓΓΛΙΑ TIME ΑΓΓΛΙΑ ΕΛΛΑΔΑ ΙΣΑΛΙΑ ΓΑΛΛΙΑ ΙΠΑΝΙΑ ΣΟΤΡΚΙΑ ΟΛΛΑΝΔΙΑ ΚΡΟΑΣΙΑ ΜΑΛΣΑ ,39-2, , ΕΛΛΑΔΑ ΙΣΑΛΙΑ ΓΑΛΛΙΑ ΙΠΑΝΙΑ ΣΟΤΡΚΙΑ ΟΛΛΑΝΔΙΑ ΚΡΟΑΣΙΑ ΜΑΛΣΑ ,25-1, , ,81-7, , ,36 0,13 1, , ,61-5, , ,00-1, , ,04 5,62 5, , ,68 0,09 1, ,58-4,76 1,65-4, ,48 0,26 1,39 0,03-0, ,30 6,75 5, ,69-1,67 0,11-0, ,50 4,19 5,60 4,75-4, ,10 2,02 2,48 0,06-0, ,81-5,89 4,80-4, ,19 1,75 1, , ,01 3,18 5,14 4,49-3, ,82 1,92 2,98 0,06 2,62 2, ,50 2,78 3, , ,08 2,15 2,00 0,21 7,53 2, ,84 3,32 4,04 4,70 3,59 3, ,95 2,28 1,88 0,47 12,25 1, ,42 3,97 4,42 4,41 3,84 4, ,11 1,07 1,69 0,22 5,64 1, ,58 4,65 5,58 5,85 4,16 5, ,36 2,05 1,85 0,68 3,70 2, ,56 3,64 6,76 5,23 4,54 4, MAX ,39 2,02 2,48 0,11-1, ,41 4,11 4,45 4,44 5,31 4, MIN ,68 0,09 1,14 0,03-0, MAX ,81 6,75 7,21 4,80 0,00 5, ΜΟ ,53 1,06 1,81 0,07-0, MIN ,50 3,18 4,76 1,65 0,00 3, ΜΕΤΑΒΟΛΗ % ,45-14, , ΜΟ ,66 4,96 5,99 3,22 0,00 4, TYΠ. ΑΠΟΚΛΙΣΗ ,17 0,93 0,44 0,04-0,46 MAX ,36 2,28 2,98 0,68 12,25 2, ΜΕΤΑΒΟΛΗ % , , , MIN ,82 1,07 1,69 0,06 2,62 1, MAX ,58 4,65 6,76 5,85 5,31 5, ΜΟ ,09 1,68 2,33 0,37 7,43 1, MIN ,41 2,78 3,98 4,41 3,59 3, ΜΕΤΑΒΟΛΗ % ,69 16,98-0, , ΜΟ ,50 3,71 5,37 5,13 4,45 4, TYΠ. ΑΠΟΚΛΙΣΗ ,96 0,43 0,47 0,25 3,79 0, ΜΕΤΑΒΟΛΗ % ,65 47,73 11, , Πίνακασ 5. Δείκτησ RXCA ςτην αγορά τησ Ιςπανίασ και τιμζσ τςιποφρασ ςτην Ιςπανία ΔΕΙΚΣΗ RCXA IΠΑΝΙΑ TIME ΙΠΑΝΙΑ ΕΛΛΑΔΑ ΓΑΛΛΙΑ ΙΣΑΛΙΑ ΣΟΤΡΚΙΑ ΟΛΛΑΝΔΙΑ ΜΑΛΣΑ ΚΡΟΑΣΙΑ ΕΛΛΑΔΑ ΓΑΛΛΙΑ ΙΣΑΛΙΑ ΣΟΤΡΚΙΑ ΟΛΛΑΝΔΙΑ ΜΑΛΣΑ ΚΡΟΑΣΙΑ ,93 0,61 0, ,84 1,94 1, ,93 1,14 0,35 32, ,57 1,61 50,21 3, ,35 0,57 3, , ,83 2,11 2, , ,61 0,48 0, ,89 3,92 1, ,12 0,64 0,14 148, ,69 8,84 1,27 4,28 2, ,93 0,37 0, , ,63 15,63 3, , ,99 0,13 0,05-0, ,07 7,42 1,98-6, ,70 0,87 0,38 27,93 0, ,97 0,78 2,01 3,62 4, ,62 0,56 0,30 16,67 0, ,43 39,34 2,33 3,13 5, ,16 0,27 0,08 3,09 0, ,67 25,54 3,87 3,46 6, ,89 0,20 0,04 2,76 0, ,22 27,07 1,77 3,90 4, ,03 0,18 0,03 11,87 0, ,29 17,31 3,80 4,78 6, ,90 0,89 0,02 91, ,95 21,59 4,01 3, ,91 0,39-18,78 0, ,14 21,99-3,86 1, MAX ,93 1,14 3,30 148,95 0, MAX ,07 15,63 50,21 4,28 6, MIN ,35 0,13 0,05 27,93 0,20 - MIN ,83 0,78 1,22 3,41 2, ΜΟ ,14 0,63 1,68 88,44 0, ΜΟ ,45 8,20 25,72 3,84 4, ΜΕΤΑΒΟΛΗ % ΜΕΤΑΒΟΛΗ % ,55 43,17 20, ,02-59,81 64, TYΠ. ΑΠΟΚΛΙΣΗ ,53 0,31 1,10 68,70 0, MAX ,16 0,89 0,30 91,78 0, MAX ,29 39,34 4,01 4,78 6, MIN ,90 0,18 0,02 2,76 0, MIN ,43 17,31 1,77 3,13 1, ΜΟ ,03 0,53 0,16 47,27 0, ΜΟ ,36 28,33 2,89 3,95 3, ΜΕΤΑΒΟΛΗ % ,78-29,97-12,66-68, TYΠ. ΑΠΟΚΛΙΣΗ ,06 0,27 0,12 33,80 0, ΜΕΤΑΒΟΛΗ % ,60-44,11-23,53-72, Πίνακασ 6. Δείκτησ RXCA ςτην αγορά τησ Ρουμανίασ και τιμζσ τςιποφρασ ςτην Ρουμανία 339

340 ΔΕΙΚΣΗ RCXA ΡΟΤΜΑΝΙΑ TIME ΡΟΤΜΑΝΙΑ ΕΛΛΑΔΑ ΙΣΑΛΙΑ ΓΑΛΛΙΑ ΙΠΑΝΙΑ ΣΟΤΡΚΙΑ ΟΛΛΑΝΔΙΑ ΚΡΟΑΣΙΑ ΜΑΛΣΑ ,26 109, ΕΛΛΑΔΑ ΙΣΑΛΙΑ ΓΑΛΛΙΑ ΙΠΑΝΙΑ ΣΟΤΡΚΙΑ ΟΛΛΑΝΔΙΑ ΚΡΟΑΣΙΑ ΜΑΛΣΑ ,88-12,28-28, , ,18-9,07-7, ,15-9,07-5, ,15-11, ,20-3, ,09-1, ,82-7, ,45 0,07 0, , ,79-8, ,90 0,04 0, , ,66 8,20 11, , ,48 0,35 0, , ,77 5,03 12, , ,52 1,59 0, , ,30 4,13 5, , ,00 0,86 0,02-4, ,67 3,64 3, , ,71 0,20 0,03-3, ,25 3, , ,04 0,26 0,08-4, ,68 4, , ,58 0, , ,65 5, , ,33 0,42 0,22-4,83-7, ,55 7, , MAX ,48 0,35 12,28-109,22 1, ,33 5,33 5,39-3,96-5,22 - MIN ,18 0,04 0,13-7,35 0, MAX ,15 8,20 12,15-5,61 12, ΜΟ ,83 0,20 6,20-58,29 0, MIN ,30 4,13 5,39 0,00 3,57 4, ΜΕΤΑΒΟΛΗ % , , ΜΟ ,72 6,17 8,77-4,59 8, TYΠ. ΑΠΟΚΛΙΣΗ ,24 0,17 5,63-53,80 0, MAX ,00 1,59 0,64-4, ΜΕΤΑΒΟΛΗ % , , MIN ,58 0,09 0,02-3, MAX ,65 7,42 5,39 0,00 4,84 8, ΜΟ ,29 0,84 0,33-4, MIN ,67 3,64 3,68 0,00 3,38 8, ΜΕΤΑΒΟΛΗ % ,59-73,81-65, ΜΟ ,66 5,53 4,54 0,00 4,11 8, TYΠ. ΑΠΟΚΛΙΣΗ ,51 0,57 0,26-0, ΜΕΤΑΒΟΛΗ % ,85 46,63 46, Πίνακασ 7. Δείκτησ RXCA ςτην αγορά τησ Γερμανίασ και τιμζσ τςιποφρασ ςτην Γερμανία ΔΕΙΚΣΗ RCXA ΓEΡΜΑΝΙΑ TIME ΓΕΡΜΑΝΙΑ ΕΛΛΑΔΑ ΙΣΑΛΙΑ ΓΑΛΛΙΑ ΙΠΑΝΙΑ ΣΟΤΡΚΙΑ ΟΛΛΑΝΔΙΑ ΚΡΟΑΣΙΑ ΜΑΛΣΑ ΕΛΛΑΔΑ ΙΣΑΛΙΑ ΓΑΛΛΙΑ ΙΠΑΝΙΑ ΣΟΤΡΚΙΑ ΟΛΛΑΝΔΙΑ ΚΡΟΑΣΙΑ ΜΑΛ ,83 11,63 3,29 1,41-0, ,82 6,35 8,34 8,40-4, ,31 11,60 2,31 0,23-0, ,15 6,19 7,35 5,67-5, ,76 11,51 1,03 0,11-0, ,33 5,62 6,82 4,35-5, ,37 13,31 1,14 0,28 0,91 0, ,15 5,61 6,04 5,67 5,95 5, ,90 16,70 1,36 0,19 29,78 0,17-0, ,83 5,93 6,80 5,78 5,89 5, ,73 10,26 1,05 0,14 16,96 0, ,53 5,85 6,68 5,36 4,41 5, ,93 10,50 1,26 0,38-0, ,91 6,23 6,67 5,73-5, ,67 9,44 1,84 2,13-0, ,50 5,37 6,77 6,76-5, ,90 6,91 1,24 0,76 1,99 0, ,71 4,55 6,56 6,05 2,64 5, ,27 5,62 1,97 0,98 6,65 0, ,17 4,85 3,72 5,58 4,06 5, ,36 5,30 1,64 0,53 12,51 0, ,67 5,49 6,37 6,77 4,58 5, ,24 5,11 1,64 0,95 8,49 0, ,80 6,30 8,38 7,48 4,96 7, ,45 2,46 1,07 0,86 10,55 0, ,21 5,46 8,50 7,13 3,43 4, ,53 5,95 0,99 0,23 10,62 1, ,66 5,99 8,21 6,59 3,70 4, MAX ,76 16,70 3,29 2,13 29,78 0,25-0,27 MAX ,82 6,35 8,34 8,40 5,95 5, MIN ,93 9,44 1,03 0,11 0,91 0, MIN ,15 5,37 6,04 4,35 4,41 4, ΜΟ ,84 13,07 2,16 1,12 15,35 0, ΜΟ ,99 5,86 7,19 6,38 5,18 5, ΜΕΤΑΒΟΛΗ % ,10-18,85-44,05 50,56-29, ΜΕΤΑΒΟΛΗ % ,69-15,42-18,84-19,56-19, TYΠ. ΑΠΟΚΛΙΣΗ ,84 2,27 0,79 0,75 14,46 0,04 MAX ,90 6,91 1,97 0,98 12,51 1, MAX ,80 6,30 8,50 7,48 4,96 7, MIN ,53 2,46 0,99 0,23 1,99 0, MIN ,71 4,55 3,72 5,58 2,64 4, ΜΟ ,71 4,69 1,48 0,61 7,25 0, ΜΟ ,76 5,43 6,11 6,53 3,80 5, ΜΕΤΑΒΟΛΗ % ,35-13,99-20,20-69,61 433,29 445, TYΠ. ΑΠΟΚΛΙΣΗ ,83 1,50 0,39 0,29 3,76 0, ΜΕΤΑΒΟΛΗ % ,51 31,56 25,19 8,85 39,88-19,

341 POSTERS 341

342 THEMATIC FIELD: AQUACULTURE 342

343 REFERENCE BLOOD PARAMETERS VALUES FOR SIBERIAN STURGEON, Acipenser baeri (Brandt) Zeynep Gülen 1, Hijran Yavuzcan Yildiz 1* 1 Department of Fisheries and Aquaculture, Ankara University, Ankara, Turkey Abstract The aim of the present study was to set up reference intervals for some blood parameters in Siberian sturgeon (Acipenser baeri). The reference values of blood parameters were assessed for hematocrit, blood cell counts (erytrocyte, total leucocyte and thrombocyte), differential leucocyte counts, prothrombin beginning and ending time, plasma glucose, plasma lactic acid, total plasma protein, plasma sodium, potassium, chloride, magnesium, calcium. In this study, hematological and biochemical reference ranges determined in the Siberian sturgeon (A. baeri) for the first time will make a significant contribution to monitor the health and physiological status of the fish. Key words: Siberian sturgeon, Acipenser baeri, blood parameters *Corresponding author: Yavuzcan Yildiz H (yavuzcan@ankara.edu.tr) Introduction Sturgeon species (Acipenseridae) are considered to be potential candidates for commercialization and species diversification in aquaculture. Along with a well-established North American species, i.e. white sturgeon (Acipenser transmontanus), Siberian sturgeon (Acipenser baeri) has also proven to be a potential candidate for aquaculture (Rad et al., 2003). Siberian sturgeon (A. baeri) is not an anadromous fish. This non-migrating freshwater species has shown a good growth performance in many types of production system and in tanks of different size and shape and is capable of reaching sexual maturity in captivity (Köksal et al., 2000). Hematological parameters of fish are closely related to the response of fish to environmental and biological factors. In response to ecological and physiological conditions, major changes occur in the fish blood composition (Zarejabad et al., 2009). Blood variables are a useful measure of physiological disturbances in intensively farmed fishes and can provide important information for diagnosis and prognosis of diseases. Therefore, haematological evaluation is gradually becoming a routine practice for determining the health status of intensively bred fishes (Tavares Dias and Moraes, 2007). Currently, the use of diagnostic clinical pathology tests is limited in aquatic veterinary medicine because of the lack of standard techniques and reliable reference values for most fish species. Differences in sampling technique and test methodology may generate variable results (Knowles et al., 2006). In order to indicate the reliability of an estimate, the results of measurements were accompanied by confidence intervals in the present study. Hence, the reference intervals were calculated according to recommendations of the International Federation of Clinical Chemistry, as stated by Solberg (2004). Siberian sturgeon (A. baeri), have been successfully adapted to the conditions of Central Anatolia, Turkey in intensive aquaculture and it was stated that this species is also less demanding than many other cultured species in terms of water quality parameters (Köksal et al., 2000). Although some blood parameters in clinically healthy Siberian sturgeon (A. baeri) were assessed by Köksal et al. (1999), reference intervals for some blood parameters hasn t established yet. The aim of the present study was to determine reference intervals for hematological and biochemical reference ranges determined in the Siberian sturgeon (A. baeri). Hence, in this study hematological and biochemical reference ranges for hematocrit, blood cell counts (erytrocyte, total 343

344 leucocyte and thrombocyte), differential leucocyte counts, prothrombin beginning and ending time, plasma glucose, plasma lactic acid, total plasma protein, plasma sodium, potassium, chloride, magnesium, calcium determined in the Siberian sturgeon (A. baeri) for the first time. Material and methods Fish Siberian sturgeon (A. baeri) sampled were in Cifteler - Sakaryabasi Fish Production and Research Station of Ankara University. Twenty-three clinically healthy individuals of similar age (14 years old), total length (102 ± 9,26 cm), weight (5.44 ± 0,5 kg) were selected to blood sampling. Groups of fish were netted calmly in <15 s from the experimental tank to an anesthetic bath. After approximately 1 min in the bath the fish were immediately sampled (Roque et al., 2010). Water temperature was 21,5 22 C, ph 5,5 6,5 and dissolved oxygen 5,80 6,00 mg lt -1. Blood sampling Blood samples were drawn by cardiac puncture into heparinized syringes for the analysis to be performed (Kolman et al., 2000). Non-heparinized syringes were used only for the prothrombin time analysis. Plasma was seperated after centrifugation at 8800 rpm in 10 min and frozen until analysis. Analytical procedures Hematocrit measurements were made immediately by drawing samples of blood into heparinized capillary tubes and centrifuging at rpm in 4 min (Siwicki and Anderson, 1993). The count of erytrocyte, total leucocyte and thrombocyte were enumerated in Neubauer hemacytometer, using Natt-Herrick solution. To estimate the differential leucocyte counts, blood smears were fixed and stained with May-Grunwald and Giemsa (Konuk, 1981). Prothrombin time was determined by the watch-glass method, as stated by Konuk (1981). Plasma glucose values were measured using the reference method (glucose hexokinase reagent). Plasma lactic acid was determined using commercial kits (manufactured by Roche) by the enzymatic / colorimetric method. Total plasma protein was determined by the biuret method using Gornall s biuret reagent (Siwicki and Anderson, 1993). Plasma sodium, potassium, chloride were determined using commercial kits (manufactured by Roche) by the ion-selective analysis (Roche Diagnostics GmbH, Mannheim). Plasma magnesium was determined using Atomic Absorption Spectrophotometer and plasma calcium was determined using Inductively Coupled Plasma Optical Emission Spectrometry by using commercial kits (PerkinElmer Inc., USA). Statistical analysis The reference intervals bounded by the 2.5th and 97.5th were calculated by means of nonparametric estimates, together with the 95% confidence intervals as the assumption of normal distribution of samples. Results and Discussion Reference intervals for some blood parameters were summarized for Siberian sturgeon (A. baeri) in Table 1 (n = 23). Hematological and biochemical can be used as an effective method for monitoring physiological and pathological changes in fish. Thus, in this study hematological and biochemical reference ranges determined in the Siberian sturgeon (A. baeri). 344

345 tial Leucocy te Count HydroMedit 2014, November 13-15, Volos, Greece In comparison with other Acipenserids, some values measured in the present study fell within the ranges, some of them were lower or higher than values reported in this study. Hematocrit values were similar to Adriatic sturgeon, Acipenser naccarii (Clementi et al., 1999) and Beluga sturgeon, Huso huso (Zarejabad et al., 2009; Hoseinifar et al., 2010). Erytrocyte count were similar to shortnose sturgeon, Acipenser brevirostrum (Knowles et al., 2006) and were lower than Beluga sturgeon, H. huso (Zarejabad et al., 2009; Hoseinifar et al., 2010). Leucocyte count were in agreement with the values determined for shortnose sturgeon, A. brevirostrum (Knowles et al., 2006; Matschel et al., 2013) and Beluga sturgeon, H. huso (Zarejabad et al., 2009; Hoseinifar et al., 2010). Thrombocyte count were lower than shortnose sturgeon, A. brevirostrum (Knowles et al., 2006). In Acipenserids, differential leucocyte count, for lymphocyte count the values were similar to Beluga sturgeon, H. huso (Zarejabad et al., 2009) and were higher than found in the same species by Hoseinifar et al. (2010). For monocyte count the values were similar to Beluga sturgeon, H. huso (Hoseinifar et al., 2010) and were higher than found in the same species by Zarejabad et al. (2009) and for shortnose sturgeon, A. brevirostrum (Matschel et al., 2013). For neutrophil count the values measured in this study were similar to shortnose sturgeon, A. brevirostrum (Matschel et al., 2013) and were lower than found in the same species (Knowles et al., 2006) and Beluga sturgeon, H. huso (Zarejabad et al., 2009; Hoseinifar et al., 2010). Eosinophil counts fell within the ranges found for shortnose sturgeon, A. brevirostrum (Knowles et al., 2006; Matschel et al., 2013) and Beluga sturgeon, H. huso (Hoseinifar et al., 2010). However, the values found by Zarejabad et al. (2009) who studied Beluga sturgeon, H. huso were lower than values reported in the present study. In biochemical parameters values, such as the plasma glucose level measured in this study were lower than Acipenserids such as shortnose sturgeon, A. brevirostrum (Knowles et al., 2006), Amur sturgeon, Acipenser schrenckii, Chinese sturgeon, Acipenser sinensis (Shi et al., 2006), Adriatic sturgeon, A. naccarii (Di Marco et al., 1999), cultured sturgeon hybrids, A. naccarii female A. baeri male (Di Marco et al., 2011), Beluga sturgeon, H. huso (Zarejabad et al., 2009; Hoseinifar et al., 2010). The total plasma protein level measured in our study were in agreement with the values determined for shortnose sturgeon, A. brevirostrum (Knowles et al., 2006), Amur sturgeon, A. schrenckii (Shi et al., 2006), Adriatic sturgeon, A. naccarii (Di Marco et al., 1999). However, the values of total plasma protein measured in our study were higher than Chinese sturgeon, A. sinensis (Shi et al., 2006) and Beluga sturgeon, H. huso (Hoseinifar et al., 2010). Conversely it was lower than cultured sturgeon hybrids, A. naccarii female A. Baeri Table 1 Reference values expressed as mean, standart deviation (SD) and 95% confidence interval for the estimated analytes in Siberian sturgeon (A. baeri). Analytes Mean (Χ) SD 95% confidence interval Skewness Kurtosis Hematocrit (% ) 26,02 9,11 14,71-37,33 0,224-1,590 Erythrocyte counts (x 10 6 µl -1 ) 0,66 0,21 0,50-0,81 1,411 2,506 Total Leucocyte counts (x 10 3 µl -1 ) 50,22 46,92 16,65-83,78 0,928-0,538 Lymphocyte counts (x 10 3 µl -1 ) 37,17 4,85 31,15-43,20-2,215 4,

346 Prothrombin time HydroMedit 2014, November 13-15, Volos, Greece Monocyte counts (x 10 3 µl -1 ) Neutrophil counts (x 10 3 µl -1 ) Eosinophil counts (x 10 3 µl -1 ) 9,50 4,68 3,68-15,31 1,656 3,485 4,44 2,95 0,78-8,09 2,205 4,891 1,58 2,83 0,00-5,10 2,151 4,683 Thrombocyte counts (x 10 3 µl -1 ) 17,07 11,89 8,56-25,58 1,317 2,520 Beginning (min) 2,03 1,16 0,81-3,25 2,000-0,769 Ending (min) 7,70 1,58 6,05-9,35 4,212-0,967 Plasma glucose (mg dl -1 ) 33,00 7,66 27,52-38,48-1,845 4,377 Plasma lactic acid (mg dl -1 ) 8,55 7,12 3,45-13,65 0,519-1,589 Total plasma protein (g dl -1 ) 3,52 1,80 2,23-4,81-0,437-1,135 Plasma sodium (meq l -1 ) 127,90 9,23 121,30-134,50-0,901 0,809 Plasma potassium (meq l -1 ) 2,73 0,78 2,17-3,29 1,712 3,147 Plasma chloride (meq l -1 ) 102,00 10,00 94,85-109,15-0,147 1,701 Plasma magnesium (mg dl -1 ) 2,89 1,00 1,96-3,81 0,823-0,487 Plasma calcium (mg dl -1 ) 21,95 17,25 9,61-34,29 1,406 1,540 male (Di Marco et al., 2011). The lactic acid level was higher than shortnose sturgeon, A. brevirostrum (Baker et al., 2005), was lower than cultured sturgeon hybrids, A. naccarii female A. baeri male (Di Marco et al., 2011), and was similar to Atlantic sturgeon, Acipenser oxyrinchus (Baker et al., 2005). In electrolytes levels such as sodium measured in this study was lower than Adriatic sturgeon, A. naccarii (Clementi et al., 1999; Di Marco et al., 1999), cultured sturgeon hybrids, A. naccarii female A. baeri male (Di Marco et al., 2011). Potassium levels was lower than shortnose sturgeon, A. brevirostrum (Knowles et al., 2006) and was higher than cultured sturgeon hybrids, A. naccarii female A. baeri male (Di Marco et al., 2011). The chloride level was lower than Adriatic sturgeon, A. naccarii (Clementi et al., 1999), shortnose sturgeon, A. brevirostrum (Knowles et al., 2006), Adriatic sturgeon, A. naccarii (Di Marco et al., 1999), cultured sturgeon hybrids, A. naccarii female A. baeri male (Di Marco et al., 2011). The magnesium level was in agreement with the values determined for shortnose sturgeon, A. brevirostrum (Knowles et al., 2006), Beluga sturgeon, H. huso (Asadi et al., 2006).However the level was lower than cultured sturgeon hybrids, A. naccarii female A. baeri male (Di Marco et al., 2011). The calcium level fell within the ranges found for Adriatic sturgeon, A. naccarii (Di Marco et al., 1999) and cultured sturgeon hybrids, A. naccarii female A. baeri male (Di Marco et al., 2011) and was higher than shortnose sturgeon, A. brevirostrum (Knowles et al., 2006), Beluga sturgeon, H. huso (Asadi et al., 2006). Some electrolyte levels measured in this study were lower than that of Acipenserids in the sea. The reason regarding the low levels of sodium, chloride and potassium is possibly related to that the Siberian sturgeon (A. baeri) is a freshwater fish. However, interestingly, plasma calcium level of the Siberian sturgeon (A. baeri) was higher than the other Acipenserids. 346

347 Hematological and biochemical reference ranges in the Siberian sturgeon (A. baeri) assessed in this study will make a significant contribution to monitor the health and physiological status of the Siberian sturgeon. References Asadi, F.; Halajian, A.; Pourkabir, M.; Asadian, P.; Jadidizadeh, F., 2006: Serum biochemical parameters of Huso huso. Journal of Comparative Clinical Pathology 15: Baker, D. W.; Wood, A, M.; Litvak, M, K.; Kieffer, J. D., 2005: Haematology of juvenile Acipenser oxyrinchus and Acipenser brevirostrum at rest and following forced activity. Journal of Fish Biology 66: Clementi, M. E.; Cataldiz, E.; Capo, C.; Petruzzelli, R.; Tellones, E.; Giardina, B., 1999: Purification and characterization of the hemoglobin components of Adriatic sturgeon (Acipenser naccarii) blood. Journal of Applied Ichthyology 15: Di Marco, P.; McKenzie, D.J.; Mandich A.; Bronzi, P.; Cataldi, E.; Cataudella, S., 1999: Influence of sampling conditions on blood chemistry values of Adriatic sturgeon Acipenser naccarii (Bonaparte, 1836). Journal of Applied Ichthyology 15: Di Marco, P.; Priori, A.; Finoia, M. G.; Petochi, T.; Longobardi, A.; Donadelli, V.; Marino, G., 2011: Assessment of blood chemistry reference values for cultured sturgeon hybrids (Acipenser naccarii female Acipenser baerii male). Journal of Applied Ichthyology 27: Hoseinifar, S. H.; Mirvaghefi, A.; Merrifield, D. L.; Amiri, B. M.; Yelghi, S.; Bastami, K. D., 2010: The study of some haematological and serum biochemical parameters of juvenile beluga (Huso huso) fed oligofructose. Fish Physiology and Biochemistry 37: Knowles, S.; Hrubec, T. C.; Smith, S. A.; Bakal, R. S., 2006: Hematology and plasma chemistry reference intervals for cultured shortnose sturgeon (Acipenser brevirostrum). Veterinary Clinical Pathology 35: Köksal, G.; Rad, F.; Kindir, M., 2000: Growth performance and feed conversion efficiency of Siberian sturgeon (Acipenser baeri) reared in concrete raceways. Turk Journal of Animal Science. 24: Köksal, G.; Yıldız, H. Y.; Rad, F.; Aydın, F.; Uysal, H., 1999: Blood parameters in sturgeon yearlings fed on rainbow trout diet with particular references to skeletal deformity. 9th International Conference European Assossiation of Fish Pathology. Kolman, H.; Kolman, R.; Siwicki, A. K., 2000: Non - specific defence mechanisms of russian sturgeon (Acipenser gueldenstaedti, Brandt) reared in cages. Archives of Polish Fisheries 8: Konuk, T., 1981: Pratik Fizyoloji 1 (in Turkish). Ankara University, Ankara, Turkey. Matsche, M. A.; Rosemary, K. M.; Brundage, H. M.; O Herron, J. C., 2013: Hematology and plasma chemistry of wild shortnose sturgeon Acipenser brevirostrum from Delaware River, USA. Journal of Applied Ichthyology 29: Rad, F.; Köksal, G.; Kindir, M., 2003: Growth performance and food conversion ratio of Siberian sturgeon (Acipencer baeri, Brandt) at different daily feeding rates. Turk Journal of Animal Science 27: Roque, A.; Yıldız, H. Y.; Carazo, I.; Duncan, N., 2010: Physiological stress responses of sea bass (Dicentrarchus labrax) to hydrogen peroxide (H 2 O 2 ) exposure. Aquaculture 304: Shi, X.; Li, D.; Zhuang, P.; Nie, F.; Long, L., 2006: Comparative blood biochemistry of Amur sturgeon, Acipenser schrenckii, and Chinese sturgeon, Acipenser sinensis. Fish Physiology and Biochemistry 32: Siwicki, A. K.; And Anderson, D. P., 1993: Immunostimulation in Fish: Measuring the Effects of Stimulants by Serological and Immunological Methods. Nordic Symposium on Fish Immunology. Solberg, H. E., 2004: The IFCC recommendation on estimation of reference intervals. The RefVal prog. Clinical Chemistry and Laboratory Medicine 42: Tavares Dias, M.; Moraes, F. R., 2007: Haematological and biochemical reference intervals for farmed channel catfish. Journal of Fish Biology 71: Zarejabad, M. A.; Jalali, M. A.; Sudagar, M. A.; Pouralimotlagh, S., 2009: Hematology of great sturgeon (Huso huso Linnaeus, 1758) juvenile exposed to brackish water environment. Fish Physiology and Biochemistry 36:

348 GILTHEAD SEABREAMS (Sparus aurata) WITH LORDOSIS DEFORMITY. WHAT ABOUT VERTEBRAS COLLAGEN FIBRILS? Berillis P. *, Karapanagiotidis I.T., Mente E. Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly. Abstract The development of skeletal deformities in seabream (Sparus aurata) farming affects their growth, survival and production costs. Research has shown that the distribution of collagen in different fish tissues might be correlated to their swimming behavior. This study investigates whether gilthead seabream with lordosis deformity showed collagen morphology abnormalities in their vertebras in comparison with those that did not show any skeletal deformities. Samples for decalcified vertebras of both groups were examined with transmission electron microscope and collagen micrographs were taken and analyzed. The results indicated that the fishes with lordosis had significant smaller mean vertebras collagen fibrils diameter than the controls. Further research to understand if skeletal deformities are linked to collagen fibril abnormalities is needed. Key words: Sparus aurata, lordosis, vertebra column, collagen. * Corresponding author: Dr. Berillis Panagiotis (pveril@uth.gr). 1. Introduction Collagen is a group of naturally occurring proteins. It is abundant in most invertebrates and vertebrates (Gallop and Paz 1975, Adams 1978). It is the main protein of connective tissue and represents about one-fourth of the total body protein content (Bailey 1968). Its molecule is formed by three polypeptide strands, called alpha chains, each possessing the conformation of a left-handed helix. Collagen is one of the long, fibrous structural proteins whose functions are different from those of globular proteins such as enzymes. Tough bundles of collagen (collagen fibers) are a major component of the extracellular matrix that supports most tissues. In fishes, collagen fibrils form a delicate network structure with varying complexity in the different connective tissues in a pattern similar to that found in mammals. The collagen in fish is much more thermolabile and contains fewer, but more labile cross-links compared to the collagen from warm-blooded vertebrates. In general, contains fewer hydroxyprolin than in mammals, although a total variation between 4.7 and 10% of the collagen is observed (Sato et al. 1989). Different fish species contain varying amounts of collagen in their body tissues. This has led to a theory that the distribution of collagen may reflect the swimming behavior of the species (Yoshinaka et al. 1988). Gilthead seabream (Sparus aurata) is one of the most important farmed fish species in the Mediterranean region (FAO 2014). Skeletal deformities is a major factor that affects the production cost, the external morphology of the fish as well as its survival and growth. The development of skeletal deformities is not well understood but it is related to nutritional, environmental and genetic factors (Fernadez et al. 2008). Fish bones consist of calcium-phosphor hydroxyapatite salts (inorganic part, about 65% of bone s dry mass) embedded in a matrix of type I collagen fibers (organic part) (Mahamid et al. 2008). The relationship between collagen and hydroxyapatite is crucial for bone toughness and stiffness. The aim of this study was to determine if the skeletal deformity of lordosis is associated with changes to the collagen fibrils morphology of the vertebras. 2. Materials and Methods At the present study adults individuals of Sparus aurata were collected from a commercial fish farm. Fishes were divided in to two groups. One with the presence of lordosis (mean weight 338.6±27.2 gr, mean length 24.8±1.3 cm), and one without any skeletal deformity (mean weight 325.6±45.7 gr, mean length 27.3±1.2 cm). Each fish was X-rayed in order to determine the lordosis deformity (Figure 1). Vertebra samples were taken from the part of the vertebra column that the lordosis occurred, fixed with glutaraldehyde, decalcified, dehydrated and embedded with resin. Ultrathin sections (60-80nm) were taken, stained with uranyl acetate and PTA and examined under a Philips CM-10 electron microscope equipped with a digital camera (Veleta, Olympus). Micrographs were taken (Figure 2) and collagen fibrils diameter were measured using a special algorithm. Further computational details appear in Tzaphlidou and Berillis (2002). The same procedure was followed for gilthead seabreams without any skeletal deformity (vertebras were taken from the middle part of the vertebra column). 3. Results The fibrils diameter measurements are presented in Table 1. There is a significant difference between the vertebras collagen fibrils diameter of the two groups, p<

349 Table 1. Vertebras collagen fibrils mean diameter from Sparus aurata with lordosis and from Sparus aurata without any skeletal deformity. Collagen fibrils mean diameter (nm) Sparus aurata with lordosis 64.00±14.82 (844) Sparus aurata without any skeletal deformity 72.79±14.81 (815) Note: Results are means±sd. The numbers of fibrils sampled are given in parenthesis. Figure 1: X-ray of Sparus aurata with lordosis deformity. 4. Discussion Gilthead seabream is one of the most important farmed fish species, as mentioned before. According to FAO the , the total European Sparus aurata aquaculture production was tones ( US dollars). Fishes with skeletal abnormalities are not preferred by the consumers, have diminished survivance and increase the production cost. As it has already been reported the development of skeletal deformities is not well understood and could be related to nutritional, environmental and genetic factors (Fernadez et al. 2008). Rapidly growing animals are more likely to develop pathological lesions to the skeleton. Thus, the hypothesis that growth rate may be another risk factor in the occurrence of spinal deformities is acceptable (Halver et al. 1969, Weisbrode and Doige 2001). In bone, collagen represents more than 90% of the organic bone matrix. It confers resistance to the structure and establishes the biomechanical properties of the tissue (Moro et al. 2000). Lim and Lower (1978) showed that vitamin C deficiency in channel catfish (Ictalurus punctatus) leaded to vertebra column deformities (kyphosis, scoliosis, lordosis) and to a decrement in the collagen content of bone. Our results showed a correlation between the lordosis deformity and the vertebras collagen fibril diameter in seabream. According to Chatain (1993) lordosis was developed in larval forms of Dicentrarchus labrax and seabream when they were forced to swim against a current of at least 20 cm/s. The luck of functional swimbladder in these species was also found to lead to lordosis development (Chatain 1993). There is also a significant effect of water temperature on the development of skeletal deformities in seabream (Georgakopoulou et al. 2010). 349

350 Figure 2: A) Collagen fibrils from vertebra of Sparus autata with lordosis deformity. B) Collagen fibrils from vertebra of Sparus autata without any skeletal deformity. References Adams E. (1978). Invertebrate collagens. Marked differences from vertebrate collagens appear in only a few invertebrate groups. Science 202(4368), Bailey A. (1968). The nature of collagen. Compr. Biochem. 26(B), Chatain B. (1994). Abnormal swimbladder development and lordosis in sea bass (Dicentrarchus labrax) and sea bream (Sparus auratus). Aquaculture 119, FAO (2014). Food and Agriculture Organization of the United Nations, Cultured Aquatic Species Information Program, Sparus aurata (Linnaeus, 1758) xml&outtype=html (accessed ). Fernández I., Hontoria F., Ortiz-Delgado J.B., Kotzamanis Y., Estévez A., Zambonino-Infante J.L., Gisbert E. (2008). Larval performance and skeletal deformities in farmed gilthead sea bream (Sparus aurata) fed with graded levels of Vitamin A enriched rotifers (Brachionus plicatilis). Aquaculture 283, Gallop P.M., Paz M.A. (1975). Posttranslational protein modifications, with special attention to collagen and elastin. Physiol. Rev. 55(3), Georgakopoulou E., Katharios P., Divanach P., Koumoundouros G. (2010). Effect of temperature on the development of skeletal deformities in Gilthead seabream (Sparus aurata Linnaeus, 1758). Aquaculture 308, Halver J.E., Ashley L.M., Smith R.R. (1969). Ascorbic acid requirements of coho salmon and rainbow trout. Trans Am Fish Soc 98, Lim C., Lowell R.T. (1978). Pathology of the vitamin C syndrome in channel catfish (Ictalurus punctatus). J. Nutr.108, Mahamid J., Sharir A., Addadi L., Weiner S. (2008). Amorphous calcium phosphate is a major component of the forming fin bones of zebrafish: Indications for an amorphous precursor phase. PNAS 105(35), Moro L., Romanello M., Favia A., Lamanna M.P., Lozupone, E. (2000). Posttranslational modifications of bone collagen type I are related to the function of rat femoral regions. Calcif. Tissue Int. 66, Sato K., Yoshinaka R., Sato M., Tomit, J. (1989). Biochemical characterization of collagen in myocommata and endomysium fractions of carp and spotted mackerel muscle. J. Food Sci. 54, Weisbrode S.E., Doige C.E. (2001): Bones and joints. In: Thompson s Specialized Veterinary Pathology McGavin M.D., Carlton W.W., Zachary J.F. (eds). St. Louis, Missouri: Mosby, p Yoshinaka R., Sato K., Anbe H., Sato M., Shimizu, Y. (1988). Distribution of collagen in body muscle of fishes with different swimming modes. Comp. Biochem. Physiol. 89B,

351 THE EFFECT OF DRIED CITRUS EXTRACT ON GROWTH, BODY PROXIMATE COMPOSITION, LIVER HISTOLOGY AND FILLET SHELF LIFE OF GILTHEAD SEA BREAM (Sparus aurata) Karapanagiotidis Η.T.*, Bouzianas A., Fountas S., Papagiannopoulos Ν., Berillis P., Boziaris I.S., Mente E. Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Fytoko street, 38446, Volos, Greece. Abstract Phytobiotics are natural plant-derived products, which are added in diets as nutritional supplements having immunostimulant effects and act as antioxidants, enhance palatability and promote growth. The aim of the present study was to evaluate the effect of dried citrus extract on the growth performance and feed utilization of seabream (Sparus aurata). Three groups of fish were fed for 120 days experimental diets that were supplemented with increasing levels of a dried citrus extract (0.25%, 0.5% and 1%), while another group were fed a control diet without the extract. At the end of the trial, there were no statistically significant differences in weight gain, feed conversion ratio and fish survival. In addition, there were not any significant differences between groups in their liver histology. In all dietary groups, the inclusion of dried citrus extract in the diet lowered the moisture and protein content of the muscle tissue and increased their lipid contents. In addition, fish fed the citrus diets had increased hepatosomatic and viscerosomatic indices indicating metabolic stress. In conclusion, the inclusion of dried citrus extract as high as 1% in the diet neither improved the feed utilization and growth performance of the gilthead seabream, nor prolonged shelf life of chilled stored fillets. Key words: Sparus aurata, nutrition, citrus extract, phytobiotics. * Corresponding author: Karapanagiotidis Ioannis T. (ikarapan@uth.gr). ΔΠΗΓΡΑΖ ΑΠΟΞΖΡΑΜΔΝΟΤ ΔΚΥΤΛΗΜΑΣΟ ΝΔΡΑΣΕΗΟΤ ΣΖΝ ΑΝΑΠΣΤΞΖ, ΣΖ ΘΡΔΠΣΗΚΖ ΤΣΑΖ, ΣΖΝ ΗΣΟΛΟΓΗΑ ΣΟΤ ΖΠΑΣΟ ΚΑΗ ΣΖ ΤΝΣΖΡΖΖ ΣΟΤ ΦΗΛΔΣΟΤ ΣΖ ΣΗΠΟΤΡΑ (Sparus aurata) Καξαπαλαγησηίδεο Η.Θ.*, Μπνπδηαλάο A., Φνχληαο., Παπαγηαλλφπνπινο Ν., Βεξίιιεο Π., Μπνδηάξεο Η., Μεληέ E. Σιήια Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ, Πακεπζζηήιζμ Θεζζαθίαξ, Φοηυημ, 38446, Βυθμξ, Δθθάδα Πεξίιεςε Σα θοημαζμηζηά απμηεθμφκ ιζα μιάδα θοζζηχκ πνμσυκηςκ ιε ακμζμεκζζποηζηέξ ζδζυηδηεξ, εκχ ηαοηυπνμκα εκδέπεηαζ κα αεθηζχκμοκ ηδ βεκζηυηενδ απυδμζδ ηςκ εηηνεθυιεκςκ μνβακζζιχκ υηακ αοηά ζοιπενζθαιαάκμκηαζ ςξ δζαηνμθζηά ζοιπθδνχιαηα. ημπυξ ηδξ πανμφζαξ ιεθέηδξ ήηακ κα ιεθεηδεεί δ επίδναζδ ημο απμλδναιέκμο εηποθίζιαημξ κεναηγζμφ ζηδ βεκζηυηενδ απυδμζδ ηδξ εηηνεθυιεκδξ ηζζπμφναξ. Σνεζξ μιάδεξ ζπεοδίςκ ηζζπμφναξ (Sparus aurata) δζαηνάθδηακ βζα ζοκμθζηά 120 διένεξ ιε αολακυιεκεξ δυζεζξ ημο εηποθίζιαημξ κεναηγζμφ (0,25%, 0,50% ηαζ 1%, ακηίζημζπα) ζηδ δίαζηα ημοξ, εκχ ιζα άθθδ μιάδα δζαηνάθδηε ιε δίαζηα πμο δεκ πενζείπε ημ ζοβηεηνζιέκμ ζοζηαηζηυ. Γεκ παναηδνήεδηε ηάπμζα ζηαηζζηζηά ζδιακηζηή (P>0,05) δζαθμνά ιεηαλφ ηςκ ηεζζάνςκ δζαηνμθζηχκ μιάδςκ ςξ πνμξ υθεξ ηζξ οπυ ιεθέηδ παναιέηνμοξ ακάπηολδξ ηςκ ζπεφςκ, ηδξ αλζμπμίδζδξ ηδξ ηνμθήξ ηαζ ημο πμζμζημφ επζαίςζδξ αοηχκ. Δπζπνυζεεηα, δεκ παναηδνήεδηε ηάπμζα ζδιακηζηή δζαθμνμπμίδζδ ζηδκ ζζημθμβία ημο ήπαημξ ιεηαλφ ηςκ μιάδςκ. Ζ πμνήβδζδ απμλδναιέκμο εηποθίζιαημξ κεναηγζμφ ζε μπμζαδήπμηε πμζυηδηα μδήβδζε ζε ζδιακηζηά ιεζςιέκδ πενζεηηζηυηδηα (%) ζε οβναζία ηαζ ζε μθζηέξ πνςηεΐκεξ ηαζ ζε ζδιακηζηά αολδιέκδ πενζεηηζηυηδηα ζε μθζηά θζπίδζα ζοβηνζηζηά ιε ημοξ ζπεφεξ πμο δεκ ηαηακάθςζακ ημ εηπφθζζια. Ζ πμνήβδζδ ημο εηποθίζιαημξ επίζδξ μδήβδζε ζε αολδιέκεξ ηζιέξ ημο δπαημζςιαηζημφ ηαζ εκδμζπθαπκζημφ δείηηδ οπμδδθχκμκηαξ ιεηααμθζηυ ζηνεξ. οιπεναζιαηζηά, δ πμνήβδζδ απμλδναιέκμο εηποθίζιαημξ κεναηγζμφ ζε πμζμζηυ ςξ ηαζ 1% ηδξ δίαζηαξ δεκ μδδβεί ζε αεθηζςιέκδ απμδμηζηυηδηα ηδξ ηνμθήξ ηδξ ηζζπμφναξ, μφηε αεθηζχκεζ ηδκ δζαηδνδζζιυηδηα ημο θζθέημο ηαηά ηδκ ζοκηήνδζή ημο οπυ ρφλδ. Λέξειρ κλειδιά: Sparus aurata, δηαηξνθή, εθρύιηζκα λεξαηδηνύ, θπηνβηνηηθά. *οββναθέαξ επζημζκςκίαξ: Καναπακαβζςηίδδξ Ηςάκκδξ Θ. (ikarapan@uth.gr) 351

352 1. Δηζαγσγή Λυβς ηςκ ανηεηχκ ιεζμκεηηδιάηςκ πμο πανμοζζάγεζ δ πνδζζιμπμίδζδ ακηζαζμηζηχκ ζηζξ ζπεομηαθθζένβεζεξ (Defoirdt et al. 2011), έπεζ δζεβενεεί έκα έκημκμ ενεοκδηζηυ εκδζαθένμκ ζπεηζηά ιε ηδ πνδζζιμπμίδζδ εκαθθαηηζηχκ θοζζηχκ πνμσυκηςκ, πμο μκμιάγμκηαζ θοημαζμηζηά (phytobiotics) (Sapkota et al. 2008, Windisch et al. 2008). Πένακ ηδξ ακηζ-ιζηνμαζαηήξ/ζσηήξ/ιοηδηζαηήξ ημοξ δνάζδξ, ηα θοημαζμηζηά ζοπκά έπμοκ ακηζμλεζδςηζηέξ επζδνάζεζξ, ηάπμζα θεζημονβμφκ ςξ εκζζποηζηά ηδξ βεφζδξ, αεθηζχκμοκ ηδ θεζημονβία ημο εκηένμο ή αηυια εκζζπφμοκ ηδκ ίδζα ηδ ζςιαηζηή ακάπηολδ (Windisch et al. 2008). Δπίζδξ, μζ μοζίεξ αοηέξ είκαζ ιδ ημλζηέξ ηαζ αζμδζαζπχιεκεξ, εκχ ιέπνζ ζήιενα δεκ έπεζ ακαθενεεί ηαιία ακεεηηζηυηδηα παεμβυκμο ζε αοηά. Πανυθμ πμο μζ ζδζυηδηεξ αοηέξ ηςκ θοημαζμηζηχκ είκαζ βκςζηέξ ζηδ θανιαηεοηζηή, ζήιενα ιυκμ ιζα ιζηνή μιάδα ηέημζςκ μοζζχκ ανίζηεζ πνήζδ ζηζξ ζπεομηαθθζένβεζεξ. ηδκ εονεία αοηή μιάδα πενζθαιαάκμκηαζ δζάθμνα αυηακα, ιπαπανζηά, νεηζίκζα ηαζ αζεένζα έθαζα απυ δζάθμνα άκεδ, θφθθα ηαζ θνμφηα. To απμλδναιέκμ εηπφθζζια κεναηγζμφ είκαζ έκα παναπνμσυκ ηδξ επελενβαζίαξ ημο ζοβηεηνζιέκμο θνμφημο ηαζ είκαζ πθμφζζμ ζε α-βθοηάκεξ, αζμθθααμκμεζδή ηαζ αθβζκζηά μλέα πμο εκζζπφμοκ ηδ ιδ εζδζηή ακμζία ημο μνβακζζιμφ ηαζ δνμοκ ςξ ζζπονά ακμζμεκζζποηζηά (Rapisarda et al. 1999). Σμ ζοζηαηζηυ αοηυ εκδέπεηαζ κα ημκχκεζ ηδκ πεπηζηυηδηα ηδξ ηνμθήξ, ηδ δζαεεζζιυηδηα ηςκ ενεπηζηχκ ζοζηαηζηχκ ηαζ ςξ εη ημφημο ηδκ ιεηαηνερζιυηδηα ηδξ ηνμθήξ. ημπυξ ηδξ πανμφζαξ ιεθέηδξ ήηακ κα ιεθεηδεεί δ επίδναζδ πμο έπεζ ημ εηπφθζζια κεναηγζμφ ζηδ βεκζηυηενδ απυδμζδ ηδξ εηηνεθυιεκδξ ηζζπμφναξ ιεθεηχκηαξ δείηηεξ υπςξ δ ζςιαηζηή ακάπηολδ, δ ιεηαηνερζιυηδηα ηδξ ηνμθήξ, δ επίδναζδ ζηδκ ενεπηζηή ζφζηαζδ ημο θζθέημο, ζηδκ ζζημθμβία ημο ήπαημξ ηαζ ημ πνυκμ δζάνηεζαξ γςήξ ημο θζθέημο ηδξ ηζζπμφναξ. 2. Τιηθά θαη Μέζνδνη οκμθζηά 240 ζπεφδζα ημο είδμοξ Sparus aurata ιέζμο ζςιαηζημφ αάνμοξ 2,02±0,24 g ηαζ μθζημφ ιήημοξ 5,43±0,25 cm ιεηαθένεδηακ, ζε εζδζηέξ ζοζηεοαζίεξ ιε μλοβυκμ, απυ ζπεομβεκκδηζηυ ζηαειυ ζηζξ εβηαηαζηάζεζξ ημο Σιήιαημξ Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ, υπμο ηαζ έθααε πχνα ημ πείναια. Σα ζπεφδζα ημπμεεηήεδηακ ζε μνεμβχκζα βοάθζκα εκοδνεία πςνδηζηυηδηαξ 60 L, ηθεζζημφ ηοηθχιαημξ ηοηθμθμνίαξ εαθαζζζκμφ κενμφ ηαζ αθέεδηακ κα εβηθζιαηζζημφκ ζηζξ πεζναιαηζηέξ ζοκεήηεξ βζα 10 διένεξ, υπμο ζζηίγμκηακ ιία θμνά ηδκ διένα ιε ηδ δίαζηα Α (Πίκαηαξ 1.). Σα ζπεφδζα δζακειήεδηακ ζε 4 δζαηνμθζηέξ μιάδεξ, θαιαάκμκηαξ δ ηάεε ιία δζαθμνεηζηή δίαζηα. Ζ ηάεε δζαηνμθζηή μιάδα απμηεθμφκηακ απυ 60 ζπεφδζα ηα μπμία ηαηακειήεδηακ ζε οπμμιάδεξ ηςκ 20 αηυιςκ ζε 3 εκοδνεία (4 δζαηνμθζηέξ ιεηαπεζνίζεζξ, 3 δελαιεκέξ-επακαθήρεζξ ακά ιεηαπείνζζδ, 20 ζπεφδζα ακά εκοδνείμ). Οζ πεζναιαηζηέξ δίαζηεξ παναζηεοάζηδηακ ιε ηδκ ιέεμδμ ηδξ ημζκήξ πεθθεημπμίδζδξ ιε ηδ πνήζδ πεθθεημιδπακήξ ηφπμο California Pellet Mill ηαζ ήηακ ηδξ ιμνθήξ αοεζγυιεκμο ζφιπδηημο δζαιέηνμο 1,5 mm. Οζ δίαζηεξ ηαηανηίζηδηακ χζηε κα είκαζ ζζμεκενβεζαηέξ (22 MJ/Kg ηνμθήξ) ηαζ ζζμπνςηεσκζηέξ (48% ηδξ ηνμθήξ) (Πίκαηαξ 1) ζηακμπμζχκηαξ ηζξ βκςζηέξ ενεπηζηέξ απαζηήζεζξ ηδξ ηζζπμφναξ. To ζοζηαηζηυ Provigoro απμηεθεί έκα ειπμνζηυ δζαηνμθζηυ ζοιπθήνςια ζε ιμνθή ζηυκδξ, ημ μπμίμ παναζηεοάγεηαζ απυ εηπφθζζια ακχνζιμο κεναηγζμφ ηαζ πενζέπεζ ηζξ αζμθθααμκμεζδείξ μοζίεξ ημο θνμφημο. Οζ δίαζηεξ Β, Γ ηαζ Γ ηαηανηίζηδηακ χζηε κα πενζέπμοκ αολακυιεκεξ δυζεζξ (0,25%, 0,50% ηαζ 1,00% ηδξ δίαζηαξ, ακηίζημζπα) ημο ζοζηαηζημφ Provigoro, εκχ δ δίαζηα Α ηαηανηίζηδηε χζηε κα ιδκ πενζέπεζ ημ ζοζηαηζηυ ηαζ κα απμηεθεί ηδ δίαζηα-ιάνηονα. Ζ πμνήβδζδ ηδξ ηνμθήξ ήηακ ηαεδιενζκά ιε ημ πένζ, 2 θμνέξ ηδκ διένα ζηζξ ηαζ Σμ δζαηνμθζηυ επίπεδμ ήηακ ιεζμφιεκμ ηαηά ηδ δζάνηεζα ημο πεζνάιαημξ απυ 5% ημο ζςιαηζημφ αάνμοξ ηςκ ζπεφςκ ανπζηά ζε 2% πνμξ ημ ηέθμξ ημο πεζνάιαημξ. Σμ πείναια δζήνηεζε ζοκμθζηά 120 διένεξ. Σα πμζμηζηά παναηηδνζζηζηά ημο κενμφ ζημ ηθεζζηυ ζφζηδια ηοηθμθμνίαξ παναημθμοεμφκηακ ζε ηαηηζηή αάζδ ηαζ ήηακ: εενιμηναζία 21±0,5 C, ph 8,00±0,4, δεζιεοιέκμ μλοβυκμ > 6,5 mg/l, αθαηυηδηα 34±0,5, δ ζοβηέκηνςζδ ηδξ μθζηήξ αιιςκίαξ ήηακ <1 mg/l, εκχ εθανιυζηδηε ηεπκδηή θςημπενίμδμξ 12 χνεξ θςξ 12 χνεξ ζηυημοξ. Καηά ηδ δζάνηεζα ημο πεζνάιαημξ, ηα ζπεφδζα γοβίγμκηακ αημιζηά ηάεε 2 εαδμιάδεξ χζηε κα επακαπνμζδζμνίγεηαζ ημ δζαηνμθζηυ επίπεδμ. ημ ηέθμξ ημο πεζνάιαημξ υθα ηα ζπεφδζα εακαηχεδηακ παναηείκμκηαξ ηδκ παναιμκή ημοξ ζε ακαζζεδηζηυ θαζκμλοεακυθδξ αολακυιεκδξ δμζμθμβίαξ ηαζ άιεζδξ ημπμεέηδζδξ ημοξ ζε πάβμ. Πναβιαημπμζήεδηακ ιεηνήζεζξ αάνμοξ ηαζ ιήημοξ ηαζ ζηδ ζοκέπεζα επζθέπηδηακ ηοπαία 6 ράνζα απυ ηάεε δζαηνμθζηή μιάδα, απμεδηεφηδηακ ηαζ ζοκηδνήεδηακ ζημοξ -20 C ιε ζημπυ ηδ πδιζηή ακάθοζδ ηδξ ενεπηζηήξ ζφζηαζδξ ημο ιοσημφ ζζημφ ημοξ. Γζα ημκ οπμθμβζζιυ ηςκ παναιέηνςκ ακάπηολδξ ηςκ ζπεφςκ ηαζ ηδξ αλζμπμίδζδξ ηδξ ηνμθήξ απυ αοηά πνδζζιμπμζήεδηακ μζ παναηάης ζπέζεζξ: Αφλδζδ αάνμοξ (g) = Wη Wα, Δζδζηυξ νοειυξ ακάπηολδξ (SGR, %/διένα) = [LnWη LnWα] / διένεξ ζίηζζδξ, οκηεθεζηήξ ιεηαηνερζιυηδηαξ ηνμθήξ (FCR) = πμνδβδεείζα ηνμθή (g) / αφλδζδ αάνμοξ (g) Ο ζοκηεθεζηήξ απμδμηζηυηδηαξ ηςκ πνςηεσκχκ (protein efficiency ratio, PER) εηθνάγεζ ηδκ ακαθμβία ιεηαλφ ηδξ αφλδζδξ αάνμοξ ηςκ ρανζχκ ηαζ ηδξ πνςηεΐκδξ πμο ηαηακαθχεδηε. Ο ζοκηεθεζηήξ οπμθμβίγεηαζ απυ ηδκ ζπέζδ: Protein efficiency ratio (PER) = Αφλδζδ αάνμοξ (g) / πνςηεΐκδ πμο πμνδβήεδηε (g), 352

353 πμο Wα ηαζ Wη, ημ ιέζμ ανπζηυ ηαζ ιέζμ ηεθζηυ ζςιαηζηυ αάνμξ ηςκ ζπεφςκ, LnWα ηαζ LnWη oζ θοζζημί θμβάνζειμζ ημο ιέζμο ανπζημφ ηαζ ιέζμο ηεθζημφ ζςιαηζημφ αάνμοξ ηςκ ζπεφςκ. Οζ ζςιαημιεηνζημί δείηηεξ πμο οπμθμβίζηδηακ ήηακ: μ δπαημζςιαηζηυξ δείηηδξ (hepatosomatic index, ΖSΗ), μ εκδμζπθαπκζηυξ δείηηδξ (viscerosomatic index, VSI) ηαζ μ δείηηδξ εονςζηίαξ (Κ): ΖSΗ = Βάνμξ ήπαημξ 100 / Βάνμξ ζχιαημξ (εηηυξ εκηυζεζςκ, ήπαημξ) VSI = Βάνμξ εκηυζεζςκ 100 / Βάνμξ ζχιαημξ (εηηυξ εκηυζεζςκ, ήπαημξ) Κ = Οθζηυ αάνμξ ζχιαημξ 100 / Οθζηυ ιήημξ 3 Πίλαθαο 1. πζηαηηθά θαη ζξεπηηθή ζχζηαζε ησλ πεηξακαηηθψλ ζηηεξεζίσλ. ΓΗΑΗΣΑ Α ΓΗΑΗΣΑ Β ΓΗΑΗΣΑ Γ ΓΗΑΗΣΑ Γ πζηαηηθά (%) Ηπεοάθεονμ 35,0 35,0 35,0 35,0 Γθμοηέκδ ηαθαιπμηζμφ 35,0 35,0 35,0 35,0 ζηάνζ, άθεονμ 14,0 13,75 13,5 13,0 Ηπεοέθαζμ 15,0 15,0 15,0 15,0 Provigoro 0,00 0,25 0,50 1,00 Βζηαιίκεξ & ακ.ζημζπεία (πνυιζβια) 0,75 0,75 0,75 0,75 Φςζθμνζηυ ιμκμαζαέζηζμ 0,25 0,25 0,25 0,25 Θξεπηηθή ζύζηαζε(%) Τβναζία 92,7 92,8 92,8 92,8 Οθζηέξ πνςηεΐκεξ 47,8 47,8 47,7 47,7 Οθζηέξ θζπανέξ μοζίεξ 18,2 18,2 18,2 18,2 Τδαηάκεναηεξ 1 21,2 21,0 20,9 20,50 Ηκχδεζξ μοζίεξ 2 1,8 1,8 1,7 1,7 Σέθνα 5,3 5,3 5,3 5,3 Δκένβεζα (Kg/g) 3 22,0 21,9 21,9 21,8 δι.: Σα ζοζηαηζηά πνμιδεεφηδηακ απυ ηδκ Biomar Hellas, ημ ζζηάνζ απυ ηδκ ημπζηή αβμνά, εκχ ημ Provigoro απυ ηδκ Citrox Technologies Ltd. 1 Σμ πμζμζηυ ηςκ οδαηακενάηςκ εηηζιήεδηε ιε αθαίνεζδ απυ ημ 100 ημο ζοκυθμο ηςκ πμζμζηχκ πνςηεΐκδξ, θζπζδίςκ ηαζ ηέθναξ. 2 Οζ ζκχδεζξ μοζίεξ εηηζιήεδηακ αάζεζ ηςκ πενζεηηζημηήηςκ ηςκ δζαθυνςκ ζοζηαηζηχκ ζφιθςκα ιε βκςζηέξ ζοβηεκηνχζεζξ (ΝRC 1993). 3 Ζ μθζηή εκένβεζα οπμθμβίζηδηε ςξ άενμζζια ηςκ επζιένμοξ μθζηχκ εκενβεζχκ πμο πνμζθένεζ ηάεε ενεπηζηυ ζοζηαηζηυ θαιαάκμκηαξ οπ υρδ ημοξ ζοκηεθεζηέξ 5,64, 9,44 ηαζ 4,11 βζα ηζξ πνςηεΐκεξ, ηα θζπίδζα ηαζ ημοξ οδαηάκεναηεξ, ακηίζημζπα. Οζ πδιζηέξ ακαθφζεζξ ηδξ ενεπηζηήξ ζφζηαζδξ ηςκ ηνμθχκ ηαζ ηςκ ζζηχκ ηςκ ζπεφςκ πναβιαημπμζήεδηακ ζφιθςκα ιε ηζξ ιεευδμοξ AOAC 1995 ςξ ελήξ: μ πνμζδνζμνζζιυξ ηδξ οβναζίαξ ιε εένιακζδ βζα 24 χνεξ ζημοξ 105 C, o πνμζδζμνζζιυξ ηςκ μθζηχκ θζπανχκ μοζζχκ έβζκε ιε ηδκ ιέεμδμ εηπφθζζδξ Soxhlet, μ πνμζδζμνζζιυξ ηςκ μθζηχκ αγςημφπςκ μοζζχκ πναβιαημπμζήεδηε ιε ηδ ιέεμδμ Kjeldahl ηαζ μ πνμζδζμνζζιυξ ηδξ ηέθναξ ιε απμηέθνςζδ ηςκ δεζβιάηςκ ζημοξ 600 C βζα 3 χνεξ. Απυ ηάεε δζαηνμθζηή μιάδα πάνεδηακ δείβιαηα ήπαημξ απυ ζοκμθζηά 9 ράνζα. Γζα ηδ ιζηνμζημπζηή ιεθέηδ ημο ήπαημξ πνδζζιμπμζήεδηακ ηεπκζηέξ ζζημθμβίαξ μζ μπμίεξ πενζεθάιαακακ ιμκζιμπμίδζδ ημο ζζημφ ζε δζάθοια μοδέηενδξ θμνιυθδξ 10% βζα 48 χνεξ, αθοδάηςζδ - δζαφβαζδ - εβηθεζζιυξ ημο ζζημφ ζε παναθίκδ, ημιέξ πάπμοξ 5-6 ιm, απμπαναθίκςζδ, πνχζδ ημο ζζημφ ζε δζάθοια πνχζδξ αζιαημλοθίκδξ εςζίκδξ ηαζ ηέθμξ ζηενεμπμίδζδ ηςκ ημιχκ. Οζ ζζημθμβζηέξ ημιέξ ιεθεηήεδηακ ζε μπηζηυ ιζηνμζηυπζμ ζε ιεβέεοκζδ 400. Μζηνμθςημβναθίεξ θήθεδζακ ιε ηδ αμήεεζα ρδθζαηήξ ηάιεναξ πνμζανιμζιέκδξ ζημ ιζηνμζηυπζμ. Φζθέηα ηςκ ζπεοδίςκ απμεδηεφεδηακ ζημοξ 0 C ηαζ ακά ηαηηά πνμκζηά δζαζηήιαηα πναβιαημπμζμφκηακ δεζβιαημθδρίεξ βζα ιζηνμαζμθμβζηέξ ακαθφζεζξ. Γέηα (10) g ζάνηαξ ιεηαθένμκηακ αζδπηζηά ζε 90 ml MRD (0,85% NaCl, 0,1%, bacteriological peptone), αημθμοεμφζε μιμβεκμπμίδζδ βζα 1 θεπηυ, δζαδμπζηέξ αναζχζεζξ, ηαζ επζθακεζαηή ελάπθςζδ 0,1 ml ακαζςνήιαημξ απυ ηδκ ηαηάθθδθδ αναίςζδ ζε ηνοαθία Plate Count Agar (PCA) ηαζ μ πθδεοζιυξ ηςκ ιεζυθζθςκ ηαζ ροπνυηνμθςκ ααηηδνίςκ ηαηαιεηνχκηακ έπεζηα απυ επχαζδ 48 ςνχκ ζημοξ 25 ηαζ 10 C, ακηίζημζπα. Σα δεδμιέκα ηςκ παναιέηνςκ ακάπηολδξ ηςκ ζπεφςκ ηαζ αλζμπμίδζδξ ηδξ ηνμθήξ επελενβάζεδηακ ιε ηδ ιέεμδμ ηδξ Ακάθοζδξ ηδξ Γζαηφιακζδξ Μμκήξ Καηεφεοκζδξ (one-way ANOVA) αημθμοεμφιεκδ απυ Tukey s test ηαζ μζ δζαθμνέξ ηνίεδηακ ζηαηζζηζηά ζδιακηζηέξ βζα ηζιέξ P<0, Απνηειέζκαηα θαη πδήηεζε ημ ηέθμξ ημο δζαηνμθζημφ πεζνάιαημξ δζάνηεζαξ 120 ζοκμθζηά διενχκ δεκ παναηδνήεδηε ηάπμζα ζηαηζζηζηά ζδιακηζηή (P>0,05) δζαθμνά ιεηαλφ ηςκ ηεζζάνςκ δζαηνμθζηχκ μιάδςκ ςξ πνμξ υθεξ ηζξ 353

354 παναιέηνμοξ ακάπηολδξ ηςκ ζπεφςκ ηαζ ηδξ αλζμπμίδζδξ ηδξ ηνμθήξ πμο ιεθεηήεδηακ (Πίκαηαξ 2). Τπήνλε ιζα ηάζδ, δ μπμία παναηδνήεδηε ήδδ απυ ηδ δεφηενδ εαδμιάδα, υπμο δ δυζδ ημο εηποθίζιαημξ κεναηγζμφ ηδξ ηάλδξ ημο 0,5% ηδξ ηνμθήξ (μιάδα Γ) πανμοζίαζε ορδθυηενδ αφλδζδ ζςιαηζημφ αάνμοξ, εζδζηυ νοειυ ακάπηολδξ ηαζ αλζμπμίδζδ ηδξ ηνμθήξ ζε ζπέζδ ηυζμ ιε ηζξ μιάδεξ πμο δζαηνάθδηακ ιε παιδθυηενδ ή ορδθυηενδ δυζδ, υζμ ηαζ ιε ηδκ μιάδα πμο δζαηνάθδηε ιε ηδκ ηνμθή ιάνηονα (ιδδεκζηή δυζδ). Ζ ηάζδ, ςζηυζμ, αοηή δεκ ήηακ ζδιακηζηή (P>0,05) ηαευθδ ηδ δζάνηεζα ημο πεζνάιαημξ. Σμ απμηέθεζια αοηυ δείπκεζ υηζ ημ απμλδναιέκμ εηπφθζζια κεναηγζμφ δεκ επζθένεζ ηάπμζα ζδιακηζηή αεθηίςζδ ζηδκ απμδμηζηυηδηα ηδξ ηνμθήξ ηαζ ζηδκ ακάπηολδ ηδξ ηζζπμφναξ. H Citrox Technologies (αδδιμζίεοηα απμηεθέζιαηα) δμηζιάγμκηαξ ημ εηπφθζζια κεναηγζμφ ζε πμζμζηυ 0,25% ζηδ δίαζηα ηδξ πέζηνμθαξ (Oncorhynchus mykiss) ακέθενε υηζ μζ ζπεφεξ απέηηδζακ ορδθυηενδ αφλδζδ αάνμοξ απυ υηζ μζ ζπεφεξ πμο δζαηνάθδηακ πςνίξ ηδκ πνμζεήηδ ημο εηποθίζιαημξ. Οζ de la Cuesta et al. (2010), δμηζιάγμκηαξ έκα ιείβια πνεαζμηζηχκ ηαζ εηποθζζιάηςκ απυ θοηά ημο βέκμοξ Citrus ζε πμζμζηυ 0,25-0,3% ηδξ δίαζηαξ ακέθενακ υηζ οπήνλε αεθηζςιέκδ ακάπηολδ ηαζ ιεηαηνερζιυηδηα ηδξ ηνμθήξ ηυζμ ζηδκ πέζηνμθα (Oncorhynchus mykiss) υζμ ηαζ ζημ θαονάηζ (Dicentrarchus labrax). Ακηίεεηα, μζ Rodrigues et al. (2011) ζοιπενζέθααακ πμφθπα κεναηγζμφ ζε ανηεηά ορδθά πμζμζηά ζηδ δίαζηα ημο βαηυρανμο (Rhamdia quelen) ηαζ ηδξ ηζθάπζαξ (Oreochromis niloticus) ηαζ δζαπίζηςζακ ιεζςιέκδ ακάπηολδ ηςκ ζπεφςκ πμο μθείθεηαζ ηονίςξ ζηδκ ορδθή πμνήβδζδ άπεπηςκ ζκςδχκ μοζζχκ. Πεναζηένς, δ πμνήβδζδ ημο εηποθίζιαημξ ζηδ δζάζηα ηδξ ηζζπμφναξ μδήβδζε ζε εθαθνχξ ιεζςιέκεξ εκδζζιυηδηεξ ζε ζφβηνζζδ ιε ηδ δίαζηα-ιάνηονα, ζδζαίηενα ζηδκ μιάδα Γ, πςνίξ ςζηυζμ ημ απμηέθεζια αοηυ κα είκαζ ζηαηζζηζηά ζδιακηζηυ (P>0,05). Αοηυ δεζηκφεζ υηζ ημ απμλδναιέκμ εηπφθζζια κεναηγζμφ δεκ μδδβεί ζε ζδιακηζηή αεθηζχζδ ηδξ επζαίςζδξ ηδξ ηζζπμφναξ. Ακηίεεηα, δ Citrox Technologies (αδδιμζίεοηα απμηεθέζιαηα) ακέθενε υηζ δ πμνήβδζδ ημο εηποθίζιαημξ ζε πμζμζηυ 0,25% ηδξ δίαζηαξ μδήβδζε ζε ζδιακηζηά ιεζςιέκεξ εκδζζιυηδηεξ ζηδκ πέζηνμθα (O. mykiss). Ακαθμνζηά ιε ηδ ενεπηζηή ζφζηαζδ ημο ιοσημφ ζζημφ ηςκ ζπεφςκ, αοηή επδνεάζηδηε ζδιακηζηά (P<0,05) απυ ηζξ πεζναιαηζηέξ δίαζηεξ. οβηεηνζιέκα, δ πμνήβδζδ ημο απμλδναιέκμο εηποθίζιαημξ κεναηγζμφ ζε μπμζαδήπμηε πμζυηδηα (μιάδεξ Β, Γ ηαζ Γ) μδήβδζε ζε ζδιακηζηά ιεζςιέκδ πενζεηηζηυηδηα (%) ζε οβναζία ηαζ μθζηέξ πνςηεΐκεξ ηαζ ζε ζδιακηζηά αολδιέκδ πενζεηηζηυηδηα ζε θίπμξ ζοβηνζηζηά ιε ημοξ ζπεφεξ πμο δεκ ηαηακάθςζακ ημ εηπφθζζια. Ζ ιεζςιέκδ πενζεηηζηυηδηα ζε ιοσηέξ πνςηεΐκεξ ηαζ δ αολδιέκδ εκαπυεεζδ θίπμοξ ζε αοηέξ ηζξ μιάδεξ δείπκεζ ιεηααμθζηή αλζμπμίδζδ (ηαηααμθζζιυξ) ηςκ πνχηςκ πνμξ παναβςβή ιεηααμθζηήξ εκένβεζαξ πμο απμεδηεφεηαζ ζημ ιοζηυ ζζηυ ζηδ ιμνθή ημο θίπμοξ. Γζαθμνμπμζήζεζξ ζηδ πμνδβμφιεκδ πμζυηδηα ημο εηποθίζιαημξ, ςζηυζμ, δεκ επέθενακ δζαθμνμπμζήζεζξ ζηδ ενεπηζηή ζφζηαζδ ημο ιοσημφ ζζημφ. Ζ πμνήβδζδ ημο εηποθίζιαημξ επίζδξ επδνέαζε (P<0,05) ζδιακηζηά ημοξ ζςιαημιεηνζημφξ δείηηεξ ηςκ ζπεφςκ, ηαεχξ ηυζμ μ δπαημζςιαηζηυξ υζμ ηαζ μ εκδμζπθαπκζηυξ ήηακ ορδθυηενμζ ζηζξ μιάδεξ ζπεφςκ πμο δζαηνάθδηακ ιε ημ εηπφθζζια, οπμδδθχκμκηαξ ηάπμζμ ιεηααμθζηυ ζηνεξ. Απυ ηδκ άθθδ, δεκ παναηδνήεδηε ηάπμζα ζδιακηζηή δζαθμνμπμίδζδ ζηδκ ζζημθμβία ημο ήπαημξ ιεηαλφ ηςκ μιάδςκ. Οζ ιζηνμαζμθμβζηέξ ακαθφζεζξ έδεζλακ υηζ δεκ οπήνπε δζαθμνά ζηζξ ιεηααμθέξ ημο ιζηνμαζαημφ πθδεοζιμφ (P>0.05) ιεηαλφ ηςκ ζπεοδίςκ πμο δζαηνάθδηακ ιε ηδκ ηνμθή ιάνηονα ηαζ ιε ηζξ ηνμθέξ πμο πενζείπακ εηπφθζζια κεναηγζμφ. Ο ειπμνζηυξ πνυκμξ γςήξ πνμζδζμνίζεδηε βζα υθεξ ηζξ ιεηαπεζνίζεζξ πενί ηζξ 14 διένεξ, υπμο ήηακ μ πνυκμξ πμο πνεζάζηδηε κα θεάζεζ μ μθζηυξ ιεζυθζθμξ ιζηνμαζαηυξ πθδεοζιμφξ ημ επίπεδμ ηςκ 10 7 cfu/g, υπμο ηαζ ζοκέπεζε ηαζ ιε ηδκ έκανλδ ηδξ ακάπηολδξ δοζάνεζηςκ μζιχκ. οιπεναζιαηζηά, δ πμνήβδζδ απμλδναιέκμο εηποθίζιαημξ κεναηγζμφ ζε πμζμζηυ ςξ ηαζ 1% ηδξ δίαζηαξ δεκ μδδβεί ζε αεθηζςιέκδ απμδμηζηυηδηα ηδξ ηνμθήξ ηδξ ηζζπμφναξ, μφηε ζηδκ επέηηαζδ ημο ειπμνζημφ πνυκμο γςήξ ηςκ θζθέηςκ. 354

355 Πίλαθαο 2. Παξάκεηξνη αλάπηπμεο, αμηνπνίεζεο ηξνθήο, ζξεπηηθή ζχζηαζε κπτθνχ ηζηνχ θαη ζσκαηνκεηξηθνί δείθηεο ηρζπδίσλ S. aurata δηαηξεθφκελα κε ηηο πεηξακαηηθέο δίαηηεο. Οη ηηκέο αληηπξνζσπεχνπλ κέζνπο φξνπο ± ηππηθή απφθιηζε (n=3). Α Β Γ Γ Παξάκεηξνη αλάπηπμεο Ανπζηυ ιήημξ (cm) 5,4±0,1 a 5,5±0,1 a 5,4±0,1 a 5,4±0,1 a Σεθζηυ ιήημξ (cm) 11,4±0,5 a 11,8±0,5 a 12,1±0,9 a 11,4±0,2 a Ανπζηυ αάνμξ (g) 2,03±0,02 a 2,02±0,03 a 2,02±0,04 a 2,02±0,04 a Σεθζηυ αάνμξ (g) 21,08±2,15 a 22,25±2,50 a 24,59±2,56 a 19,89±0,37 a Θκδζζιυηδηεξ (%) 26,7±12,6 a 20,0±5,0 a 8,3±2,9 a 20,0±5,0 a Αολ. αάνμοξ (WG, g) 19,06±2,13 a 20,23±2,46 a 22,56±2,56 a 17,86±0,40 a Καηακάθςζδ ηνμθήξ (g) 20,56±3,53 22,67±2,72 24,22±0,50 20,27±3,13 SGR (%/δι.) 1,95±0,08 a 2,00±0,08 a 2,08±0,05 a 1,90±0,03 a FCR 1,07±0,09 1,12±0,12 1,07±0,10 1,13±0,15 ύζηαζε κπτθνύ ηζηνύ (%) Τβναζία 78,49±1,08 a 76,19±1,77 b 76,16±0,58 b 75,89±0,54 b Οθζηέξ πνςηεΐκεξ 80,80±0,50 a 74,62±0,22 b 75,80±1,39 b 75,99±1,17 b Οθζηά θζπίδζα 5,14±2,16 a 10,91±2,13 b 10,21±2,03 b 10,11±2,18 b σκαηνκεηξηθνί δείθηεο HIS 5,54±0,87 a 8,19±2,06 b 6,75±1,54 ab 7,42±0,99 ab VSI 1,17±0,32 a 1,70±0,39 b 1,30±0,44 ab 1,51±0,41 b δι.: Σζιέξ πμο δεκ ακηζπνμζςπεφμκηαζ απυ ημκ ίδζμ εηεέηδ δείπκμοκ ζηαηζζηζηχξ ζδιακηζηή δζαθμνά (P<0,05) ιεηαλφ ηςκ δζαηνμθζηχκ μιάδςκ. Δπραξηζηίεο Δοπανζζημφιε ημκ ζπεομβεκκδηζηυ ζηαειυ ηδξ «ΓΗΑ ΗΥΘΤΟΚΑΛΛΗΔΡΓΔΗΔ» (Πεθαζβία Φεζχηζδμξ) βζα ηδκ δςνεά ηςκ ζπεοδίςκ ηαζ ηδ αζμιδπακία ζπεομηνμθχκ «BioMar Hellas» βζα ηδ δςνεά ηςκ πνχηςκ οθχκ ηςκ δζαίηςκ. Βηβιηνγξαθία Defoirdt T., Sorgeloos P., Bossier P. (2011). Alternatives to antibiotics for the control of bacterial disease in aquaculture. Current Opinion in Microbiology 14, de la Cuesta S., López I., Martínez A., Muñoz L. (2010). Phytobiotics and prebiotics, a new alternative for sustainable aquaculture. International Aquafeed May-June, 25. Rapisarda P., Tomaino A., Lo Cascio R., Bonina F., De Pasquale A., Saija A. (1999). Antioxidant effectiveness as influenced by phenolic content of fresh orange juices. Journal of Agricultural and Food Chemistry 47, Rodrigues A.P.O., Gominho-Rosa M.D.C., Cargnin-Ferreira E., De Franscisco A., Fracalossi D.M. (2011). Different utilization of plant sources by the omnivores jundia catfish (Rhamdia quelen) and Nile tilapia (Oreochromis niloticus). Aquaculture Nutrition 18, Sapkota A., Sapkota A.R., Kucharski M., Burke J., McKenzie S., Walker P., Lawrence R. (2008). Aquaculture practices and potential human health risks: current knowledge and future priorities. Environmental International 34, Windisch W., Schedle K., Plitzner C., Kroismayr A. (2008). Use of phytogenic products as feed additives for swine and poultry. Journal of Animal Sciences 86, E140-E

356 POPULATION GENETIC STRUCTURE OF COMMON CARP Cyprinus carpio IN ANZALI WETLAND AND GORGANROUD ESTUARY USING MICROSATELLITE MARKERS Amirjanati A., Norouzi M.*, Behruz M. Department of Marine Biology and Fisheries Sciences, Tonekabon Branch, Islamic Azad University, Tonekabon, Iran. ABSTRACT The common carp Cyprinus carpio L. belongs to the Cyprinidae, the largest freshwater teleost family and is an important economic species in Caspian Sea. In recent decades the restructuring of common carp stocks has been done through artificial propagation that can change the genetic diversity. Five highly variable microsatellite loci (MFW6, MFW7,MFW9, Syp4, Ca3/4) were used to investigate genetic diversity and population structure of common carp in Anzali wetland and Gorganroud estuary. Totally, 60 samples of fin fish were collected. Allele frequencies, the fixation index Fst, Rst, Fis, observed and expected heterozygosity, genetic distance, Hardy- Weinberg equilibrium were determined at disomic loci amplified from fin tissue samples. The average of alleles per locus was 9.5 (range 7 to 12 alleles per locus in regions). All sampled regions contained private alleles. Average observed and expected heterozygosity were and respectively. In all cases, significant deviations from Hardy-Weinberg equilibrium were reported (P 0.01); only one locus (Syp4) was in Hardy- Weinberg (HW) equilibrium in Anzali wetland samples. Basis on AMOVA for Fst, Rst and Nm values among them indicated a significant difference between the populations. The genetic distance between populations which indicates that the genetic difference among the studied populations is pronounced. These results support the existence of different genetic populations in the Anzali Wetland and Gorganroud estuary. Keywords: Cyprinus carpio, microsatellite, Caspian Sea. *Corresponding author: Mehrnoush Norouzi (mnoroozi@toniau.ac.ir) 1. Introduction Wild carp Cyprinus carpio Linnaeus, 1758, prefers slow waters and inhabits the lower reaches of the Volga and Ural rivers, as well as freshened waters of the North Caspian. It spawns in spring, in the shallows around the islands in the avant-delta. Batch spawning starts at water temperature С and goes through spring and summer. Feeding is suspended prior to and during spawning. Wild carp is a commercially valuable fish, also used in aquaculture. It reaches 1 m in length and more than 30 kg weight. Commercial catches are based on 7- year old fish (60 cm TL, > 5 kg Wt). The maximum recorded age is 20 years. Age of maturity 3-4 years. Fecundity amounts to 1,130 thousand eggs (Kazancheev, 1981). Wild carp is an omnivorous fish, the so-calledwater hog. It feeds on various benthic organisms (chironomids, insect larvae, and mollusks), aquatic plants, and small fish. In winter it stays in holes and does not feed. In recent years, the intensity of wild carp migration into rivers declined and its catches are largely determined by fishing efficiency in the coastal zone and the rivers avant-deltas. In addition to hydrological factors (regulation of runoff, sea level rise, etc.) the population dynamics is influenced significantly by the increased volume of unreported fishing, which affects directly the uptake of commercial fishing quotas and reproduction of fish stocks (Velikova et al. 2012). Among molecular techniques, microsatellite markers are seen as the best way to identify the population structures of pelagic marine fishes because they are abundantly distributed across the genome, demonstrate high levels of allele polymorphism and can easily be amplified with PCR (Sekar et al. 2009). Microsatellite genotypes are particularly helpful in the detection of structure in closely related populations, regardless of whether they are in evolutionary equilibrium. Additionally, primers designed for one species can often be used in other related species (Chistiakov et al. 2005). 356

357 So, the objectives of the present study are to investigate the genetic structure of the common carp and test the hypothesis that the common carp has an identical population in different regions of the South Caspian Sea. 2. Materials and Methods The fishes were caught from two different regions, including 30 samples from Anzali wetland and 30 samples from Gorganroud estuary (Iran) (Figure.1). Fin tissue samples were prepared from 60 fishes of each location and preserved in 95% ethanol and stored at room temperature. Genomic DNA was extracted from fin tissue using a high pure PCR Template preparation kit (Roach, Germany) according to the manufacturer s instructions. The quality and concentration of DNA were assessed by 1% agarose gel electrophoresis and spectrophotometry (CECIL model CE2040) and then stored at -20 C until use. Genomic DNA was used as a template to amplify microsatellite loci by touchdown polymerase chain reaction (PCR). The nuclear DNA was amplified using 5microsatellite primers designed for Cyprinidea (MFW6, MFW7, MFW9 (Dimsoski et al., 2000) SyP4, Ca3/4 (Crooijmans et al., 1997). PCR products were electrophoresed on 10% polyacrylamide gels (29:1 acrylamide: bis-acrylamide; 1X TBE buffer) and followed by silver-staining. Gels were run at 40 ma for 14h. Alleles were sized using Uvitec software, and each gel contained an allelic ladder (100bp) to assist with consistent scoring (by ruler) of alleles. Allele frequencies were estimated using F-statistics and Nei s genetic distance. The total genetic diversity (heterozygosity) within and among populations can be classified as follows: Ho =observed heterozygosity and He=expected heterozygosity. Hardy-Weinberg tests of equilibrium were estimated. Wright s F-statistics (Wright, 1965) as follows: Fis =inbreeding coefficient within individuals relative to the subpopulation for each locus and stellate sturgeon sampling site were assessed; and Fst =inbreeding coefficient within subpopulations relative to the total Fst and Rst were calculated using analysis of molecular variance (AMOVA) to estimate genetic variation among populations and regions. AMOVA calculations and allelic richness (A R ) were performed on Arlequin 3.5 (Excoffier & Lischer 2010) using 10,000 permutations in each case. Nei s genetic identity and distance were determined using a pairwise, individual-by-individual genetic distance, with all codominant data computed in GeanAlex 6 software (Peakall & Smouse 2005). Figure 1. Map showing sampling locations of populations of common carp: Anzali wetland (1) and Gorganroud estuary (2). 357

358 3. Results Overall 5 loci were successfully amplified. All microsatellite primers that were able to produce DNA bands displayed a characteristic disomic banding pattern (Figures 2, 3). The allele frequencies at all loci are given in Table 1. The average number of alleles found per site was 9.5, and the number of alleles in MFW6 ranged from 10 to 11 (A R =9.8), in MFW7 from 12 to 11 (A R =9.6), in MFW9 from 7 to 8 (A R =9.4), in SyP4 from 8 to 11 (A R =9.9), in Ca3/4 from 9 to 8 (A R =9.2). Out of 56 observed alleles, 35 alleles occurred at frequencies of less than 0.05 in all samples. All sampled populations contained a significant number of private alleles (P < 0.05). In total, 8 alleles were found, with the number of private alleles being Anzali wetland 2 alleles, and Gorganroud estuary 6 alleles, none of which was found in other region. The observed and expected heterozygosity averaged and respectively; the observed heterozygosity ranged from In all cases, deviations from Hardy-Weinberg equilibrium were significant (P < 0.01), except for SyP4 in Anzali wetland (Table 1). Estimates of inbreeding coefficient or Fis values were between at MFW9 and at Ca3/4 (mean Fis = 0.043), and positive Fis values a relative dearth of heterozygotes. The average of Fst and Nm via frequency was and 2.7, respectively, and as analyzed with AMOVA, showed a significant genetic differentiation among sites (P<0.01), which suggested that the populations diverged from each other. Figure 2. Microsatellite banding profile of C. carpio using primer pair Ca3/4. Figure 3. Microsatellite banding profile of C. carpio using primer pair MFW7. 358

359 Table 1. Numbers of allelles observed within 2 sampling sites using 5 sets of microsatellite primers. Number of studied samples (n), Observed (Ho) and expected (He) heterozygosities, number of alleles (Na), effective allele (Ne) at 10 loci in three sampling sites. Loci in accordance with H-W equilibrum *P < 0.05; **P < 0.01; ***P < 0.001; ns= not significant. Anzali wetland Gorganroud estuary Touchdown protocol Actual size (bp) MFW6 Na/Ne 10/ / o C/ 35 Ho/He 1* / *** / MFW7 Na/Ne 12/ / o C/ 35 Ho/He 0.700***/ ** / MFW9 Na/Ne 7/ / o C/ 35 Ho/He 1***/ * / SyP4 Na/Ne 8/ / o C/ 35 Ho/He 1ns/ *** / Ca3/4 Na/Ne 9/ / o C/ 35 Ho/He 0.367*** / **/ Average Na/Ne 9.2/ / /9.6 Ho/He / / / Discussion The present study showed the mean number of alleles 6.9 and the allelic range Although the two locations did not show a significant difference in genetic variation between the different loci, there was a significant difference in genetic differentiation. In recent years, increased legal and illegal fishing activities, the reduced return rate of released baby fish resulting from decreased released weight, and reduced natural reproduction have decreased the catch of bony fish (Ghorbani et al., 2010). Although the alleles were observed in the location of freshwater fish and common carps, a large number of alleles with a low frequency were found in this study. The existence of many low-frequency alleles points to genetic bottlenecks or to the effects of inbreeding (Alarcon et al., 2004). The loss of genetic variability in the wild stocks might be related to the severe reduction in the stock of this fish in the past years as a result of overutilization of stocks and excessive non-standard catch of immature fish. The small size of the spring in beach seines has highly increased the portion of the catch of non-standard fish (Ghorbani et al., 2010). Furthermore, issues such as overfishing, environmental pollution, the destruction of the main habitat (the Anzali wetland), and the falling water levels in the Caspian Sea in the past decades have reduced the fish stock in the Anzali wetland (Jafari, 2009). The reducing trend of genetic diversity would predispose them to diseases and increase other selective parameters (Shen and Gong, 2004). If the present trend continues, it will lead to a severe reduction in the population of this species in near future. 359

360 The present research on the common carp shows the mean heterozygosity at 0.81 (±0.09), which is higher than that in freshwater fish (0.54± 0.25) (Dewoody and Avis, 2000). The mean heterozygosity in both sampling locations was lower than the expected heterozygosity. The increased heterozygosity in some places might be due to the existence of null alleles, which are ranked by mistake. Besides the low-frequency alleles, the positive inbreeding coefficient is another reason for reduced genetic diversity and increased inbreeding, which are affected by issues such as overfishing, reduced natural reproduction, and improper artificial reproductive methods. In this study on the common carp, in both sampling locations, almost all loci were out of Hardy- Weinberg equilibrium. The cause for deviation from Hardy-Weinberg equilibrium might be the mixing of populations and non-random mating. The AMOVA test showed a significant difference between the Fst and Rst of the two sampling locations (P<0.01); therefore, the genetic structure of the populations are separated from each other, and at least, two genetically different populations exist in the Anzali wetland and estuary of Gorganroud. The low Fst is due to the high polymorphism (resulting from mutation) in microsatellites, which significantly reduce the Fst (Balloux and Lugan, 2002). Shaklle (1982), Thorpe and Sol-cave (1994), Nei (1972) has reported the Mean genetic distance for the separation of populations at 0.3 (ranging from 0.03 to 0.61), which is compatible with the genetic distance observed in this study, and confirms the genetic distinction between the observed populations. The results of the present study offer initial evidence for the existence of the distinct populations of the common carp in the Anzali Lagoon and the estuary of Gorganroud. Acknowledgments The study was supported by Islamic Azad University, Tonekabon Branch and was performed in Molecular Genetic Lab. We would like to thank Dr. Nazemi (Dept. of Biology). References Alarcon, J. A., Magoulas, A., Georgakopoulos, T., Zouros, E., Alvarez, M. C. (2004). Genetic comparison of wild and cultivated European populations of the gilthead sea bream (Sparus aurata) Aquaculture. Vol. 230, pp Balloux, F., Lugon-Moulin, N. (2002). The estimate of population diffraction with microsatellite markers. Molecular Ecology. 11, Chistiakov, D.A., Hellemans, B., Haley, C.S., Law, A.S., Tsigenopoulos, C.S., Kotoulas, G., Bertotto, D., Libertini A. and Volckaert, F.A. (2005). A microsatellite linkage map of the European sea bass Dicentrarchus labrax L. Genetics. 170, Crooijmans, R. P. M., Bierbooms, V., Komeh, J., Vanderpoe, J. J., Groenen, M. (1997). Microsatellite markers in common carp (Cyprinus carpio). Animal genetics. 28, Dewoody, J. A., Avise, J. C. (2000). Microsatellite variation in Marine, freshwater and anadramous fishes compared with other animals. Journal of fish biology. 56, Dimsoski, P., Toth, G. P., Bagley, M. J. (2000). Microsatellite chaeacterization in (Cyprinidae). Molecular Ecology.9, Excoffier L., Lischer H.E.L. (2010) Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology Resource 10, Ghorbani, R., Yelghi, S., Aghili, S.M. (2010). Survey and Assessment of Predation of Fish Beach seine Cooperative Companies in Golestan Province in Journal of Fisheries Islamic Azad University, Azadshahr Branch. 4, Jafari, N. (2009). Ecological integrity of wetland, their functions and sustainable use, Journal of Ecology and Natural Environment. 1,

361 Kazancheev, E.N. (1981). Fishes of the Caspian Sea. M., Light and food ind. publishers. 167 p. Nei, M., Genetic distance between populations. American Naturalist.106, Nei M. (1972). Genetic distance between populations. American Naturalist 106, Peakall, R., Smouse, P. E. (2006). GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes. 6, Sekar, M., Suresh E., Kumar N.S., Nayak S.K., Balakrishna C. (2009). Microsatellite DNA markers, a fisheries perspective Part 1: The nature of microsatellites. Aquaculture Asia Magazine Shaklle, J. B., Tamaru, C. S., Waples, R. S. (1982). Speciation and evolution of marine fishes studied by electrophoretic analysis of proteins. Pacific Science, Vol.36, pp Shen, X.Y., Gong, Q. L. (2004). Population genetic structure analysis of the imported turbot seedlings Scophthalmus maximus. Using RAPD and microsatellite technique. Oceanology and Limnology Science, Vol. 35, pp Thorpe JP, Sole-Cava A.M. (1994). The use of allozyme electrophoresis in invertebrate systematics. Zoologica Scripta 23, Velikova V.N., Shaudanov A.K., Gasimov A., Korshenko A., Abdoli A., Morozov B., Katunin D. N., Mammadov E., Bokova E. B., Emadi H., Annachariyeva J., Isbekov K., Akhundov M., Milchakova, N., Muradov O., Khodorevskaya R., Shahifar R., Shiganova, T., Zarbaliyeva T. S., Mammadli T., Velikova, V., Barale, V., Kim Y. (2012). Review of the environment and bioresources in the Caspian Sea ecosystem CaspEco Report, 423P. 361

362 MICROSCOPIC STRUCTURE OF SPLEEN IN PERSIAN STURGEON Acipencer persicus Morovvati H. 1 *, Basir Z. 2 *, Abdi R. 3 1 Department of basic Science, Faculty of Veterinary Medicine, University of Tehran, Tehran, Iran 2 Department of basic Science, Faculty of Veterinary Medicine, Ahvaz University of Shahid Chamran, Ahvaz, Iran 3 Department of Marine Biology, Faculty of Marine Science, Khorramshahr University of Marine Science and Technology, Khorramshahr, Iran Abstract The spleen in sturgeons was the largest mass of lymphatic tissue in the body, and is found between abdominal cavity. There two main types of tissue in the spleen are specialised for its two main functions as White pulp contains lymphoid aggregations, mostly lymphocytes, and macrophages which are arranged around the arteries and Red pulp is vascular, and has parencyhma and lots of vascular sinuses was founded.the histological structure of spleen from 3 females and 2 males mature Persian sturgeon was studied.the splenic white pulp diameter, the lymphoid follicles diameter, the splenic capsule thickness, and the splenic trabeculae thickness were determined. In addition, a wide marginal zone surrounded the white pulp and contained sheathed arteries was found. Also, the cross section of the periarterial lymphatic sheath (PALS) containing 1-2 arteries. Key words: Microscopic structure, spleen, Persian sturgeon *Corresponding author: Morovvati Hassn (hmorovvati@ut.ac.ir) 1. Introduction Sturgeons are commercially important fishes valued for their meat but mainly for their role. Formerly omnipresent in the region, heavy fishing of the sturgeon for caviar has forced it to Endangered Species status (North et al, 2002). The Persian Sturgeon has an elongated, bulky body with a bluish tint. Spleen is one of the largest lymphoid organ in the body, and the most important organ of immunological defense for blood invasion (Cataldi & Albano 2002). Generally, blood parasites are removed and phagocytosed in the spleen (Bacha & Linda 2000). Immunohistochemical characterization of the splenic compartments has been performed in humans, bovine, sheep and rats (Cesta 2006). Detailed information about the splenic cellular composition is important for the understanding of its immunological role and for the analysis of several diseases, which causes their main health disorders (Luna 1960). The aim of this study was to examine the different histological compartments and developmental biology in the spleen of persian sturgeon. 2. Materials and Methods The histological structure of spleens from 3 females and 2 males Persian sturgeon was studied. Fresh spleens of fish were collected on the animals directly in breeding center in Iran and were fixed in 10% formalin. All specimens were prepared for paraffin sections as dehydration, clearing, embedding and blocking and stained with haematoxylin and eosin (H&E). The histological work was achieved in our Laboratory of histology at the faculty of veterinary medecine, university of Tehran. The histological structure of spleens was examined, the splenic white pulp diameter, the lymphoid follicles diameter, thickness of the capsule and trabeculae of all samples were measured under a microscopy using micrometer eye piece. 3. Results A thin capsule of connective tissue of the Persian sturgeon spleen was found to have surrounding the splenic parenchyma of 47.13±1.64 ιm. The outermost layer of the splenic capsule was composed of mesothelial cells and was divided into clearly distinguished outer and inner layers. The outer layer consisted mainly of connective tissue including collagen, elastic and fibroblast. The inner layer was composed predominantly of thin smooth muscle cells which seem parallel along in the longitudinal section. The capsule was variable in its thickness between the different areas. The trabeculae extended from the capsule and branched, so it divided the spleen area to many parts. The average thickness of trabeculae was 36.5±1.29ιm, and it consisted of three layers which contain white fibers, fibroblast and smooth muscle cells. Two longitudinal muscle layers were observed and transverse intermediate layer, with very clear space found between the capsule, trabeculae and the parenchyma. The white pulp area was large and its diameter was 92.35±1.2 ιm and irregular shape, and the (PALS), lymph follicles and the marginal zone were very clear. The lymphoid follicles were spherical in shape 362

363 and their diameter measured ±1.81 ιm. The cross section of the PALS contained 1 to2 arteries; the artery was tortuous and branched in PALS. A wide marginal zone surrounds the white pulp and it was contained sheathed arteries and smooth muscle cells (Figures 1&2). Figure 1. External capsule (above arrow) that elongated to the spleen tissue (down arrow) (H&E, 4X). Figure 2. Capsule was variable in its thickness outer layer (o), inner layer (I) with smooth muscles cell and trabeculae (T) (H&E, 4X). 4. Discussion This study showed that the capsule of the Persian sturgeon was thick and divided into an outer connective tissue layer and an inner parallel thin smooth muscle layer. Cesta (2006) described that the capsule is composed of dense fibrous tissue, elastic fibers, and smooth muscle and showed that the outermost layer of the splenic capsule is composed of mesothelial cells, While in some mammales they have only 2-3 layers of smooth muscle cells are oriented perpendicular to each other (Chen & Weiss). Brown and Dellmann (1976) showed that the capsule of horse consists of an outer thick connective tissue and an inner thinner smooth muscle layer. The thickness of the capsule, trabeculae and concentration of smooth muscles are very important agents to make strong contraction when the body need the blood and the smooth muscle concentration may play a role in the immune reactions, and this agree with what was found by Milicevic et al (1986). in their study on human spleen.the white pulp is subdivided into the PALS, the follicles, and the marginal zone. It is composed of lymphocytes, macrophages, dendrite cells, plasma cells, arterioles, and capillaries in a reticular framework similar to that found in the red pulp (Keresztes et al, 1996). Therefore, the large area of white pulp and entity of the tortuous of artery which that supply the PALS area by blood may be play essential role in production blood antibodies. Acknowledgements Financial support was provided by department of basic science, faculty of veterinary medicine, University of Tehran and department of marine biology, faculty of marine science, Khorramshahr University of Marine Science and Technology. The authors gratefully acknowledge deputy of research and technology for her excellent technical assistance in rearing persian sturgeon. References Bacha, W. J., Linda, M. B. (2000). Color Atlas of Veterinary Histology. 2nd Ed. Brown, E., Dellmann H. D. (1976). Lymphatic system. In Textbook of Veterinary Histology (Ed. H. D. Dellmann and E. Brown). pp Philadelphia: Lea & Febiger. Cataldi, E., Albano, C. (2002). Acipenser nccarii; Fine structure of the alimentary canal references to its ontogenesis, Applied Ichthyology 18, Cesta, M. F. (2006). Normal structure, function, and histology of spleen. Toxicological Pathology 34, Chen, L., Weiss, L. (1973). The role of the sinus wall in the passage of the erythrocytes through the spleen. Blood 41, Keresztes, G., Takacs, L., Vilmos, P., Kurucz, E., Ando, I. (1996). Monoclonal antibodies detecting components of the bovine immune system in formaldehyde fixed paraffin-embedded tissue specimens. Veterinary Immunology Immunopathology 52, Luna, L.G. (1960). Manual of Histological Staining Methods of the Armed Forces Institute of Pathology. 3rd ed. by McGraw Book Company. New York, London. Milicevic, Z., Cuschieri, A., Xuereb, A. Milicevic, N. (1996). Stereological study of tissue compartments of the human spleen. Histology Histopathology 11, North, J., Farr, R., Vescei, P. (2002). A comparison of meristic and morphometric characters of green sturgeon Acipenser medirostris. Applied Ichthyology 18,

364 EFFECT OF EXOGENOUS LPS ADMINISTRATION ON MOLECULAR MECHANISMS IN GILTHEAD SEABREAM, Sparus aurata Kyriakis D. 1 *, Feidantsis K. 1, Kaitetzidou E. 1, Triantafyllidis A. 2, Antonopoulou Δ. 1 1 Department of Zoology, eantono@bio.auth.gr 2 Department of Genetics, Development and Molecular Biology, atriant@bio.auth.gr School of Biology, Aristotle University of Thessaloniki, Thessaloniki, Greece Abstract The lipopolysaccharide (LPS) is a factor that resembles bacterial infection and activates the innate immune system. The aim of the present study was to investigate the effect of exogenous in vivo administration of LPS (6 mg/kg body weight) on the expression of signaling proteins, i.e. members of the mitogen activated protein kinases (MAPKs) superfamily, protein-markers of cellular stress, like heat shock proteins (Hsps) and protein markers of apoptosis (Bcl-2, Ubiquitin) in the gilthead seabream (Sparus aurata), after 24 and 72 h. Specifically, we studied the heat shock proteins Hsp70 and Hsp90, the members of the MAPKs ERK 1/2 (Extracellular Signal-Regulated Kinase), JNKs (Jun N-terminal kinases) and p38 MAPK, and Bcl-2 using Western blot analysis. For ubiquitin dot blot analysis was used. LPS administration affected the Hsps in gills after 24h, whereas in the kidney, only Hsp70 levels were affected. After 72h of LPS treatment, an increase was observed in Hsp70 levels in the kidney and the red muscle. Activation of SAPKs (JNKs & p38mapk) was present in all the examined tissues. The phosphorylation ratio of ERKs (phospho ERKs/ERKs) increased in the liver at the 24h trial, while after 72h it decreased in the red muscle and gills. Bcl-2 decreased in all examined tissues except for kidneys at 24 hours. At 72 hours, however, an increase was observed in the brain, liver and red muscle. Concerning the ubiquitin, diminished levels were found in all examined tissues besides the gills and kidneys at 24 hours, while at 72 hours the levels increased. In conclusion, the administration of LPS and the subsequent activation of immunity in sea bream, mobilized tissue-specific and time-dependent homeostatic mechanisms. Keywords: Lipopolysaccharide, MAPKs, HSPs, Bcl2,Ubiquitin *Corresponding author: Kyriakis Dimitrios (kyriakds@bio.auth.gr) ΔΠΗΓΡΑΖ ΔΞΧΓΔΝΟΤ ΥΟΡΖΓΖΖ ΛΗΠΟΠΟΛΤΑΚΥΑΡΗΣΖ Δ ΜΟΡΗΑΚΟΤ ΜΖΥΑΝΗΜΟΤ ΣΖΝ ΣΗΠΟΤΡΑ, Sparus aurata Κπξηάθεο Γ. 1*, Φεηδάληζεο Κ. 1, Κατηεηδίδνπ Δ. 1, Σξηαληαθπιιίδεο Α. 2, Αλησλνπνχινπ Δ. 1 1 Δνβαζηήνζμ Φοζζμθμβίαξ Εχςκ, eantono@bio.auth.gr 2 Δνβαζηήνζμ Γεκεηζηήξ, Ακάπηολδξ ηαζ Μμνζαηήξ Βζμθμβίαξ, atriant@bio.auth.gr Σιήια Βζμθμβίαξ, Ανζζημηέθεζμ Πακεπζζηήιζμ Θεζζαθμκίηδξ, Θεζζαθμκίηδ Πεξίιεςε Ο θζπμπμθοζαηπανίηδξ (Lipopolysaccharide, LPS), πνμζμιμζάγεζ ηδ ααηηδνζδζαηή ιυθοκζδ ηαζ επάβεζ ηδ ιδ εζδζηή ακμζία. ημπυξ ηδξ πανμφζαξ ενβαζίαξ ήηακ δ δζενεφκδζδ ηδξ επίδναζδξ ηδξ ελςβεκμφξ in vivo πμνήβδζδξ LPS (6 mg/kg αάνμξ ζχιαημξ) ζηδκ έηθναζδ ζδιαημδμηζηχκ πνςηεσκχκ ιεθχκ ηδξ οπενμζημβέκεζαξ ηςκ εκενβμπμζμφιεκςκ απυ ιζημβυκα πνςηεσκζηχκ ηζκαζχκ (MAPKs - Mitogen Activated Protein Kinases), πνςηεσκχκ δεζηηχκ ηοηηανζηήξ ηαηαπυκδζδξ, υπςξ μζ πνςηεΐκεξ εενιζημφ πθήβιαημξ (Hsps Heat Shock Proteins) ηαζ πνςηεσκζηχκ δεζηηχκ απυπηςζδξ (Bcl-2, Ubiquitin), ζηδκ ηζζπμφνα (Sparus aurata), ιεηά απυ 24 ηαζ 72 χνεξ. οβηεηνζιέκα ιεθεηήεδηακ ιε ακμζμακίπκεοζδ ηαηά Western Blot, μζ Hsp70 ηαζ Hsp90, ηα ιέθδ ηςκ ΜΑΡΚs, ERK 1/2 (Extracellular Signal-Regulated Kinase), JNKs (Jun N-terminal kinases), p38 MAPK ηαζ δ Bcl-2. Γζα ηδκ μοαζημοζηίκδ πνδζζιμπμζήεδηε δ ιέεμδμξ Dot Blot. Ζ πμνήβδζδ LPS επδνέαζε ηζξ Hsps ζηζξ 24 χνεξ ζηα ανάβπζα, εκχ ζηα κεθνά επδνέαζε ιυκμ ηα επίπεδα ηδξ Hsp70. Μεηά ηζξ 72 χνεξ, πανμοζζάζηδηε αφλδζδ ηςκ επζπέδςκ ιυκμ ηδξ Hsp70 ζηα κεθνά ηαζ ζημκ ενοενυ ιο. Ζ εκενβμπμίδζδ ηςκ SAPΚs (JNKs & p38mapk) θαίκεηαζ υηζ επδνεάζηδηε ζε υθμοξ ημο ζζημφξ. Ο θυβμξ θςζθμνοθίςζδξ ηςκ ERKs (phospho ERKs/ERKs) αολήεδηε ζηζξ 24h ζημ ήπαν, εκχ ιεηά ηζξ 72h ιεζχεδηε ζημκ ενοενυ ιο ηαζ ζηα ανάβπζα. Aφλδζδ ηδξ Bcl-2 πανμοζζάζηδηε ιυκμ ζηα κεθνά ζηζξ 24 χνεξ. ηζξ 72 χνεξ, ςζηυζμ, παναηδνήεδηε 364

365 αφλδζδ ζημκ εβηέθαθμ, ημκ ενοενυ ιο ηαζ ημ ήπαν. ζμ αθμνά ζηδκ μοαζημοζηίκδ, πανμοζζάζηδηε ανπζηά ζηζξ 24 χνεξ ιείςζδ ηδξ έηθναζδξ ηδξ ζημοξ ελεηαγυιεκμοξ ζζημφξ ιε ελαίνεζδ ηα ανάβπζα ηαζ ηα κεθνά, εκχ ακηίεεηα ζηζξ 72 χνεξ αθέπμοιε αφλδζδ αοηήξ. οιπεναζιαηζηά, δ πμνήβδζδ LPS ηαζ δ επαηυθμοεδ εκενβμπμίδζδ ηδξ ακμζίαξ ζηδκ ηζζπμφνα, ηζκδημπμίδζε μιμζμζηαηζημφξ ιδπακζζιμφξ ιε ζζημεζδζηυ ηαζ πνμκμελανηχιεκμ ηνυπμ. Λέμεηο θιεηδηά: Lipopolysaccharide, MAPΚs, HSPs, Bcl2,Ubiquitin *οββναθέαξ επζημζκςκίαξ: Κονζάηδξ Γδιήηνζμξ 1.Δηζαγσγή Γζα ηδ ιεβζζημπμίδζδ ηδξ απυδμζδξ ζηδκ παναβςβή ηςκ ζπεομηαθθζενβεζχκ, ηνίκεηαζ ακαβηαία δ ιεθέηδ ηδξ επίδναζδξ δζαθυνςκ παναβυκηςκ, ζοιπενζθαιαακμιέκςκ ηαζ ηςκ ακμζμπμζδηζηχκ, ζε είδδ μζημκμιζηήξ ζδιαζίαξ, υπςξ δ ηζζπμφνα, Sparus aurata. Ζ επίδναζδ ημο θζπμπμθοζαηπανίηδ (Lipopolysaccharide, LPS), πμο πνμζμιμζάγεζ ηδ ααηηδνζδζαηή ιυθοκζδ ηαζ επάβεζ ηδ ιδ εζδζηή ακμζία, δεκ έπεζ ενεοκδεεί πθήνςξ ζηα εηηνεθυιεκα ράνζα. Δκημφημζξ, ζηδκ ηζζπμφνα, δ πμνήβδζδ LPS επδνεάγεζ ηδκ έηθναζδ ηςκ οπμδμπέςκ πμο εκενβμπμζμφκηαζ απυ πμθθαπθαζζαζηέξ οπενμλεζδζμζςιάηςκ (PPARs) ζε ζοζηήιαηα in vivo ηαζ in vitro (Αntonopoulou et al., 2008; Κασηεηγίδμο et al. (2008, 2011), Δπίζδξ ιε ηδ πνήζδ ιζηνμζοζημζπίαξ έπμοκ ακαδεζπεεί ηα βμκίδζα πμο ειπθέημκηαζ ζημ ιοσηυ ζζηυ ηαζ ηαη επέηηαζδ ζηζξ θεζημονβίεξ ημο ιε ηδκ επίδναζδ ηδξ ακμζμδζέβενζδξ ηαζ πανμοζίαξ παεμβυκςκ ζηδ ηζζπμφνα (Kaitetzidou et al. 2010, 2011, 2012). ημπυξ ηδξ πανμφζαξ ενβαζίαξ ήηακ δ δζενεφκδζδ ηδξ in vivo επίδναζδξ ημο LPS ζηδκ έηθναζδ πνςηεσκχκ δεζηηχκ ηαηαπυκδζδξ (HSPs, MAPKs) ηαζ απυπηςζδξ (Bcl-2 & Ubiquitin) ζε ζζημφξ πμο ζοιιεηέπμοκ ζηδκ ιδ εζδζηή ακμζία. 2. Τιηθά θαη Μέζνδνη Υνδζζιμπμζήεδηακ άημια ηζζπμφναξ ιέζμο αάνμοξ 47g, ζε δελαιεκέξ πςνδηζηυηδηαξ 500 L, ζηα μπμία πμνδβήεδηε 6mg LPS απυ Escherichia coli (Sigma) ακά kg αάνμοξ ζχιαημξ. Πναβιαημπμζήεδηε δεζβιαημθδρία ιεηά απυ 24 ηαζ 72 χνεξ ζε ακαζζεδημπμζδιέκα ράνζα ζημοξ αηυθμοεμοξ ζζημφξ: εβηέθαθμ, ανάβπζα, ήπαν, κεθνυ ηαζ ενοενυ ιο. Σα δείβιαηα ρφπεδηακ ζε οβνυ άγςημ ηαζ απμεδηεφηδηακ ζημοξ -80 C ιέπνζ ηζξ ακαθφζεζξ. Πναβιαημπμζήεδηε μιμβεκμπμίδζδ ηςκ δεζβιάηςκ ζζημφ (5 αζμθμβζηέξ επακαθήρεζξ βζα ηάεε ζζηυ) ηαζ πνμζδζμνζζιυξ ηδξ μθζηήξ πνςηεΐκδξ ιε ηδ ιέεμδμ Bradford, ιε πνήζδ δζαθφιαημξ πνςζηζηήξ Bio-Rad Protein Assay (Bio-Rad, Hercules, CA). Ζ ακμζμακίπκεοζδ ηςκ MAPKs, HSPs ηαζ Bcl2 έβζκε ιε πνήζδ ηδξ ιεευδμο SDS-PAGE ηαζ Western blot, εκχ βζα ηδκ μοαζημοζηίκδ πνδζζιμπμζήεδηε δ ιέεμδμξ Dot blot. Γζα ηζξ ιειανάκεξ πνδζζιμπμζήεδηε ημ δζάθοια πδιεζμθεμνζζιμφ (LumiGLO Reagent and Peroxide: 2,7 ml dh 2 O, 0,15 ml LumiGLO, 0,15 ml Peroxide. Σέθμξ, δ ποηκμιέηνδζδ ηςκ πνςηεσκχκ έβζκε ιε ηδ αμήεεζα ημο πνμβνάιιαημξ GelPro (GelPro Analyzing Software, Media Cybernetics) (Φεζδάκηζδξ, 2012). 3. Απνηειέζκαηα - πδήηεζε 3.1 Δπίδναζδ LPS ζηζξ HSPs Οζ Hsps απμηεθμφκ ιζα μζημβέκεζα ελαζνεηζηά ζοκηδνδιέκςκ πνςηεσκχκ. Γζαδναιαηίγμοκ έκα πμθφ ζδιακηζηυ γςηζηυ νυθμ ζηδ δζαηήνδζδ ηδξ θοζζμθμβζηήξ ηοηηανζηήξ μιμζυζηαζδξ, πνμζηαηεφμκηαξ ημ ηφηηανμ απυ πμζηίθμοξ πενζααθθμκηζημφξ ηαζ θοζζμθμβζημφξ πανάβμκηεξ (ππ. ζζημί πανάβμκηεξ ηαζ ιμνζαηέξ ημλίκεξ, δ εενιμηναζία). Ζ πμνήβδζδ LPS επδνέαζε ηζξ HSPs ζηζξ 24 χνεξ ζηα ανάβπζα, εκχ ζηα κεθνά επδνέαζε ιυκμ ηα επίπεδα ηδξ Hsp70. ηζξ 72 χνεξ, πανμοζζάζηδηε επαβςβή ιυκμ ηδξ Hsp70 ζηα κεθνά ηαζ ζημκ ενοενυ ιο ζηα άημια ιε LPS πμνήβδζδ (πήια 1,2). ρήκα 1,2: Έθθξαζε ησλ Hsp70 & Hsp90 ππφ ηελ επίδξαζε LPS ζηελ ηζηπνχξα κεηά απφ 24 θαη 72 ψξεο. 3.2 Δπίδναζδ LPS ζηζξ MAPKs Ζ οπενμζημβέκεζα MAPK απμηεθείηαζ απυ ηνεζξ ηφνζεξ μζημβέκεζεξ ζοκηδνδιέκςκ πνςηεσκζηχκ ηζκαζχκ: ERKs, JNKs, ηαζ p38 MAPK. Παίγμοκ ζδιακηζηυ νυθμ ζηδ νφειζζδ ηδξ βμκζδζαηήξ έηθναζδξ, ζηδκ μνβάκςζδ ημο ηοηηανζημφ ζηεθεημφ, ζηδ μιμζυζηαζδ ημο ιεηααμθζζιμφ, ζηδ ηοηηανζηή αφλδζδ ηαζ ζηδκ απυπηςζδ. Ζ εκενβμπμίδζδ ηςκ SAPΚs (JNKs & p38mapk) θαίκεηαζ υηζ επδνεάζηδηε ζε υθμοξ ημο ζζημφξ 24 χνεξ ιεηά ηδ 365

366 πμνήβδζδ LPS. οβηεηνζιέκα, μ θυβμξ θςζθμνοθίςζδξ ηςκ JNKs (phosphojnks/jnks) αολήεδηε ζδιακηζηά ζε ήπαν ηαζ ενοενυ ιο, εκχ ιεζχεδηε ζδιακηζηά ζηα ανάβπζα. Δπίζδξ, μ θυβμξ θςζθμνοθίςζδξ ηδξ p38 MAPK (phospho p38 MAPK/p38 MAPK) αολήεδηε ζδιακηζηά ζημκ ενοενυ ιο, αθθά ιεζχεδηε ζδιακηζηά ζημ ήπαν ηαζ ζηα κεθνά. Ο θυβμξ θςζθμνοθίςζδξ ηςκ ERKs (phospho ERKs/ERKs) αολήεδηε ζδιακηζηά ζημ ήπαν. Μεηά ηζξ 72 χνεξ, πανμοζζάζηδηε ζδιακηζηή ιείςζδ ημο θυβμο θςζθμνοθίςζδξ ηςκ JNKs ζηα ανάβπζα ηαζ ζημκ ενοενυ ιο, εκχ μ θυβμξ θςζθμνοθίςζδξ ηδξ p38 MAPK αολήεδηε ζδιακηζηά ζημ ήπαν ηαζ ιεζχεδηε ζδιακηζηά ζηα ανάβπζα. Ο θυβμξ θςζθμνοθίςζδξ ηςκ ERKs (phospho ERKs/ERKs) ιεζχεδηε ζδιακηζηά ζημκ ενοενυ ιο ηαζ ζηα ανάβπζα (πήια 4,5,6). ρήκα 4,5,6. Φσζθνξπιίσζε ησλ ERK 1/2, ησλ JNKs θαη ηεο p38 MAPK ζηνλ εγθέθαιν, βξάγρηα, λεθξφ, εξπζξφ κπ θαη ήπαξ ππφ ηελ επίδξαζε LPS ζηελ ηζηπνχξα κεηά απφ 24 θαη 72 ψξεο. 3.3 Δπίδναζδ LPS ζηδκ Bcl-2 Σα ιέθδ ηδξ μζημβέκεζαξ Bcl-2 εθέβπμοκ ημ εζςηενζηυ ιμκμπάηζ ηδξ απυπηςζδξ. Ζ ζζμννμπία ιεηαλφ ηδξ επζαίςζδξ ηαζ ημο εακάημο εκυξ ηοηηάνμο ηαεμνίγεηαζ απυ ηα ακηζ-απμπηςηζηά ηαζ πνμ-απμπηςηζηά ιέθδ ηδξ μζημβέκεζαξ (Mérino & Bouillet, 2009). πςξ θαίκεηαζ ζηδκ Δζη. 7, δ Bcl-2 ζηζξ 24 χνεξ επάβεηαζ ζδιακηζηά ιυκμ ζηα κεθνά. ηζξ 72 χνεξ ςζηυζμ, παναηδνήεδηε αφλδζδ ζημκ εβηέθαθμ, ενοενυ ιο ηαζ ήπαν ζε ζπέζδ ιε ηδκ μιάδα εθέβπμο (πήια 7). ρήκα 7. Έθθξαζε ηεο Bcl-2 ππφ ηελ επίδξαζε LPS ζηελ ηζηπνχξα κεηά απφ 24 θαη 72 ψξεο. 3.4 Δπίδναζδ LPS ζηδκμοαζημοσηίκδ Ζ μοαζημοσηίκδ απμηεθεί ααζζηή πνςηεΐκδ ημο ιδπακζζιμφ απμζημδυιδζδξ ηςκ πνςηεσκχκ ημο ηοηηάνμο, μδδβχκηαξ ηζξ ιεημοζζςιέκεξ πνςηεΐκεξ πμο δεκ ακαδζπθχεδηακ απυ ηζξ HSPs, ζηα πνςηεμζχιαηα ηαζ θοζμζχιαηα. Ανπζηά ζηζξ 24 χνεξ αθέπμοιε ιείςζδ ηδξ έηθναζδξ ηδξ μοαζημοζηίκδξ ιε ελαίνεζδ ηα ανάβπζα ηαζ ηα κεθνά, εκχ ακηίεεηα ζηζξ 72 χνεξ αθέπμοιε αφλδζδ αοηήξ ζε ζπέζδ ιε ηδκ ακηίζημζπδ μιάδα εθέβπμο (πήια 8) 366

367 ρήκα 8. Έθθξαζε ηεο νπβηθνπηηίλεο ππφ ηελ επίδξαζε LPS ζηελ ηζηπνχξα κεηά απφ 24 θαη 72 ψξεο. πκπεξαζκαηηθά: H πμνήβδζδ LPS ηαζ δ επαηυθμοεδ εκενβμπμίδζδ ηδξ ιδ εζδζηήξ ακμζίαξ ζηδκ ηζζπμφνα ηζκδημπμίδζε μιμζμζηαηζημφξ ιδπακζζιμφξ ιε ζζημεζδζηυ ηαζ πνμκμελανηχιεκμ ηνυπμ. Βηβιηνγξαθία Κασηεηγίδμο Δ., Βνάζημο Γ., Planas J.V., Ακηςκμπμφθμο Δ. (2008). Διπθμηή ηςκ οπμδμπέςκ πμο εκενβμπμζμφκηαζ απυ πμθθαπθαζζαζηέξ οπενμλεζδζμζςιάηςκ (PPAR) ζηδ ιδ εζδζηή ακμζία ηδξ ηζζπμφναξ (Sparus aurata). ημ 30 o Δπηζηεκνληθό πλέδξην ηεο Διιεληθήο Δηαηξίαο Βηνινγηθώλ Δπηζηεκώλ, Θεζζαθμκίηδ, Μαΐμο, ζεθ Κασηεηγίδμο, Δ., Crespo, D., Βνάζημο, Γ., Planas, J., Ακηςκμπμφθμο, Δ. (2010). Γμκζδζαηή έηθναζδ ζημ ιοσηυ ζζηυ ηδξ ηζζπμφναξ (Sparus aurata, Linnaeus, 1758) ιεηά απυ πνυηθδζδ εκενβμπμίδζδξ ηδξ ιδ εζδζηήξ ακμζίαξ. ημ 14 ν Παλειιήλην πλέδξην Ιρζπνιόγσλ, Πεζναζάξ, 6-9 Μαΐμο, 2010, ζεθ Κασηεηγίδμο Δ.,Βνάζημο Γ., Planas J.V., Ακηςκμπμφθμο Δ. (2011). Δπίδναζδ ακμζμθμβζηχκ παναβυκηςκ ζηδκ έηθναζδ ηςκ οπμδμπέςκ πμο εκενβμπμζμφκηαζ απυ πμθθαπθαζζαζηέξ ηςκ οπενμλεζδζμζςιάηςκ (PPAR) ζε ηοηηανζηή ζεζνά ηδξ ηζζπμφναξ (Sparus aurata, Linnaeus 1758). ημ 33 o Δπηζηεκνληθό πλέδξην ηεο Διιεληθήο Δηαηξίαο Βηνινγηθώλ Δπηζηεκώλ, Έδεζζα, Μαΐμο, ζεθ Φεζδάκηζδξ Κ. (2012) Eπμπζαηέξ αζμπδιζηέξ ηαζ θοζζμθμβζηέξ απμηνίζεζξ ηδξ ηζζπμφναξ (Sparus aurata). οζπέηζζδ ιε ηδ εενιμηναζία ηδξ εάθαζζαξ ηαζ ηδκ ηθζιαηζηή αθθαβή. Γζδαηημνζηή δζαηνζαή. Σιήια Βζμθμβίαξ, Α.Π.Θ. Antonopoulou, E., Kaitetzidou, E., Vraskou, G., Planas, J. (2008). PPAR expression during immune and metabolic challenges in fish. In 33rd FEBS Congress & 11th IUBMB Conference Athens, Greece, 28 June-3 July FEBS Journal 275 (Suppl.1) (2008) ζεθ Kaitetzidou E, Crespo D., Vraskou G., Planas JV, Antonopoulou E. (2011). Transcriptional effects of lipopolysaccharide in sea bream (Sparus aurata, Linnaeus 1758) tissues with emphasis on the regulation of peroxisome proliferator activated receptors. In: International Symposium Genomics in Aquaculture 2011, Heraklion, Crete, September, Kaitetzidou E., Crespo D., Vraskou Y., Antonopoulou E., Planas J.V. (2012). Transcriptomic Response of Skeletal Muscle to Lipopolysaccharide in the Gilthead Seabream (Sparus aurata) Mar Biotechnol 14:

368 SPERM QUALITY CHARACTERISTICS OF WILD THICK LIPPED GREY MULLET Chelon labrosus Kokokiris L. 1 *, Minos G. 1, Simeonidis C. 1, Mylonas C. 2, Nathanailides C. 3 1 Department of Fisheries Technology and Aquaculture, Alexander Technological Educational Institute of Thessaloniki, P.O. BOX 157, GR-63200, Nea Moudania, Hellas, 2 Institute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, P.O. Box 2214, Iraklion, Crete 71003, Hellas, 3 Department of Fisheries Technology and Aquaculture, Technological Educational Institution of Western Greece, Nea Ktiria 30200, Messolonghi, Hellas Abstract The objectives of this study were to determine the basic parameters of thick lipped grey mullet, Chelon labrosus semen in terms of sperm volume, sperm concentration, and sperm motility. Sperm was analyzed in 28 mature male individuals from Thermaikos Gulf, sampled during February and March. Sperm volume ranged from 1.5 to 6 ml -1 Kg BW (mean value: 4.0 ml ± 1.5) and density from 4 to 45.5 x 10 9 spermatozoa ml -1 sperm (mean value: 26.5 ± 2.5 x 10 9 spz x ml -1 ). The percentage of motile spermatozoa (sperm motility) ranged between 10 and 95% (mean value: 40.4% ± 4) and the duration of their forwarded movement from 1.14 to 2.39 min (mean value: 1.6 ± 0.05 min). Sperm quality parameters ranged in values similar to those of male thick lipped grey mullets kept in captivity. Data collected on sperm quality could be useful for optimization of fertilization procedures and procedures of storage of milt. Key words: sperm quality parameters, thick lipped grey mullet *Corresponding author: Lambros Kokokiris (lamprosk@aqua.teithe.gr) ΕΚΣΙΜΗΗ ΣΗ ΠΟΙΟΣΗΣΑ ΣΟΤ ΠΕΡΜΑΣΟ ΑΓΡΙΩΝ ΓΕΝΝΗΣΟΡΩΝ ΣΟΤ ΚΕΦΑΛΟΕΙΔΟΤ Chelon labrosus Κοκοκφρησ Λ. 1 *, Μίνοσ Γ. 1, υμεωνίδησ X. 1, Mυλωνάσ Κ. 2, Ναθαναηλίδησ Κ. 3 1 Σιήια Σεπκμθμβίαξ Αθζείαξ ηαζ Τδαημηαθθζενβεζχκ, Αθελάκδνεζμ Σεπκμθμβζηυ Δηπαζδεοηζηυ Ίδνοια Θεζζαθμκίηδξ, Σ.Θ 157, 63200, Νέα Μμοδακζά, Δθθάδα, 2 Ηκζηζημφημ Θαθάζζζαξ Βζμθμβίαξ, Βζμηεπκμθμβίαξ ηαζ Τδαημηαθθζενβεζχκ, Δθθδκζηυ Κέκηνμ Θαθάζζζςκ Δνεοκχκ, Σ.Θ. 2214, 71003, Ζνάηθεζμ, Δθθάδα, 3 Σιήια Tεπκμθμβίαξ Αθζείαξ ηαζ Τδαημηαθθζενβεζχκ, ΣΔΗ Γοηζηήξ Δθθάδμξ, Νέα Κηίνζα 30200, Μεζμθυββζ, Δθθάδα Πεξίιεςε O ζημπυξ ηδξ ενβαζίαξ ήηακ κα πενζβνάρεζ ηα ααζζηά πμζμηζηά παναηηδνζζηζηά ημο ζπένιαημξ άβνζςκ βεκκδηυνςκ ημο ηεθαθμεζδμφξ, Chelon labrosus (πεθυκζ, πεθμκάνζ, ιαονάηζ). Ζ ακάθοζδ ημο ζπένιαημξ έβζκε ζε 28 βεκκήημνεξ (0,54-1,2 Kg) πμο αθζεφεδηακ ζημ Θενιασηυ Κυθπμ, ημο ιήκεξ Φεανμοάνζμ ηαζ Μάνηζμ. Ο υβημξ ημο ζπένιαημξ ηοιάκεδηε απυ 1,5 έςξ ηαζ 6 ml ακά Kg ζςιαηζημφ αάνμοξ (ιέζμξ υβημξ: 4,0 ± 1,5mL ) εκχ δ ποηκυηδηα ημο απυ 4 έςξ ηαζ 45,5 x 10 9 ζπενιαημγςάνζα ακά ml ζπένιαημξ (ιέζδ ηζιή: 26,5 ± 2,5 x

369 ml -1 ). Σα ζπενιαημγςάνζα εκενβμπμζήεδηακ ζε εαθαζζζκυ κενυ, ζε πμζμζηυ απυ 10 έςξ ηαζ 95% αθθά δ ιέζδ ηζκδηζηυηδηα ήηακ παιδθή (40,4% ± 4). Ζ δζάνηεζα ηδξ ηζκδηζηυηδηαξ ηςκ ζπενιαημγςανίςκ, ηοιάκεδηε απυ 1,14 έςξ ηαζ 2,39 min (ιέζδ ηζιή: 1,6 ± 0.05 min). H πμζυηδηα ημο ζπένιαημξ είκαζ πανυιμζα ι αοηή βεκκδηυνςκ πμο δζαηδνμφκηακ ζε ζοκεήηεξ αζπιαθςζίαξ. Σα δεδμιέκα ηδξ ενβαζίαξ εα πνδζζιμπμζδεμφκ βζα ηδ αεθηζζημπμίδζδ ηςκ πνςημηυθθςκ παναβςβήξ βμκζιμπμζδιέκςκ αοβχκ ηαζ δζαηήνδζδξ ημο ζπένιαημξ. Λέξειρ κλειδιά: Chelon labrosus, πνηόηεηα ζπέξκαηνο, ρειόλη, ρεινλάξη, αλαπαξαγσγή *οββναθέαξ επζημζκςκίαξ: Λάιπνμξ Κμημηφνδξ (lamprosk@aqua.teithe.gr) 1. Δηζαγσγή Σμ ηεθαθμεζδέξ Chelon labrosus (Risso, 1827), ημζκχξ πεθμκάνζ, πεθυκζ ή ιαονάηζ, δζαεέηεζ ζάνηα ελαζνεηζηήξ πμζυηδηαξ ηαζ πανάθθδθα ορδθή πνμζανιμζηζηυηδηα ζε ζοκεήηεξ εηηνμθήξ ζε έκα ιεβάθμ εφνμξ αθαηυηδηαξ, παναηηδνζζηζηά πμο ημο πνμζδίδμοκ μζημκμιζηυ εκδζαθένμκ βζα ηδ Μεζμβεζαηή ζπεομηαθθζένβεζα (Ben Khemis et al. 2006). Χζηυζμ, δ ειπμνζηή ακάπηολδ ηδξ εηηνμθήξ εκυξ είδμοξ πνμτπμεέηεζ ημκ έθεβπμ ηδξ ακαπαναβςβήξ ζε ζοκεήηεξ αζπιαθςζίαξ ηαζ ηδ ιαγζηή παναβςβή βμκζιμπμζδιέκςκ αοβχκ (Mylonas & Zohar 2009). Ζ πμζυηδηα ημο ζπένιαημξ είκαζ ιία απυ ηζξ ζδιακηζηυηενεξ παναιέηνμοξ ηδξ ακαπαναβςβζηήξ θοζζμθμβίαξ ηςκ ρανζχκ βζαηί επδνεάγεζ ηαεμνζζηζηά ηδκ επζηοπία ηδξ βμκζιμπμίδζδξ ηαζ ηδκ παναβςβή ηςκ αοβχκ (Billard et al. 1995). Οζ δδιμζζεοιέκεξ πθδνμθμνίεξ πμο δζαεέημοιε βζα ηδ θοζζμθμβία ημο ζπένιαημξ ηςκ ηεθαθμεζδχκ, ζοιπενζθαιαακμιέκμο ημο ημζκμφ ηέθαθμο (Mugil cephalus) είκαζ εθάπζζηεξ (Lee et al. 1992, Sahinoz et al. 2008, Yeganeh et al. 2008) εκχ δεκ βκςνίγμοιε ηαευθμο ηα ααζζηά παναηηδνζζηζηά ηαζ ηδ θοζζμθμβία ημο ζπένιαημξ ημο πεθμκζμφ. Ο ζημπυξ αοηήξ ηδξ ενβαζίαξ ήηακ κα πενζβνάρεζ ηα παναηηδνζζηζηά ηδξ πμζυηδηαξ ημο ζπένιαημξ ημο πεθμκζμφ ηαζ κα ζοβηεκηνχζεζ δεδμιέκα πνήζζια βζα ηδ αεθηζζημπμίδζδ ηςκ πνςημηυθθςκ βμκζιμπμίδζδξ ηαζ δζαηήνδζδξ ημο ζπένιαημξ. 2. Τιηθά θαη κέζνδνη H πμζυηδηα ημο ζπένιαημξ πενζβνάθδηε ζε 28 ανζεκζηά άημια ημο είδμοξ Chelon labrosus, ηα μπμία ζοθθέπεδηακ ιε ηοηθζηά δίπηοα, ζε πανάηηζα πενζμπή ημο Θενιασημφ Κυθπμο (40º Ν; 22º Δ, 12-13ºC, αθαηυηδηα: psu, δζαθοιέκμ μλοβυκμ: ppm) ημοξ ιήκεξ Φεανμοάνζμ ηαζ Μάνηζμ. Μεηά απυ πθήνδ κάνηςζδ ζε δζάθοια 2-θαζκμλοαζεακυθδξ (300 ppm), λεπθφεδηε δ ημζθζαηή πενζμπή ιε εαθαζζζκυ κενυ ηαζ ζημοπίζηδηε ιε απμννμθδηζηυ πανηί μ βεκκδηζηυξ πυνμξ. Σμ ζπένια ελςεήεδηε ιε πνμζεηηζηέξ ιαθάλεζξ χζηε κα απμθεοπεεί δ ακάιζλδ ημο ιε ημ πενζεπυιεκμ ημο εκηένμο ηαζ ηα μφνα ηαζ μβημιεηνήεδηε ζε δζαααειζζιέκμ ζςθήκα υβημο 5 ml, ζε 22 άημια ηα μπμία έδζκακ άθεμκμ ζπένια µεηά απυ εθαθνά πίεζδ ή έδζκακ εφημθα ζπένµα µεηά ηδκ πνχηδ µάθαλδ (δείηηδξ ζπενιίαζδξ 3 ηαζ 2 ακηίζημζπα, Mylonas et al. 2003). Ζ ποηκυηδηα ημο ζπένιαημξ (ανζειυξ ζπενιαημγςανίςκ x ml -1 ) οπμθμβίζηδηε ζε υθα ηα άημια, ζε δείβια 0,1mL ζπένιαημξ ημ μπμίμ αναζχεδηε 2500x ζε απζμκζζµέκμ κενυ. Ο οπμθμβζζιυξ έβζκε ιε ηαηαιέηνδζδ ηςκ ζπενιαημγςανίςκ ζε ηοηυιεηνμ Neubauer, ζε μπηζηυ ιζηνμζηυπζμ (ΟΜ, 400x, 2 επακαθήρεζξ ακά δείβια). Ζ ηζκδηζηυηδηα (% πμζμζηυ ηζκμφιεκςκ ζπενµαημγςανίςκ µε εµπνυζεζα ηζκδηζηυηδηα) εηηζιήεδηε ζε ΟΜ (400 x) ζε ζπένια υβημο 1-5 ιl, ημ μπμίμ ζοθθέπεδηε ζηδ ιφηδ αεθυκαξ 19G ηαζ αναζχεδηε ζε ακηζηεζιεκμθυνμ πθάηα ιε ιζα ζηαβυκα εαθαζζζκμφ κενμφ (1 ml, 32 psu). ημ ίδζμ δείβια εηηζιήεδηε ηαζ δ δζάνηεζα ηδξ ηζκδηζηυηδηαξ ηςκ ζπενιαημγςανίςκ (μ πνυκμξ πμο ιεζμθααεί βζα ηδ µείςζδ ηδξ ηζκδηζηυηδηαξ ζημ 10% ηςκ παναηδνμφµεκςκ ζπενµαημγςανίςκ), πνδζζιμπμζχκηαξ ρδθζαηυ νμθυζ. Ζ πμζυηδηα ημο ζπένµαημξ εηηζµήεδηε απυ ημκ ίδζμ παναηδνδηή ζε υθα ηα δείβιαηα 3. Aπνηειέζκαηα To αάνμξ ηςκ ανζεκζηχκ ηοιάκεδηε απυ 0,54 έςξ 1,2 Kg (ιέζδ ηζιή: 0,80±0,17 Kg, δθζηίαξ 7-10 εηχκ, αδδιμζίεοηα απμηεθέζιαηα). Μυκμ δφμ (6% ηςκ βεκκδηυνςκ) απυ ημοξ βεκκήημνεξ δεκ πανήβαβακ 369

370 ζπένια εκχ ακηίεεηα μζ οπυθμζπμζ έδζκακ απυ θίβμ (12%) έςξ πμθφ ζπένια (82%), ζημζπείμ πμο οπμδδθχκεζ υηζ ημκ Φεανμοάνζμ ηαζ ημ Μάνηζμ ηα άβνζα πεθμκάνζα είκαζ ήδδ χνζια. Ο υβημξ ημο ζπένιαημξ ηοιάκεδηε απυ 1,5 έςξ ηαζ 6 ml ακά Kg ζςιαηζημφ αάνμοξ (ιέζμξ υβημξ: 4,0 ± 1,4mL) εκχ δ ποηκυηδηα ημο απυ 4 έςξ ηαζ 45,5 x 10 9 ζπενιαημγςάνζα ακά ml ζπένιαημξ (ιέζδ ηζιή: ± SE: 26.5 ± 2,5 x 10 9 ml -1 ). Σα ζπενιαημγςάνζα ιεηά ηδκ εκενβμπμίδζδ ημοξ ιε εαθαζζζκυ κενυ, ειθάκζζακ ειπνυζεζα ηζκδηζηυηδηα ζε πμζμζηυ απυ 10 έςξ ηαζ 95% αθθά βεκζηά δ ιέζδ ηζκδηζηυηδηα ήηακ παιδθή (40,4%±4). Ζ δζάνηεζα ηδξ ηζκδηζηυηδηαξ ηοιάκεδηε απυ 1,14 έςξ ηαζ 2,39 min (ιέζδ ηζιή: 1,6 ± 0.05 min). Ζ ακάθοζδ ζοζπέηζζδξ Pearson δεκ πνμζδζυνζζε ηάπμζα ζπέζδ ακάιεζα ζημ ζςιαηζηυ αάνμξ ιε μπμζαδήπμηε απυ ηζξ ελεηαγυιεκεξ παναιέηνμοξ, βζα ημ ιέβεεμξ (εφνμξ αάνμοξ) ηςκ αηυιςκ πμο ελεηάζηδηακ. 4. πδήηεζε Οζ πανάιεηνμζ ηδξ πμζυηδηαξ ημο ζπένιαημξ (υβημξ, ποηκυηδηα, ηζκδηζηυηδηα, δζάνηεζα ηζκδηζηυηδηαξ) ηςκ άβνζςκ βεκκδηυνςκ ημο πεθμκζμφ ηοιαίκμκηαζ ζε πανυιμζεξ ηζιέξ ιε αοηέξ βεκκδηυνςκ πμο δζαηδνήεδηακ ζε ζοκεήηεξ αζπιαθςζίαξ ηαζ παναημθμοεήεδηακ ζε εαδμιαδζαία αάζδ ηαηά ηδκ πενίμδμ ηδξ ζπενιίαζδξ (Κμημηφνδξ θαη ζπλ. 2013) αθθά ηαζ βεκκδηυνςκ ζημοξ μπμίμοξ πμνδβήεδηε μ εηθοηζηυξ πανάβμκηαξ ηδξ ςπνζκμπμζδηζηήξ μνιυκδξ (GnRHa) βζα κα ελεηαζηεί δ επίδναζδ ημο ζηδκ πμζυηδηα ημο ζπένιαημξ (Kokokiris et al. 2014). H ζοβηνζηζηή αλζμθυβδζδ δείπκεζ υηζ δ δζαηήνδζδ ηςκ βεκκδηυνςκ ζε ζοκεήηεξ αζπιαθςζίαξ αθθά ηαζ δ πμνήβδζδ ημο GnRHa δεκ επζθένμοκ ζδιακηζηέξ αθθαβέξ ζηζξ παναιέηνμοξ ημοξ ζπένιαημξ ημο πεθμκζμφ. Οζ πανάιεηνμζ ημο ζπένιαημξ ημο πεθμκζμφ ηοιαίκμκηαζ ζε ηζιέξ πανυιμζεξ ιε αοηέξ ζε άθθα ζε άθθα Μεζμβεζαηά εαθαζζζκά είδδ (Πίκαηα 1, δεξ ακαζηυπδζδ ηςκ Suquet et al., 1994). Πανυιμζεξ ηζιέξ ηζκδηζηυηδηαξ ημοξ ζπένιαημξ έπμοκ ακαθενεεί βζα ημ Liza abu (26-77%, ιέζδ ηζιή: 54,25%, Sahinoz et al. 2008) αθθά ζδιακηζηά ορδθυηενεξ (πμο θεάκμοκ ημ 100%) ακαθένεδηακ βζα ημκ ημζκυ ηέθαθμ, M. cephalus, ηαηά ηδκ εκενβμπμίδζδ ζπένιαημξ ημο, ιε εαθαζζζκυ κενυ αθαηυηδηαξ psu (Lee et al. 1992). Δπίζδξ, πανυιμζα δζάνηεζα ηζκδηζηυηδηαξ ακαθένεδηε βζα ημκ ημζκυ ηέθαθμ (3 min, Τeganeh et al. 2008) αθθά ηαζ βζα ημ ηεθαθμεζδέξ, L. abu (ιέζδ ηζιή: 5,5 min, Sahinoz et al. 2008). Πίλαθαο 1. Βαζηθά γλσξίζκαηα ηεο πνηφηεηαο ηνπ ζπέξκαηνο ηνπ θεθαινεηδνχο Liza abu θαη εθηξεθφκελσλ εηδψλ ηεο Μεζνγεηαθήο ηρζπνθαιιηέξγεηαο. βημξ ζπένιαημξ (ml Kg -1) Ποηκυηδηα (x 10 9 ml -1 ) Κζκδηζηυηδηα (%) Γζάνηεζα ηζκδηζηυηδηαξ (min) οββναθέαξ Liza abu 0,02-0,08 1 4,27 26,5-77,1 0,25-12 Sahinoz et al., 2008 Pagrus pagrus 2-5,3 8,6-23, Mylonas et al., 2003 Diplodus puntazzo 1, >80% 2-6 Papadaki et al., 2008 Argyrosomus regius - 18,9-31, ,78-1,27 Mylonas et al., 2013 Scopthalmus maximus 0,2-2,2 0,7-38,3-1-7 Suquet et al., 1992,1994 Dicentrarchus labrax , ,66-3 Sorbera et al., 1996, Fauvel et al., 1999, Rainis et al., 2003 Σhynnus thynnus 0, Suquet et al., υβημξ ζπένιαημξ ζε ml ηαζ υπζ ζε ml x Kg -1. Ακ ηαζ ζηα ράνζα, o υβημξ ημο ζπένιαημξ ιπμνεί κα ιεηααάθθεηαζ ηαηά ηδ δζάνηεζα ηδξ ζπενιίαζδξ (Mylonas et al. 2003, Papadaki et al. 2008, Suquet et al. 2010) μ ιέζμξ υβημξ ηςκ 4mL Kg -1 ζε ζοκδοαζιυ ιε ηδκ ορδθή ποηκυηδηα ημο ζπένιαημξ, επανηεί βζα ηδκ ηεπκδηή βμκζιμπμίδζδ ηαζ δεκ εέηεζ ηάπμζμ πενζμνζζιυ ζηα πνςηυημθθα βζα ηδκ παναβςβή βμκζιμπμζδιέκςκ αοβχκ. ηα πενζζζυηενα είδδ ρανζχκ παναηδνείηαζ ιζα 370

371 πμζηζθυηδηα ηςκ ηζιχκ ηδξ ποηκυηδηαξ ιεηαλφ ηςκ αηυιςκ (Suquet et al. 1994). ηδκ πενίπηςζδ ημο πεθμκζμφ, έκα ιένμξ αοηήξ ηδξ πμζηζθυηδηαξ ιπμνεί κα ενιδκεοεεί απυ ηδ ζοπκή πανμοζία δεζβιάηςκ ζπένιαημξ ιε ιεβάθμ ζλχδεξ, ηα μπμία βεκζηά δίκμοκ ζδιακηζηά ιεβαθφηενεξ ποηκυηδηεξ απυ ηα θζβυηενμ παπφννεοζηα δείβιαηα, υπςξ έδεζλακ μζ Suquet et al (1992) ζημ ηαθηάκζ, Scopthalmus maximus. Οζ ορδθέξ ηζιέξ αθαηυηδηαξ αολάκμοκ ηδκ ηζκδηζηυηδηα ηαζ ηδ δζάνηεζα ηδξ ηζκδηζηυηδηαξ ηςκ ζπενιαημγςανίςκ ημο ημζκμφ ηέθαθμο (Lee et al. 1992, Zaki et al in Yeganeh et al. 2008, Yeganeh et al. 2008). ιςξ, πανυθμ πμο δ εκενβμπμίδζδ ημο ζπένιαημξ ημο πεθμκζμφ έβζκε ζε κενυ ηδξ ίδζαξ αθαηυηδηαξ (32 psu) ιε αοηυ πμο πνδζζιμπμίδζακ μζ Lee et al. (1992) ηαζ Τeganeh et al. (2008), δ ηζκδηζηυηδηα ηςκ ζπενιαημγςανίςκ ήηακ παιδθυηενδ. φιθςκα ιε ημοξ Lee et al. (1992), δ ζμκηζηή ζφζηαζδ ημο ιέζμο δεκ επδνεάγεζ ηδκ ηζκδηζηυηδηα ηςκ ζπενιαημγςανίςκ ημο ηέθαθμο εκχ ακηίεεηα μζ Yeganeh et al. (2008), οπμζηδνίγμοκ υηζ δ πανμοζία ζυκηςκ Ca +2 επζιδηφκεζ ηδκ ηζκδηζηυηδηα. ηα εαθαζζζκά είδδ, μζ ιεβάθεξ αναζχζεζξ ημο ζπένιαημξ ηείκμοκ κα ιεζχκμοκ ηδκ ηζκδηζηυηδηα ηαζ ηδ δζάνηεζα ηδξ (Suquet et al. 1992, 2010) ηαζ αοηυ βζαηί ημ ιέζμ εκενβμπμίδζδξ ακαηυπηεζ ημκ πνμζηαηεοηζηυ νυθμ ημο ζπενιαηζημφ οβνμφ ζηα ζπενιαημγςάνζα (Billard 1982, 1983), επίδναζδ πμο πενζμνίγεηαζ ιε ηδκ πνμζεήηδ BSA (Bovine Serum Albumin) ζημ ιέζμ (Suquet et al. 1994, 2010). Δπζπθέμκ, ζηδκ πενίπηςζδ εζδχκ ιε παπφνεοζημ ζπένια, δ αναίςζδ ημο είκαζ ηαθυ κα ακαπηφζζεηαζ ζε δφμ αήιαηα. Ανπζηά, ημ ζπένια κα αναζχκεηαζ ζε ιέζμ πμο δζαηδνεί ηα ζπενιαημγςάνζα ακεκενβά αθθά επζηνέπεζ ηδκ πθήνδ ακάιεζλδ ημο ζπένιαημξ (1:100) ηαζ αημθμφεςξ, κα αναζχκεηαζ ζημ ιέζμ εκενβμπμίδζδξ (1:10) χζηε κα δζαζθαθζζηεί δ ιέβζζηδ εκενβμπμίδζδ ημο, ηδκ χνα ηδξ ιέηνδζδξ (Βillard & Cosson, 1992). Δπίζδξ, αλίγεζ κα ζδιεζςεεί υηζ δ ημπμεέηδζδ δφμ ακελάνηδηςκ ζηαβυκςκ κενμφ ηαζ ζπένιαημξ επάκς ζηδκ ακηζηεζιεκμθυνμ, ηαζ δ ακάιεζλδ ημοξ απυ ηδκ εθεφεενδ πηχζδ ηδξ ηαθοπηνίδαξ (υπςξ έβζκε απυ ημοξ Lee et al., 1992) ελαζθαθίγεζ ζοκεήηεξ ηαθφηενδξ ακάιεζλδξ ημο ζπένιαημξ ηαζ ζε ζοκδοαζιυ ιε ηδ ιέηνδζδ ηδξ ηζκδηζηυηδηαξ ιυκμ ζηδκ πενζμπή πθήνμοξ ακάιεζλδξ ζπένιαημξ ηαζ ιέζμο (πενζμπή πνχηδξ επαθήξ ηςκ δφμ οβνχκ) ιπμνμφκ κα δζηαζμθμβήζμοκ ηζξ ορδθυηενεξ ηζιέξ ηζκδηζηυηδηαξ πμο ηαηαβνάθδηακ απυ ημοξ Lee et al. (1992), ζοβηνζηζηά ιε αοηέξ πμο ηαηαβνάθδηακ ζ αοηή ηδκ ενβαζία. οιπεναζιαηζηά, ζηδκ ενβαζία αοηή ζοβηεκηνχεδηακ πθδνμθμνίεξ πνήζζιεξ βζα ηδ αεθηζζημπμίδζδ ηςκ ηεπκζηχκ βμκζιμπμίδζδξ ηαζ ηδκ ακάπηολδ ηεπκζηχκ δζαηήνδζδξ ημο ζπένιαημξ ημο πεθμκζμφ. Χζηυζμ, πνεζάγεηαζ πεναζηένς ένεοκα βζα κα ηαηακμήζμοιε ηδ θοζζμθμβία ημο ζπένιαημξ ημο είδμοξ αοημφ, δζενεοκχκηαξ ημοξ πανάβμκηεξ πμο επδνεάγμοκ ηδκ εκενβμπμίδζδ ηαζ ηδκ πμζυηδηα ηδξ ηζκδηζηυηδηαξ ηςκ ζπενιαημγςανίςκ. Eπραξηζηίεο H πανμφζα ένεοκα ζοβπνδιαημδμηήεδηε απυ ηδκ Δονςπασηή Έκςζδ (Δονςπασηυ Κμζκςκζηυ Σαιείμ - ΔΚΣ) ηαζ απυ εεκζημφξ πυνμοξ ιέζς ημο Δπζπεζνδζζαημφ Πνμβνάιιαημξ «Δηπαίδεοζδ ηαζ Γζα Βίμο Μάεδζδ» ημο Δεκζημφ ηναηδβζημφ Πθαζζίμο Ακαθμνάξ (ΔΠΑ) Δνεοκδηζηυ Υνδιαημδμημφιεκμ Ένβμ: ΑΡΥΗΜΖΓΖ ΗΗΗ. Δπέκδοζδ ζηδκ ημζκςκία ηδξ βκχζδξ ιέζς ημο Δονςπασημφ Κμζκςκζημφ Σαιείμο. Βηβιηνγξαθία Κμημηφνδξ Λ., Μίκμξ Γ., οιεςκίδδξ Υ., Αθελάκδνμο Μ., Σμζμφκδξ Γ., Κανφδαξ Θ. (2011). Γζενεφκδζδ ηδξ δοκαηυηδηαξ ακαπαναβςβήξ ημο πεθμκζμφ (Chelon labrosus, Risso 1827) ζε ζοκεήηεξ αζπιαθςζίαξ. Πναηηζηά 4 μο Γζεεκμφξ οκεδνίμο Τδνμαζμθμβίαξ-Αθζείαξ, 9-11 Ημοκίμο 2011, Βυθμξ, Δθθάδα. Ben Khemis I., Zouiten D., Besbes R., Kamoun F. (2006). Larval rearing and weaning of thick lipped grey mullet (Chelon labrosus) in mesocosm with semi-extensive technology. Aquaculture 259, Billard R., Importance des protéines du liquide coelomique sur la fertilité des gametes de la truite arc en ciel et possibilités de substitution. Bulletin Francaise de la Péche et de la Pisciculture 284: 168-l

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373 ΗNVESTIGATION OF THE POSSIBILITY OF ESTABLISHING AND OPERATING, INTENSIVE, SEMI-INTENSIVE AND SEMI-EXTENSIVE LAND-BASED SYSTEM OF PRODUCTION OF MARINE FISHES IN SUITABLE LOCATION OF PAGASITIKOS GULF. Karamitros G.*, Papoutsoglou S. Ε., Tsimpoukas K., Karakatsouli N. Laboratory of Applied Hydrobiology, Department of Animal Science and Aquaculture, Agricultural University of Athens, Iera Odos 75, Votanikos, 11855, Athens, Greece Abstract Pagasitikos Gulf is a semi-closed gulf in the prefecture of Magnisia, at the coast of which thrives a multitude of urban, industrial, agricultural and touristic activities. The purpose of the present study, is the investigation of the possibility of establishing and operating in-land system of production of marine fishes. This investigation concerns the main factors involved such as the selection of the most suitable available location, the characteristics and the availability of water, as well as the relationship between natural (water), biological (organisms) and economic conditions (height of production), especially regarding the selection of the most suitable aquatic organisms and the advantages and the possibilities for rearing, farming and marketing. In this frame the socio-economic characteristics of the study region were examined, as well as the general situation of Pagasitikos Gulf, the farmed species and the in-land systems of production. Besides was created a geographic system of information and were drawn thematic maps, as well as a map of regions which are more appropriate for the installation of land-based systems of production. In the investigation of possibilities of establishing and operating in-land system of production of marine species, an economic analysis of in-land farm in the study region was included. For this reason, a production system was designed and evaluated for cost of investment and production, as well as expected economical results. Key words: in-land system of production of marine fishes, Pagasitikos Gulf, geographic system of information. Corresponding author: Karamitros Grigorios (gkaramit@yahoo.com) ΓΗΔΡΔΤΝΖΖ ΓΤΝΑΣΟΣΖΣΧΝ ΔΦΑΡΜΟΓΖ ΔΝΣΑΣΗΚΧΝ ΖΜΗΔΝΣΑΣΗΚΧΝ ΖΜΗΔΚΣΑΣΗΚΧΝ ΤΣΖΜΑΣΧΝ ΠΑΡΑΓΧΓΖ ΘΑΛΑΗΧΝ ΔΗΓΧΝ ΗΥΘΤΧΝ Δ ΚΑΣΑΛΛΖΛΔ ΥΔΡΑΗΔ ΠΔΡΗΟΥΔ ΣΟΤ ΠΑΓΑΖΣΗΚΟΤ ΚΟΛΠΟΤ Καξακήηξνο Γξ.*, Παπνπηζφγινπ., Σζηκπνχθαο Κ., Καξαθαηζνχιε Ν. Δνβαζηήνζμ Δθδνιμζιέκδξ Τδνμαζμθμβίαξ, Σιήια Δπζζηήιδξ Εςζηήξ Παναβςβήξ ηαζ Τδαημηαθθζενβεζχκ, Γεςπμκζηυ Πακεπζζηήιζμ Αεδκχκ, Ηενά Οδυξ 75, Βμηακζηυξ, 11855, Αεήκα, Δθθάδα. Πεξίιεςε Ο Παβαζδηζηυξ ηυθπμξ απμηεθεί έκακ διίηθεζζημ ηυθπμ ζημ Νμιυ Μαβκδζίαξ, ζηα πανάθζα ημο μπμίμο ανίζηεηαζ έκα πθήεμξ αζηζηχκ, αζμιδπακζηχκ, αβνμηζηχκ ηαζ ημονζζηζηχκ δναζηδνζμηήηςκ. ημπυξ ηδξ πανμφζαξ ιεθέηδξ είκαζ δ δζενεφκδζδ ηςκ δοκαημηήηςκ εβηαηάζηαζδξ ηαζ θεζημονβίαξ πενζαίμο ζοζηήιαημξ παναβςβήξ εαθάζζζςκ εζδχκ ζπεφςκ. Ζ δζενεφκδζδ αοηή αθμνά ημοξ ηονζυηενμοξ ειπθεηυιεκμοξ πανάβμκηεξ, υπςξ, δ επζθμβή ηδξ ηαηάθθδθδξ ημπμεεζίαξ βζα ηδκ εβηαηάζηαζδ ηδξ ιμκάδαξ, ηα παναηηδνζζηζηά ηαζ δ δζαεεζζιυηδηα ημο κενμφ, ηαεχξ ηαζ δ ζπέζδ ιεηαλφ θοζζηχκ (κενυ), αζμθμβζηχκ (μνβακζζιμί) ηαζ μζημκμιζηχκ (φρμξ παναβςβήξ) ζοκεδηχκ, ζδζαίηενα απυ ηδκ άπμρδ ηδξ επζθμβήξ ηςκ ηαηάθθδθςκ οδνυαζςκ μνβακζζιχκ 373

374 ηαζ ηα πθεμκεηηήιαηα ηαζ ηζξ δοκαηυηδηεξ ηδξ εηηνμθήξ αθθά ηαζ ηδξ ειπμνίαξ ημοξ. ημ πθαίζζμ αοηυ ελεηάζεδηακ ηα ημζκςκζηυ-μζημκμιζηά παναηηδνζζηζηά ηδξ πενζμπήξ ιεθέηδξ, ηαεχξ ηαζ δ βεκζηή ηαηάζηαζδ ημο Παβαζδηζημφ Κυθπμο, ηα είδδ εηηνεθυιεκςκ εζδχκ ζπεφςκ ηαζ ηα πενζαία ζοζηήιαηα παναβςβήξ. Δπζπνυζεεηα, δδιζμονβήεδηε έκα βεςβναθζηυ ζφζηδια πθδνμθμνζχκ, ζπεδζάζεδηακ εειαηζημί πάνηεξ, ηαεχξ ηαζ έκαξ πάνηδξ ηςκ πενζμπχκ πμο ειθακίγμοκ ιεβαθφηενδ ηαηαθθδθυηδηα βζα εβηαηάζηαζδ πενζαίςκ ζοζηδιάηςκ παναβςβήξ. ηδκ δζενεφκδζδ ηςκ δοκαημηήηςκ εβηαηάζηαζδξ ηαζ θεζημονβίαξ πενζαίμο ζοζηήιαημξ παναβςβήξ εαθάζζζςκ εζδχκ ζπεφςκ, εκηάπηδηε ιζα μζημκμιζηή ακάθοζδ ιζαξ πενζαίαξ ιμκάδαξ εηηνμθήξ ζηδκ πενζμπή ιεθέηδξ ηαζ βζα ημκ θυβμ αοηυ ζπεδζάζεδηε έκα πζεακυ ζφζηδια παναβςβήξ, απμηζιήεδηε ημ ηυζημξ επέκδοζδξ ηαζ παναβςβήξ ηαεχξ ηαζ ηα ακαιεκυιεκα μζημκμιζηά απμηεθέζιαηα. Λέξειρ κλειδιά: Υεξζαία ζπζηήκαηα εθηξνθήο, Παγαζεηηθόο θόιπνο, γεσγξαθηθά ζπζηήκαηα πιεξνθνξηώλ. *οββναθέαξ επζημζκςκίαξ: Καναιήηνμξ Γνδβυνδξ 1. Δηζαγσγή Πανά ημ βεβμκυξ υηζ μ ηθάδμξ ηςκ οδαημηαθθζενβεζχκ έπεζ ζδιεζχζεζ ναβδαία ακάπηολδ ζηδκ πχνα ιαξ ηα ηεθεοηαία πνυκζα, δ δναζηδνζυηδηα αοηή πενζμνίγεηαζ ζε ζπεηζηά ιζηνυ ανζειυ εζδχκ εηηνεθυιεκςκ μνβακζζιχκ, ηαεχξ ηαζ πνδζζιμπμζμφιεκςκ ηεπκζηχκ. Πανάβμκηεξ πμο ζοκεηέθεζακ ζηδκ ακάπηολδ ημο ηθάδμο ηαζ έδςζακ ηδκ απαναίηδηδ χεδζδ, απμηεθμφκ ιεηαλφ άθθςκ, δ αολδιέκδ γήηδζδ πνμσυκηςκ οδαημηαθθζενβεζχκ, δ έθθεζρδ αθζεοηζηχκ πνμσυκηςκ, θυβς νφπακζδξ ηαζ οπεναθίεοζδξ εαθάζζζςκ πενζμπχκ, ηαεχξ επίζδξ ηαζ δ απυηηδζδ ηδξ ηαηάθθδθδξ ηεπκμβκςζίαξ απυ ημοξ παναβςβμφξ ηαζ δ αφλδζδ ημο επεκδοηζημφ εκδζαθένμκημξ. Δπζπνυζεεηα, δ ακάβηδ βζα ηδκ παναβςβή υζμ ημ δοκαηυκ ηαθφηενςκ δζαηνμθζηχκ πνμσυκηςκ, υζμ ηαζ δ επζηαηηζηή ακάβηδ βζα ιείςζδ ηςκ πενζααθθμκηζηχκ επζπηχζεςκ, απμηεθμφκ πανάβμκηεξ πμο εα επζδνάζμοκ δοκαιζηά ζηδκ ιεθθμκηζηή ελέθζλδ ηδξ οδαημηαθθζενβδηζηήξ δναζηδνζυηδηαξ. ημπυξ ηδξ πανμφζαξ ενβαζίαξ, είκαζ δ δζενεφκδζδ ηςκ δοκαημηήηςκ εβηαηάζηαζδξ ηαζ θεζημονβίαξ εκυξ πενζαίμο ζοζηήιαημξ παναβςβήξ εαθάζζζςκ εζδχκ ζπεφςκ ζημκ Παβαζδηζηυ Κυθπμ. Γζα ηδκ εβηαηάζηαζδ ιζαξ πενζαίαξ ιμκάδαξ εηηνμθήξ εαθάζζζςκ εζδχκ ζπεφςκ ζηδκ πενζμπή ελεηάζηδηακ πανάβμκηεξ υπςξ δ δζαεεζζιυηδηα κενμφ ηαζ δ πμζυηδηα ημο, δ ημπμβναθία ηαζ ημ ηθίια ηδξ πενζμπήξ, ηαεχξ ηαζ δ πζεακή φπανλδ ακηαβςκζζηζηχκ δναζηδνζμηήηςκ ζηδκ πενζμπή, υπςξ βζα πανάδεζβια ημονζζηζηέξ, αζμιδπακζηέξ, αβνμηζηέξ ή άθθεξ δναζηδνζυηδηεξ. 2. Τιηθά θαη Μέζνδνη Σα ζημζπεία πμο πνδζζιμπμζήεδηακ βζα ηδκ εηπυκδζδ ηδξ ενβαζίαξ πνμένπμκηαζ απυ αζαθζμβναθζηέξ πδβέξ, ηαεχξ ηαζ ζπεηζηέξ ιεθέηεξ, πμο έπμοκ πναβιαημπμζδεεί ζημ πανεθευκ βζα ηδκ πενζμπή ημο Παβαζδηζημφ Κυθπμο ηαζ ημο Νμιμφ Μαβκδζίαξ βεκζηυηενα (Θεμδχνμο & ζοκ., 1997, Θεμδχνμο, 2000, Πεηνάηδξ, 2000, Mitsios & Gatsios, 2000, Triantafyllou et al., 2001, Petihakis et al., 2002, Petihakis et al., 2005). Πανάθθδθα, ζοθθέπεδηακ ζδιακηζηά ζημζπεία απυ ηζξ ημπζηέξ ανιυδζεξ οπδνεζίεξ ηδξ πενζμπήξ βζα ζπεηζηά εέιαηα, εκχ βζα ηδκ απμηυιζζδ ιζαξ πζμ άιεζδξ εζηυκαξ ηςκ πενζμπχκ, ηαεχξ ηαζ ημκ ζπμθζαζιυ ηςκ απμηεθεζιάηςκ, πναβιαημπμζήεδηε επζηυπζα επίζηερδ ηςκ επζιένμοξ πενζμπχκ. Γζα ιζα πζμ ζοζηδιαηζηή ιεθέηδ ηδξ εονφηενδξ πενζμπήξ, πναβιαημπμζήεδηε επελενβαζία ηςκ δεδμιέκςκ ιε ηδκ πνήζδ βεςβναθζηχκ ζοζηδιάηςκ πθδνμθμνζχκ ηαζ ζπεδζάζεδηακ εειαηζημί πάνηεξ ηδξ πενζμπήξ, ηαεχξ ηαζ πάνηδξ ιε ηζξ επζιένμοξ πενζμπέξ πμο ειθακίγμοκ εοκμσηέξ ζοκεήηεξ βζα ηδκ εβηαηάζηαζδ πενζαίςκ ζοζηδιάηςκ παναβςβήξ ζπεφςκ. Γζα ημκ ζπεδζαζιυ ηςκ εειαηζηχκ πανηχκ, πνδζζιμπμζήεδηε ημ θμβζζιζηυ ArcGIS, εκχ βζα ημκ ζπεδζαζιυ ημο αοεμιεηνζημφ πάνηδ ημο Παβαζδηζημφ Κυθπμο ημ θμβζζιζηυ Surfer 7.0 ιε δεδμιέκα ακηίζημζπμο καοηζημφ πάνηδ ηδξ πενζμπήξ απυ ηδκ Τδνμβναθζηή Τπδνεζία ημο Πμθειζημφ Ναοηζημφ. Ζ ιέεμδμξ πνμζέββζζδξ ιε ηδκ πνήζδ ηςκ βεςβναθζηχκ ζοζηδιάηςκ πθδνμθμνζχκ, ζοκέααθε ζδιακηζηά ζηδκ ζοζηδιαηζηή επελενβαζία ηςκ δεδμιέκςκ, δ μπμία ηαζ ιε ηδκ αμήεεζα ηαζ ηδξ επζηυπζαξ επαθήεεοζδξ ηαζ ελέηαζδξ ηςκ πενζμπχκ μδήβδζε ζηζξ ηεθζηέξ απμθάζεζξ επζθμβήξ. Σα ηνζηήνζα επζθμβήξ ηςκ πενζμπχκ πμο εθανιυζηδηακ ζηδ επελενβαζία ηςκ βεςβναθζηχκ ζοζηδιάηςκ ήηακ δ ηθίζδ ημο εδάθμοξ, πενζμπέξ νφπακζδξ, εηαμθέξ πεζιάννςκ, πενζμπέξ Natura, 374

375 μζηζζηζηέξ πενζμπέξ, ανπαζμθμβζημί πχνμζ, αζμιδπακζηέξ πενζμπέξ, μδζηυ δίηηομ, απυζηαζδ απυ ηδκ αηηή ηαζ έηηαζδ ηδξ πενζμπήξ. Ακαθμνζηά ιε ηδκ μζημκμιζηή δζενεφκδζδ πζεακήξ επέκδοζδξ ηαζ βζα ηδκ ελέηαζδ ηδξ απμδμηζηυηδηαξ ηδξ ιμκάδαξ εηηνμθήξ πμο επζθέπεδηε κα ζπεδζαζηεί πνδζζιμπμζήεδηακ ηα ηνζηήνζα ηδξ Καεανήξ Πανμφζαξ Αλίαξ (ΚΠΑ) ηαεχξ ηαζ μ Δζςηενζηυξ οκηεθεζηήξ Απυδμζδξ (ΔΑ). 3. Απνηειέζκαηα πδήηεζε Ο Παβαζδηζηυξ Κυθπμξ, απυ ηδκ μπηζηή ηδξ πμζυηδηαξ ημο κενμφ, βζα ηδκ πνήζδ αοημφ βζα εηηνμθή ηςκ ελεηαγυιεκςκ ζηδκ πανμφζα ιεθέηδ εζδχκ ζπεφςκ, δεκ δζαθαίκεηαζ κα ειθακίγεζ πανάβμκηεξ μζ μπμίμζ κα εέημοκ μοζζαζηζημφξ πενζμνζζιμφξ. Δπζπνυζεεηα, ακαθμνζηά ιε ηδκ ακάπηολδ ηδξ εηηνμθήξ ζπεφςκ, δ μπμία είκαζ έκημκδ ζε άθθμοξ ηθεζζημφξ ή διίηθεζζημοξ ηυθπμοξ ηδξ πχναξ ιαξ, ζημκ Παβαζδηζηυ Κυθπμ δ δναζηδνζυηδηα αοηή ειθακίγεηαζ ζδζαίηενα πενζμνζζιέκδ. φιθςκα ιε ηα απμηεθέζιαηα ημο Γεςβναθζημφ οζηήιαημξ Πθδνμθμνζχκ (GIS) πμο πναβιαημπμζήεδηε βζα ηδκ πενζμπή ιεθέηδξ, μπμφ θαιαάκμκηαζ οπυρδ ηαζ μζ βεκζηυηενεξ οπμδμιέξ ηςκ πενζμπχκ, ιπμνμφκ κα δζαηνζεμφκ ηνεζξ εονφηενεξ πενζμπέξ υπμο πενζθαιαάκμκηαζ εηηάζεζξ πμο πθδνμφκ ηζξ ααζζηέξ απαζηήζεζξ βζα ηδκ εθανιμβή πενζαίςκ εβηαηαζηάζεςκ ακελάνηδηα απυ ημκ πανάβμκηα ηδξ πμζυηδηαξ ημο δζαεέζζιμο κενμφ. α) Οζ πενζμπέξ ζηα πανάθζα ημο δοηζημφ Παβαζδηζημφ Κυθπμο. α) Οζ πενζμπέξ ζηα ακαημθζηά πανάθζα ημο Παβαζδηζημφ Κυθπμο έςξ ηαζ κμηζυηενα ζηδκ πενζμπή ημο Σνίηενζ. β) Οζ εονφηενεξ εηηάζεζξ βεζημκζηά ηδξ πενζμπήξ ημο Πηεθεμφ, Απζθθείμο. Ζ εονφηενδ πενζμπή Πηεθεμφ Απζθθείμο παναηηδνίγεηαζ ςξ βεςνβζηή βδ ορδθήξ παναβςβζηυηδηαξ. ηδκ πενζμπή αοηή, θαίκεηαζ κα επζηναημφκ ζπεηζηά μιαθέξ ηθίζεζξ εδάθμοξ (<5%) βεβμκυξ πμο ηαεζζηά ηδκ πενζμπή εθηοζηζηή απυ πθεονάξ βεςιμνθμθμβίαξ βζα ηδκ εβηαηάζηαζδ πενζαίςκ ζοζηδιάηςκ εηηνμθήξ ζπεφςκ. Ακαθμνζηά ιε ηδκ εθανιμβή ζοζηδιάηςκ διζεηηαηζημφ παναηηήνα, εα πνέπεζ κα ακαθενεεί υηζ πανά ημ βεβμκυξ υηζ δ ακάθοζδ ιε ηδκ ιέεμδμ ημο GIS ηαηαδεζηκφεζ ηαηάθθδθεξ εηηάζεζξ βζα ηέημζα ζοζηήιαηα, μζ ακηαβςκζζηζηέξ πνήζεζξ ημο εδάθμοξ ηδξ πενζμπήξ, είκαζ δοκαηυκ, κα εηημπίγμοκ ιζα ηέημζα επζπεζνδιαηζηή πνμζπάεεζα. Οζ πενζμπέξ ζηα πανάθζα ημο δοηζημφ Παβαζδηζημφ Κυθπμο παναηηδνίγμκηαζ ηονίςξ απυ, μιαθυ ακάβθοθμ ηαζ ιζηνέξ ηθίζεζξ ημο εδάθμοξ πνμξ ηδ εάθαζζα, βεβμκυξ πμο ηαηά αάζδ εοκμεί ηδκ εθανιμβή ηςκ πενζαίςκ εβηαηαζηάζεςκ εηηνμθήξ. Δπζπνυζεεηα μζ πενζμπέξ αοηέξ είκαζ εφημθα πνμζαάζζιεξ απυ ηδκ εεκζηή μδυ Αεδκχκ Θεζζαθμκίηδξ, πανάβμκηαξ πμο ηαεζζηά εφημθδ ηδκ πνμζπέθαζδ ζε ιεβαθφηενεξ, ηςκ ημπζηχκ, αβμνέξ. Δκημφημζξ, μζ εηηάζεζξ αοηέξ απμηεθμφκ πενζμπέξ εκηαηζηήξ βεςνβζηήξ δναζηδνζυηδηαξ, εκχ ζημ κμηζυηενμ ιένμξ ηδξ πενζμπήξ εκημπίγεηαζ δ εβηαηάζηαζδ ηδξ αζμιδπακζηήξ πενζμπήξ ημο Αθιονμφ, δ μπμία ηαζ ανίζηεηαζ ζε θάζδ ακάπηολδξ. Ζιζεηηαηζηά ζοζηήιαηα παναβςβήξ, πμο ζηυπμ εα έπμοκ ηδκ αλζμπμίδζδ ηδξ θοζζηήξ παναβςβζηυηδηαξ πζεακυηαηα δεκ απμηεθμφκ ακηαβςκζζηζηή δναζηδνζυηδηα έκακηζ ηςκ ήδδ εθανιμγυιεκςκ βεςνβζηχκ δναζηδνζμηήηςκ. Σα ζοζηήιαηα αοηά, πνμτπμεέημοκ ηδκ φπανλδ ανηεηά εηηεηαιέκςκ ηαηάθθδθςκ ηαζ δζαεέζζιςκ εηηάζεςκ, έηζζ χζηε δ εηηνμθή, ιε ιζηνέξ ηζιέξ ζπεομποηκυηδηαξ, πμο ηα ζοζηήιαηα αοηά πνμτπμεέημοκ, κα είκαζ μζημκμιζηά απμδμηζηή βζα ηα ελεηαγυιεκα είδδ. Ζ εονφηενδ πενζμπή ζηα ακαημθζηά πανάθζα ημο Παβαζδηζημφ Κυθπμο δ μπμία εηηείκεηαζ απυ ηδκ πενζμπή ηςκ Λεπςκίςκ έςξ ηδκ πενζμπή ημο Σνίηενζ πανμοζζάγεζ έκημκδ μζηζζηζηή ακάπηολδ, ιε παναεενζζηζηέξ ηαημζηίεξ ηαζ ημονζζηζηέξ επζπεζνήζεζξ ιζηνχκ λεκμδμπεζαηχκ εβηαηαζηάζεςκ. Δλεηάγμκηαξ ηδκ πενζμπή ηςκ Λεπςκίςκ υπμο οπάνπμοκ εκηαηζηέξ δεκδνμηαθθζένβεζεξ, ζηζξ οπυθμζπεξ πενζμπέξ δ βεςνβζηή δναζηδνζυηδηα πενζμνίγεηαζ ζε εθαζχκεξ. Πανυθα αοηά ηαζ πανά ημ βεβμκυξ υηζ μζ ηθίζεζξ ημο εδάθμοξ ειθακίγμκηαζ ιεβαθφηενεξ ζοβηνζηζηά ιε ηδκ πενζμπή ημο Αθιονμφ οπάνπμοκ πενζμπέξ ζηζξ μπμίεξ εα ήηακ δοκαηή δ εθανιμβή πενζαίςκ ζοζηδιάηςκ εηηνμθήξ. πςξ έδεζλακ ηαζ ηα απμηεθέζιαηα ημο Γεςβναθζημφ οζηήιαημξ Πθδνμθμνζχκ, δζάζπανηεξ ηαζ ζπεηζηά ιζηνήξ έηηαζδξ πενζμπέξ πμο ειθακίγεηαζ κα πθδνμφκ ηζξ πνμτπμεέζεζξ πμο ηέεδηακ ηαηά ηδκ επελενβαζία ηςκ δεδμιέκςκ, απμηεθμφκ πνμηάζεζξ πζμ ζδιεζαημφ παναηηήνα. Σα ζοζηήιαηα παναβςβήξ πμο εα ιπμνμφζακ κα εθανιμζημφκ ζηδκ εονφηενδ πενζμπή αοηή, εα πενζμνζζεμφκ ζε ιεβάθμ ααειυ απυ ημ 375

376 αολδιέκμ ηυζημξ επέκδοζδξ, θυβς ενβαζζχκ δζαιυνθςζδξ ηδξ πενζμπήξ, ηαεχξ ηαζ ημ αολδιέκμ ηυζημξ άκηθδζδξ ημο κενμφ θυβς ορμιεηνζηήξ δζαθμνάξ απυ ηδκ επζθάκεζα ηδξ εάθαζζαξ, πανάβμκηεξ πμο εα πνέπεζ κα ιεθεηδεμφκ πνμζεηηζηά ηαζ βζα ηάεε ζοβηεηνζιέκδ πενίπηςζδ. Σα ζοζηήιαηα επμιέκςξ πμο θαίκεηαζ κα ειθακίγμκηαζ πθεμκεηηζηυηενα βζα ηδκ πενζμπή εα πνέπεζ κα εκζςιαηχκμοκ αεθηζςιέκεξ δζαπεζνζζηζηέξ πναηηζηέξ ηαζ πζεακυκ ηεπκμθμβίεξ ακαηφηθςζδξ ημο κενμφ εηηνμθήξ. φιθςκα ιε ηδκ βεκζηυηενδ ηάζδ βζα εκηαηζημπμίδζδ ηδξ παναβςβήξ ηαζ αθμιμίςζδ ελεθζβιέκδξ ηεπκμθμβίαξ ζηα ζοζηήιαηα παναβςβήξ, μζ πνμηάζεζξ πμο εα ιπμνμφζακ κα ηεεμφκ ακαθμνζηά ιε ηδκ εθανιμβή πενζαίςκ ζοζηδιάηςκ παναβςβήξ εαθάζζζςκ εζδχκ ζπεφςκ ζηδκ πενζμπή εα εζηίαγακ ζε ζοζηήιαηα πενζζζυηενμ εκηαηζημφ πανά διζεηηαηζημφ παναηηήνα. Ακαθμνζηά ιε ηζξ πνμηεζκυιεκεξ πενζμπέξ, ιπμνεί κα ακαθενεεί υηζ μζ εονφηενεξ εηηάζεζξ βεζημκζηά ηδξ πενζμπήξ ημο Πηεθεμφ, ειθακίγμκηαζ πθεμκεηηζηυηενεξ ζπεηζηά ιε ηζξ οπυθμζπεξ εηηάζεζξ. Ζ μζημκμιζηή ακάθοζδ πμο πναβιαημπμζήεδηε βζα ηδκ εβηαηάζηαζδ ηαζ θεζημονβζά ιζαξ πενζαίαξ ιμκάδαξ εηηνμθήξ εαθάζζζςκ εζδχκ ζπεφςκ, ακαδεζηκφεζ ηζξ μζημκμιζηέξ δοζημθίεξ πμο ειθακίγεζ ιζα ηέημζμο είδμοξ επζπεζνδιαηζηή δναζηδνζυηδηα, πανμοζζάγμκηαξ πανάθθδθα ηζξ εοηαζνίεξ ηαζ δοκαηυηδηεξ πμο δδιζμονβμφκηαζ. Ζ θήρδ επζδυηδζδξ, εκυξ ζδιακηζημφ πμζμζημφ ημο ανπζημφ ηυζημοξ επέκδοζδξ, ζηδκ πανμφζα ιεθέηδ, ηαεμνίγεζ ηδκ μζημκμιζηή αζςζζιυηδηα ή υπζ ηδξ ιμκάδαξ εηηνμθήξ πμο ζπεδζάζεδηε. οκεπχξ, είκαζ θακενή δ ακάβηδ θεπημιενμφξ ηαζ ζοβηνδηζηήξ ελέηαζδξ υθςκ ηςκ πζεακχκ εκαθθαηηζηχκ ζπεδίςκ πμο ιπμνμφκ κα πνμηφρμοκ βζα ηδκ δδιζμονβία ιζαξ ιμκάδαξ πενζαίςκ εβηαηαζηάζεςκ εηηνμθήξ ζπεφςκ ζηδκ εονφηενδ πενζμπή ημο Παβαζδηζημφ Κυθπμο. Ζ ημζκςκζηή ηαζ μζημκμιζηή εοδιενία ημο Νμιμφ, ηαεχξ ηαζ δ ημονζζηζηή ημο ακάπηολδ, απμηεθμφκ έκα εεηζηυ ζημζπείμ βζα ηδκ ακάθδρδ επζπεζνδιαηζηχκ πνςημαμοθζχκ βζα ηδκ εηηνμθή ζπεφςκ. Ζ ζδιακηζηά ορδθή αλία ημο εδάθμοξ υιςξ, ζηζξ παναεαθάζζζεξ πενζμπέξ πενζιεηνζηά ημο Παβαζδηζημφ Κυθπμο, είκαζ ίζςξ μ ααζζηυηενμξ πανάβμκηαξ πμο ζοιαάθεζ ζδιακηζηά ζημ αφλδζδ ημο ηυζημοξ επέκδοζδξ. Σμ βεβμκυξ αοηυ, απμηεθεί ίζςξ ηαζ ημκ ηονζυηενμ πανάβμκηα πμο ςεεί ζηδκ εκηαηζημπμίδζδ ηςκ ζοζηδιάηςκ παναβςβήξ, αολάκμκηαξ ηδκ ζπεομποηκυηδηα εηηνμθήξ. Οπςζδήπμηε, μζ ζηυπμζ ηαζ μζ απαζηήζεζξ ζε πμζυηδηα παναβυιεκμο πνμσυκημξ, ηαεχξ ηαζ δ ακάβηδ βζα παναβςβή πμζμηζηχκ πνμσυκηςκ ηαεμνίγμοκ ημ μζημκμιζηυ φρμξ επέκδοζδξ ιζαξ ηέημζαξ επζπεζνδιαηζηήξ πνμζπάεεζαξ, ημ ηυζημξ παναβςβήξ, αθθά ηαζ ηα έζμδα απυ ηα παναβυιεκα πνμσυκηα. Βηβιηνγξαθία Θεμδχνμο, Α. Η., Πακαβζςηάηδ, Π., Μπμοθηαδάηδ, Α. ηαζ Πκεοιαηζηάημξ Ζ. (1997). Οζημθμβζηή ηαηάζηαζδ ημο Παβαζδηζημφ ηαζ δοκαηυηδηεξ πνήζδξ πανάηηζςκ πενζμπχκ ημο βζα εηηνμθή ζπεφςκ. Δπζεεχνδζδ Εςμηεπκζηήξ Δπζζηήιδξ, 23, ζεθ Θεμδχνμο, Α.Η. (2000). Ακάπηολδ Οθμηθδνςιέκδξ Πμθζηζηήξ βζα ηδκ Αεζθυνμ Γζαπείνζζδ ημο Παβαζδηζημφ Κυθπμο. Σεθζηή Έηεεζδ. Πεηνάηδξ, Γ. (2000). Ακάπηολδ Οθμηθδνςιέκδξ Πμθζηζηήξ βζα ηδκ Αεζθυνμ Γζαπείνζζδ ημο Παβαζδηζημφ Κυθπμο. Σεθζηή έηεεζδ. ΔΚΘΔ. Mitsios, I. K. and Gatsios, F. A. (2000). Development of an integrated policy for the sustainable management of Pagasitikos Gulf. Assessment of nitrate, nitrite, phosphate and pesticide input concentrations from agriculture effluents, Volos: University of Thessaly. Papoutsoglou S. E. (2000). Monitoring and regulation of marine aquaculture in Greece: licensing, regulatory control and monitoring guidelines and procedures. Journal of Applied Ichthyology, 16, Papoutsoglou, E. S. (1991). Impact of aquaculture on the aquatic enviroment in relation to applied production systms. Aquaculture and the enviroment De Pauw, N. and J. Joyce (Eds). European Aquaculture Society Special Publication No. 16, Petihakis, G., Triantafyllou, G. Pollani, A., Koliou, A. and Theodorou, A. (2005). Field data analysis and application of a complex water column biogeochemical model in different areas of a semi- enclosed basin: towards the development of an ecosystem management tool. Marine Environmental Research, 59,

377 Petihakis, G., Triantafyllou, G., Koliou, A. and Theodorou, A. (2002). Exploring the Dynamics of a Marine Ecosystem (Pagasitikos Gulf, Western Aegean, Greece) through the Analysis of Temporal and Spatial Variability of Nutrients. Littoral, Triantafyllou G., Petihakis, G., Dounas, C. and Theodorou, A. (2001). Assessing Marine Ecosystem Response to Nutrient Inputs. Marine Pollution Bulletin, 43, (7-12),

378 INVESTIGATING THE POTENTIAL OF FRESHWATER AQUACULTURE PRODUCTION IN TWO ECUADORIAN PROVINCES: OPPORTUNITΗES & CHALLENGES Pantazis Panagiotis A. 1,2 * a Department of Ichthyology, Aquatic Fauna and Fish Diseases, Faculty of Veterinary Medicine, School of Health Sciences, University of Thessaly, 224 Trikalon Street, P.O.Box 199, Gr-43100, Karditsa, Greece b Becario PROMETEO, Secretaria Nacional De Educacion Superior, Ciencia Tecnologia E Innovacion- SENESCYT, Sanchez Y Cifuentes Y Velasco, Edificio «La Provisora», Ibarra, ECUADOR Abstract Ecuador is a developing country where the continuous increase in the standard of living and the low average per capita fish consumption, guarantee the absorption of new aquaculture products. However, there seem to be a lack of central planning in issues of inland aquaculture and in the assessment of inland natural water resources for aquaculture purposes. This research aimed at recording the status of inland aquaculture at two Ecuadorian provinces (Esmeraldas & Sucumbios) and at compiling suggestions for its amelioration in terms of production methods, total biomass production and the sustainable management of human and natural resources. The two research areas present significant potential for inland aquaculture development. Particular emphasis should be given to exploring the culture requirements (reproduction, management, nutrition) of endemic species for the selection of the most suitable ones for rearing in local geomorphological and climatic conditions. Furthermore, the elaboration of a national business plan is deemed necessary, a plan that will thoroughly explore the possibilities for inland aquaculture development without detrimental effects on the environment, the unique biodiversity of this country and by ensuring the sustainability of natural and human resources. Key words: Ecuador, freshwater aquaculture, sustainable aquaculture. * Corresponding author: Pantazis Panagiotis A. (ppantazis@vet.uth.gr) 1 ΠΡΟΟΠΣΗΚΔ ΑΝΑΠΣΤΞΖ ΣΖ ΤΓΑΣΟΚΑΛΛΗΔΡΓΔΗΑ ΔΧΣΔΡΗΚΧΝ ΤΓΑΣΧΝ Δ ΓΤΟ ΔΠΑΡΥΗΔ ΣΟΤ ΗΖΜΔΡΗΝΟΤ (ECUADOR): ΔΤΚΑΗΡΗΔ & ΠΡΟΚΛΖΔΗ. Παληαδήο Π. Α. 1, 2 * Δνβαζηήνζμ Ηπεομθμβίαξ, Τδνυαζαξ Πακίδαξ & Ηπεομπαεμθμβίαξ, Σιήια Κηδκζαηνζηήξ, πμθή Δπζζηδιχκ Τβείαξ, Πακεπζζηήιζμ Θεζζαθίαξ, Σνζηάθςκ 224, Σ.Θ. 199, Σ.Κ , Κανδίηζα, Δθθάδα 2 Τπυηνμθμξ PROMETEO, Secretaria Nacional De Educacion Superior, Ciencia Tecnologia E Innovacion- SENESCYT, Sanchez Y Cifuentes Y Velasco, Edificio La Provisora», Ibarra, ECUADOR ΠΔΡΗΛΖΦΖ Ο Ηζδιενζκυξ (Ecuador) είκαζ ιζα ακαπηοζζυιεκδ πχνα υπμο δ ζοκεπήξ αφλδζδ ημο αζμηζημφ επζπέδμο ηαζ δ παιδθή ιέζδ ηαηά ηεθαθήκ ηαηακάθςζδ ζπεοδνχκ, εββοχκηαζ ηδκ απμννυθδζδ κέςκ οδαημηαθθζενβδηζηχκ πνμσυκηςκ. Οιςξ ζηα εέιαηα οδαημηαθθζένβεζαξ εζςηενζηχκ οδάηςκ παναηδνείηαζ ιία έθθεζρδ ηεκηνζημφ 378

379 ζπεδζαζιμφ ηαζ αλζμθυβδζδξ ηςκ δοκαημηήηςκ ηςκ θοζζηχκ οδάηζκςκ πυνςκ βζα οδαημηαθθζενβδηζημφξ ζημπμφξ. Ζ ένεοκα αοηή ζημπεφεζ ζηδκ ηαηαβναθή ηδξ πανμφζαξ οδαημηαθθζενβδηζηήξ δναζηδνζυηδηαξ ζε δφμ επανπίεξ ημο Ηζδιενζκμφ (Esmeraldas & Sucumbios) ηαζ ζηδκ ζοβηνυηδζδ πνμηάζεςκ βζα ηδκ αεθηίςζδ ηδξ υζμκ αθμνά ηζξ ιεευδμοξ παναβςβήξ, ημ φρμξ παναβςβήξ ηαζ ηδκ αεζθμνζηή δζαπείνζζδ ηςκ ακενχπζκςκ ηαζ θοζζηχκ πυνςκ. Οζ δφμ πενζμπέξ ένεοκαξ πανμοζζάγμοκ ζδιακηζηέξ δοκαηυηδηεξ ακάπηολδξ ηδξ οδαημηαθθζένβεζαξ εζςηενζηχκ οδάηςκ. Ηδζαίηενδ έιθαζδ πνέπεζ κα δμεεί ζηδκ δζενεφκδζδ ηςκ απαζηήζεςκ εηηνμθήξ (ακαπαναβςβή, δζαπείνζζδ, δζαηνμθή) ηςκ εκδδιζηχκ εζδχκ βζα ηδκ ακάδεζλδ ηςκ ηαηαθθδθυηενςκ βζα εηηνμθή ζηζξ ημπζηέξ βεςιμνθμθμβζηέξ ηαζ ηθζιαημθμβζηέξ ζοκεήηεξ. Απαναίηδηδ εεςνείηαζ ηαζ δ εηπυκδζδ εκυξ εεκζημφ επζπεζνδιαηζημφ ζπεδίμο (business plan) πμο εα δζενεοκήζεζ δζελμδζηά ηζξ δοκαηυηδηεξ ακάπηολδξ ηδξ οδαημηαθθζένβεζαξ εζςηενζηχκ οδάηςκ πςνίξ ανκδηζηέξ επζπηχζεζξ ζημ πενζαάθθμκ, ηδκ ιμκαδζηή αζμπμζηζθυηδηα ηδξ πχναξ ηαζ ιε ελαζθάθζζδ ηδξ αεζθμνίαξ ηςκ θοζζηχκ ηαζ ακενχπζκςκ πυνςκ ηδξ. Λέξειρ κλειδιά: Ιζεκεξηλόο, πδαηνθαιιηέξγεηα εζσηεξηθώλ πδάησλ, αεηθνξηθή πδαηνθαιιηέξγεηα. * οββναθέαξ επζημζκςκίαξ : Πακηαγήξ Πακαβζχηδξ Α. (ppantazis@vet.uth.gr) 1. Δηζαγσγή Σμ 2011, δ μθζηή ζπεομπαναβςβή ημο Ecuador (αθζεία & οδαημηαθθζένβεζα) ηαηαβνάθδηε ζημοξ πζθζάδεξ ηυκμοξ (24.26% αφλδζδ απυ ημ 2000) εη ηςκ μπμίςκ ηςκ 37.8% πνμήθεε απυ ηδκ οδαημηαθθζένβεζα ηαζ ημ οπυθμζπμ 62% πνμήθεε απυ ηδκ αθζεία. Σμ 2011, δ οδαημηαθθζένβεζα εζςηενζηχκ οδάηςκ απμηέθεζε ημ 18.8% ηδξ μθζηήξ οδαημηαθθζενβδηζηήξ παναβςβήξ ημο Ecuador. Γεδμιέκμο υηζ δ μθζηή επζθάκεζα ηςκ εζςηενζηχκ οδάηςκ ημο Ecuador οπμθμβίγεηαζ ζε πενζζζυηενμ ημο 30% ηδξ επζθάκεζαξ ηςκ οδάηςκ ηδξ δπεζνςηζηήξ οθαθμηνδπίδαξ ημο, δζαβνάθεηαζ ιζα ζδιακηζηή πνμμπηζηή ακάπηολδξ ηδξ οδαημηαθθζένβεζαξ εζςηενζηχκ οδάηςκ ζηδκ πχνα αοηή. Πανάθθδθα ημ ζζμγφβζμ ελαβςβχκ/εζζαβςβχκ (million USD) ημο Ecuador υζμκ αθμνά ηα πνμσυκηα αθζείαξ & οδαημηαθθζένβεζαξ είκαζ εεηζηυ (2,494.0 / 293.7) εκχ δ ηαηά ηεθαθή ηαηακάθςζδ ζπεοδνχκ ακένπεηαζ πενίπμο ζηα 8kg/yr, ηαηά πμθφ παιδθυηενδ ημο ιέζμο υνμο ηδξ Δονςπασηήξ Δκςζδξ ηαζ άθθςκ πςνχκ εηηυξ Δονχπδξ (FAO 2014). Ζ ένεοκα αοηή ζημπεφεζ ζηδκ ηαηαβναθή ηδξ πανμφζαξ οδαημηαθθζενβδηζηήξ δναζηδνζυηδηαξ ζε δφμ επανπίεξ ημο Ecuador (Esmeraldas & Sucumbios) ηαζ ζηδκ ζοβηνυηδζδ πνμηάζεςκ βζα ηδκ αεθηίςζδ ηδξ υζμκ αθμνά ηζξ ιεευδμοξ παναβςβήξ, ημ φρμξ παναβςβήξ ηαζ ηδκ αεζθμνζηή δζαπείνζζδ ηςκ ακενχπζκςκ ηαζ θοζζηχκ πυνςκ. 2. Τιηθά θαη Μέζνδνη Ζ ένεοκα δζεκενβείηαζ ιε ηδκ αμήεεζα ημο Τπμονβείμο Γεςνβίαξ, Κηδκμηνμθίαξ, Αθζείαξ & Τδαημηαθθζενβεζχκ ημο Ecuador (MAGAP 2014) ημ μπμίμ πανέπεζ ηεπκζηή αμήεεζα βζα ηζξ ιεηαηζκήζεζξ ζηζξ πενζμπέξ ένεοκαξ εκηυξ ηδξ πχναξ ηαεχξ ηαζ οπμζηήνζλδ ζε ακενχπζκμ δοκαιζηυ βζα ηζξ επαθέξ ιε ημπζημφξ θμνείξ, ηαθθζενβδηέξ βήξ, οδαημηαθθζενβδηέξ, αθζείξ ηαζ επζζηήιμκεξ άθθςκ οπδνεζζχκ πμο ζπεηίγμκηαζ ιε ημ ακηζηείιεκμ ηδξ ένεοκαξ. Πανάθθδθα απυ ημ ίδζμ Τπμονβείμ πανέπεηαζ ηαζ αζαθζμβναθζηή οπμζηήνζλδ ιέζς ηεπκζηχκ εηεέζεςκ ηαζ ακαθμνχκ πμο ηαηά ηαζνμφξ έπμοκ ζοκηαπεεί απυ οπαθθήθμοξ ημο. 3. Απνηειέζκαηα θαη πδήηεζε Ζ επανπία Sucumbios παναηηδνίγεηαζ απυ πμζηζθία εδαθμθμβζηχκ ηαζ ιεηεςνμθμβζηχκ παναηηδνζζηζηχκ ηαζ ςξ εη ημφημο απυ ζδιακηζηή αζμπμζηζθυηδηα. ηα Γοηζηά ηδξ επανπίαξ ηαζ ζηα ζφκμνα ιε ηζξ επανπίεξ Carchi ηαζ Imbaburra, οπάνπμοκ μνεζκμί υβημζ ιε ιεβάθα ορυιεηνα (2,500-4,000 m), πμο εοκμμφκ ηδκ παναβςβή ροπνυθζθςκ εζδχκ π.π. ζνζδίγμοζαξ πέζηνμθαξ, δ μπμία ηαζ ήδδ εηηνέθεηαζ εηεί. ηα Ακαημθζηά ηδξ επανπίαξ Sucumbios, ημ φρμξ απυ ηδκ επζθάκεζα ηδξ εάθαζζαξ είκαζ ιζηνυ ( m) ηαζ ζηα ζφκμνα ιε 379

380 ημ Πενμφ ηαζ ηδκ Κμθμιαία επζηναηεί ηνμπζηυ ηθίια ηφπμο Αιαγμκίμο ( πενζμπή Amazonia). Οζ εενιμηναζίεξ αένα (ιέζδ εθαπ. 21 o C- ιέζδ ιεβ. 30 o C) ηαζ δ αηιμζθαζνζηή οβναζία (70% - 90%) είκαζ ορδθέξ ηαευθδ ηδκ δζάνηεζα ημο πνυκμο εκχ μζ ανμπμπηχζεζξ είκαζ ζοκεπείξ ιε επμπζαηέξ δζαηοιάκζεζξ (2.0cm 9.0cm ιέζδ ιδκζαία). ηδκ πενζμπή αοηή ηδξ Αιαγμκίαξ οθίζηαηαζ ζδιακηζηή οδαημηαθθζενβδηζηή δναζηδνζυηδηα ιε είδδ εκδδιζηά αθθά ηαζ αθθυπεμκα. Σα ηονζυηενα ελ αοηχκ είκαζ: Cachama blanca (Piaractus brachypomus), Cachama negra (Colossoma macropomum), Sabalo (Brycon spp.), Bocachico (Prochilodus nigricans) ηαζ ηζθάπζα (Oreochromis spp.). Ζ εηηνμθή ημοξ δζεκενβείηαζ ζε πςιάηζκεξ δελαιεκέξ δζαθυνςκ δζαζηάζεςκ ακάθμβα ιε ηδκ δθζηία ηαζ ημ ιέβεεμξ: 15mX17m, 35mX17m, and 70mX17m. Σα είδδ αοηά εηηνέθμκηαζ ζοκήεςξ ζε ζοζηήιαηα πμθοηαθθζένβεζαξ δζυηζ είκαζ ζε εέζδ κα αλζμπμζμφκ δζαθμνεηζηά ηιήιαηα ηδξ οδάηζκδξ ζηήθδξ ηαζ ημο αέκεμοξ. Ζ ακακέςζδ κενμφ πμζηίθθεζ απυ 5% έςξ 40% ημο υβημο δελαιεκήξ διενδζίςξ (Saltos 2011). Παναηδνμφκηαζ επμπζαηά πνμαθήιαηα μλέςζδξ ημο κενμφ ηαεχξ ηαζ επμπζαηυξ εοηνμθζζιυξ πμο εα ιπμνμφζακ κα ακηζιεηςπζζημφκ ιε ηαθφηενδ δζαπείνζζδ ημο κενμφ εηηνμθήξ ηαεχξ ηαζ ηαθφηενδ δζαπείνζζδ ημο πανεπυιεκμο ζζηδνεζίμο. Ζ ζοκήεδξ πναηηζηή είκαζ δ ζε αναζά πνμκζηά δζαζηήιαηα πανμπή ζπυνςκ ή αθεφνςκ ζε πνςημβεκή ιμνθή πςνίξ πνμδβμφιεκδ επελενβαζία ημοξ βζα ηδκ δζαιυνθςζδ ζοιπήηηςκ, ιε ελαίνεζδ ηδκ ηζθάπζα βζα ηδκ μπμία πανέπμκηαζ εζδζηά ζφιπδηηα πμο δζαηίεεκηαζ ζημ ειπυνζμ. Γέκ οθίζηακηαζ ζημζπεία βζα ηζξ εζδζηέξ δζαηνμθζηέξ απαζηήζεζξ ηςκ εκδδιζηχκ εζδχκ. ηδκ πενζμπή ακαθένεηαζ δ φπανλδ ιμκάδαξ επελενβαζίαξ ζπεοδνχκ πμο δδιζμονβήεδηε ηφνζα βζα ηα είδδ cachama ηαζ ηζθάπζα, υιςξ δ ιμκάδα αοηή οπμ-θεζημονβεί δζυηζ μζ ημπζημί οδαημηαθθζενβδηέξ δεκ δφκακηαζ κα ελαζθαθίζμοκ ιία ζοκεπή νμή ειπμνεφζζιμο πνμσυκημξ (πνμζςπζηή επζημζκςκία ιε Blgo. Roberto Dixon Saltos, MAGAP - Sucumbios). Ζ επανπία Esmeraldas ζηα Ακαημθζηά ηδξ, ζοκμνεφεζ ιε ηζξ δπεζνςηζηέξ επανπίεξ Carchi, Imbaburra, Pinchincha εκχ ζηα Γοηζηά απμηεθεί ηιήια ηδξ αηημβναιιήξ ημο Δζνδκζημφ Χηεακμφ. Σμ ιεβαθφηενμ % ηδξ επζθάκεζαξ ηδξ επανπίαξ αοηήξ ανίζηεηαζ ζε ορυιεηνμ <450m απυ ηδκ επζθάκεζα ηδξ εάθαζζαξ ηαζ παναηηδνίγεηαζ απυ ηθίια ηνμπζηυ (ιέζδ εθαπ. 22 o C- ιέζδ ιεβ.29 o C, 0.6 cm 5.6 cm ιέζδ ιδκζαία ανμπυπηςζδ). ηδκ επανπία αοηή ημ ιεβαθφηενμ % ηςκ ζπεοδνχκ πνμένπεηαζ απυ ηδκ εαθάζζζα αθεία εκχ δ οδαημηαθθζένβεζα εηπνμζςπείηαζ ζε ιζηνυ % ηαζ ηφνζα απυ ηδκ βανίδα. ηδκ επανπία αοηή παναηδνείηαζ έθθεζρδ πνμσυκημξ ζηζξ ημπζηέξ ζπεοαβμνέξ δζυηζ ηα πενζζζυηενα αθζεφιαηα δζμπεηεφμκηαζ ζηα ιεβάθα αζηζηά ηέκηνα ηδξ εκδμπχναξ. Χξ εη ημφημο οπάνπεζ ιία αολδιέκδ ακάβηδ βζα πνμιήεεζα πνμσυκηςκ οδαημηαθθζένβεζαξ ζηζξ ζπεοαβμνέξ ηδξ επανπίαξ αοηήξ (πνμζςπζηή επζημζκςκία ιε ειπυνμοξ αθζεοηζηχκ πνμσυκηςκ ζηδκ επανπία). Σμ 2012 λεηίκδζε έκα ηναηζηυ πνυβναιια δδιζμονβίαξ πςιάηζκςκ δελαιεκχκ (40mX25m) βζα ηδκ εηηνμθή ηζθάπζαξ ζε δζάθμνεξ πενζμπέξ ηδξ επανπίαξ αοηήξ. Λυβς αηαηάθθδθδξ ημηημιεηνζηήξ ζφζηαζδξ ημο εδάθμοξ (έθθεζρδ ανβίθθμο) ζηζξ πενζζζυηενεξ απυ ηζξ δελαιεκέξ αοηέξ παναηδνήεδηε ζδιακηζηή οπυβεζα δζαθοβή κενμφ ηαζ απχθεζα ζπεοδίςκ. Πανάθθδθα πνμέηορακ ηαζ πνμαθήιαηα ιε ημ ζδζμηηδζζαηυ ηαεεζηχξ ηςκ δελαιεκχκ αοηχκ δζυηζ ζε πμθθέξ πενζπηχζεζξ μζ ειπθεηυιεκμζ οδαημηαθθζενβδηέξ δεκ ήηακ ηαζ ζδζμηηήηεξ ηςκ εκ θυβς εηηάζεςκ (πνμζςπζηή επζημζκςκία ιε Blgo Fabio Sixto Caicedo, Sub Secretaria De Acuicultura, MAGAP - Esmeraldas). Δκ ημφημζξ ζε πμθθέξ πενζμπέξ ηδξ επανπίαξ αοηήξ (ηφνζα ζημ ΒΑ ηιήια ηδξ), οπάνπμοκ ιζηνμί ηαθθζενβδηέξ πενζαίςκ αβνμηζηχκ πνμσυκηςκ πμο έπμοκ εηδδθχζεζ εκδζαθένμκ βζα ηδκ εηηνμθή δζαθυνςκ εκδδιζηχκ ρανζχκ υπςξ: Sabalo (Brycon spp.), Belone (Strongylura fluviatilis), Guayas cichlid (Cichlasoma festae) & Chame (Dormitator latifrons). Σα είδδ αοηά εα ιπμνμφζακ κα «εκζςιαηςεμφκ» ζημ οπάνπμκ ζφζηδια πενζαίςκ ηαθθζενβεζχκ ιε ηδκ δδιζμονβία πςιάηζκςκ δελαιεκχκ εηηνμθήξ ιζηνήξ έηηαζδξ ηαζ κα ζοιαάθθμοκ ζδιακηζηά ζηδκ αεθηίςζδ ημο αζμηζημφ επζπέδμο ηςκ ηαθθζενβδηχκ αοηχκ, αθθά ηαζ κα ηνμθμδμηήζμοκ ηζξ ημπζηέξ ζπεοαβμνέξ ηαθφπημκηαξ ιένμξ ηδξ αολδιέκδξ ημπζηήξ γήηδζδξ (πνμζςπζηή επζημζκςκία ιε Eduardo Rebolledo Monsalve, Director Centro de Investigacion y Desarrollo, PUCESE). Χξ εη ημφημο δ ακάπηολδ ηδξ οδαημηαθθζένβεζαξ εζςηενζηχκ οδάηςκ ζηδκ επανπία Esmeraldas εα ιεζχζεζ ημ έθθεζια πμο παναηδνείηαζ ζηζξ ημπζηέξ ζπεοαβμνέξ αθθά πανάθθδθα εα είκαζ ζε εέζδ κα ηνμθμδμηήζεζ ηαζ άθθεξ επανπίεξ ηδξ εκδμπχναξ (i.e. Imbaburra, Pinchincha) υπμο παναηδνείηαζ ιζα ζοκεπχξ αολακυιεκδ γήηδζδ ζε αθζεφιαηα. Πανάθθδθα οπάνπεζ πάκηα ηαζ δ επζθμβή ηδξ ελαβςβήξ ιένμοξ ηδξ αολδιέκδξ παναβςβήξ ζε βεζημκζηέξ πχνεξ (Πενμφ, Κμθμιαία) υπμο δ γήηδζδ είκαζ ζοκεπήξ ηαζ αολακυιεκδ. 380

381 5. πκπεξάζκαηα - Πξνηάζεηο Σμ Ecuador είκαζ ιζα ακαπηοζζυιεκδ πχνα υπμο δ ζοκεπήξ αφλδζδ ημο αζμηζημφ επζπέδμο ηαζ δ παιδθή ιέζδ ηαηά ηεθαθήκ ηαηακάθςζδ ζπεοδνχκ, εββοχκηαζ ηδκ απμννυθδζδ κέςκ οδαημηαθθζενβδηζηχκ πνμσυκηςκ. Οιςξ ζηα εέιαηα οδαημηαθθζένβεζαξ εζςηενζηχκ οδάηςκ παναηδνείηαζ ιία έθθεζρδ ηεκηνζημφ ζπεδζαζιμφ ηαζ αλζμθυβδζδξ ηςκ δοκαημηήηςκ ηςκ θοζζηχκ οδάηζκςκ πυνςκ βζα οδαημηαθθζενβδηζημφξ ζημπμφξ. Αοηυ ηαείζηαηαζ αηυια πζυ δφζημθμ απυ ηδκ ηαοηυπνμκδ εηιεηάθθεοζδ ηςκ οδάηζκςκ πυνςκ απυ άθθεξ αζμιδπακίεξ (ελυνολδ πεηνεθαίμο, ελυνολδ ιεηαθθεοιάηςκ, οδνμδθεηηνζηή εκένβεζα) πμο οπυ μνζζιέκεξ ζοκεήηεξ είκαζ δοκαηυκ κα ηαηαζημφκ νοπμβυκεξ βζα ημοξ ίδζμοξ αοημφξ ημοξ οδάηζκμοξ πυνμοξ πμο πνδζζιμπμζμφκ (Rebolledo & Prado 2014). Πανάθθδθα οπάνπεζ ηαζ έθθεζρδ ελεζδζηεοιέκμο πνμζςπζημφ ζηζξ ανιυδζεξ οπδνεζίεξ πμο ζοπκά αδοκαημφκ κα ενιδκεφζμοκ ηα απμηεθέζιαηα δζαθυνςκ ενεοκδηζηχκ πνμζπαεεζχκ ηαζ κα ζοκημκίζμοκ υθεξ αοηέξ ηζξ δναζηδνζυηδηεξ πςνίξ ανκδηζηέξ αθθδθεπζδνάζεζξ βζα ηζξ ίδζεξ αθθά ηαζ ημ πενζαάθθμκ. Οζ δφμ πενζμπέξ ένεοκαξ πανμοζζάγμοκ ζδιακηζηέξ δοκαηυηδηεξ ακάπηολδξ ηδξ οδαημηαθθζένβεζαξ εζςηενζηχκ οδάηςκ, πάκηα υιςξ ιε ημοξ πνμακαθενυιεκμοξ πενζμνζζιμφξ. Πένακ ηςκ πενζμνζζιχκ αοηχκ, ζδζαίηενδ έιθαζδ πνέπεζ κα δμεεί ζηδκ δζενεφκδζδ ηςκ απαζηήζεςκ εηηνμθήξ (ακαπαναβςβή, δζαπείνζζδ, δζαηνμθή) ηςκ εκδδιζηχκ εζδχκ βζα ηδκ ακάδεζλδ ηςκ ηαηαθθδθυηενςκ βζα εηηνμθή ζηζξ ημπζηέξ βεςιμνθμθμβζηέξ ηαζ ηθζιαημθμβζηέξ ζοκεήηεξ. ηα πθαίζζα αοηά εα πνέπεζ πνςηανπζηά κα δδιζμονβδεμφκ ενεοκδηζηά ηέκηνα ιε ηζξ ηαηάθθδθεξ οθζημηεπκζηέξ ηαζ ακενχπζκεξ οπμδμιέξ, εκχ δεοηενεουκηςξ εα ήηακ ζηυπζιδ ηαζ δ δδιζμονβία ζπεομβεκκδηζημφ ζηαειμφ πμο κα πνμιδεεφεζ ημοξ παναβςβμφξ ιε ζπεφδζα ηαθήξ πμζυηδηαξ ηαζ ζοβηεηνζιέκςκ πνμδζαβναθχκ. Απαναίηδηδ εεςνείηαζ ηαζ δ εηπυκδζδ εκυξ εεκζημφ επζπεζνδιαηζημφ ζπεδίμο (business plan) πμο εα δζενεοκήζεζ δζελμδζηά ηζξ δοκαηυηδηεξ ακάπηολδξ ηδξ οδαημηαθθζένβεζαξ εζςηενζηχκ οδάηςκ πςνίξ ανκδηζηέξ επζπηχζεζξ ζημ πενζαάθθμκ, ηδκ ιμκαδζηή αζμπμζηζθυηδηα ηδξ πχναξ ηαζ ιε ελαζθάθζζδ ηδξ αεζθμνίαξ ηςκ θοζζηχκ ηαζ ακενχπζκςκ πυνςκ ηδξ. Δπραξηζηίεο Ζ ένεοκα αοηή πνδιαημδμηήεδηε απυ ηδκ Γεκζηή Γναιιαηεία Ακχηαηδξ Δηπαίδεοζδξ, Δπζζηήιδξ, Σεπκμθμβίαξ ηαζ Καζκμημιίαξ ημο Ecuador (Secretaria Nacional De Educacion Superior, Ciencia Tecnologia E Innovacion - SENESCYT), Contract No διακηζηή ήηακ ηαζ δ ζοιαμθή ημο Τπμονβείμο Γεςνβίαξ, Κηδκμηνμθίαξ, Αθζείαξ & Τδαημηαθθζενβεζχκ ημο Ecuador (MAGAP - Ministerio de Agricultura, Ganadería, Acuacultura y Pesca Zona 1) ημ μπμίμ ιε ηδκ ακενχπζκδ & οθζημηεπκζηή ημο οπμδμιή ελαζθάθζζε ηδκ ζοθθμβή πθδνμθμνίςκ απμ ηζξ πενζμπέξ ένεοκαξ. Γεκ πνέπεζ κα παναθεζθεεί δ ζδιακηζηή αμήεεζα ηςκ ζοκαδέθθςκ ενεοκδηχκ Eduardo Rebolledo Monsalve ηαζ Pedro Jiménez Prado ημο πακεπζζηδιίμο Pontificia Universidad Catolica del Ecuador, Sede Esmeraldas - (PUCESE) πμο πανείπακ ζημζπεία βζα ηδκ αθζεία & οδαημηαθθζένβεζα ζηδκ επανπία Esmeraldas. Βηβιηνγξαθία FAO (2014). Food and Agriculture Organization of the United Nations, Departamento depesca y Acuicultura, Perfiles sobre la pesca y la acuicultura por países, La República Del Ecuador. (Πνυζααζδ ). MAGAP (2014). Ministerio de Agricultura, Ganadería, Acuacultura y Pesca Zona 1. (Πνυζααζδ ). 381

382 Rebolledo E. M., Prado P. J. (2014). Calidad de agua, actividad minera aurífera y comunidades de peces de agua dulce de la zona media baja del sistema hidrográfico Santiago- Cayapas, Esmeraldas, Ecuador. Memorias de 1mero Encuentro Nacional De Ictiologia, PUCESE, Esmeraldas, Ecuador, pp Saltos, Roberto Dixon (2011). Guia tecnica para la produccion piscicola. Gobierno Autonomo Descentralizado De Sucumbios. Centro De Investigaciones Y Servicios Agropecuarios Sucumbios CISAS. Coordinación General Ing. Lidio Villarreal Bolaños, Director del CISAS, Ecuador, pp

383 COMPARATIVE HISTOPATHOLOGICAL AND IMMUNOHISTOCHEMICAL EVALUATIONS IN JUVENILE SEA BASS (Dicentrarhus labrax) AND GILTHEAD SEA BREAM (Sparus aurata) NATURALLY INFECTED WITH Photobacterium damselae subsp. piscicida Hamdi AVCI 1, S.Serap BIRINCIOĞLU 1, Erkmen Tuğrul EPIKMEN 1, Melike DERELI 1 1 Department of Pathology, Faculty of Veterinary Medicine, University of Adnan Menderes, Isikli-Aydin, TURKEY sbirincioglu@adu.edu.tr ABSTRACT The present study describes pathological and immunohistochemical findings resulting from acute and chronic infections in juvenile sea bass (Dicentrarhus labrax) and gilthead sea bream (Sparus aurata) naturally infected with Photobacterium damselae subsp. piscicida. The disease has an acute presentation in sea bass while in gilthead sea bream acute and chronic forms were recorded. The highest mortality rates in both fish species were observed in June when the water temperature is elevated. In both species, the acute form is histopathologically characterized by the abundance of bacterial clusters coupled to vascular lesions in many organs (gills, heart, kidney, spleen, liver and gastrointestinal tract at a lesser extend). In the chronic form, granulomatous lesions consisted in clusters of bacteria in the center surrounded by epithelial histiocytes and macrophages and finally fibroblasts. By immunohistochemistry, immunopositive bacteria were densely evidenced in the kidney, spleen, gills, heart and liver in acute cases in both fish species whereas they were mainly located in kidney and spleen during the chronic form. Keywords: Fish pasteurellosis, sea bass, gilthead sea bream, pathological findings, immunohistochemistry. Introduction Photobacterium damselae subsp. piscicida, the causative agent of fish pasteurellosis, was initially isolated from natural populations of white perch (Morone americanus) and striped bass (Morone saxatilis) in 1963 during a massive epizootic in Chesapeake Bay, USA [16], and is now widely distributed throughout the world [5,18]. Sea bass (Dicentrarhus labrax) and gilthead sea bream (Sparus aurata) fish are the species most susceptible to the disease [7,9, 18]. The disease generally affects larvae causing mortality of %, but the disease can also affect juveniles with mortality up to 50% [2, 15]. The incidence of diseases and types of bacterial pathogens has well documented in several cultured fish species [3]. The disease was described as an acute to chronic disease [17]. 383

384 The aims of the study are to present and evaluate histopathological and immunohistochemical findings of fish pasteurellosis in juvenile sea bass (Dicentrarhus labrax) and gilthead sea bream (Sparus aurata) naturally infected with Photobacterium damselae subsp. piscicida. Materials and Methods In the early summer, an outbreak was occurred in a fish farm, which was located in the southern Aegean of part Turkey. Fish samples were collected monthly from the rearing pools from March to June. For bacteriological examinations, samples were taken in cooled boxes (1-4 O C) to laboratory and then the samples were processed within 1 hour after collection for bacteria identification using microbiological methods [5, 10]. For histological examinations, a total of 96 dead or euthanized fish (44 juvenile sea bass and 52 juvenile gilthead sea bream) were fixed in 10% neutral-buffer formalin solution, embedded in paraffin, sectioned at 5 µm and stained routinely with haematoxylin and eosin and examined using light microscope. The selected kidney, liver, spleen, heart and gill sections were also stained by Brown and Brenn staining method for bacteria [6]. Replicated sections were also used for immunohistochemistry.the immunohistochemical procedure used in the present study was based on the method of ADAMS and MARIN DE MATEO [1]. Results Clinical and Macroscopical Findings Photobacterium damselae subsp. piscicida was isolated and identified from the sea bass and gilthead sea bream samples Only acute form of the disease was observed in sea bass whereas chronic and acute forms were recorded in gilthead sea bream. In both fish species, the highest mortality rates were seen in June when the temperature of the water reached 24 C. During the investigation period, water salinity and quality were uniform, but it was noted that water temperatures ranged between C during the epizootics. However, globally morbidity and mortality rates were higher in gilthead sea breams than in sea basses. In acute form, darkening of skin colour and swimming near to the water surface were among clinical findings. Fishes with these clinical findings usually died within 2-3 days. In chronic form (only seen in gilthead sea breams), the prominent clinical findings were decrease in food consumption, irregular swimming movements, lethargy and varying degrees of skin colour modifications (darkening or lightening). In addition, unilateral exophthalmia and erosive changes in the skin were also seen in acute and chronic forms. Vascular lesions in many organs and tissues consisting in oedema, hyperaemia and haemorrhages were found during the acute form in both fish species. In the chronic form, adhesions were seen in the abdominal cavity of some gilthead sea breams but the prominent macroscopic finding was light greyish white nodules at the size of mm, hardly visible with naked eye. 384

385 Histopathological Finding The most important histopathological finding seen in both sea basses and gilthead sea breams was the presence of dense bacterial clusters in the parenchyma and vessel lumens of kidney, spleen and liver and in vessel lumens of gills, heart, stomach, pyloric caecum, peritoneum, pancreas, muscles and meninges. In acute form, vessel lumens were enlarged in gills and they were filled with plasma, erythrocytes and clusters of bacteria. In secondary lamellae telangiectasias containing bacterial clusters were present in many cases of both fish species (figure 1A). Necrosis was present in primary and secondary lamellar epithelium, but more commonly and severely in the secondary lamella. In the heart, pericardial cavity was expanded due to haemorrhages containing large clusters of bacteria (figure 1B). In many cases, lumen of ventricle and atrium were filled with bacterial clusters and erythrocytes. Spleen and kidney were the more affected organs both in sea bass and gilthead sea bream. In the acute form, spleen lesions including focal or irregularly located multifocal necrotic areas containing clusters of bacteria, oedema, severe hyperaemia and haemorrhages were related to septicaemia. Clusters of bacteria either completely filled the vessel lumens or were focally or diffusely distributed in parenchyma. In kidney, vessels were hyperaemic and in many cases, focal or diffuse haemorrhagic areas were present in interstitium. In all cases, clusters of bacteria were distributed to the whole organ including vessel lumens and parenchyma (figure 1C). Tubular epithelia were generally swollen and in some epithelial cells, cytoplasm had granular eosinophilic appearance. Necrotic changes were present in haematopoietic tissues of the kidney as well (figure 1D). Necrotic lesions were often focal or multifocal but sometimes they were in the form of single cell necrosis. Especially in gilthead sea breams, macrophages containing bacteria in their cytoplasm were seen in the renal haematopoietic tissue. In the chronic form, marked lesions were noticed in spleen (figure 2A) and kidney (figure 2B) and at a lower degree in peritoneum and gills. The lesions were similar to those found in the acute form but they were generally less intense and were associated to the presence of granulomas with clusters of bacteria in the center surrounded by epithelial histiocytes and macrophages and finally fibroblasts at the outermost forming a thin connective tissue. In newly formed granulomas, macrophages with a dark eosinophilic cytoplasm containing bacteria and picnotic nucleus were often evidenced. Immunohistochemical Findings Bacteria found in many tissues and organs from sea basses and gilthead sea breams were stained positively by immunohistochemistry and bacterial morphology was clearly evidenced. In necrotic areas, positive reactions were usually in granular appearance and less dense. In the acute form, positive reactions were prominently encountered in kidney (figure 3A), spleen and gills (figure 3B) whereas immunolabelling was less intense in heart (figure 3C) and in liver. Immunopositive reactions were also detected in cytoplasm of few macrophages in the kidney, spleen, gills, heart and liver but 385

386 also in the submucosa of pyloric caecum and intestines. In the chronic form, immunopositive bacteria were essentially observed in the kidney and spleen. Positive staining was strongly marked in the vessel lumens (figure 3D) and in parenchyma while in the center of newly formed or old granulomas, immunopositive bacterial density was decreased or sometimes null. Additionally, strong immunopositive reactions were also detected in macrophage cytoplasms (figure 3D). Staining in the other organs and tissues was less dense than in the acute form. Table I: Clinical and macroscopical findings (number of cases) in juvenile sea bass (Dicentrarhus labrax) and gilthead sea bream (Sparus aurata) naturally infected with Photobacterium damselae subsp. piscicida. Necropsied animals Length of fish (cm) Morbidity (%) Mortality (%) Irregular swimming Coloration in the skin Skin erosion Exophthalmia Adhesion Granuloma in kidney Granuloma in the spleen Sea bass Gilthead sea bream Table II: Histopathological and immunohistochemical findings (number of cases) in juvenile sea bass (Dicentrarhus labrax) and gilthead sea bream (Sparus aurata) naturally infected with Photobacterium damselae subsp. piscicida. Sea bass Gilthead sea bream Gill Cluster of bacteria Necrosis

387 Telangiectasia Granuloma Immunohistochemistry Heart Cluster of bacteria Pericardial haemorrhages Necrosis Endothelial macrophage activation Immunohistochemistry Liver Cluster of bacteria Hyperaemia- Haemorrhages Degeneration Necrosis Fatty droplets in the hepatocytes Immunohistochemistry Spleen Cluster of bacteria Hyperaemia- Haemorrhages Necrosis Granuloma Immunohistochemistry Kidney Cluster of bacteria Hyperaemia- Haemorrhages Necrosis (tubular epithelium) Necrosis (glomerulus) Necrosis (haematopoietic tissues)

388 Granuloma Immunohistochemistry Discussion In the present study, clinical, pathological and immunohisto-chemical findings of natural pasteurellosis occurring in juvenile sea basses and gilthead sea breams were investigated comparatively and findings were comprehensively evaluated. In pasteurellosis cases reported by many investigators [2, 4, 14], kidney and spleen are among the organs where microscopic and macroscopic findings are commonly seen. However, whereas clusters of bacteria were common in acute cases, sometimes clusters of bacteria were few or even absent in chronic cases. Additionally, immunopositive bacteria detected by immunohistochemistry were also found to be more abundant in acute cases than in chronic cases, suggesting that in juvenile fish, kidney and spleen might be not enough sufficient in isolation and identification of the pathogen agent, probably because of activation of cellular immunity, whilst in chronic cases, this situation should be taken into account [ 11, 13, 14]. The immunoperoxidase method is used for the definitive diagnosis of fish pasteurellosis [ 8, 12]. In the present study, when two forms of the disease were compared (acute vs. chronic forms), the distribution of immunopositive bacteria in tissues and organs varied: positive reactions were more common in the acute form than in the chronic one and even, in some fishes chronically affected no immunopositive bacteria were identified. References 1. ADAMS A., MARIN DE MATEO M.: Imnunohistochemical detection of fish pathogens. In: Techniques in fish imnunology, STOLEN J.S., FLETCHER T.C., ROWLEY A.F., ZELIKOFF J.T., KAATTARI S.L. and SMITH S.A. (eds.): SOS Publication, USA, 1994, pp.: BAKOPOULOS V., PERIC Z., RODGER H., ADAMS A., RICHARDS R.H.: First report of fish pasteurellosis from Malta. J. Aquat. Anim. Health, 1997, 9, BALEBONA M.C., ZORRILLA I., MORINIGO M.A., BORREGO J.J.: Survey of bacterial pathologies affecting farmed gilt-head sea bream (Sparus aurata L.) in southwestern Spain from Aquaculture, 1998, 166, BAPTISTA T., ROMALDE J.L., TORANZO A.E.: First occurence of pasteurellosis in Portugal affecting cultured gilthead seabream (Sparus auratus). Bull. Eur. Assoc. Fish Pathol., 1996, 16, CANDAN A., KUCKER M.A., KARATAS S.: Pasteurellosis in cultured sea bass (Dicentrarchus labrax) in Turkey. Bull. Eur. Assoc. Fish Pathol., 1996, 16,

389 6. CULLING A.F., ALLISON T.R., BARR T.W.: Cellular Pathology Technique, CULLING A.F., ALLISON T.R. and BARR T.W. (eds), 4 th edition, Butterworth & Co.(Publ.). Ltd., London, 1985, pp.: JONES M.W., COX D.I.: Clinical Disease in seafarmed Atlantic salmon (Salmo salar) associated with a member of the family pasteurellaceae-a case history. Bull. Eur. Assoc. Fish Pathol., 1999, 19, JUNG T.S., THOMPSON K.D., MORRIS D.J., ADAMS A., SNEDDON K.: The production and characterization of monoclonal antibodies against Photobacterium damselae ssp. piscicida and initial observations using immunohistochemistry. J. Fish Dis., 2001, 24, KUSUDA R., KAWAI K.: Bacterial diseases of cultured marine fish in Japan. Fish Pathol., 1998, 33, LIU P.C., CHENG C.F., CHANG C.H., LIN S.L., WANG W.S., HUNG S.W., CHEN M.H., LIN C.C., TU C.Y., LIN Y.H.: Highly virulent Photobacterium damselae subsp. Piscicida isolated from Taiwan paradise fish, Macropodus opercularis (L.), in Taiwan. Afr. J. Microbiol. Res., 2011, 5, MAGARINOS B., TORANZO A.E., ROMALDE J.L.: Different susceptibility of gilthead seabream and turbot to Pasteurella piscicida infection by the water route. Bull. Eur. Assoc. Fish Pathol., 1995, 15, MANIATIS K., MORRIS D.J., ADAMS A., PEARSON M.: Detection of Photobacterium damsela subspecies piscicida in fixed tissue sections using immnunohistochemistry and antigen retrieval immunohisto-chemistry. J Fish Dis., 2000, 23, MLADINEO I., MILETIC I., BOCINA I.: Photobacterium damselae subsp. piscicida outbreak in cagereared Atlantic bluefin tuna Thunnus thynnus. J. Aquat. Anim. Health, 2006, 18, NAGANO I., INOUE S., KAWAI K., OSHIMA S.I.: Repeatable immersion infection with Photobacterium damselae subsp. piscicida reproducing clinical signs and moderate mortality. Fish. Sci., 2009, 75, NOYA M., MAGARINOS B., LAMAS J.: Interactions between peritonel exudate cells (PECs) of gilthead seabream (Sparus aurata) and Pasteurella piscicida. A morphological study. Aquaculture, 1995, 131, SNIESZKO S.F., BULLOCK G.L., HOLLIS E., BOONE J.G.: Pasteurella sp. from an epizootic of white perch (Roccus americanus) in Chesapeake Bay tidewater areas. J. Bacteriol., 1964, 88, THUNE R.L. STANLEY L.A., COOPER R.K.: Pathogenesis of gram-negative bacterial infections in warmwater fish. Annu. Rev. Fish Dis., 1993, 3, TORANZO A.E. BARREIRO S., CASAL J.F., FIGUERAS A., MAGARINOS B., BARJA J.L.:Pasteurellosis in cultured gilthead seabream (Sparus aurata):first report in Spain. Aquaculture, 1991,99,

390 DEVELOPMENT OF A DIGITAL CHECKLIST OF GREEK FISH FAUNA Minos G. 1 *, Kostoglou V. 2, Tsilvelis S. 2 1 Department of Fisheries and Aquaculture Technology, Alexander Technological Educational Institute of Thessaloniki, P.O. Box. 157, GR-63200, Nea Moudania, Greece. 2 Department of Information Technology, Alexander Technological Educational Institute of Thessaloniki, P.O. Box. 141, GR-57400, Thessaloniki, Greece. ABSTRACT The present work focuses on the development of a digital checklist of all the fish species inhabiting the Greek Seas and inland waters. The developed application is fully interactive and has an easy to use and friendly user interface providing to the user excellent operational capabilities to search and find any species together with complete information on it (scientific and Greek-English common names, systematic, morphological and ecological information, a picture of the fish and the geographical distribution). It is an easy to use and scalable digital application, very useful to the scientific community, as it enables an easy and fast way to achieve information on a given fish species or on a group (e.g. family), further assisting ichthyologists, students, professional or recreational fishermen. Key words: Identification, classification, fish, *Corresponding author: Minos George (gminos@otenet.gr) ΑΝΑΠΣΤΞΖ ΦΖΦΗΑΚΟΤ ΚΑΣΑΛΟΓΟΤ ΣΖ ΔΛΛΖΝΗΚΖ ΗΥΘΤΟΠΑΝΗΓΑ Μίλνο Γ. 1 *, Κψζηνγινπ, Β. 2, Σζηιβειήο. 2 1 Σιήια Σεπκμθμβίαξ Αθζείαξ ηαζ Τδαημηαθθζενβεζχκ, Αθελάκδνεζμ Σεπκμθμβζηυ Δηπαζδεοηζηυ Ίδνοια Θεζζαθμκίηδξ, Σ.Θ. 157, 63200, Νέα Μμοδακζά, Δθθάδα. 2 Σιήια Μδπακζηχκ Πθδνμθμνζηήξ, πμθή Σεπκμθμβζηχκ Δθανιμβχκ, Αθελάκδνεζμ Σεπκμθμβζηυ Δηπαζδεοηζηυ Ίδνοια Θεζζαθμκίηδξ, Σ.Θ. 141, 57400, Θεζζαθμκίηδ, Δθθάδα. Πεξίιεςε Ζ πανμφζα ενβαζία επζηεκηνχκεηαζ ζηδκ ακάπηολδ εκυξ ρδθζαημφ ηαηαθυβμο ιε υθα ηα είδδ ρανζχκ πμο απακηχκηαζ ζηζξ εθθδκζηέξ εάθαζζεξ ηαζ ηα εζςηενζηά φδαηα. Ζ εθανιμβή πμο ακαπηφπεδηε είκαζ πθήνςξ δζαδναζηζηή ηαζ δζαεέηεζ έκα εφημθμ ζηδ πνήζδ ηαζ θζθζηυ πενζαάθθμκ ενβαζίαξ πμο πανέπεζ ζημοξ πνήζηεξ ελαζνεηζηέξ δοκαηυηδηεξ βζα κα ακαγδηήζμοκ ηαζ κα ανμοκ υθα ηα είδδ ηςκ ρανζχκ ιαγί ιε πθδνμθμνίεξ ζπεηζηά ιε ηδκ (επζζηδιμκζηή ηαζ εθθδκζηή - αββθζηή ημζκή μκμιαζία, ηδκ ζοζηδιαηζηή ημο ηαηάηαλδ, 390

391 ιμνθμθμβζηά ηαζ μζημθμβζηά ζημζπεία, ιζα εζηυκα ηςκ ρανζχκ ηαζ ηδξ βεςβναθζηήξ ημο ελάπθςζδξ). Δίκαζ ιζα εφημθδ ζηδ πνήζδ ηαζ ρδθζαηή εθανιμβή, πμθφ πνήζζιδ βζα ηδκ επζζηδιμκζηή ημζκυηδηα, ηαεχξ επζηνέπεζ έκα εφημθμ ηαζ βνήβμνμ ηνυπμ βζα ηδκ επίηεολδ πθδνμθμνζχκ ζπεηζηά ιε έκα ζοβηεηνζιέκμ είδμξ ρανζμφ ή ζε ιζα μιάδα (π.π. μζημβέκεζα), βζα κα αμδεήζεζ ζπεομθυβμοξ, θμζηδηέξ, επαββεθιαηίεξ ή εναζζηέπκεξ αθζείξ. Λέξειρ κλειδιά: Tylosurus, βάζε δεδνκέλσλ, ςάξηα *οββναθέαξ επζημζκςκίαξ: Μίκμξ Γεχνβζμξ 1. Δηζαγσγή ήιενα πενζβνάθμκηαζ παβημζιίςξ πενίπμο είδδ ρανζχκ (Froese & Pauly 2014) εκχ ζηδκ Μεζυβεζμ εάθαζζα ακαθένμκηαζ 735 είδδ (Froese & Pauly 2014) ή ιε ζοκηδνδηζηυηενμοξ οπμθμβζζιμφξ 684 είδδ (602 μζηεζπεφεξ, 79 Υμκδνζπεφεξ ηαζ 3 Κοηθυζημιμζ) (Psomadakis et al., 2012). ηζξ Δθθδκζηέξ εάθαζζεξ ζοκακηάιε πενίπμο 510 είδδ ρανζχκ (441 Οζηεζπεφεξ, 68 Υμκδνζπεφεξ ηαζ 1 Άβκαεα) (Papaconstantinou, 2014) εη ηςκ μπμίςκ 414 είδδ ζημ Αζβαίμ πέθαβμξ (Froese & Pauly 2014). ηα βθοηά κενά ηδξ Δθθάδαξ έπμοκ ηαηαβναθεί 154 είδδ ρανζχκ (Kottelat & Freyhof 2007, Λεβάηζξ & Μαναβημφ 2009). Πμθθά υιςξ απυ αοηά ηα είδδ ηςκ ρανζχκ απακηχκηαζ ηαζ ζηδ εάθαζζα (π.π. 3 ζημονζυκζα, 1 θάιπναζκα, 6 ηέθαθμζ, 1 αεενίκα, 1 ζαημνάθα, 1 ζανδεθμιάκα, 1 πέθζ, 1 θαανάηζ), ιε απμηέθεζια ημ άενμζζια 664 ( ) βζα ημκ ζοκμθζηυ ανζειυ ηςκ ρανζχκ πμο απακηχκηαζ ζηα Δθθδκζηά φδαηα κα είκαζ αζθαθχξ ιζηνυηενμ (π.π. 649). Μέπνζ ζήιενα, μζ πθδνμθμνίεξ βζα ηα ράνζα ηδξ Δθθάδαξ ιπμνμφζακ κα ακαγδηδεμφκ ζε έκηοπμοξ ηαηαθυβμοξ (π.π. Καζπίνδξ 2000, Kottelat & Freyhof 2007, Λεβάηζξ & Μαναβημφ 2009, Μίκμξ 2011, Papaconstantinou 2014). Ακ ηαζ μζ ηαηάθμβμζ αοημί πνμζθένμοκ αλζυπζζηδ ηαζ εκοπυβναθδ πθδνμθυνδζδ, ημ πνυαθδια είκαζ υηζ δ εκδιένςζή ημοξ είκαζ δφζημθδ ηαζ πνμκμαυνα θυβς ηδξ δζαδζηαζίαξ επακεηηφπςζδξ ηαζ ηςκ ηεθεοηαίςκ ελεθίλεςκ ιε ηδ ζπεδυκ ηαεδιενζκή ειθάκζζδ κέςκ εζδχκ ζηδκ πενζμπή ή αθθαβή ζηδκ επζζηδιμκζηή ημοξ μκμιαζία, ημ απμηέθεζια είκαζ κα λεπενκζμφκηαζ βνήβμνα. Σα ηεθεοηαία πνυκζα ιε ηδκ ακάπηολδ ημο δζαδζηηφμο ειθακίζηδηακ παβηυζιζμζ δθεηηνμκζημί ηαηάθμβμζ ιε ράνζα, υπςξ δ FishBase (Froese & Pauly 2014), ημ Integrated Taxonomic Information System (ITIS 2014), ημ World Register of Marine Species (WoRMS 2014), ημ IUCN Red List of Threatened Species (IUCN 2014) ηαζ ημ Marine Species Identification Portal (2014) πμο πενζθαιαάκμοκ ηαζ είδδ πμο απακηχκηαζ ηαζ ζηδκ Δθθάδα. Οζ δθεηηνμκζημί ηαηάθμβμζ έπμοκ ηδ δοκαηυηδηα ηδξ ζοκεπμφξ εκδιένςζδξ ηςκ δεδμιέκςκ ημοξ αθθά απαζημφκ ζφκδεζδ ιέζς δζαδζηηφμο ηαζ πανάθθδθα πνέπεζ ζε ηάεε ακαγήηδζδ κα βίκεζ δζαζηαφνςζδ ηδξ πθδνμθμνίαξ απυ πενζζζυηενεξ απυ ιία πδβέξ θυβς ιεζςιέκδξ αλζμπζζηίαξ ηςκ εηάζημηε δζαδζηηοαηχκ ηυπςκ. Μζα άθθδ πνμζέββζζδ ζημ γήηδια είκαζ ρδθζαηέξ εθανιμβέξ πμο εηηεθμφκηαζ ημπζηά ζημκ οπμθμβζζηή ηαζ δίκμοκ πανάθθδθα ζημ πνήζηδ ηδ δοκαηυηδηα εκδιένςζδξ (πνμζεήηδξ, δζαβναθήξ, αθθαβήξ) ηδξ ημπζηήξ αάζδξ δεδμιέκςκ. Με ημκ ηνυπμ αοηυ ημο δίκεηαζ δ εθεοεενία βζα δζαιυνθςζδ ηδξ ρδθζαηήξ ημο αάζδξ ηαηά ημ δμημφκ επζθέβμκηαζ μ ίδζμξ ηζξ πδβέξ πμο εα ζοιαμοθεοηεί βζα ηδ ζοιπθήνςζδ ηδξ αάζδξ ηδξ εθανιμβήξ. Σέημζεξ ρδθζαηέξ εθανιμβέξ πμο εηηεθμφκηαζ πςνίξ κα απαζηείηαζ δ πνήζδ ημο δζαδζηηφμο (οπάνπεζ ημπζηή αάζδ) είκαζ είηε βζα ηδκ ηαοημπμίδζδ ηςκ εζδχκ ηςκ ρανζχκ ιέζς δθεηηνμκζηχκ ηθεζδχκ (Kostoglou et al. 2013, Minos et al. 2013) είηε βζα ηδκ ακαγήηδζδ ηδξ ζοζηδιαηζηήξ ηαλζκυιδζδξ ηςκ ζπεφςκ ιε ηδ πνήζδ βναιιςημφ ηχδζηα (Μίκμξ ηαζ ζοκ. 2013). ηδκ πανμφζα ενβαζία πανμοζζάγεηαζ ιζα ημπζηή εθανιμβή πμο πενζθαιαάκεζ έκα ηαηάθμβμ ιε ηα ράνζα ηδξ Δθθάδαξ, ιε ηδ ζοζηδιαηζηή ημοξ ηαηάηαλδ, πθδνμθμνίεξ βζα ηδκ ιμνθμθμβία ηαζ ηδκ μζημθμβία ημοξ ηαεχξ ηαζ ζπεηζηέξ πθδνμθμνίεξ βζα ημ ηάεε είδμξ. 2. Τιηθά θαη Μέζνδνη Ζ εθανιμβή ακαπηφπεδηε ιε ηδ βθχζζα πνμβναιιαηζζιμφ Microsoft Visual Basic 6.0 ηαζ οθμπμζήεδηε ιε ημ Microsoft Visual Studio Σα δεδμιέκα βζα ηα είδδ ηςκ ρανζχκ ηδξ Δθθάδμξ ακηθήεδηακ απυ ημοξ 391

392 Καζπίνδξ (2000), Kottelat & Freyhof (2007), Λεβάηζξ & Μαναβημφ (2009), Μίκμξ (2011), Froese & Pauly (2014) ηαζ Papaconstantinou (2014). Αημθμοεείηαζ δ ζοζηδιαηζηή ηαζ μκμιαημθμβία ηςκ εζδχκ ζφιθςκα ιε ημκ Eschmayer (2014), ηδκ FishBase (Froese & Pauly, 2014), ημ Integrated Taxonomic Information System (ITIS 2014) ηαζ ημ WoRMS (2014). 3. Απνηειέζκαηα ηδκ πανμφζα ρδθζαηή εθανιμβή πενζέπμκηαζ ζοβηεκηνςιέκα υθα ηα είδδ ζπεφςκ πμο ζοκακηάιε ζηζξ εθθδκζηέξ εάθαζζεξ, πανέπμκηαζ πμθθέξ πθδνμθμνίεξ βζα ημ ηάεε έκα ηαζ δίκεηαζ δ δοκαηυηδηα ζημκ ηάεε πνήζηδ κα αθθάγεζ (εζζάβεζ-δζαβνάθεζ-εκδιενχκεζ) ηζξ πθδνμθμνίεξ ημο ηαηαθυβμο. Πανάθθδθα, δ εθανιμβή είκαζ ζδζαίηενα πνήζζιδ βζα άιεζδ πθδνμθυνδζδ, πςνίξ κα απαζηείηαζ ζφκδεζδ ζημ δζαδίηηομ βζα δζάθμνα εέιαηα, ζοιπενζθαιαακμιέκμο ηςκ ημζκχκ μκμιάηςκ ηςκ ρανζχκ, ηδξ πανμοζίαξ ηςκ εζδχκ ζηα Δθθδκζηά φδαηα. Αοηυ έπεζ ςξ απμηέθεζια μ πεζνζζηήξ ηδξ, κα ιπμνεί κα ακαγδηήζεζ μπμζμδήπμηε είδμξ επζεοιεί, εφημθα ηαζ πςνίξ ηαεοζηένδζδ ηαζ κα θάαεζ υθεξ ηζξ απαναίηδηεξ πθδνμθμνίεξ ζπεηζηά ιε αοηυ. Τπάνπμοκ δφμ ηνυπμζ ακαγήηδζδξ ζηδ αάζδ. Ο πνχημξ πναβιαημπμζείηαζ ζφιθςκα ιε ηδκ ζοζηδιαηζηή ηαλζκυιδζδ ηςκ ρανζχκ ( Search by Systematics ) ηαζ ειθακίγμκηαζ ςξ απμηέθεζια ηα είδδ ηςκ ρανζχκ πμο πενζθαιαάκμκηαζ ζε ιζα ζοζηδιαηζηή μιάδα πμο επζθέπεδηε (ακχηενδ υπςξ π.π. Οιμηαλία, Σάλδ ή ηαηχηενδ υπςξ π.π. Οζημβέκεζα). Ο δεφηενμξ ηνυπμξ πναβιαημπμζείηαζ πθδηηνμθμβχκηαξ ημ επζζηδιμκζηυ υκμια ημο ρανζμφ ( Search by Scientific Name ), ακαγδηχκηαξ άιεζα έκα ζοβηεηνζιέκμ είδμξ ρανζμφ ακάιεζα ζε αοηά πμο απακηχκηαζ ζηα Δθθδκζηά οδάηζκα πενζαάθθμκηα (εάθαζζα ηαζ εζςηενζηά κενά) ηαζ πενζθαιαάκμκηαζ ζηδκ ημπζηή αάζδ. Ακαθοηζηυηενα, ζηδκ πενίπηςζδ πμο μ πνήζηδξ επζθέλεζ ηδκ ακαγήηδζδ ζφιθςκα ιε ηδ ζοζηδιαηζηή ηαλζκυιδζδ ημο είδμοξ Search by Systematics, ειθακίγμκηαζ ηα επίπεδα ηδξ ζοζηδιαηζηήξ ηαλζκυιδζδξ ηςκ δζαθυνςκ εζδχκ ηςκ ζπεφςκ (Δζηυκα 1). Ξεηζκχκηαξ απυ ημ πζμ βεκζηυ ζοζηδιαηζηυ επίπεδμ ηαζ ηαηαθήβμκηαξ ζημ πζμ εζδζηυ, έπμοιε ηα αηυθμοεα: SuperClass (Τπενηθάζδ), Group (Οιάδα), Class (Κθάζδ), SubClass (Τπμηθάζδ), Division (-), SuperOrder (Τπένηαλδ), Order (Σάλδ), SubOrder (Τπυηαλδ), Family (Οζημβέκεζα), Genus (Γέκμξ), Species (Δίδμξ). Ζ εθανιμβή είκαζ ζπεδζαζιέκδ έηζζ χζηε ακελάνηδηα απυ ημ επίπεδμ βκχζεςκ ημο πνήζηδ πάκς ζημ ακηζηείιεκμ, μζ επζθμβέξ (Δζηυκα 1) κα ημκ αμδεμφκ κα ηαηαθήλεζ ζημ απμηέθεζια πμο ακαγδηεί. Γζα πανάδεζβια, μ πνήζηδξ ηδξ εθανιμβήξ πμο δε βκςνίγεζ ηδ ζοζηδιαηζηή ηαλζκυιδζδ ημο ηάεε είδμοξ, ιπμνεί κα ηαεμδδβδεεί απυ ηα εζδζηά Labels υπμο οπάνπμοκ δίπθα απυ ηάεε επζθμβή (Step 1, Step 2, Step 3, ) ηαζ ημο δείπκεζ ηα αήιαηα υπμο πνέπεζ κα αημθμοεήζεζ λεηζκχκηαξ απυ εονφηενα επίπεδα ζοζηδιαηζηήξ ηαηάηαλδξ (π.π. Superclass, Class) πνμξ ηα πζμ εζδζηά (π.π. Family). 392

393 Δηθφλα 1. Γηαδηθαζία θαη απνηειέζκαηα αλαδήηεζεο ηεο ζπζηεκαηηθήο θαηάηαμεο. Δίκαζ ζδιακηζηυ υηζ φζηενα απυ ηάεε επζθμβή ημο πνήζηδ, βζα πανάδεζβια ιζα ζοβηεηνζιέκδ μζημβέκεζα (Step 9. Select Family), μζ δζαεέζζιεξ επζθμβέξ ημο ζημ επυιεκμ αήια (Step 10. Select Genus) έπμοκ πνμζανιμζηεί ιυκμ ακάιεζα ζηα βέκδ ηαζ ηα είδδ ηςκ ζπεφςκ πμο ακήημοκ ζηδκ μζημβέκεζα ηδξ πνμδβμφιεκδξ επζθμβήξ (Δζηυκα 1). Πανάθθδθα ιπμνεί ακά πάζα ζηζβιή κα εθέβλεζ πμζα είδδ πενζθαιαάκεζ ηάεε ζοζηδιαηζηή μιάδα πμο επζθέβεζ. Γζα πανάδεζβια, εάκ επζθέλεζ (Step 9. Select Family) ηδκ μζημβέκεζα Mugilidae ιπμνεί ζηδ ζοκέπεζα κα εθέβλεζ ηα βέκδ (Step 10. Select Genus) ηαζ ηα είδδ (Step 11. Select Species) πμο πενζθαιαάκεζ δ ζοβηεηνζιέκδ μζημβέκεζα ζπεοχκ ηαζ απακηχκηαζ ζηα Δθθδκζηά φδαηα (Δζηυκα 1). Αθμφ μθμηθδνςεεί δ δζαδζηαζία ηςκ επζθμβχκ, ειθακίγεηαζ ζημ ηάης ιένμξ ηδξ μευκδξ ιήκοια πμο εκδιενχκεζ ημ πνήζηδ βζα ημκ αηνζαή ανζειυ ηςκ ρανζχκ πμο έπμοκ ακεονεεεί ζφιθςκα ιε ηα παναηηδνζζηζηά πμο έπεζ επζθέλεζ (Δζηυκα 1). Γζα ηδκ ειθάκζζδ ημο απμηεθέζιαημξ (Δζηυκα 2), ιπμνεί πμθφ απθά κα παηήζεζ ημ ημοιπί Show (Δζηυκα 1) εκχ ζηδκ πενίπηςζδ πμο επζεοιεί κα βίκεζ ηαεανζζιυξ ηςκ επζθμβχκ ημο ιπμνεί κα παηήζεζ ημ ημοιπί Clear Selections (Δζηυκα 1) ηαζ κα λεηζκήζεζ λακά απυ ηδκ ανπή ηζξ επζεοιδηέξ ηζξ επζθμβέξ ηδξ ζοζηδιαηζηήξ ηαηάηαλδξ (Δζηυκα 1). ζμκ αθμνά ημ απμηέθεζια ηδξ ακαγήηδζδξ (Δζηυκεξ 2 ηαζ 3), μ πνήζηδξ ιπμνεί κα ηάκεζ επζθμβή μπμζμοδήπμηε ρανζμφ απυ αοηά πμο ειθακίγμκηαζ ςξ απμηέθεζια ηδξ ακαγήηδζδξ ημο επζπέδμο ζοζηδιαηζηήξ ηαηάηαλδξ. ηδκ πανμφζα έηδμζδ δ εθανιμβή πενζθαιαάκεζ 643 είδδ ρανζχκ ιε ηζξ ακηίζημζπεξ πθδνμθμνίεξ βζα ημ ηάεε έκα απυ αοηά. 393

394 Δηθφλα 2. Αλαδήηεζε ζχκθσλα κε ην επηζηεκνληθφ φλνκα. ηδκ πενίπηςζδ πμο επζθεβεί δ ακαγήηδζδ ζφιθςκα ιε ημ επζζηδιμκζηυ υκμια ημο ρανζμφ, ειθακίγεηαζ ζημ άκς ιένμξ ηδξ μευκδξ, έκα πεδίμ (Scientific name) βζα ηδκ εζζαβςβή ηεζιέκμο (Δζηυκα 2 ηαζ 3) ζημ μπμίμ μ πνήζηδξ πθδηηνμθμβεί ημ επζζηδιμκζηυ υκμια ημο ρανζμφ ή έκα ιένμξ ημο μκυιαημξ ημο. Καηά ηδ δζάνηεζα ηδξ εββναθήξ ηάεε βνάιιαημξ ημο επζζηδιμκζημφ μκυιαημξ απυ ημ πνήζηδ, πναβιαημπμζείηαζ αοηυιαηδ ηάκεζ ακαγήηδζδ ζηδ αάζδ ηαζ ειθακίγμκηαζ απμηεθέζιαηα ζπεηζηά ιε ηδκ ακηίζημζπδ εββναθή. Ακ μ πνήζηδξ βνάρεζ ιενζηχξ ημ υκμια ηαζ οπάνπμοκ πενζζζυηενεξ απυ ιία εββναθέξ, ηυηε μ πνήζηδξ εα έπεζ ηδκ δοκαηυηδηα κα ηάκεζ επζθμβή μπμζαζδήπμηε απυ αοηέξ επζεοιεί. Δηθφλα 3. Δπηινγή είδνπο ζην απνηέιεζκα ηεο αλαδήηεζεο κε ην επηζηεκνληθφ φλνκα. Σμ απμηέθεζια ηςκ ακαγδηήζεςκ ζε υθεξ ηζξ πενζπηχζεζξ (Δζηυκα 3) πενζθαιαάκεζ πθδνμθμνίεξ υπςξ: α) ημ επζζηδιμκζηυ, ημ εθθδκζηυ/ά ηαζ ημ αββθζηυ υκμια ημο είδμοξ ημο ρανζμφ, α) ιμνθμθμβζηή ηαζ μζημθμβζηή πενζβναθή ημο είδμοξ, β) ηδ ζοζηδιαηζηή ημο ηαλζκυιδζδ ηαζ εζηυκεξ ηυζμ ηδξ ιμνθμθμβίαξ ημο είδμοξ υζμ ηαζ ηδξ βεςβναθζηήξ ημο ελάπθςζδξ. Απυ ημ ιεκμφ File, ζηδκ επζθμβή Print ιπμνεί κα βίκεζ είηε εηηφπςζδ ημο 394

395 απμηεθέζιαημξ είηε δδιζμονβία ανπείμο ιμνθήξ pdf βζα ηδκ απμεήηεοζδ ημο απμηεθέζιαημξ ζημκ οπμθμβζζηή (επζθέβμκηαξ ηδκ εθανιμβή PdfCreator πμο ζοκμδεφεζ ηδκ εθανιμβή ηαζ έπεζ εβηαηαζηαεεί ζημκ οπμθμβζζηή). Με ηδκ επζθμβή Back μ πνήζηδξ ιπμνεί κα επζζηνέρεζ ζηδκ επζθμβή ηςκ πεδίςκ ηδξ ζοζηδιαηζηήξ (Δζηυκεξ 1) ή ιε ηδκ επζθμβή Exit απυ ημ ιεκμφ File κα ηάκεζ έλμδμ απυ ηδκ εθανιμβή (Δζηυκεξ 1, 2 ηαζ 3) είηε κα επζζηνέρεζ ζηδκ ανπή ή ζε ηάπμζμ απυ ηα εκδζάιεζα ζηάδζα παηχκηαξ ημ ιζηνυ αεθάηζ ημ μπμίμ ανίζηεηαζ πάκς απυ ημ Help ηαζ κα επζθέλεζ υπμζα επζθμβή επζεοιεί (Δζηυκα 3). 4. πδήηεζε Ο πθδεοζιυξ ηςκ ρανζχκ ζε ιζα πενζμπή οθίζηαηαζ ζοκεπείξ αθθαβέξ ηαεχξ ιε ηδκ πάνμδμ ημο πνυκμο μνζζιέκα είδδ ελαθακίγμκηαζ (θυβς αθθαβήξ ημο πενζαάθθμκημξ ηαζ ακενςπμβεκείξ επζδνάζεζξ), εκχ ζοκήεςξ ειθακίγμκηαζ κέα λεκζηά (ηνμπζηά) είδδ ιε απμηέθεζια ηδκ αθθαβή ηδξ ζφκεεζδξ ηςκ ζπεομπθδεοζιχκ. Παναηδνείηαζ ςξ απμηέθεζια εκίζποζδ ηςκ ηνμθζηχκ ακηαβςκζζιχκ υπμο ηα κεμεζζενπυιεκα είδδ αζημφκ ζδιακηζηή πίεζδ ζημοξ οπάνπμκηεξ πθδεοζιμφξ θυβς ηαζ ηδξ έθθεζρδξ εδνεοηχκ βζα ηα κεμεζζενπυιεκα είδδ. ζμκ αθμνά ηδ ζφκεεζδ ηςκ εζδχκ ηςκ ρανζχκ ζηα Δθθδκζηά κενά, δ πνμζεήηδ κέςκ εζδχκ είκαζ ζοκεπήξ ηαζ ιε αολδηζηή ηάζδ ηα ηεθεοηαία πνυκζα. διακηζηυ νυθμ ζε αοηυ ημ βεβμκυξ παίλεζ δ βεςβναθζηή εέζδ ηδξ πχναξ ιαξ ηαεχξ βζα ημκ πνυζθαημ ειπθμοηζζιυ ηδξ Δθθδκζηήξ ζπεομπακίδαξ εοεφκεηαζ δ επζηοπία ηςκ Λεζζερζακχκ ιεηακαζηχκ ζημκ απμζηζζιυ ηδξ Ακαημθζηήξ Μεζμβείμο ηαεχξ ηαζ δ αφλδζδ ηδξ εενιμηναζίαξ ηςκ Δθθδκζηχκ Θαθαζζχκ ηαηά ηδ δζάνηεζα ηςκ ηεθεοηαίςκ εηχκ πμο μδήβδζε ζηδκ πνμξ ηα αυνεζα ιεηακάζηεοζδ ηςκ πζμ εενιυθζθςκ εζδχκ (Papakonstantinou 2014). Σα ηεκά ημο Γζαναθηάν είκαζ επίζδξ ζδιακηζηά βζα ηδκ ελάπθςζδ εζδχκ πμο πνμένπεηαζ απυ ημκ Αηθακηζηυ ζηζξ Δθθδκζηέξ εάθαζζεξ. Σέθμξ δ ακάπηολδ ηδξ πμκημπυνμο καοζζπθμΐαξ ηαζ δ θεζημονβία δζαιεηαημιζζηζηχκ ηέκηνςκ ζηα ιεβάθα θζιάκζα ηδξ Δθθάδαξ εκίζποζε ηδ ιεηαθμνά κέςκ εζδχκ ιε ημ εηθουιεκμ ένια απυ ηα πθμία. Με ηδ ζοκεπή αθθαβή ζηδκ ζφκεεζδ ηςκ εζδχκ ηςκ ζπεφςκ ζε ιζα βεςβναθζηή πενζμπή, είκαζ ζδιακηζηή δ δοκαηυηδηα ηδξ ζοκεπμφξ εκδιένςζδξ ηςκ ηαηαθυβςκ ηςκ ζπεφςκ. Με ηδκ πανμφζα εθανιμβή πμο δδιζμονβήεδηε ζημ Αθελάκδνεζμ ΣΔΗ Θεζζαθμκίηδξ, ζοκεπίγεηαζ δ ακάπηολδ ημπζηχκ εθανιμβχκ (πςνίξ κα απαζηείηαζ δ πνήζδ ημο δζαδζηηφμο) βζα ηδκ ζπεομθμβζηή ένεοκα ηαζ ηδκ δζάποζδ ηδξ πθδνμθμνίαξ βζα ηα ράνζα. Πνυηεζηαζ βζα εθανιμβή πμο δίκεζ ζημ πνήζηδ ηδ δοκαηυηδηα παναιεηνμπμίδζδξ ηδξ ημπζηήξ αάζδξ δεδμιέκςκ (πνμζεήηδξ, δζαβναθήξ, αθθαβή δεδμιέκςκ) επζθέβμκηαζ μ ίδζμξ ηζξ πδβέξ πμο εα ζοιαμοθεοηεί βζα ηδκ δζαιυνθςζδ ηδξ αάζδξ ηδξ εθανιμβήξ. ηδκ πανμφζα εθανιμβή δ αάζδ πενζθαιαάκεζ έκακ ηαηάθμβμ ιε ηα ράνζα ηδξ Δθθάδαξ, ιε ηδ ζοζηδιαηζηή ημοξ ηαζ υθεξ ηζξ δζαεέζζιεξ πθδνμθμνίεξ βζα ημ ηάεε είδμξ υπμο μ πνήζηδξ ιπμνεί κα εηηοπχζεζ ημ απμηέθεζια ή κα ημ απμεδηεφζεζ ημπζηά. Ζ εθανιμβή δζαηίεεηαζ δςνεάκ ηαζ είκαζ εφημθδ ζημ πεζνζζιυ απυ ηάεε πνήζηδ, απυ ημκ ελεζδζηεοιέκμ επζζηήιμκα (ζπεομθυβμ, αζμθυβμ), ημκ θμζηδηή ηαζ ημκ θοζζμδίθδ ιέπνζ ημκ δφηδ, ημκ ζπεοέιπμνμ, ημκ επαββεθιαηία ή εναζζηέπκδ αθζέα ηαζ ημκ απθυ θάηνδ ηςκ ρανζχκ. ε ηάεε ηαζκμφνβζα έηδμζδ ηδξ εθανιμβήξ πμο εα δζαηίεεηαζ, εα εκδιενχκεηαζ μ ηαηάθμβμξ ηςκ ρανζχκ (πζεακέξ αθθαβέξ ζηδκ επζζηδιμκζηή μκμιαζία ή ηδκ ζοζηδιαηζηή ηςκ ρανζχκ, ειθάκζζδ κέςκ εζδχκ) αημθμοεχκηαξ ηζξ κευηενεξ επζζηδιμκζηέξ ελεθίλεζξ. Πανάθθδθα, ζε ιεθθμκηζηέξ ακαααειίζεζξ ηδξ εθανιμβήξ εα βίκεζ ειπθμοηζζιυξ ηςκ πθδνμθμνζχκ ηδξ αάζδξ είηε εζδζηά βζα ημ ηάεε είδμξ ρανζμφ (π.π. ειθάκζζδ ζοκςκφιςκ, ηνμθζηά επίπεδα, εάκ πενζθαιαάκεηαζ ζημ Κυηηζκμ Βζαθίμ ηςκ Απεζθμφιεκςκ Εχςκ ηδξ Δθθάδαξ) είηε βεκζηά βζα ηδκ ηάεε ζοζηδιαηζηή μιάδα (π.π. Τπενηθάζδ, Κθάζδ, Σάλδ). Δπραξηζηίεο H πανμφζα ένεοκα ζοβπνδιαημδμηήεδηε απυ ηδκ Δονςπασηή Έκςζδ (Δονςπασηυ Κμζκςκζηυ Σαιείμ - ΔΚΣ) ηαζ απυ εεκζημφξ πυνμοξ ιέζς ημο Δπζπεζνδζζαημφ Πνμβνάιιαημξ «Δηπαίδεοζδ ηαζ Γζα Βίμο Μάεδζδ» ημο Δεκζημφ ηναηδβζημφ Πθαζζίμο Ακαθμνάξ (ΔΠΑ) Δνεοκδηζηυ Υνδιαημδμημφιεκμ Ένβμ: ΑΡΥΗΜΖΓΖ ΗΗΗ. Δπέκδοζδ ζηδκ ημζκςκία ηδξ βκχζδξ ιέζς ημο Δονςπασημφ Κμζκςκζημφ Σαιείμο. 395

396 Βηβιηνγξαθία Eschmeyer, W.N. (2014). Catalog of fishes: genera, species, references. Electronic version. (Πνυζααζδ: ). Froese R., Pauly D. (2014). FishBase. World Wide Web electronic publication. (Πνυζααζδ: ). ITIS (2014). Integrated Taxonomic Information System on-line database. (Πνυζααζδ: ). IUCN (2014). The IUCN Red List of Threatened Species. Version (Πνυζααζδ: ). Καζπίνδξ Π. (2000) Σα ράνζα ηδξ Δθθάδαξ (Κθείδεξ πνμζδζμνζζιμφ). ΣΤΠΟffset Κ. Μακμφδδ-ηακίδδ. Πάηνα Kostoglou V., Minos G., Tolis E. (2013). Development of an innovative information system: A fish identification e-key with update capabilities. Information Systems and e-business Management 11(2), Kottelat M., Freyhof J. (2007). Handbook of European Freshwater Fishes. Kottelat, Cornol and Freyhof, Berlin, pp. xiv Λεβάηζξ Α., Μαναβημφ, Π. (2009). Σμ Κυηηζκμ Βζαθίμ ηςκ Απεζθμφιεκςκ Εχςκ ηδξ Δθθάδαξ. Δθθδκζηή Εςμθμβζηή Δηαζνεία, Αεήκα, 528 ζεθ. Marine Species Identification Portal (2014). Electronic version. (Πνυζααζδ: ). Minos G., Kostoglou V., Tolis E. (2013). An innovative decision making e-key application for the identification of fish species. In: 'Optimization Theory, Decision Making, and Operational Research Applications, Migdalas A., Sifaleras A., Georgiadis C.K., Papathanasiou J., Stiakakis E. (eds.). Springer Proceedings in Mathematics & Statistics 31, p Μίκμξ Γ. (2011). διεζχζεζξ Μαεήιαημξ Βζμθμβία & οζηδιαηζηή Ηπεφςκ. Σεφπμξ Γεφηενμ. Αθελάκδνεζμ Σ.Δ.Η. Θεζζαθμκίηδξ, Πανάνηδια Ν. Μμοδακζχκ, Σιήια Σεπκμθμβίαξ Αθζείαξ & Τδαημηαθθζενβεζχκ. 209 ζεθ. Μίκμξ Γ., Γήιμο Η., Κχζημβθμο Β. (2013). Ακάπηολδ εθανιμβήξ βζα ηδκ ακαγήηδζδ ηδξ ζοζηδιαηζηήξ ηαλζκυιδζδξ ηςκ ζπεφςκ ιε πνήζδ βναιιςημφ ηχδζηα. Πναηηζηά Πακεθθδκίμο οκεδνίμο Ηπεομθυβςκ 15, pp Papaconstantinou C. (2014). Fauna Graeciae. An updated checklist of the fishes in the Hellenic Seas, Monographs on Marine Sciences, 7, Athens 2014, HCMR, pp Psomadakis P.N., Giustino S., Vacchi M. (2012). Mediterranean fish biodiversity: an updated inventory with focus on the Ligurian and Tyrrhenian seas. Zootaxa, 3263, WoRMS Editorial Board (2014). World Register of Marine Species. Available from at VLIZ. Accessed 2 September

397 THEMATIC FIELD: FISHERIES TECHNOLOGY 397

398 SOME CHARACTERISTICS OF BOGUE, Boops boops (LINNAEUS, 1758) FROM BOKA KOTORSKA BAY, SOUTH ADRIATIC SEA Marković O. 1*, Djurović M., Pešić A., Ikica Z., Joksimović A. 1 Laboratory of Ichthyology and Marine Fishery, Institute of Marine Biology, University of Montenegro, P.O. Box 69, Kotor, Montenegro ABSTRACT The bogue, Boops boops (Linnaeus, 1758) is one of the commercially important species of the small-scale fishery in Montenegrin waters. A total of 283 specimens of bogue were collected by gill net and trammel net fishing between May 2013 and April 2014 in Boka Kotorska Bay (south Adriatic Sea). Total length ranged from 12.2 to 30.3 cm, while weight varied between and g. Female:male ratio was 2.6. A negative allometric growth was recorded for the all sampled specimen as well as for the both sexes. The highest gonadosomatic index value was in winter when Fulton's condition factor showed minimum value. Key words: Boops boops, small-scale fishery, Boka Kotorska Bay, South Adriatic Sea *Corresponding author: Olivera Marković ( omarkovic@ac.me) 1. Introduction One of the semi-pelagic species caught in Montenegrin territorial waters by vessels under 12 metres is bogue, Boops boops. During the sampling months, it was noted that bogue was mainly caught by gill and trammel nets. Gillnets are the most common type of fishing gear used in small scale fisheries, followed closely by trammel nets. Out of the 70 vessels registered, 71% operate in Boka Kotorska Bay (ports of Herceg Novi, Zelenika, Kotor and Tivat), the area where small scale fisheries, particularly those involving beach seines, have been present for centuries, and are part of the cultural identity of the people from the region. Around 61%, are vessels with length overall below 6 m, and the rest (39%) are in the 6 12 m segment (Ikica et al., 2013). Previous studies showed that significant quantities of bogue were caught by trawlers (Kasalica et al., 2011) and the few existing references concerning the species are from trawl fishery. The objective of this study was to gather some information of the length-weight relationship, length frequency distribution, sex ratio, spawning period and condition of bogue caught by the small-scale fishery in Boka Kotorska Bay. 2. Material and methods A total of 283 B. boops specimens (179 females; 68 males; 36 undetermined) were collected from monthly commercial catches using gill nets and trammel nets in the Boka Kotorska Bay, southern Adriatic Sea from May 2013 to April Sampling was conducted in the framework of the MORM-MONT national project (Monitoring of small-scale coastal fisheries and composition of fish fry with the aim of conservation and 398

399 management of marine fishery resources). Collected fish were preserved with ice in a cooler box and immediately transported to the laboratory. Fish total length and body weight were measured to the nearest 0.1 cm and nearest 0.01 g, respectively. The general power equation (W = a*l b ) was applied to estimate the lengthweight relationship, where a and b are constants whose values were estimated by the least square method. The significant difference of b values from 3, which represent isometric growth, was tested with the Student's t-test. Fulton s condition factor (K=100W/TL 3 ) (Fulton, 1904) was calculated for each specimen and for each season (autumn, winter, spring and summer). Sex was assigned macroscopically. Gonads of all specimens were dissected and weighed to the nearest 0.01 g to calculate the GSI (GSI = weight of gonads/weight of fish x 100). This index was calculated for each of the analyzed specimen and, finally, a mean seasonal index was estimated. Correlation between GSI and Fulton's condition factor was examined using the Pearson's r coefficient. The sex ratio (female:male) was calculated and significant differences from the expected ratio (1:1) were tested by means of π 2 test. Maturity stages were recorded according to the MEDITS protocol: specimens were considered adult when classified as: 2b (recovering), 2c (maturing), 3 (mature/spawner), 4a (spent) and 4b (resting), while immature/juvenile ones were classified as 1 (immature virgin) and 2a (virgin developing) (ICES, 2008). 3. Results and Discussion Of the 283 collected specimens, 24% were males, 63.25% were females and 12.75% undetermined. Length frequency data for all collected specimen is presented in Figure 1. Total length of the sampled fish ranged from 12.2 to 30.3 cm TL with the mean length of cm TL. The body weight ranged between g and g. The mean observed length of the commercial catch of B. boops (17.35cm) was higher than that the value obtained in (13.95 cm: Marković et al., 2014) and almost the same with the value obtained in (17.10 cm; Kasalica et al, 2011). The lower value of the mean length in 2007/2008 could be explained by disappearance of larger fish from the catch and different fishing area because that catch was caught in the Montenegrin territorial waters and on continental shelf and significant quantities were caught by trawlers. The LFD of the whole sample (pooled data) shows that the majority of catches consisted of individuals ranging in length from 16.0 to 20.0 cm TL. The total length of females and males ranged from 12.2 to 30.3 cm (17.48 cm ± 2.91), and from 12.6 to 21.2 cm (17.61 ± 1.43), respectively. Females were more frequent at bigger size classes than males which is similar to what Mozara (2013) reports for the bogue in the southeastern Adriatic Sea. Gordo (1992) observed that the relative percentages of females increase with length class and he concluded that the bogue might be considered a rudimentary hermaphrodite species in which the majority of males develop from bisexual gonads in the juvenile stage (primary males) while a small proportion goes through sexual inversion (secondary males). Massaro (2012) reported the opposite situation, the predominance of females at the smaller sizes and the high number of males at larger sizes. So, we can conclude that variations of the sex ratio at different sizes are related to unequal rates of growth and mortality. The overall sex ratio during the study period was in favor of females (F/M=2.6). This ratio was significantly different from the expected value of 1:1 (ρ 2 =49.88, P < 0.01). High ratio of females in the catch may be caused by several factors related to the physiology and the ethology of the species, such as the age, a tendency for slower growth or a higher mortality rates in males (Desbrosses, 1933) as well as different catchability between two sexes. 399

400 Number HydroMedit 2014, November 13-15, Volos, Greece Total length (cm) Females Males Undetermined Figure 1. Length frequency distribution for Boops boops females, males and undetermined from the Boka Kotorska Bay, South Adriatic Sea The length-weight relationships of bogue was W=0.0338*L for females, W=0.0114*L for males and W=0.0218*L for the total sampled population (Figure 2). The b values were within the limits of reported by Froese (2006) and showed significant differences from 3. All relationships were statistically highly significant (r 2 > 0.85, P < 0.001). The length-weight relationship of B. boops shows a negative allometric growth which is not in agreement with various studies which indicated positive allometric growth or isometric growth (Petrakis & Stergiou, 1995; Özaydin & Taskavak, 2005, Massaro, 2012). Similar growth pattern was observed in Croatian waters (central and southeastern Adriatic) (Dulĉić & Glamuzina, 2006; Mozara, 2013) and in Egyptian Mediterranean waters off Alexandria (El-Okda, 2008). This variation in the b exponents for the same species could be attributed to differences in sampling, sample size or length ranges (Šantić et al., 2005). 400

401 GSI Weight (g) HydroMedit 2014, November 13-15, Volos, Greece Males y = x R 2 = Females y = x R 2 = Females Males Total length (cm) Figure 2. Relationship between total length (TL) and body weight (W) in Boops boops (sexes separated) The gonadosomatic index was used to determine the reproductive period and according to Tsikliras et al., (2013) it remains the best predictor of spawning period (i.e., onset and duration of spawning). The GSI reached maximum values in winter period and minimum in summer and autumn (Figure 3). Previous study on reproductive biology of bogue also observed that spawning activity occurred in winter season in Montenegrin waters (max GSI values for both sexes were recorded in February). (Kasalica et al., 2011). Both indices followed the same pattern. This time period is in line with reports in the literature on the maturity cycle of bogue in eastern Mediterranean (Vidalis, 1950; Hassan, 1990; Mozara, 2013) and eastern Atlantic (Gordo, 1995; Massaro, 2012). Alegria-Hernández (1990) found that the almost the entire population of bogue is spent in June from the mid-adriatic Dalmatian channels which is in agreement with our findings of post-spawning specimen in the early summer. The greatest number of specimen in stage 2c and stage 3 was in winter period as Massaro (2012) found in central-east Atlantic SPRING SUMMER AUTUMN WINTER Season Females Males Figure 3. Seasonal variation of mean GSI index by sex of bogue, B. boops 401

402 GSI Fulton's condition factor HydroMedit 2014, November 13-15, Volos, Greece Fulton's condition factor ranged from to Monthly changes of Fulton's condition factor showed a seasonal cycle with a peak in spring and minimum value in winter when the spawning begin. This factor and gonadosomatic index showed almost the same pattern, except in winter where they showed high negative correlation (r = ) (Figure 4). Mozara (2013) also found this negative correlation for bogue in southeastern Adriatic. Fulton's condition factor varied between season, with the highest value in spring probably caused by an inflow of nutrition and food as the sea temperatures increased. This high factor value could probably be attributed to ndividual recruits in spring using energy from food for both gonad development and muscle development. The condition factor normally decreases at the start of the spawning period due to very high metabolic rates GSI Fulton SPRING SUMMER AUTUMN WINTER Season Figure 4. Fulton's condition factor and gonadosomatic index in bogue samples of the Boka Kotorska Bay (south Adriatic Sea), during May 2013-April 2014 In conclusion, this study provides the some useful information which are important data for the fisheries management. References Alegria-Hernández, V. (1990). Some aspects of reproductive biology of bogue (Boops boops L., Pisces Sparidae) from the Mid-Adriatic channels. Acta Adriatica., 31 (1/2): Desbrosses, P. (1933). Contribution a la biologie du rouget-barbet en Antlantique Nord (Contribution to the biology of red mullet in the North Atlantic). Revue des Travaux de l'office des Peches Maritimes, 6 (3): Dulĉić, J., Glamuzina, B. (2006). Length weight relationships for selected fish species from three eastern Adriatic estuarine systems (Croatia). Journal of Applied Ichthyology, 22 (4), El-Okda, N. I. (2008). Age and growth of Boops boops (L.) from Egyptian Mediterranean waters off Alexandria. Egyptian Journal of Aquatic Biology & Fisheries. Vol 12, No 1: Froese, R. (2006). Cube law, condition factor and weight-length relationships: History, meta-analysis and recommendations. Journal of Applied Ichthyology, 22,

403 Fulton, T. W. (1904). The rate of growth of fishes. Twenty-second Annual Report, Part III. Fisheries Board of Scotland, Edinburgh, pp Gordo, L. S. (1992). Contribuição para o conhecimento da biologia e do estado de exploração do stock de boga (Boops boops Linné. 1758) da costa portuguesa. Faculdade de Ciências, Tese de Doutoramento, Lisboa, pp Gordo, L. S. (1995). On the sexual maturity of the bogue (Boops boops) (Teleostei, Sparidae) from the Portuguese coast. Scientia Marina, 59 (3-4): Hassan, M. W. A. (1990). Comparative biological studies between two species of family Sparidae, Boops boops and Boops salpa in Egyptian Mediterranean waters. M.Sc. Thesis, Faculty of Science, Alexandria University, pp ICES (2008). Report of Workshop on Maturity Ogive Estimation for Stock Assessment (WKMOG). 3 June 2008, Lisbon, Portugal, pp. 68. Ikica Z., Djurović M., Joksimović A., Mandić M., Marković O., Pešić A. (2012). Small-scale fisheries in Montenegro. In: AdriaMed Report of the AdriaMed Technical meeting on Adriatic Sea Smallscale Fisheries (Split, Croatia, 13th-14th November 2012). AdriaMed Technical Documents, 33: Kasalica, O., Regner, S., Djurović, M. (2011). Some aspects of the biology of the bogue, Boops boops (Linnaeus, 1758) in Montenegrin waters (south Adriatic Sea). Studia Marina, 25 (1): Livadas, R. J. (1989). The growth and maturity of bogue (Boops boops L.), family Sparidae, in waters of Cyprus. F.A.O. Fisheries Report (412): Marković, O., Ikica, Z., Pešić, A., Joksimović, A., Djurović, M., Mandić, M. (2014). Length-weight relationship and condition factors of the bogue, Boops boops (Linnaeus, 1758) in the south Adriatic Sea (Montenegro). Natura Montenegrina 12 (3), in press. Massaro, A. (2012). Reproductive biology of bogue Boops boops (Linnaeus, 1758) off Gran Canaria (Canary Islands): a preliminary study. Phd in Sustainable Management of Fisheries Resources. Faculty of Marine Science, Universidad de Las Palmas de Gran Canaria, pp. 33. Mozara, R. (2013). Histological aspect of the reproductive cycle of bogue, Boops boops, (Linnaeus, 1758). Master in Mariculture. Department of Aquaculture, University of Dubrovnik, pp. 35. Özaydin, O, Taskavak, E. (2006) Length-weight relationship for 47 fish species from Izmir Bay (eastern Aegean Sea, Turkey). Acta Adriatica 47 (2): Petrakis, G., Stergiou, K. I. (1995). Weight-length relationships for 33 fish species in Greek waters. Fisheries Research, 21: Šantić, M., Pallaoro, A., Jardas, I. (2006). Co-variation of gonadosomatic index and parameters of length-weight relationships of Mediterranean horse mackerel, Trachurus mediterraneus (Steindachner, 1868), in the eastern Adriatic Sea. Journal of Applied Ichthyology, 22 (3): Tsikliras, A. C., Stergiou, K. I., Froese, R. (2013). Editorial note on reproductive biology of fishes. Acta Ichthyologica et Piscatoria., 43 (1): 1-5. Vidalis, E. (1950). Contribution to the study of the biology of the bogue (Boops boops Lin.) in Greek waters. Prak. Hell. Hidrobiol. Inst., 4 (1):

404 DIFFERENCE BETWEEN BAYESIAN AND CLASSICAL ESTIMATION OF GROWTH PARAMETERS OF Mullus barbatus barbatus (Linnaeus, 1758) Gündoğdu S.*, Baylan M. Department of Basic Sciences, Faculty of Fisheries, Cukurova University, Balcalı, Sarıçam, 01330, Adana, Turkey Abstract The aim of this study was to compare Bayesian and Classical estimation for describing the growth curves of red mullet (Mullus barbatus barbatus Linnaeus, 1758). Classical nonlinear regression method and Bayesian estimation method were used to obtain the estimation of the components of the von Bertalanffy growth model. The estimated parameters showed that Bayesian estimation is better than Classical nonlinear regression in estimating growth parameters and reducing variation of growth model parameters. Key words: Mullus barbatus barbatus, Bayes theory, Growth, von Bertalanffy *Corresponding author: Sedat Gündoğdu ( sgundogdu@cu.edu.tr) 1. Introduction Generally, the von Bertalanffy growth equation (VBGE) is fit to length-age data using classical nonlinear methods such as nonlinear regression. Classical nonlinear regression assumes that there are enough measurements to say something meaningful. This assumption somehow affects the assumptions of the VBGE. In the Bayesian approach, the data are supplemented with additional information in the form of a prior probability distribution. The prior information comes from past experience or prior belief about parameters. The prior belief is combined with the data's likelihood function according to Bayes theorem to compute the posterior (Congdon 2003; Siegfried & Sanso 2006; Link & Barker 2010; Box & Tiao 2011; Akar & Gundogdu 2014). For this reason Bayesian inference provide a quantitative concept and obvious language in so as to analyze and express growth procedures. Logically, Bayesian inference is the clearest way of analyzing and interpreting growth models in light of data. In this study we used Bayesian approach and classical approach to estimate VBGE parameters. Estimates of the von Bertalanffy growth parameters are compared with estimates of the classical method. By this way, we tried to explain biological plausibility of parameters estimated by both methods. 2. Material and Methods Length and age data of red mullet were collected between 2012 and 2013 from Iskenderun Bay of the Northeast Mediterranean Sea (Figure 1). The materials were collected by seasonally sampling using commercial bottom trawl. The fork length (FL) was measured to the nearest 1 mm. The sagittal otoliths were examined under stereo microscope for age determination. Figure 1. Study area. 404

405 The form of VBGE described by many researchers is the following; where and K are the VBGE parameters, and the are assumed to be normally distributed error. The growth parameters and K were estimated using the Classical Least Squares Method as recommended by Sparre & Venema (1998). This produced least-squares estimates of the three von Bertalanffy growth parameters. Bayesian approach fits the VBGE to the length at age data using Markov Chain Monte Carlo (MCMC) methods (Hastings 1970; Gelman et al. 2004). These methods has four steps; i) finding likelihood of the data, ii) defining priors for all parameters, iii) defining conditional probabilities for all parameters, and iv) using the Bayesian method to estimate the posterior distribution for parameters (Gelman et al. 2004; Siegfried & Sanso 2006). Thus, our likelihood is as following: We used informative priors for FishBase (Froese & Pauly 2012): and K based on published estimates of the same parameters in the We used uninformative priors for, giving the full power of estimation to the data: OpenBUGS (Spiegelhalter et al. 2007; was used to fit the model. The estimates of parameters were evaluated based on samples, from Markov chain Monte Carlo (MCMC) simulation of the joint posterior distribution. We used a burn-in period of chains and generated posteriors for the parameters of the VBGE with the remaining chains. 3. Results A total of 422 individuals were sampled, ranging in size from 6.2 to 27.5 cm FL. Overall mean FL was calculated as cm. Length-frequency distribution, minimum, maximum length, standard error, sample size, mean length and its confidence interval values of red mullet for each age class are listed in Table 1. As it can be seen, the age of Red Mullet ranged from I to VI age classes and the most dominant age class was 2 with a value of 43.8% and age class 3 ranks second with a value of 27.9%. Table 1. Length-frequency distribution, minimum, maximum, standard error (SE), 95% confidence interval and mean fork length values for each age class for Red Mullet Age N Mean SE 95% CI for Mean Lower Upper Min Max I II III IV V VI Total The growth parameters calculated by classical nonlinear and by Bayesian nonlinear regression are shown in Table 2. The growth curve estimated by both methods and the observed length fitted to lengths-age are showed in Figure 2. Table 2. Parameter estimations of both methods. Estimated Length at Age I II III IV V VI K von Bertalanffy Growth Parameters Bayesian

406 Classical The estimates of of Bayesian approach were much closer to the observed maximum length than those of the Classical approach. The coefficient of K estimated by both approaches was between 0 and 1. However, the K value of Bayesian approach was higher than K values estimated by the Classical approach and Bayesian value was much closer to zero than Classical value. Correlation between parameters was found as, and using Bayesian approach. Note that they decrease as increases. Figure 2. Bayesian and Classical von Bertalanffy length-at-age growth curves and observed lengths at age for the red mullet. A burn in sample of was initially rejected and the remaining iterations from the chain sequence thinned at a rate of 1 sample in 10 (for removing autocorrelation of MCMC). Autocorrelation of the chain diminished after a lag of about 5. Discussion Since the growth function may vary, the shape of the growth curve may vary between various fish populations or species. Therefore, it is essential to assess the goodness of fit in any comparison among approaches. According to many authors (Pauly 1979; Chen et al. 1992; Sparre & Venema 1998), should be reasonably close to the maximum fish length in observed data, should be smaller or equal to zero and, and might vary between 0 and 1. The results of Bayesian approach showed that value was closer to maximum observed length (27.5 cm) compared to value of the Classical approach and was almost equal to zero (Table 2, Figure 2). The comparison of the Bayesian estimates in this study with growth estimates of the red mullet poulations along the Turkish coast (Table 3) indicate the production of more plausible estimations by the Bayesian approach. Table 3. Growth estimates for red mullet from various studies. (cm) (year -1 ) (year) Author This study (Bayesian) This stuy (Classical) Kınacıgil et al. (2001) Özbilgin et al. (2004) Özvarol et al. (2006) The estimated parameters of VBGE should be related to the biological characteristics of the inspected species (Pauly 1978, Sparre & Venema 1998). As a demersal fish species, the red mullet is expected to have a low K value similarly to what has been reported by various studies along the Turkish coast (mean K value: 0.3, Table 3). The estimated value by the Bayesian approach in this study was closer to 0 value comparing to values reported (Table 3), since the prior knowledge taken into account by the Bayesian approach minimizes 406

407 differences between real values and estimations (Box & Tiao 2011; Lee 2004). Otherwise, the value should equals zero, since fish larvae at hatching (when fish growth begins) they already have their length (Sparre & Venema 1998), Concluding, the non-linear analysis using Bayesian inference can effectivley used to assses growth of the red mullet, M. barbatus. Main conclusion from this study of Red Mullet growth is that suitable statistical methods can be used to assess growth parameters. Our use of nonlinear analysis using Bayesian inference for fish growth has the advantage of biological plausibility. Acknowledgement This study is supported by Cukurova University Scientific Research Found Project No:SUF2012D4. References Akar M., Gundogdu S. (2014). The usage of Bayes Theory in fisheries sciences. Journal of FisheriesSciences.com 8(1), Beverton R.J.H. (1992). Patterns of reproductive strategy parameters in some marine teleost fishes. Journal of Fish Biology 41, Beverton R.J.H., Holt S.J. (1957). A.review of methods for estimating mortality rates in exploited fish populations, with special reference to sources of bias in catch sampling. Rapp. P.-v. Reun. CIEM, 140(1), Box G.E., Tiao G.C. (2011). Bayesian inference in statistical analysis (Vol. 40). John Wiley & Sons. Toronto. pp.588. Chen Y., Jackson D.A., Harvey H.H. (1992). A comparison of von Bertalanffy and polynomial functions in modelling fish growth data. Canadian Journal of Fisheries and Aquatic Science 49, Congdon P. (2003). Applied bayesian modelling. Wiley Series in Probabilty and Statistics, Jon Wiley and Sons. London. pp Froese R., Pauly D. (2012). FishBase. World Wide Web electronic publication, version 12/2012: Available at: Gelman A., Carlin J.B., Stern H.S., Rubin D.B. (2004). Bayesian data analysis. Chapman and Hall. Boca Raton. pp Hastings W. (1970). Monte Carlo sampling methods using Markov chains and their applications. Biometrika 57, Helser T.E., Lai H.L. (2004). A Bayesian hierarchical meta-analysis of fish growth: with an example for North American largemouth bass (Micropterus salmoides) Ecological Modelling 178(3), Helser T.E., Stewart I.J., Lai H.L. (2007). A Bayesian hierarchical meta-analysis of growth for the genus Sebastes in the eastern Pacific Ocean. Canadian Journal of Fisheries and Aquatic Science 64(3), Kinacigil H.T., İlkyaz A.T., Akyol O., Metin G., Çira E., Ayaz A. (2001). Growth parameters of red mullet (Mullus barbatus L., 1758) and seasonal cod-end selectivity of traditional bottom trawl nets in izmir Bay (Aegean Sea). Acta Adriatica 42 (1), Lee P.M. (2004). Bayesian Statistics an Introduction. Arnold Publication. London. pp Link W.A., Barker R.J. (2010). Bayesian inference with ecological applications. Elsevier Academical Publication. California. pp Özbilgin H., Tosunoglu Z., Bilecenoğlu M., Tokaç A. (2004). Population parameters of Mullus barbatus in Izmir bay (Aegean sea), using length frequency analysis. Journal of Applied Ichthyology 20, Özvarol Z.A.B., Balcı B.A., Özbaş M., Gökoğlu M., Gülyavuz H., Taşlı A., Pehlivan M., Kaya Y. (2006). An investigation on the growth properties of red mullet (Mullus barbatus L., 1758) in Antalya Bay. E.U. Journal of Fisheries & Aquatic Sciences 23, Ricker W.E. (1975). Computation an interpretation of biological statistics of fish population. Journal of Fisheries Research Board of Cananada 191, 382. Pauly D. (1979). A preliminary computation of fish length growth parameters. Berichte des Institut für Meereskunde an der Universitat Kiel. No. 55, 200. Siegfried K.I., Sansó B. (2006). Two Bayesian methods for estimating parameters of the von Bertalanffy growth equation. Environmental Biology of Fishes 77, Sparre P., Venema S.C. (1998). Introduction to tropical fish stock assessment. Part 1. Manual. FAO. Rome. Spiegelhalter D., Thomas A., Best N., Lunn D. (2007). OpenBUGS user manual, version MRC Biostatistics Unit. Cambridge. 407

408 DIET COMPOSITION OF GOLDEN GREY MULLET, Liza aurata (Risso, 1810) IN THE MAZANDARAN COSTLINE, CASPIAN SEA Zandavar H. 1, Norouzi M.* 1, Faghani, H. 1 1 Department of Marine Biology and Fisheries Sciences, Tonekabon Branch, Islamic Azad University, Tonekabon, Iran. Abstract Feeding activity and diet composition of Liza aurata in mazandaran costline, south Caspian Sea was studied between November 2013 and March The maximum and minimum total length and weight of fish in autumn were 52.5 cm and 40 cm; 990 and 384 g respectively. The maximum and minimum total length and weight of fish in spring were 61 cm and 42.2 cm; 1844 g and 472 g respectively. Feeding intensity increased as the fish got bigger and was higher in the autumn season (VI =20±23.09) than in spring season (VI = 5±10.00). Eight major items constituted the diet of L. aurata. These included Crustacean (Gammarus), Bivalvia (Mytilus and Cardium),Gastropoda (Hydrobia), Polychaeta (Nereis), shironomidea larva, Ulvales (Entermorpha), Ctenophora (Mnemiopsis leidyi) as dietaries. Keywords: Diet composition, Feeding intensity, Liza aurata, Caspian Sea. *Corresponding author: Mehrnoush Norouzi (mnoroozi@toniau.ac.ir) Introduction Golden grey mullet Liza aurata (Risso, 1810) is a typical marine schooling fish. It was introduced into the Caspian from the Black Sea (targeted acclimatization) and spread widely within the Caspian Sea, except for the estuarine sea areas. Golden grey mullet is found in the southern part of the sea throughout the year; in the Middle Caspian it appears in spring and migrates back to the south in autumn. During migration, it feeds intensively, preferring shallow coastal areas (Velikova et al., 2012). The Golden gray mullet, as the Mugilidae in general, is a euryhaline species. This characteristic allows to this species to migrate annually from the sea to lagoons, estuaries or lakes (Lafaille et al., 2000; Gautier & Hussenot, 2005; Cardona, 2006). And sensitive to a decrease in water temperature. Age of maturity 3-4 years old. It feeds on detritus, silt, and occasional mollusks. The species winters in the southern part of the Caspian. The fish is concentrated mostly in the sectors with rich marine vegetation and in areas with muddy bottoms. There are many factors that potentially influence both the amount and type of food found in the digestive tracts of fish, including the diel cycle, seasonal change, size of fish, food availability, and differential digestion rates (Bowen and Allanson, 1982). That juvenile mullet are initially carnivorous and planktonic feeders and the adults detritovores has also been noted by Odum (1970). It has been suggested that ingested sand acts as a grinding paste for the degradation of plant cell walls in the pyloric portion of the stomach (Thomson, 1966). The suitable environment has enabled the population to increase in number rapidly, Nowadays they provide one of the principal fishing resources, especially in the southern part of the Caspian Sea. The aim of present study was to determine any difference diet of grey mullet in the middle of the South Caspian Sea and to observe difference diet of L. aurata in this region. 2. Materials and Methods A total of 40 samples of adult fish were collected during the autumn and spring seasons ( ) from four commercial catches in the middle of the South Caspian Sea, Tonekabon, Nowshahr, Fereydunkenar and Behshahr, Mazandaran Province, Iran (Figure. 1). Fish were preserved in ice immediately after capture. The stomach contents were obtained after killing the fish. Stomachs were removed and the stomach contents were weighed and were preserved in 4% formaldehyde immediately. Prey items were identified to as low a taxonomic level as possible. 408

409 Figure 1. Map showing sampling locations of Golden grey mullet: 1-Tonekabon, 2-Nowshahr, 3- Fereydunkenar and 4-Behshahr coastline. In the laboratory, the total and standard length was measured to the nearest 0.1 cm using a measuring board. Fish were weight to the nearest 0.1 g. The intestine length was measured to the nearest 0.1 cm. Feeding intensity was determined using the vacuity index. This index is defined as the number of empty stomach divided by total number of stomachs multiplied by 100. Ontogenic, seasonal and sexual variations in feeding intensity based on the vacuity index were examined. The point and frequency of occurrence methods were used to assess the food composition. The fish stomach was removed and dissected. The contents were displayed in a petri dish with a few drops of distilled water and examined microscopically and with unaided eyes. The percentage frequency of occurrence (F) was based on the number of stomachs in which a food item was found, expressed as a percentage of the total number of nonempty stomach (Hynes, 1950). 3. Results Golden grey mullet obtained for this study consisted of 40 specimens in total length ranging from 42.2 cm (Fereydunkenar) to 61 cm (Behshahr) in autumn and from 40 cm (Nowshahr) to 52.5 cm (Behshahr) in spring, and weight of fish ranging from 472 (Fereydunkenar) g to 1844 g (Behshahr) in autumn and from 384 g (Nowshahr) to 990 g (Behshahr) in spring. This result indicates that significant change in the weight occurred with total length of the fish (Figure 2). A total of 40 stomachs were examined of which 5 were empty. The overall vacuity index (VI) of L. aurata was 12.5± Figure 3 shows the vacuity index of Liza aurata. The trophic spectrum of L. aurata shows that its diet was made up of Eight major items, with the dietaries including Crustacean (Gammarus), Bivalvia (Mytilus and Cardium), Gastropoda (Hydrobia), Polychaeta (Nereis), shironomidea larva, Ulvales (Entermorpha), Ctenophora (Mnemiopsis leidyi) were of diet importance (Table 1). Frequency of occurrence (%F) of food items in the diet of L. aurata show in figure 3 and they are different in autumn and spring seasons (Figure. 4). 409

410 Weight (g) HydroMedit 2014, November 13-15, Volos, Greece Total length (cm) Figure 1. Relationship between total weight and total length of L. aurata. Empty Stomach Full Stomach Figure 2. The vacuity index of L. aurata in the Caspian Sea. Table 1. Overall composition variation in the diet of L. aurata in the Caspian Sea. Stomach Contents Station Gammarus Mytilus Cardium Hydrobia Nereis Chironomide Entromorpha M. leidyi Tonekabon Nowshahr Fereydoun kenar Behshahr Total

411 Mnemiopsi s leidyi 27% Gammarus 15% Entromorp ha 2% Nereis 17% Chironomi de larva 3% Hydrobia 1% Cardium 15% Mytilus 20% Figure 3. Frequency of occurrence (%F) of food items in the diet of L. aurata spring autumn Figure 4. Frequency of occurrence (%F) of food items in the diet of L. aurata in autumn and spring seasons. 4. Discussion The importance of detritus as a major food source for estuarine organisms has been widely reported (Fagade and Olaniyan, 1973; Barnes, 1974). Mugilids generally prefer fine particles to coarser ones. The significance of this has been discussed by Odum (1970), Marias (1980) and Brusle (1981). It include amongst other things, the fact that fine particles are richer in absorbed organic matter, bacteria, protozoa and other microorganisms than coarser ones. This promotes growth and brings about an increase in invertebrate productivity (Olojo et al., 2003). On the whole, the trophic flexibility of this species ensures a supply of constant energy which is important for sustenance of its population. The variations in the food habits of the different seasons of L. aurata were possibly determined by abundance and types of food materials available in the habitat. In conclusion, L. aurata is omnivorous, and its wide food spectrum may be attributed to the high productivity of south Caspian Sea. Seasonal fluctuations observed in the volume and composition of food consumed by L. aurata was correlated with the relative abundance of the food material in the environment. Acknowledgments The study was supported by Islamic Azad University, Tonekabon Branch and was performed in Fishery Research Lab. We would like to thank Mr. Bagheri. 411

412 References Bowen S.H., Allanson B.R. (1982). Behavioral and trophic plasticity of juvenile Tilapia mossambica in utilization of the unstable littoral habitat. Environmental Biology of Fishes 7, Lafaille P., Feunteun E., Lefeuvre, J.C. (2000). Composition of fish communities in a European macrodidal salt marsh (the Mont saint-michel Bay, France). Estuarine, Coastal and Shelf Science 51, Gautier D., Hussenot, J. (2005). Mullets of the European Seas. Summary of knowledge about their biological bases and aquaculture techniques. Brest Ifremer 120p. Cardona, L., Habitat selection by grey mullets (Osteichthyes: Mugilidae) in Mediterranean estuaries: the role of salinity. Scientia Marina, 70(3), Odum W.E. (1970). Utilization of the direct grazing and plant detritus food chains by the striped mullet Mugil cephalus. In Marine food chains, edited by J.H. Steele, Edinburgh, Oliver and Boyd pp Thomson J.M. (1966). The grey mullet. Oceanography and Marine Biology. Annual Review 4, Hynes H. B.N. (1950). The food of fresh water sticklebacks (Gasterosteus acutectus and Pygosteus punigitius) with a review of methods used in studies of the food of fish. Journal of Animal Ecology 19, Fagade S. O., Olaniyan, C. I. O. (1973). The food and feeding interrelationship of the fishes in the Lagos Lagoon. Journal of Fish Biology 5, Barnes, R. S. K. (1974). Estuarine Biology. Journal of Fish Biology 49, 77. Marias, J. F. K. (1980). Aspects of food intake, food selection and elementary canal morphology of Mugil cephalus Linnaeus, 1758, Liza tricuspidens (Smith, 1935) and Liza dumerili (Steindachner, 1870). Journal of Experimental Marine Biology and Ecology 44, Brusle J. (1981). Food and feeding in grey mullet. In: O. H. Oren. Aquaculture of grey mullet. International. Biology Program. 26. Cambridge Univ. Press. p Olojo E. A. A., Olurin, K. B., Osikoya, O. J. (2003). Food and Feeding Habits of Synodontis nagrita from Osun River, SW, Nigeria. NAGA, World Fish Center Quarterly. 26(4), Velikova V.N., Shaudanov A.K., Gasimov A., Korshenko A., Abdoli A., Morozov B., Katunin D. N., Mammadov E., Bokova E. B., Emadi H., Annachariyeva J., Isbekov K., Akhundov M., Milchakova, N., Muradov O., Khodorevskaya R., Shahifar R., Shiganova, T., Zarbaliyeva T. S., Mammadli T., Velikova, V., Barale, V., Kim Y. (2012). Review of the environment and bioresources in the Caspian Sea ecosystem CaspEco Report, pp

413 PRELIMINARY STUDY ON THE REPRODUCTIVE BIOLOGY AND LENGTH- WEIGHT RELATIONSHIPS OF Galeus melastomus IN THE EASTERN IONIAN SEA Apostolopoulos G. 1*, Anastasopoulou A. 2, Mytilineou Ch. 2, Smith C. J. 2, Megalofonou P. 1 1 Department of Biology, Section of Zoology- Marine Biology, University of Athens, Panepistimiopolis, Ilisia, 15784, Athens, Greece. 2 Hellenic Centre for Marine Research, Institute of Marine Biological Resources and Inland Waters, 46.7 km Athens- Sounio, Mavro Lithari, PO BOX 712, 19013, Anavissos Attica, Greece. Abstract Aspects on the biology of Galeus melastomus in the Ionian Sea were studied from a total of 257 specimens (124 male and 133 female). Specimens were caught with bottom longlines in depths ranging between m. The length distribution of the examined individuals showed that females attained slightly larger lengths compared to males. Total length (TL) of males and females ranged between mm and mm respectively. Length-weight relationships were found to differ significantly between males and females. Allometric coefficient (b) values for females were higher. Gonadosomatic index (GSI) appeared to increase with maturity stage until spawning, while the hepatosomatic index (HSI) decreased during spawning, indicating that liver may play an important role for vitellogenesis and egg case production. The smallest mature male and female were 393 mm ηαζ 395 mm in TL, respectively; all males and females were mature above 430 mm and 478 mm TL, respectively. Length at first maturity (L 50 ) was estimated at mm for males and mm for females. Egg cases, 1-4 per oviduct, were on average 41.6 mm in length without horns, 17.4 mm wide and weighed 2.33 g. Key words: Galeus melastomus, length-weight relationship, gonadosomatic index, hepatosomatic index, length at first maturity *Corresponding author: Apostolopoulos George ( betterpace@yahoo.gr ) ΠΡΟΚΑΣΑΡΚΣΗΚΖ ΜΔΛΔΣΖ ΣΖ ΒΗΟΛΟΓΗΑ ΑΝΑΠΑΡΑΓΧΓΖ ΚΑΗ ΣΖ ΥΔΖ ΜΖΚΟΤ-ΒΑΡΟΤ ΣΟΤ Galeus melastomus ΣΟ ΗΟΝΗΟ ΠΔΛΑΓΟ Απνζηνιφπνπινο Γ. 1*, Αλαζηαζνπνχινπ Α. 2, Μπηηιελαίνπ Υξ. 2, Smith C. J. 2, Μεγαινθψλνπ Π. 1 1 Σιήια Βζμθμβίαξ, Σμιέαξ Εςμθμβίαξ- Θαθάζζζαξ Βζμθμβίαξ, Δεκζηυ ηαζ Καπμδζζηνζαηυ Πακ/ιζμ Αεδκχκ, Πακεπζζηδιζμφπμθδ Ηθίζζα, 15784, Αεήκα, Δθθάδα. 2 Δθθδκζηυ ηέκηνμ Θαθαζζίςκ Δνεοκχκ, Ηκζη. Θαθάζζζςκ Βζμθμβζηχκ Πυνςκ ηαζ Δζςηενζηχκ Τδάηςκ, 46.7 πθι. Αεδκχκ- μοκίμο, Μαφνμ Λζεάνζ, Σ.Θ. 712, Ακάαοζζμξ Αηηζηήξ, Δθθάδα. 413

414 Πεξίιεςε ημζπεία ηδξ ακαπαναβςβζηήξ αζμθμβίαξ ημο είδμοξ Galeus melastomus ζημ Ηυκζμ Πέθαβμξ ιεθεηήεδηακ ζε ζοκμθζηά 257 άημια (124 ανζεκζηά ηαζ 133 εδθοηά). Σα δείβιαηα ζοθθέπεδηακ ιε παναβάδζ αοεμφ ζε αάεδ πμο ηοιαίκμκηακ απυ 440 έςξ 818 m. Ζ ιεθέηδ ηδξ ηαηά ιήημξ ζφκεεζδξ έδεζλε υηζ ηα εδθοηά ήηακ θίβμ ιεβαθφηενα ζε ζπέζδ ιε ηα ανζεκζηά, ιε ημ μθζηυ ιήημξ ηςκ ανζεκζηχκ κα ηοιαίκεηαζ απυ 247 έςξ 495 mm, εκχ ηςκ εδθοηχκ απυ 203 έςξ 518 mm. Ζ ζπέζδ ιήημοξ-αάνμοξ ανέεδηε κα δζαθένεζ ζηαηζζηζηά ζδιακηζηά ιεηαλφ ηςκ δφμ θφθςκ, ιε ηα εδθοηά κα έπμοκ ιεβαθφηενεξ ηζιέξ αθθμιεηνζημφ ζοκηεθεζηή b. Ο βμκαδμζςιαηζηυξ δείηηδξ (GSI) θάκδηε κα αολάκεηαζ ηαεχξ ςνζιάγμοκ ηα άημια έςξ ηδκ ςμημηία, εκχ μ δπαημζςιαηζηυξ (HSI) κα ιεζχκεηαζ ηαηά ηδκ ςμημηία, βεβμκυξ πμο απμηεθεί έκδεζλδ υηζ ημ ήπαν ζοζπεηίγεηαζ ιε ηδ θεηζεμβέκεζδ ηαζ ηδκ παναβςβή ηαρχκ. Σμ ιζηνυηενμ χνζιμ ανζεκζηυ ηαζ εδθοηυ άημιμ είπακ ιήημξ 393 mm ηαζ 395 mm ακηίζημζπα, εκχ χνζια ήηακ υθα ηα ανζεκζηά ηαζ εδθοηά άημια πάκς απυ ηα 430 mm ηαζ 478 mm ακηίζημζπα. Σμ ιήημξ ηδξ πνχηδξ βεκκδηζηήξ ςνίιακζδξ (L 50 ) ανέεδηε βζα ηα ανζεκζηά 412,2 mm ηαζ βζα ηα εδθοηά 444,2 mm. Οζ ηάρεξ αοβχκ (1-4 ακά ςαβςβυ) είπακ ιέζδ ηζιή ιήημοξ πςνίξ άβηζζηνα 41,6 mm, πθάημοξ 17,4 mm ηαζ αάνμοξ 2,33 g. Λέξειρ κλειδιά: Galeus melastomus, ζρέζε κήθνπο-βάξνπο, γνλαδνζσκαηηθόο δείθηεο, επαηνζσκαηηθόο δείθηεο, κήθνο πξώηεο γελλεηηθήο σξίκαλζεο *οββναθέαξ επζημζκςκίαξ: Απμζημθυπμοθμξ Γζχνβμξ ( betterpace@yahoo.gr ) 1. Δηζαγσγή Ζ δζεεκχξ αολακυιεκδ αθζεοηζηή πίεζδ ηαζ δ ακάβηδ βζα αζχζζιδ αθζεοηζηή πμθζηζηή έπεζ μδδβήζεζ ζηδκ επζηαβή ηδξ ιεθέηδξ ηςκ ζπεομαπμεειάηςκ ηςκ Υμκδνζπεφςκ, μζ πθδεοζιμί ηςκ μπμίςκ είκαζ οπμιεθεηδιέκμζ (Vannuccini 1999), ζδζαίηενα εοαίζεδημζ ζηδκ οπεναθίεοζδ ηαζ ανβμί ζηδκ ακάηαιρή ημοξ (Musick 2005). Σμ Galeus melastomus (Rafinesque, 1810) είκαζ έκαξ ςμηυημξ Υμκδνζπεφξ ηδξ Οζημβέκεζαξ ηςκ Scyliorhinidae πμο ελαπθχκεηαζ ζημκ Ακαημθζηυ Αηθακηζηυ ηαζ ηδ Μεζυβεζμ, παιδθμφ ειπμνζημφ εκδζαθένμκημξ ηαζ ιε ιεβάθδ αθεμκία αθθά ηαζ έκημκδ πανμοζία ζηδκ απμννζπηυιεκδ αθζεία (Costa et al. 2005). Πανμοζζάγεζ εονεία ααεοιεηνζηή ηαηακμιή ( m) αθθά πζμ ζοπκά ζοκακηάηαζ ζηα m (Rey et al. 2005). Μεθέηεξ πμο έπμοκ πναβιαημπμζδεεί βζα ημ Galeus melastomus ζπεηίγμκηαζ ιε ηδκ αθεμκία, ηδ ααεοιεηνζηή ηαηακμιή ηαζ ηδ αζμθμβία ημο (π.π. Ragonese et al. 2009, Tserpes et al. 2013, Anastasopoulou et al. 2013, Costa et al. 2005). Γζαεέζζια ζημζπεία βζα ηδκ ακαπαναβςβή ημο είδμοξ ζηδ Μεζυβεζμ πνμένπμκηαζ απυ ηδ Βυνεζα (Capape et al. 2008), ηδ Νμηζμδοηζηή (Rey et al. 2005) ηαζ ηδκ ηεκηνζηή Μεζυβεζμ (Ragonese et al. 2009, Rinelli et al. 2005, Sion et al. 2004). Ζ πανμφζα ενβαζία επζηεκηνχεδηε ζηδ ιεθέηδ ηδξ ακαπαναβςβήξ ημο G. melastomus ζηδ πενζμπή ημο Ακαημθζημφ Ημκίμο Πεθάβμοξ. 2. Τιηθά θαη Μέζνδνη Σα δείβιαηα ζοθθέπεδηακ ζημ πθαίζζμ ημο πνμβνάιιαημξ Coral Fish ζημ Ηυκζμ πέθαβμξ ημκ Οηηχανζμ ημο 2010 ιε παναβάδζ αοεμφ (αβηίζηνζα Νμ.7 ηαζ Νμ.9) ζε αάεμξ m ιε επαββεθιαηζηυ αθζεοηζηυ ζηάθμξ. οκμθζηά ιεθεηήεδηακ 124 ανζεκζηά ηαζ 133 εδθοηά άημια. Σα δείβιαηα ηαηαρφπεδηακ ηαζ ιεηαθένεδηακ βζα πεναζηένς επελενβαζία ζημ ενβαζηήνζμ. Πναβιαημπμζήεδηακ ιεηνήζεζξ μθζημφ ιήημοξ (TL) ιε αηνίαεζα 1 mm, μθζημφ (RW) ηαζ ηαεανμφ (DW) αάνμοξ ζχιαημξ ιε αηνίαεζα 1 g, αάνμοξ βμκάδςκ ηαζ ήπαημξ ιε αηνίαεζα 0,01 g, ηαεχξ ηαζ ιήημοξ ηαζ πθάημοξ ηαρχκ αοβχκ ιε αηνίαεζα 1 mm ηαζ αάνμοξ ηαρχκ ιε αηνίαεζα 0,01 g. Ζ ζφβηνζζδ ηδξ ηαηά ιήημξ ζφκεεζδξ ανζεκζηχκ ηαζ εδθοηχκ έβζκε ιε ημκ έθεβπμ Kolmogorov- Smirnov. Ζ ζπέζδ ιήημοξ- αάνμοξ ααζίζηδηε ζηδκ ελίζςζδ παθζκδνυιδζδξ ηδξ ιμνθήξ RW = a 414

415 TL b βζα ημ ζφκμθμ ηςκ δεζβιάηςκ ηαζ λεπςνζζηά βζα ανζεκζηά ηαζ εδθοηά άημια. Οζ δζαθμνέξ ιεηαλφ ηςκ παναιέηνςκ ηςκ ανζεκζηχκ ηαζ εδθοηχκ ελεηάζηδηακ ζηαηζζηζηά ζηδ θμβανζειζηή ιμνθή ηςκ ιεηααθδηχκ. Tα ζηάδζα βεκκδηζηήξ ςνζιυηδηαξ εηηζιήεδηακ ιε ιαηνμζημπζηή ελέηαζδ ημο ακαπαναβςβζημφ ζοζηήιαημξ ημο ηάεε αηυιμο ιε αάζδ ηδκ ηθίιαηα βζα ςμηυημοξ Δθαζιαημανάβπζμοξ πμο πνμηάεδηε ζημ Workshop on Sexual Maturity Staging of Elasmobranchs (WKMSEL, ICES 2012) ημ μπμίμ μνίγεζ ηα ζηάδζα ςξ ελήξ: Ανζεκζηά: 1. πανεέκα, 2. ακαπηοζζυιεκα, 3a. ζηακά βζα ακαπαναβςβή, 3b. εκενβά, 4a. ελακηθδιέκα, Θδθοηά: 1. πανεέκα, 2. ακαπηοζζυιεκα, 3a. ζηακά βζα ακαπαναβςβή, 3b. ςμημημφκηα, 4a. ελακηθδιέκα ηαζ 4b. οπυ ακάηαιρδ. Γζα ηδ ιεθέηδ ημο δπαημζςιαηζημφ (HSI) ηαζ ημο βμκαδμζςιαηζημφ δείηηδ (GSI) ζε ηάεε ζηάδζμ βεκκδηζηήξ ςνζιυηδηαξ πνδζζιμπμζήεδηακ μζ ιέζεξ ηζιέξ ηαζ ημ ηοπζηυ ζθάθια αοηχκ, λεπςνζζηά βζα ανζεκζηά ηαζ εδθοηά. Ο HSI ηαζ μ GSI μνίγμκηαζ ςξ ελήξ: ΖSI = (Βάνμξ ήπαημξ / DW) 100 ηαζ GSI = (Βάνμξ βμκάδςκ / DW) 100. Γζα ηδ εηηίιδζδ ημο ιήημοξ πνχηδξ βεκκδηζηήξ ςνίιακζδξ L 50 πνδζζιμπμζήεδηε ημ θμβζζηζηυ ιμκηέθμ. Χξ «ακχνζια» παναηηδνίζηδηακ ηα ανζεκζηά ηαζ εδθοηά άημια ηςκ ζηαδίςκ 1 ηαζ 2, εκχ ςξ «χνζια» ηα ανζεκζηά ηςκ ζηαδίςκ 3a, 3b ηαζ 4a ηαζ ηα εδθοηά ηςκ ζηαδίςκ 3a, 3b, 4a ηαζ 4b. Πναβιαημπμζήεδηακ ιεηνήζεζξ ζε 97 ηάρεξ αοβχκ απυ 34 ςμημημφκηα εδθοηά άημια ηαζ οπμθμβίζηδηακ μζ δζαζηάζεζξ ημοξ (± ηοπζηή απυηθζζδ). 3. Απνηειέζκαηα Σμ ιήημξ ηςκ ανζεκζηχκ ηοιάκεδηε απυ mm (ιέζδ ηζιή 395 mm ± 68 mm) ηαζ ηςκ εδθοηχκ απυ mm (ιέζδ ηζιή 408 mm ± 86 mm), ιε ηα ιεβαθφηενα πμζμζηά κα ειθακίγμκηαζ ηονίςξ ζηζξ ηθάζεζξ άκς ηςκ 440 mm (πήια 1). ηζξ ιεβαθφηενεξ ηθάζεζξ ( mm) οπενίζποε δ πανμοζία ηςκ εδθοηχκ. Ζ ζφβηνζζδ ηδξ ηαηά ιήημξ ζφκεεζδξ ανζεκζηχκ ηαζ εδθοηχκ έδεζλε ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ ιεηαλφ ηςκ ηαηακμιχκ (p < 0,0001). 415

416 ΑΡΗΘΜΟ ΑΣΟΜΧΝ HydroMedit 2014, November 13-15, Volos, Greece Αρςενικά (Ν=124) Θθλυκά (Ν=133) 5 0 TL (mm) ρήκα 1. Καηά κήθνο ζχλζεζε ηνπ G. melastomus ζην Αλαηνιηθφ Ηφλην. Απυ ηδ ζοζπέηζζδ ιήημοξ-αάνμοξ πνμέηορακ μζ ελήξ ελζζχζεζξ: Ανζεκζηά: RW= TL 3,0575, Ν=123, R 2 =0,9826 Θδθοηά: RW = TL 3,1739, N = 133, R 2 =0,9818 οκμθζηά: RW = TL 3,1331, Ν=256, R 2 =0,9818 Ζ ζφβηνζζδ ηςκ παναιέηνςκ ηςκ ελζζχζεςκ ιήημοξ-αάνμοξ ιεηαλφ ηςκ ανζεκζηχκ ηαζ εδθοηχκ έδεζλε ζηαηζζηζηά ζδιακηζηέξ δζαθμνέξ ιυκμ βζα ηζξ ηθίζεζξ b (p = 0,0364). Σα απμηεθέζιαηα ηδξ ακάθοζδξ ηςκ HSI ηαζ GSI ακά ζηάδζμ βεκκδηζηήξ ςνζιυηδηαξ πανμοζζάγμκηαζ ζηα δζαβνάιιαηα ηςκ πδιάηςκ 2 ηαζ 3. Σα απμηεθέζιαηα απυ ηδκ ακάθοζδ ημο GSI έδεζλακ ηαζ βζα ηα δφμ θφθα αολδηζηέξ ηζιέξ ζηα ζηάδζα βεκκδηζηήξ ςνζιυηδηαξ ημο είδμοξ (3a ηαζ 3b) ιε επαηυθμοεδ ιείςζδ ζηδ θάζδ ελάκηθδζδξ (4a) ηζ επακάηαιρδξ (4b). Ακηίεεηα, μζ ηζιέξ ημο HSI έθααακ ηδ παιδθυηενδ ηζιή ημοξ ζημ ζηάδζμ ςμαπυεεζδξ (3b) βζα ηα εδθοηά, εκχ ζηα ανζεκζηά δ ιείςζδ ήηακ ζηαδζαηή απυ ημ 3a ζημ 4a. 416

417 HSI GSI 1 2 3a 3b 4a ηάδην γελλεηηθήο σξηκφηεηαο ρήκα 4. Μήθνο πξψηεο γελλεηηθήο σξίκαλζεο (L ρήκα 50 ) αξζεληθψλ 2. Γηαθχκαλζε αηφκσλ G. ηνπ melastomus. HSI θαη ηνπ Με GSI θφθθηλν ησλ ην αξζεληθψλ 95% δηάζηεκα G. melastomus εκπηζηνζχλεο. αλά ζηάδην γελλεηηθήο σξηκφηεηαο. Γείρλεηαη ην ηππηθφ ζθάικα θαη ν αξηζκφο αηφκσλ/ζηάδην a 3b 4a 4b ηάδην γελλεηηθήο σξηκφηεηαο ρήκα 5. Μήθνο πξψηεο γελλεηηθήο σξίκαλζεο ρήκα (L 50 ) ζειπθψλ 3. Γηαθχκαλζε αηφκσλ ηνπ G. melastomus. HSI θαη ηνπ Με GSI θφθθηλν ησλ ζειπθψλ ην 95% δηάζηεκα G. melastomus εκπηζηνζχλεο. αλά ζηάδην γελλεηηθήο σξηκφηεηαο. Γείρλεηαη ην ηππηθφ ζθάικα θαη ν αξηζκφο αηφκσλ/ζηάδην HSI GSI 2 2 οκμθζηά ιεθεηδεήηακ 139 ακχνζια (66 ανζεκζηά, 73 εδθοηά) ηαζ 118 χνζια άημια (58 ανζεκζηά, 60 εδθοηά). Σμ ιζηνυηενμ χνζιμ ανζεκζηυ άημιμ είπε ιήημξ 393 mm TL, εκχ ημ ιεβαθφηενμ ακχνζιμ είπε 430 mm. θα ηα ανζεκζηά πάκς απυ 430 mm TL ήηακ χνζια. Ακηίζημζπα, ημ ιζηνυηενμ χνζιμ εδθοηυ άημιμ ήηακ 395 mm TL, εκχ ημ ιεβαθφηενμ ακχνζιμ 477 mm. θα ηα εδθοηά πάκς απυ ηα 478 mm TL ήηακ χνζια. Σμ ιήημξ πνχηδξ βεκκδηζηήξ ςνίιακζδξ (L 50 ) ιε αάζδ ημ θμβζζηζηυ ιμκηέθμ (πήιαηα 4 ηαζ 5) ανέεδηε βζα ηα ανζεκζηά L 50 = 412,2 mm (Ν=124 άημια) ηαζ βζα ηα εδθοηά L 50 = 444,2 mm (Ν=133 άημια). Οζ ηάρεξ αοβχκ είπακ ιήημξ ιε άβηζζηνα πμο ηοιαζκυηακ ιεηαλφ mm (ιέζδ ηζιή 46,3 ± 2,9 mm), ιήημξ πςνίξ άβηζζηνα mm (ιέζδ ηζιή 41,6 ± 2,6 mm), πθάημξ 16-19,5 mm (ιέζδ ηζιή 17,4 ± 0,8 mm) ηαζ αάνμξ 1,79-3,02 g (ιέζδ ηζιή 2,33 ± 0,32 g). Ο ανζειυξ ηςκ ηαρχκ ηοιαζκυηακ απυ 1 έςξ 4 ακά ςαβςβυ ηαζ ήηακ ζζυπμζα ηαηακειδιέκεξ ιεηαλφ ηςκ δφμ ςαβςβχκ, ιε ελαίνεζδ έκα άημιμ πμο έθενε 1 ηάρα ζημκ ανζζηενυ ςαβςβυ ηαζ ηαιία ζημ δελζυ ηαζ δφμ άημια πμο έθενακ 2 ηάρεξ ζημκ ανζζηενυ ςαβςβυ ηαζ 1 ζημ δελζυ. ηα οπυθμζπα δείβιαηα ανέεδηακ 2 ηάρεξ ακά άημιμ (21 άημια), 4 ηάρεξ (7 άημια), 6 ηάρεξ (2 άημια) ή 8 ηάρεξ (1 άημιμ). 4. πδήηεζε Οζ ηαηά ιήημξ ζοκεέζεζξ έδεζλακ υηζ ηα εδθοηά θηάκμοκ ζε ιεβαθφηενα ιήηδ, βεβμκυξ πμο έπεζ ακαθενεεί ηαζ απυ άθθμοξ ενεοκδηέξ βζα ημ είδμξ ζηδ Μεζυβεζμ ηαζ ημκ Αηθακηζηυ (Sion et al. 2004, Costa et al. 2005). Δπίζδξ επζαεααζχκμοκ υηζ ζηδ Μεζυβεζμ αθζεφμκηαζ άημια ιζηνυηενμο ιήημοξ ζε ζπέζδ ιε ημκ Αηθακηζηυ (Costa et al. 2005). Ο ιεβαθφηενμξ αθθμιεηνζηυξ ζοκηεθεζηήξ (b) πμο παναηδνήεδηε ζηα εδθοηά, πζεακυκ ακηακαηθά ηζξ αολδιέκεξ εκενβεζαηέξ ακάβηεξ πμο έπμοκ ηα εδθοηά ηαηά ηδ δζάνηεζα ηδξ θεηζεμβέκεζδξ (Capapé et al. 2008). Τρδθυηενεξ ηζιέξ b ζηα εδθοηά έπμοκ ακαθενεεί ηαζ απυ ημοξ Ragonese et al. (2009) ζηδ ζηεθία, ημοξ Capapé et al. (2008) ζηδ Ν. Γαθθία ηαζ ημοξ Moore et al. (2013) ζημκ Αηθακηζηυ. Ο GSI έδεζλε, υπςξ ακαιεκυηακ, αολδηζηή ηάζδ απυ ηα ακχνζια πνμξ ηα χνζια άημια, εκχ άνπζζε κα ιεζχκεηαζ ζηα άημια πμο έπμοκ βεκκήζεζ ηαζ παθζκδνμιμφκ, πνμεημζιαγυιεκα βζα έκα κέμ ακαπαναβςβζηυ ηφηθμ. O GSI πανμοζίαζε ιεβαθφηενεξ ηζιέξ ζηα εδθοηά απυ υ,ηζ ζηα ανζεκζηά, ζηα ζηάδζα 3a ηαζ 3b (ςμημηία), θυβς ηδξ αφλδζδξ ηςκ 417

418 ςμηοηηάνςκ ηαηά ηδ θεηζεμβέκεζδ, εκχ δ ιείςζή ημο ζηα ζηάδζα ιεηά ηδ ςμημηία είκαζ πζμ ιεβάθδ ζε ζπέζδ ιε ηα ανζεκζηά, βεβμκυξ πμο ελδβείηαζ απυ ημ υηζ δ ςμεήηδ οθίζηαηαζ ιεβάθεξ αθθαβέξ ηαζ δεκ πενζέπεζ πθέμκ ακεπηοβιέκα ςάνζα. Οζ ιεηααμθέξ ημο HSI δείπκμοκ υηζ ημ ήπαν πζεακά παίγεζ επίζδξ ζδιακηζηυ νυθμ ζηδκ ακαπαναβςβή ημο είδμοξ. ημ ζηάδζμ ηδξ ςμημηίαξ (3b) μ HSI ιεζχκεηαζ. Ζ ιείςζδ ημο HSI είκαζ πζμ ειθακήξ ζηα εδθοηά άημια, πζεακά επεζδή ζπεηίγεηαζ ιε ηδ δζαδζηαζία ηδξ θεηζεμβέκεζδξ ηαζ ηδξ παναβςβήξ ηαρχκ, ιζα ιεηααμθζηή δζαδζηαζία ηαηά ηδκ μπμία ζημ ήπαν παναηδνείηαζ ζοζζχνεοζδ ηαζ ηαηακάθςζδ δπαηζηχκ θζπζδίςκ (Capapé et al. 2008). Σμ ιήημξ ηδξ πνχηδξ βεκκδηζηήξ ςνίιακζδξ είκαζ πανυιμζμ ιε ηζξ πενζζζυηενεξ ακαθμνέξ απυ ηδ Μεζυβεζμ εάθαζζα (Ragonese et al. 2009, Tursi et al. 1993, Rey et al εκχ αθέπε Capapé et al. 2008) εκχ είκαζ ιζηνυηενμ ζε ζπέζδ ιε ημκ Αηθακηζηυ (Costa et al. 2005, Moore et al. 2013). Σα ανζεκζηά θάκδηε κα εζζένπμκηαζ ζημ ζηάδζμ βεκκδηζηήξ ςνίιακζδξ ζε ιζηνυηενα ιήηδ απυ ηα εδθοηά, βεβμκυξ πμο έπεζ ακαθενεεί ηαζ απυ άθθμοξ ενεοκδηέξ (π.π. Ragonese et al. 2009, Capapé et al. 2008, Rey et al. 2005, Costa et al. 2005, Moore et al. 2013). Οζ δζαζηάζεζξ ηςκ ηαρχκ αοβχκ δζαθένμοκ ακάθμβα ιε ηδ βεςβναθζηή πενζμπή. Οζ ηάρεξ αοβχκ πμο πνμένπμκηαζ απυ ημκ Αηθακηζηυ πανμοζζάγμοκ ιεβαθφηενεξ δζαζηάζεζξ (π.π. Bannister 1998, Costa et al. 2005, Iglesias et al. 2002) απυ αοηέξ ηδξ Μεζμβείμο (π.π. Tursi et al. 1993, Capapé et al. 2008). Σα δζηά ιαξ απμηεθέζιαηα ζοιθςκμφκ πενζζζυηενμ ιε αοηά ηδξ Μεζμβείμο. Ο ανζειυξ ηςκ ηαρχκ αοβχκ ακά άημιμ (2-8) ηδξ πανμφζαξ ενβαζίαξ ζοιθςκεί ιε αοηά πμο ακαθένμοκ μζ Costa et al. (2005) ηαζ Capapé et al. (2008) εκχ μζ Tursi et al. (1993) ηαζ Iglesias et al. (2002) ανήηακ ιεβαθφηενμ ανζειυ ηαρχκ ακά άημιμ. Πεναζηένς ιεθέηδ ηςκ ζημζπείςκ αοηχκ ηαηά ηδ δζάνηεζα υθμο ημο έημοξ εα ιαξ δχζεζ πθδνέζηενδ ηαζ πζμ μθμηθδνςιέκδ εζηυκα βζα ηδκ ακαπαναβςβζηή αζμθμβία ημο G. melastomus ζημ Ακαημθζηυ Ηυκζμ. Βηβιηνγξαθία Anastasopoulou A., Mytilineou Ch., Lefkaditou E., Dokos J., Smith C.J., Siapatis A., Bekas P., Papadopoulou K.-N. (2013). Diet and feeding strategy of blackmouth catshark Galeus melastomus. Journal of Fish Biology 83 (Issue 6), Bannister K. (1998). The book of the shark, 2nd edn. Grange Books Publishing Ltd., London. Capapé C., Guélorget O., Vergne Y., Reynaud C. (2008). Reproductive biology of the blackmouth catshark, Galeus melastomus (Chondrichthyes: Scyliorhinidae) off the Languedocian coast (southern France, northern Mediterranean). Journal of the Marine Biological Association of the United Kingdom 88 (2), Compagno L.J.V. (1984). Sharks of the World: An Annotated and Illustrated Catalogue of Shark Species Known to Date. FAO, Rome, pp Costa M.E., Erzini K., Borges T.C. (2005). Reproductive biology of the blackmouth catshark, Galeus melastomus, off the south coast of Portugal. Journal of the Marine Biological Association of the United Kingdom 85, ICES. (2013). Report of the workshop on Sexual Maturity Staging of Elasmobranchs (WKMSEL), December ICES CM 2012/ACOM:59, Lisbon, Portugal, pp. 66. Iglesias S.P., Du Buit M.H., Nakaya K. (2002). Egg capsules of deep-sea catsharks from eastern north Atlantic, with first descriptions of the capsule of Galeus murinus and Apristurus aphyodes (Chondrichthyes: Scyliorhinidae). Cybium 26, Moore D.M., Neat F.C., McCarthy I.D. (2013). Population biology and ageing of the deep water sharks Galeus melastomus, Centroselachus crepidater and Apristurus aphyodes from the 418

419 Rockall Trough, north-east Atlantic. Journal of the Marine Biological Association of the United Kingdom 93 (7), Musick J. A. (2005). Introduction: management of sharks and their relatives (Elasmobranchii). In: FAO Fisheries Technical Paper 474: Management techniques for elasmobranch fisheries, Musick J. A., Bonfil R. (eds). FAO, Rome, p Quéro J.C. (1984). Scyliorhinidae. In: Fishes of the north-eastern Atlantic and the Mediterranean (FNAM), Whitehead P.J.P. et al (eds). Vol. 1. UNESCO, Paris, p Rey J., De Sola L. G., Massutí E. (2005). Distribution and Biology of the Blackmouth Catshark Galeus melastomus in the Alboran Sea (Southwestern Mediterranean). Journal of Northwest Atlantic Fishery Science 35, Ragonese S., Nardone G., Ottonello D., Gancitano S., Giusto G.B., SinacoriI G. (2009). Distribution and biology of the Blackmouth catshark Galeus melastomus in the Strait of Sicily (Central Mediterranean Sea). Mediterranean Marine Science 10/1, Rinelli P., Bottari T., Florio G., Romeo T., Giordano D., Greco S. (2005). Observations on distribution and biology of Galeus melastomus (Chondrichthyes, Scyliorhinidae) in the southern Tyrrhenian Sea (central Mediterranean). Cybium 29, Sion L., Bozzano A., D Onghia G., Capezzuto F., Panza M. (2004). Chondrichthyan species in deep waters of the Mediterranean sea. Scientia Marina 68 (Suppl.3), Tserpes G., Maravelias C.D., Pantazi M., Peristeraki P. (2013). Distribution of relatively rare demersal elasmobranchs in the eastern Mediterranean. Estuarine, Coastal and Shelf Science 117, Tursi A., D Onghia G., Matarrese A., Piscitelli G. (1993).Observations on population biology of the blackmouth catshark Galeus melastomus (Chondrichthyes, Scyliorhinidae) in the Ionian Sea. Cybium 17, Vannuccini S. (1999). FAO Fisheries Technical Paper No. 389: Shark utilization, marketing and trade. FAO, Rome, pp

420 MSY ASSESSMENT IN DATA-SCARCE SITUATIONS: TWO CASE STUDIES Bianchini M.L. 1 *, Pigliarien E. 2, Argenti L. 3, Ragonese S. 1 1 IAMC-CNR, Institute for the Coastal Marine Environment, Italian National Research Council, Via L. Vaccara 61, I Mazara del Vallo (TP), Italy 2 private laboratories, I Moncalieri (TO), Italy 3 private laboratories, Via Clarice Tartufari 162, I Roma, Italy Abstract With the aim of implementing long-term management plans for all its fisheries, the European Union considered MSY as the upper benchmark. Many fisheries in Europe, particularly in the Mediterranean, lack enough data to estimate the MSY, and therefore other reference points must be employed, e.g. the more precautionary F 0.1 ; this approach is especially needed for fragile or overexploited stocks. Having in mind these objective difficulties, this paper suggests a rapid procedure for establishing a global production model using as case studies two species in the northern Tyrrhenian Sea: a selachian fish, the blackmouth catshark (Galeus melastomus), and a stomatopod crustacean, the mantis shrimp (Squilla mantis). The method is that proposed by Garcia et al. (1989), i.e. using published and grey data on catch, standing stock and a likely estimate of mortality to assess the MSY: in the specific cases, F 0.1 (as proxy of F MSY ), gross catches and standing biomasses reported by STECF and/or MEDITS estimates have been employed. This approach may allow fixing an exploitation limit coherent with the EU decision also in data-scarce situations. keywords: mantis shrimp, blackmouth catshark, fisheries, MSY, stock assessment, Tyrrhenian Sea * Corresponding author: Marco L. Bianchini (bradipo50@yahoo.com) 1. Introduction The demersal resources of the Mediterranean have a long history of high exploitation and most of them seem in a chronic state of sustainable overfishing (Lleonart & Maynou, 2003). After many unsuccessful attempts to improve the situation (Khalilian et al., 2010), limiting capacity and effort, setting alternative reference point and spending money in subsidies, the European Union (EU) decided to implement long-term management plans based on scientific assessments of its fisheries (CEC, 2006a; 2006b), to reach quantitative goals on the basis of specific target and limit reference points, following the Marine Strategy Directive 2008/56/CE and the Green Paper on the Reform of the CFP (CEC, 2009). In the framework of its decision, the maximum sustainable yield (MSY) has been recently adopted as upper benchmark, i.e. as an overfishing limit (OFL) (Mace, 2001), notwithstanding serious 420

421 shortcomings (Finley & Oreskes, 2013). Many fisheries in Europe, particularly in the Mediterranean, lack enough data to implement surplus production models and to estimate MSY-related parameters, and therefore other reference points have been employed, e.g. the fishing mortality parameter F 0.1 (Froese et al., 2011), easy to assess despite its lack theoretical foundation (Jensen, 2000); this precautionary strategy appears particularly necessary when managing fragile and/or overexploited resources, like cartilaginous fishes and demersal shrimps. This paper suggests a data-scarce approach, using F 0.1 as proxy of the required F MSY, for establishing a global production model, both for management of their fisheries and as case studies, on two such species in the northern Tyrrhenian Sea (part of GFCM s GSA9), i.e. Galeus melastomus, a selachian fish, and Squilla mantis, a stomatopod crustacean. The small blackmouth catshark (Galeus melastomus RAFINESQUE, 1810) occurs from m down to more than 1000 m, and is a low-value bycatch (mainly of bottom trawling fisheries), often rejected at sea (with unknown survival rates); like many other selachians, its stocks are in general considered highly vulnerable to trawling (Ragonese et al., 2009; Dell Apa et al., 2012). The Mediterranean mantis shrimp (Squilla mantis L., 1758) is a sedentary, territorial and opportunistic predator, occurring on soft bottoms, and is a common catch of coastal fisheries; notwithstanding its supposed resilience, due to its borrowing and nictemeral behaviours, the mantis shrimp appears in many instances as highly stressed (Ragonese et al., 2012). 2. Material and methods The approach is that proposed by Garcia et al. (1989), i.e. using published and grey metadata on gross catch (or landings), standing stock and a likely estimate of mortality at MSY to assess Fox s surplus production models per each available year, not necessarily ordered in time series: MSY = F MSY B curr exp [ 1 + Y curr /(F MSY B curr )] where B curr and Y curr represent the considered standing stock and yield (note that yield and landings do not always correspond) of a particular year. Speaking of the blackmouth catshark in the northern Tyrrhenian, F 0.1 (0.125 [mean], as proxy of F MSY ) reported by STECF (2011; 2012), and landings ( t) and standing biomasses ( t) obtained from MEDITS (2012) direct estimates and/or from a LCA exercise (232 t) have been employed; average F est have been derived from B curr /Y curr. In the case of Squilla mantis from the GSA9, F 0.1 (0.59 [mean], as proxy of F MSY ), landings as equivalent to gross catches ( t) and standing biomasses ( t) reported by STECF (2012) for the triennium have been utilized; again, average F est have been derived from B curr /Y curr. 421

422 3. Results Notwithstanding the paucity of the data, the Fox's surplus production model has been fitted averaging the available yearly estimates (landings + discards; years 2009 and 2010) for the blackmouth catshark in the GSA9. The graph (Figure 1) clearly shows a not-fully developed fishery, with dead catches securely on the left side of the Fox's surplus-production model (SPM), and F est ( ) lower than F 0.1. Figure 1 Exploitation level of Galeus melastomus in the northern Tyrrhenian Sea 422

423 Moreover, given the fishermen habit of throwing overboard almost all blackmouth catsharks while still alive, different scenarios (based on the 2010 LCA simulation) considered alternative hypotheses on survival of sharks returned at sea; in every case, the graphical integration shows that, at the present exploitation levels, survival may not be of major concern for the Galeus melastomus stock in GSA9. Figure 2 Exploitation levels of Galeus melastomus in the northern Tyrrhenian Sea, under different hypotheses of survival after returning at sea (LCA simulation) It was also possible to fit the production model averaging the available yearly estimates for the mantis shrimp in the northern Tyrrhenian Sea. The graph (Figure 3) and the corresponding F est ( ) show an overexploited situation in 2009 and 2010, with catches on the right side of the Fox's SPM, and F est much higher than F 0.1, while in 2011 the status of the fishery seems improving. 423

424 yield (t) fishing mortality (F) Figure 3 Exploitation level of Squilla mantis in the northern Tyrrhenian Sea 4. Discussion and conclusions There are two basic approaches in population dynamics studies, both formalized in the 50s (Quinn & Deriso, 1999): the Beverton and Holt s dynamic pool models (DPM) and the Schaefer s surplus-production models (SPM). Notwithstanding the lack of agreement among scientists, SPM are often preferred over DPM, being easier to understand and to sell to fishermen and politicians. In data-scarce situations, scientists were asked by the EU to estimate the fishing mortality via F 0.1 by applying synthetic models and use this target reference point as a substitute (proxy) for F MSY. F 0.1 is expected to be lower than F MSY in the most productive stocks, corresponding on a theoretical basis to around 90% of F MSY (Prager, 1994); matter-of-factly, F 0.1 lower than 0.3 do not perform well as proxy of F MSY. Still, the possibility of determining the (mean) MSY as a benchmark for management may allow fixing an exploitation limit coherent with the EU decision (CEC, 2009). The major caveats of any assessment based on MSY are the steady state assumption (Hilborn & Walters, 1992) and the congruity of landings and standing data; nevertheless, notwithstanding its limitations, there seems to be no operational rival to MSY (Barber, 1988), especially in complex circumstances, such as those frequent in the Mediterranean. The blackmouth catshark is caught frequently and abundantly in bottom trawling for deep-water red shrimps (Ragonese et al., 2000), and its stocks may seem theoretically vulnerable; in fact, even if the effective survival rate of animals returned to sea is unknown, they all appear vital and viable when tossed overboard, and this fact could explain the assessed resilience of the species. Mantis shrimp resources are considered quite tough to fisheries due to burrowing habits and preference for coastal bottoms, generally closed to trawling. Despite this fact, current analytical 424

425 models (STECF, 2011; 2012) highlighted a strong overexploitation (F curr =1.24 >> F MSY ), requiring fishing effort cuts almost unacceptable by administrators and fishermen (Mace, 2001). On the contrary, present results support a moderate resilience of the stock, showing a status between the fully exploitation and moderate overexploitation (F curr F MSY ). In conclusion, the proposed approach, already implemented in different cases (Bianchini & Ragonese, 2012; Ragonese et al., 2012) supports the possibility of getting an independent assessment of MSY, as well as the congruity as proxy of F 0.1 derived from analytical models, when "true" F MSY is not available. References Barber W.E Maximum sustainable yield lives on. North American Journal Fisheries Management, 8: Bianchini M.L., Ragonese S An approach to more sustainable fisheries: the European Union's MSY requirement and the case of the turbot in the Black Sea. Proceedings 3 rd International Scientific Congress of the Technical University of Varna, 7: CEC (Commission of the European Communities). 2006a. Communication from the Commission to the Council and the European Parliament: implementing sustainability in EU fisheries through maximum sustainable yield. COM(2006)/360: CEC (Commission of the European Communities). 2006b. Technical background to the Commission s Communication "Implementing sustainability in EU fisheries through maximum sustainable yield: a strategy for growth and employment" {COM(2006)/360}. Commission Staff Working Document, SEC(2006)/868: CEC (Commission of the European Communities) Green paper: reform of the Common Fisheries Policy. COM(2009)/163. Dell Apa A., Kimmel D.G., Clò S Trends of fish and elasmobranch landings in Italy: associated management implications. ICES Journal of Marine Science, 69(6): Finley C., Oreskes N Maximum sustainable yield: a policy disguised as science. ICES Journal of Marine Science, 70(2): Froese R., Branch T.A., Proelß A., Quaas M., Sainsbury K., Zimmermann C Generic harvest control rules for European fisheries. Fish and Fisheries, 12: Garcia S., Sparre P., Csirke J Estimating surplus production and maximum sustainable yield from biomass data when catch and effort time series are not available. Fisheries Research, 8: Hilborn R., Walters C.J Quantitative fisheries stock assessment: choice, dynamics and uncertainty. Chapman & Hall: 570 p. Jensen A.L Harvest reference points for the Beverton and Holt dynamic pool model. Fisheries Research, 47(1): Khalilian S., Froese R., Proelß A., Requate T Designed for failure: a critique of the Common Fisheries Policy of the European Union. Marine Policy, 34(6): Lleonart J., Maynou F Fish stock assessments in the Mediterranean: state of the art. Scientia Marina, 67(Suppl.1): Mace P.M A new role for MSY in single-species and ecosystem approaches to fisheries stock assessment and management. Fish and Fisheries, 2:

426 MEDITS (International Bottom Trawl Survey in the Mediterranean) available at < Prager M A suite of extensions to a non-equilibrium surplus production model. Fishery Bulletin, 92: Quinn T.J. II, Deriso R.B Stock productivity and surplus production. in: Quantitative fish dynamics. Oxford University Press: Ragonese S., Di Stefano L., Bianchini M.L Catture e selettività di pesci cartilaginei nella pesca dei gamberi rossi nello Stretto di Sicilia. Biologia Marina Mediterranea, 7(1): Ragonese S., Nardone G., Ottonello D., Gangitano S., Giusto G.B., Sinacori G Distribution and biology of the blackmouth catshark Galeus melastomus of the Strait of Sicily (Central Mediterranean Sea). Mediterranean Marine Science, 10(1): Ragonese S., Morara U., Canali E., Pigliarino E., Bianchini M.L Abundance and biological traits of the spottail mantis shrimp, Squilla mantis (L., 1758) (Stomatopoda - Crustacea), off the southern coast of Sicily. Cahiers de Biologie Marine, 53(4): Ragonese S., Pigliarino E., Bianchini M.L Testing the Fox s surplus production model for the pink shrimp, Parapenaeus longirostris, in the Mediterranean. X Crustacea Decapoda Mediterranea, Athens (Greece), 03-07/06/12: 236. STECF (Scientific, Technical and Economic Committee for Fisheries) & Assessment of Mediterranean Sea stocks (37 th / 39 th ). available at < 426

427 SEXUAL MATURITY OF THE AGUJON NEEDLEFISH Tylosurus acus imperialis Kokokiris L.* 1, Minos G. 1, Kiriakidou Μ. 1, Alexandrou M. 1, Papadaki Μ. 2, Karidas T. 1, Economidis P.S. 3 1 Alexander Technological Educational Institute of Thessaloniki, Department of Aquaculture and Fisheries Technology, P.O.Box 157, HL-63200, Nea Moudania, Hellas, 2 Hellenic Centre for Marine Research, Institute of Marine Biology, Biotechnology and Aquaculture, P.O.Box 2214, 71003, Iraklion, Crete, Hellas, 3 Karakasi 79, GR , Thessaloniki, Hellas Abstract The present study was designed to identify maturity of the agujon needlefish, Tylosurus acus imperialis, using microscopic criteria. Histological analysis was applied on 110 individuals sampled between May and August in Thermaikos Gulf (N. Aegean Sea, Greece). Female gonadal development was observed in that only one functional ovary persisted in all females. This was normally on the right, while on the left side the ovary failed to differentiate. Male agujon needlefish had bilateral testes but an asymmetry between testes became evident, with the left testis being significantly less developed. All female and male individuals were in spawning capability or even in spawning active phase, providing evidence of a spawning period from May to August with a peak in June and July. The minimum size for maturity of females was 64.5 cm TL whilst minimum size for male maturity was 59.3 cm TL. The coexistence within ovary of oocytes at various maturity steps, i.e. secondary growth full grown, hydrated oocytes (eggs) and postovulatory follicles clearly indicated T. acus imperialis as a multiple spawner. Furthermore, the absence of immature individuals among specimens provided strong evidence for the existence of a spawning ground in the study area. Keywords: Tylosurus, histology, maturity, spawning period *Corresponding author: Lambros Kokokiris (lamprosk@aqua.teithe.gr) ΣΟΙΧΕΙΑ ΓΕΝΝΗΣΙΚΗ ΩΡΙΜΑΝΗ ΣΗ ΒΑΙΛΟΖΑΡΓΑΝΑ Tylosurus acus imperialis Κοκοκφρησ Λ. *1, Μίνοσ Γ. 1, Κυριακίδου Μ. 1, Αλεξάνδρου Μ. 1, Παπαδάκη Μ. 2, Καρφδασ Θ. 1, Οικονομίδησ Π Σιήια Σεπκμθμβίαξ Αθζείαξ ηαζ Τδαημηαθθζενβεζχκ, Αθελάκδνεζμ Σεπκμθμβζηυ Δηπαζδεοηζηυ Ίδνοια Θεζζαθμκίηδξ, Σ.Θ. 157, 63200, Νέα Μμοδακζά, Δθθάδα, 2 Ηκζηζημφημ Θαθάζζζαξ Βζμθμβίαξ, Βζμηεπκμθμβίαξ ηαζ Τδαημηαθθζενβεζχκ, Δθθδκζηυ Κέκηνμ Θαθάζζζςκ Δνεοκχκ, Σ.Θ. 2214, 71003, Ζνάηθεζμ, Δθθάδα, 3Καναηάζδ 79, 54453, Θεζζαθμκίηδ, Δθθάδα 427

428 Πεξίιεςε ηδκ ενβαζία αοηή πενζβνάθεηαζ δ βεκκδηζηή ςνίιακζδ ηδξ ααζζθμγανβάκαξ Tylosurus acus imperialis, ιε αάζδ ηδκ ζζημθμβζηή ακάθοζδ ηςκ βμκάδςκ 110 αηυιςκ, ηα μπμία αθζεφεδηακ ηδκ πενίμδμ Μαΐμο-Αοβμφζημο ζημ Θενιασηυ Κυθπμ. ηα εδθοηά άημια ήηακ ακεπηοβιέκδ ιυκμ δ δελζά βμκάδα εκχ ζηα ανζεκζηά άημια παναηδνήεδηε έκημκδ αζοιιεηνία ηςκ υνπεςκ ιε ημκ ανζζηενυ υνπζ κα είκαζ ζδιακηζηά πζμ ιζηνυξ απυ ημ δελζυ. θα ηα άημια ήηακ χνζια εκχ ηα πενζζζυηενα ημοξ ιήκεξ Ημφκζμ ηαζ Ημφθζμ ήηακ ζηα ηεθζηά ζηάδζα ηδξ ςνίιακζδξ (ζηάδζμ ςμημηίαξ, ζηάδζμ ζπενιίαζδξ). Ζ πενίμδμξ ςμημηίαξ ηδξ ααζζθμγανβάκαξ ζημ Θενιασηυ Κυθπμ εηηείκεηαζ απυ ημκ Μάζμ ιέπνζ ημκ Αφβμοζημ, ιε ηδκ ςμημηία κα ημνοθχκεηαζ ημοξ ιήκεξ Ημφκζμ ηαζ Ημφθζμ. Σμ εθάπζζημ ιέβεεμξ ηςκ χνζιςκ αηυιςκ ήηακ 64,5 cm μθζημφ ιήημοξ βζα ηα εδθοηά άημια ηαζ 59,3 cm βζα ηα ανζεκζηά. Ζ ηαοηυπνμκδ ζοκφπανλδ ςμηοηηάνςκ ζε πενζζζυηενα απυ δφμ ζηάδζα ακάπηολδξ ηαζ εζδζηυηενα δ ζοκφπανλδ θεηζεζηχκ ςμηοηηάνςκ, ςμηοηηάνςκ ζημ ζηάδζμ ηδξ ηεθζηήξ ςνίιακζδξ (οαθχδδ ή εκοδαηςιέκα) ηαζ ηεκχκ ςμεοθαηίςκ, οπμδδθχκμοκ υηζ δ ααζζθμγανβάκα είκαζ πμθθαπθυξ απμεέηδξ. Ζ πακηεθήξ απμοζία ακχνζιςκ αηυιςκ ζηα δείβιαηα απυ ηδκ πενζμπή ιεθέηδξ, δείπκεζ υηζ δ ζοβηεηνζιέκδ πενζμπή ιπμνεί κα είκαζ πεδίμ ςμημηίαξ ηδξ ααζζθμγανβάκαξ. Λέξειρ κλειδιά: Tylosurus, ηζηνινγία, σξίκαλζε, πεξίνδνο σνηνθίαο *οββναθέαξ επζημζκςκίαξ: Λάιπνμξ Κμημηφνδξ 1. Introduction The needlefish, Tylosurus acus (Belonidae, Lacepède 1803) is an epipelagic species that is widely distributed in tropical and subtropical waters with many subspecies that have been recognized depending to their geographical distribution (Collette 2003). T. a. acus (Lacépède 1803) is found in the Western Atlantic; T. a. rafale (Collette & Parin 1970) is mainly distributed in the Gulf of Guinea, T. a. melanotus (Bleeker 1850) is found throughout the Indo-Western Pacific, extending to the Eastern Pacific and the agujon needlefish T. a. imperialis is found in the Mediterranean Sea (Collette 2003). The agujon needlefish T. a. imperialis consists part of the catches of the coastal small scale fishery in Thermaikos Gulf (N. Aegean Sea) since Agujon needlefish are usually being caught by gillnets, beach seines and night spear fishing throughout late spring and summer months reaching a relatively high price in local fish markets. Despite the existence of various information on its distribution in the Meditteranean Sea (Bello 1995, Akyol & Kara 2011, Pećarević et al. 2013, Türker Çakır & Zengin 2013, Imsiridou et al. 2014), information on its biology and particularly on its reproductive biology is still scarce. Moreover, the biological information accumulated on species of the six Tylosurus genera (Collette 2003) across their world-wide distribution is not well documented. To our knowledge, detailed information on the reproductive biology of Tylosurus genera is rather limited to T. a. melanotus in waters of southeastern Taiwan (Liao & Chang 2011). However, the reproductive biology information is essential for fisheries management schemes. The aim of this study was to identify the maturity of the agujon needlefish, T. a. imperialis, using microscopic criteria, coming to a better understanding of its reproductive biology and contributing to the development of appropriate management schemes. 2. Materials and methods A total of 110 T. a. imperialis individuals were sampled on a monthly basis between May and August, during 2013 and All fish were caught by artisanal fishery (gillnets, beach seines, permanent fish traps, night spear fishing from boat, arrowhead fixed fish trap) operating in Thermaikos Gulf (40º23 00 N; 22º47 00 E). For each specimen, total length (TL) to the nearest centimetre, as well as the total and gutted 428

429 weight (gw b ), and gonad and liver weights were measured (accuracy of 0.01 g). Specimens ranged from 59 to 107 cm (TL) and 0.23 to 1.7 kg (W b ). Slices of the gonads were fixed in 10% buffered formaldehyde. After h, a segment from the central part of the left lobe was dehydrated in increasing concentrations of ethanol and clarified in xylene. Each segment was then embedded in paraffin wax and cross-sections of 4 5ιm thickness were cut and stained with Mayers haematoxylin-eosin. Sex and maturity stage (MS) were determined from microscopic observations of histological slides. Ovarian maturity was defined by the maturation stage of the most advanced oocytes and testicular maturity by the most advanced spermatic cells. For the development classification of oocytes, the classification scheme of Grier et al. (2009) was used. Ovarian and testicular maturity was divided into phases, following the conceptual models and the standardised terminology proposed by Brown-Peterson et al. (2011). The presence of postovulatory and atretic follicles was also recorded. For each individual the following indices were calculated: (i) gonadosomatic index (I g ), (I g =100 x gonads weight/gutted weight), (ii) hepatosomatic index (I h ), (I h =100 x liver weight/gutted weight, and (iii) condition index (K n =total weight/tl b ). 3. Results Specimens were caught only from May to August. Males outnumbered females. The smaller specimen collected was of 64.5 cm TL for females and 59.3 cm for males. Those sizes were also the minimum sizes for maturity of females and males, since all specimens were sexually mature with gonads capable of spawning and no immature individual was collected at lower length sizes. Female gonadal development was observed in that only one functional ovary persisted in all mature females. This was normally on the right, while on the left side the ovary failed to differentiate and underwent a degenerative fate along with its associated reproductive tract. Adult male agujon needlefish had bilateral testes but an asymmetry between left and right testes became very evident, with the left testis significantly less developed than the right testis (reaching only up to 10% of the right testis). Mature ovaries were cylindrical, swollen, ranging from 13.4 to 33.1 cm in length (Table 1), having a deep yellowish-orange in colour. Ovaries divided into those being capable of spawning ( spawning capable ) and actively spawning ( active spawning ). Spawning capable ovaries contained oocytes at all steps of oogenesis but fullgrown vitellogenic oocytes (SG fg ), were the most advanced and large oocytes. SG fg oocytes were distinguished by the formation of large regions of fluid yolk, the appearance of an ooplasm displaced into the peripheral rim surrounding the yolk mass and a zona pellucida having its maximum length. The oil droplets concentrated around the nucleus, then fused into one or a few oil drops. The germinal vesicle was of an irregular shape with an envelope became progressively folded. Numerous small and large nucleoli could also be seen. Spawning active ovaries were characterised by the presence of hydrated oocytes (final maturation step, OM); having the yolk material completely fused with a few or one oil drops formed inside. The appearance of the oocyte was homogenous, finely granular, whilst the germinal vesicle was invisible due to disintegration and dispersion of the nuclear membrane (GVBD). The ooplasm, was restricted to a narrow rim, laying next to the zona pellucida, which had became thinner. At the late portion of the spawning season (i.e. August) in some spawning-capable ovaries, empty ovarian follicles (post ovulatory follicles, POFs) were present, indicating that ovulation had occurred. Clear sings of atresia could be also identified in some ovaries. Mature testes were triangular or diamond shaped, white in colour, thick and long in size with an average length of 16.8 cm significantly less elongated than ovaries (ANOVA, P=0.04, Table 1). Testes in spawning 429

430 capable phase were identified by the presence of spermatozoa in the lumen of the lobules and in the sperm ducts. Some males were moved to the actively spawning subphase, releasing milt after a gentle pressure was placed on the abdomen (spermiating males). Males remained in the spawning capable phase during the majority of the period from May to August and underwent active spermatogenesis during which all stages of spermatogenesis were observed. They were classified as being in the early, middle or late portion of the spawning season based on continuous or discontinuous germinal epithelium (GE). During the early GE subphase of the spawning capable phase, they were distinguished by a continuous GE throughout testis and the presence of spermatogonia (Sg) in the spermatocyts. During the mid-ge subphase, spermatogenesis ceased in some spermatocysts in lobules near the sperm ducts, resulting in a discontinuous GE near the ducts but a continuous GE at the periphery of the lobules. By the end of July, males were in late GE subphase having a discontinuous GE throughout the testis, an increasing prevalence of anastomosing lobules and reduced spermatogenesis. During August, at the late portion of the spawning season some males with testes entering the regressing phase were seen. Table 1. Mean values (± SD) and range of values for body weight (W b ), gutted body weight (gw b ), total length (TL), gonadosomatic index (I g ), hepatosomatic index (I h ), condition index (K n ) and gonads length in female and male spawning capable needlefish, T. acus imperialis. Females (n=29) Males (n=81) Mean (±SD) Range Mean (±SD) Range W b (g) (±359) (±287) gw b (g) (±296) (±258) TL (cm) 81.1 (±12.5) (±10.2) I g (%) 9.7 (±5.5) (±0.8) I h (%) 2.9 (±1.5) (±1.5) K n (%) 1.1 (±0.08) (±0.11) L g (cm) 24.6 (±5.0) (±4.8) Discussion Collette (1981) and Bauchot (1987) were the first to report the existence of L-R gonads asymmetry in T. a. imperialis individuals, where only a functional ovary exists in females but they reported the presence of two asymmetric testes in male individuals. Similarly, L-R asymmetry of paired gonads has been also reported for the congeneric species, T. crocodiles (Colette 1981) but no gonads asymmetry has been reported for the subspecies T. a. melanotus or other species of Belonidae family. It seems that further research is required towards the 430

431 identification of factors controlling the establishment of L-R gonads asymmetry and its functional significance in this species. The histomorphological characteristics of gametogenesis of T. a. imperialis in Thermaikos Gulf are similar to those described for the needlefish T. a. melanotus in waters off Southwestern Taiwan (Liao & Chang, 2011). The capture of spawning active individuals with running milt and hydrated oocytes (eggs), additionally to the increased catches since 2012, provide evidence of a functional adaptation and successful spawning in the study area. The appearance of spawning capable individuals from May to August with a peak in June and July, provide evidence of a spawning period during the early summer months, when temperature begins to rise. Similarly, the spawning period lasts from April to August with a peak between May and July in coastal waters off the eastern coast of Tunisia (Chaari et al. 2011) or in June for needlefish T. a. melanotus in waters around Hsiao-Liu-Chiu island off southwestern Taiwan (Liao & Chang 2011). The coexistence within ovary of oocytes at various maturity steps, i.e. SG fg, oocytes, hydrated oocytes (eggs) and POFs clearly indicate T. a. imperialis as a multiple spawning species, similarly to what has been shown for the congeneric needlefish, T. a. melanotus (Liao & Chang 2011). Furthermore, the absence of immature individuals among specimens provides strong evidence for the existence of a spawning ground in the study area. Sustainable fisheries management should be complemented by other ecosystem-based measures, such as large marine protected areas where fishing is totally prohibited to ensure the survival of mature individuals. References Akyol, O. and Kara, A. (2011). Occurrence of Tylosurus acus imperialis (Rafinesque, 1810) (Osteichthyes: Belonidae) in the northern Aegean Sea. Journal of Applied Ichthyology 27, Bauchot M.L., (1987). Poissons osseux. In: W. Fischer, M.L. Bauchot and M. Schneider (eds.) Fiches FAO d'identification pour les besoins de la pêche (rev. 1). Méditerranée et mer Noire. Zone de pêche 37. Vol. II. Commission des Communautés Européennes and FAO, Rome., p Bello G. (1995). Tylosurus acus imperialis (Osteichthyes: Belonidae), a fish new to the Adriatic Sea. Cahier de Biologie Marine 36, Brown-Peterson N., Wyanski D.M., Saborido-Rey F., Macewicz B.J., Lowerre-Barbieri S.K. (2011). A standardized terminology for describing reproductive development in fishes. Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science 3, Collette B. (1981). Belonidae. In: FAO species identification sheets for fishery purposes. Eastern Central Atlantic. Fishing Area 34 and part of 47. Canada Funds-in-Trust. Ottawa. Fischer W., Bianchi G., Scott W.B. (eds), Department of Fisheries and Oceans Canada, by arrangement with FAO of the United Nation. Vols. 1-6: pag. var. Collette B.B. (2003). Family Belonidae (Bonaparte, 1832) needlefish. Annotated checklist of fish. California Academy of Sciences 16, Châari M., Derbel H., Neifar L. (2013). Lecithostaphylus tylosuri sp. nov. (Digenea, Zoogonidae) from the digestive tract of the needlefish Tylosurus acus imperialis (Teleostei, Belonidae). Acta Parasitologica 58, Grier H.J., Carmen Uribe M., Aranzabal M.C., Patino R. (2009). The ovary, folliculogenesis, and oogenesis in teleosts. In: Reproductive biology and phylogeny of fishes (Agnathans and Bony Fishes), Vol. 8, A. B.G. M. Jamieson, (Ed.) Science Publishers, Enfield, pp Imsiridou A., Minos G., Kokokiris L. (2014). Documentary appearance of Tylosurus acus imperialis individuals in Thermaikos Gulf. Proceedings of HydroMedit 2014, 1 st International Congress on Applied Ichthyology and Aquatic Environment, Volos, Hellas (accepted). Liao Y. & Chang, Y. (2011). Reproductive Biology of the Needlefish Tylosurus acus melanotus in Waters around Hsiao-Liu-Chiu Island, Southwestern Taiwan. Zoological Studies 50,

432 Pećarević M., Mikuš J., Bratoš Cetinić A., Dulĉić J. and M. Ĉalić (2013). Introduced marine species in Croatian waters (Eastern Adriatic Sea). Mediterranean Marine Science, 14/1,: Türker Çakır, D. and Zengin, K. (2013). Occurrence of Tylosurus acus imperialis (Rafinesque, 1810) (Osteichthyes: Belonidae) in Edremit Bay (Northern Aegean Sea). Journal of Applied Ichthyology 29,

433 THEMATIC FIELD: ENVIROMENTAL MANAGEMENT 433

434 NALYSIS OF GENETIC VARIABILITY AND DIFFERENTIONIN OF STALLATE STURGEON, Acipenser stellatus (Pallas, 1771), USING MICROSATELLITE MARKERS Norouzi M. 1 *, Pourkazemi M. 2, Ghasemi A. 3 1 Department of Marine Biology and Fisheries Sciences, Tonekabon Branch, Islamic Azad University, Tonekabon, Iran. 2 Iranian Fishery Research Organization, Tehran, Iran. 3 Persian Gulf Institute, Persian University, Boushehr, Iran. Abstract In total, 135 samples of adult stellate sturgeon Acipenser stellatus were collected at three sites (the estuaries of the Ural, Kura and Sefidrud Rivers) around the Caspian Sea. Fifteen sets of microsatellite primers were tested on genomic DNA. Ten primer sets revealing polymorphic loci were used to analyze the genetic variation found in adults of the stellate sturgeon populations. The analyses revealed that the average of alleles per locus was 12.1 and all the sampled regions contained private alleles. The observed and expected heterozygosity averaged and 0.860, respectively. Average of Fis, Fit and Nm were 0.181, 2.16 and 5.21 respectively. Fst, Rst and gene flow estimates in AMOVA indicated significant genetic differentiation among regions (P 0.01), indicating that the populations were divergent. The genetic distance between populations was 0.530, thus indicating that the genetic difference among populations is pronounced. These results provide useful information on the genetic variation and differentiation among the Caspian Sea populations of the stellate sturgeon. Keywords: Microsatellite, Genetic variability, genetic differentiation, Caspian Sea, Acipenser stellatus *Corresponding author: Mehrnoush Norouzi (mnoroozi@toniau.ac.ir) 1. Introduction Sevruga or stellate sturgeon (anadromous fish) is a brackish-water species, the most euryhaline among the Caspian sturgeons. In the last decade, due to higher water temperature considerable part of the North Caspian sevruga winters at the steep slopes of the North Caspian and in the north-eastern Middle Caspian. In spring, the North Caspian population migrates northward and then mature spawners enter the Volga and Ural Rivers. South Caspian population spawns in the Sefidrud and Kura Rivers. The post-spawn fish migrate back into the sea for feeding. Feeding migrations take place within the shelf zone of the sea. Food spectrum of sevruga is highly diverse (Velikova et al., 2012). Overfishing and illegal catches are the main causes of decrease in stocks of this species and of the number of adult spawners and, being also listed as endangered species by IUCN (Pourkazemi 2006). Microsatellites are frequent in fish genome and can easily be amplified with PCR; they denote high levels of allele polymorphism (Chistiakov et al., 2005). These features, taken together, offer the basis for a successful analysis in a wide range of fundamental and applied sectors of fisheries and aquaculture (Sekar et al. 2009). The development of management plans and the implementation of actions to restore stellate sturgeon within its native stocks can benefit from an understanding of the genetic diversity of its populations. This information is helpful in choosing donor populations to use as sources of reintroduction, as well as in formulating restoration goals regarding the population structure. This study was aimed at analyzing inter-population genetic diversity in stellate sturgeon by the analysis of microsatellites. 2. Materials and Methods The fishes were caught from three different regions, including 43 samples from Ural (Kazakhstan), 49 samples from Kura (Azerbaijan) and 43 samples from Sefidrud estuary (Iran) (Fig.1). Fin tissue samples were prepared from 135 fishes of each location and preserved in 95% ethanol and stored at room temperature. The genomic DNA was extracted following the method described by Pourkazemi et al. (1999). The quality and concentration of DNA were assessed by 1% agarose gel electrophoresis and then stored at -20 C until use. The nuclear DNA was amplified using 15 microsatellite primers designed for Acipenser and Scaphirhynchus (LS-19, 434

435 34, 39, 54, 57, 62, 68, 69, May et al. 1997; Spl-104, 105, 113, 163, 168, 170, 173, McQuown et al Polymerase Chain Reaction (PCR) conditions for each primer set was optimized for stellate sturgeon. The annealing temperatures were: 56 C for LS-19 and Spl-113, 58 C for LS-34 and Spl-163 /170, 59 C for LS-54 and Spl-105, 61.2 C for LS-68, 57 C for Spl-104, and 58.5 C for Spl-173. Polymerase chain reaction was performed in 20 ιl volume containing 100 ng of template DNA, pmol of each primer, 200 mm each of the dntps, 0.5 U of Taq DNA polymerase and 1-2.5mM MgCl2. PCR products were separated on 6% polyacrylamide gels (29:1 acrylamide: bis-acrylamide; 1X TBE buffer) and followed by silverstaining. The gels were run at 170 W for 2h and 30 min. Alleles were sized using BioCapt software, and each gel contained an allelic ladder (50bp) to assist in consistent scoring of alleles. Allele frequencies were estimated using F-statistics and Nei s genetic distance. The total genetic diversity (heterozygosity) within and among populations can be classified as follows: Ho =observed heterozygosity and He=expected heterozygosity. Hardy-Weinberg tests of equilibrium were estimated. Wright s F-statistics (Wright, 1965) as follows: Fis =inbreeding coefficient within individuals relative to the subpopulation for each locus and stellate sturgeon sampling site were assessed; Fit =the inbreeding coefficient within individuals relative to the total; and Fst =inbreeding coefficient within subpopulations relative to the total Fst and Rst were calculated using analysis of molecular variance (AMOVA) to estimate genetic variation among populations and regions. AMOVA calculations and allelic richness (A R ) were performed on Arlequin 3.5 (Excoffier & Lischer 2010) using 10,000 permutations in each case. Nei s genetic identity and distance were determined using a pairwise, individual-by-individual genetic distance, with all codominant data computed in GeanAlex 6 software (Peakall & Smouse 2005). The Cornuet and Luikart (1996) programme BOTTLENECK ver was used to detect recent effective population size reduction (to assess the impact of population decline) using data from the microsatellites under the more suitable two-phased model (TPM). 3. Results Overall 10 loci were successfully amplified (LS-19, 34, 54, 68, Spl-105, 104, 163, 170, 173, 113). The allele frequencies at all loci are given in Table 1. The average number of alleles found per site was 12.1, and the number of alleles in LS-34 ranged from 8 to 9 (A R =13), in LS-19 from 12 to 14 (A R =18), in LS-54 from 10 to 13 (A R =46), in LS-68 from 11 to 12 (A R =14), in Spl-105 from 8 to 11 (A R =11), in Spl-104 from 13 to 14 (A R =14), in Spl-163 from 11 to 14 (A R =20), in Spl-170 from 13 to 15 (A R =24), in Spl-173 from 13 to 14 (A R =25), and in Spl- 113 from 11 to 17 (A R =15). Out of 165 observed alleles, 110 alleles occurred at frequencies of less than 0.05 in all samples. All sampled populations contained a significant number of private alleles. In total, 21 alleles were found, with the number of private alleles being Ural 10 alleles, Kura 7 alleles, Sefidrud 4 alleles, none of which was found in other seasons. The observed and expected heterozygosity averaged and 0.860, respectively; the observed heterozygosity ranged from in Sefidrud estuary to 1 in Kura (Table 1). Bottleneck analysis of stellate sturgeon was in Ural, in Kura and in Sefidrud. Figure 1. Map showing sampling locations of populations of stellate sturgeon: Ural, Kura and Sefidrud Rivers. Estimates of inbreeding coefficient or Fis values were positive and between LS-19, ; LS-34, 0.25; LS54, 0.238; LS-68, -0.5; Spl104, 0.326; Spl105, 0.073; Spl113, 0.213; Spl163, 0.097; Spl170, 0.323; Spl173, (mean Fis =0.181; Fit=2.16), and high Fis values a relative dearth of heterozygotes and may be due to homozygotes. In all cases, deviations from Hardy-Weinberg equilibrium were significant (P < 0.01), except for LS-68 in Sefidrud and Spl-104 in Ural (Table 1). The Fst and Nm via frequency ranged from to and from to 8.289, respectively (Table 2) and as analyzed with AMOVA, showed a significant genetic differentiation among sites (P<0.01), which suggested that the populations diverged from each other. Values pair wise of Rst among samples were consistently much higher (as much as an order of magnitude) than equivalent Fst values but the difference was not significant (P > 0.05). The genetic distance computed by Nei (1972) between the Ural and Kura populations was 0.547, Ural and Sefidrud 0.522, and Sefidrud and Kura The mean genetic distance was (±0.08) between the populations. Table 1. Numbers of allelles observed within 3 sampling sites using 10 sets of microsatellite primers. Number of studied 435

436 samples (n), Observed (Ho) and expected (He) heterozygosities, number of alleles (Na), effective allele (Ne) at 10 loci in three sampling sites. Loci in accordance with H-W equilibrum *P < 0.05; **P < 0.01; ***P < 0.001; ns=not significant. Ural Kura Sefidrud Touchdown protocol Loci Actual size (bp) LS-19 Na/Ne 14/ / / o C/ 35 Ho/He 0.977*** / *** / *** / LS-34 Na/Ne 8/ 6.0 9/ 5.3 9/ o C/ 35 Ho/He 0.442***/ *** / ***/ LS-54 Na/Ne 11/ / / o C/ 35 Ho/He 0.488*** / *** / ***/ LS-68 Na/Ne 12/ / / o C/ 35 Ho/He 0.698***/ ** / ns / Spl104 Na/Ne 14/ / / o C/ 25 Ho/He 0.744ns / **/ *** / Spl105 Na/Ne 11/ / / o C/ 25 Ho/He 0.372***/ *** / ***/ Spl113 Na/Ne 17/ / 9/78 11/ o C/ 35 Ho/He / *** / *** ***/ Spl163 Na/Ne 14/ / / o C/ 35 Spl170 Ho/He 0.935***/ * / ***/ Na/Ne 14/ / 9/16 13/ o C/ 35 Ho/He 0.465***/ *** / *** / Spl173 Na/Ne 14/ / / o C/ 30 Ho/He 0.442*** / *** / ***/ Average Na/Ne 12.9/ / / 6.8 Ho/He / / / Table 2. Pairwise estimates of genetic differentiation detected at 10 loci in stellate sturgeon samples, using Nm values (above diagonal) and Fst (below diagonal). Samples Ural Kura Sefidrud Ural Fst Kura Sefidrud Discussion Of the 15 pairs of primers, 4 were not amplified by the PCR reaction, due to the lack of flanking sites in these primers, possibly as the result of the high genetic distance between stellate sturgeon and the species used as source of these primers. The proportion of polymorphic loci among the markers that did amplify decreased with the increasing genetic distance (Cui et al. 2005). The average number of alleles per locus and the observed heterozygosity were comparable in the populations from the north and south of the Caspian Sea, as reported previously using RFLP on these same populations (Shabani et al. 2006). In fact, although these populations do not differ in the amount of genetic variation expressed as heterozygosity or alleles per loci, they differ highly for the nature of their genetic variation, which depends on the private alleles and genotypes. The losses of alleles and heterozygosity may increase with bottlenecking and inbreeding through time in the artificial propagation center stocks. Regular monitoring of genetic variability among the progenies is essential to avoid the loss of current polymorphism due to inbreeding and outbreeding. In this study, a deviation from the H-W equilibrium was observed in most loci and no significant differences were found between the observed and the expected heterozygosities among the populations. The significant deviations from H-W equilibrium can be due to a bias in our samples or because we have not used speciesspecific primers or as the result of null alleles occurring in the studied populations. Heterozygotes with a null Nm 436

437 allele could be erroneously recorded as homozygotes for the variant allele. Similar results have been reported in lake and white sturgeons (Rodzen and May 2002; McQuown et al. 2003; Welsh and May 2006), Chinese sturgeon (Zhao et al. 2005) and it may also be related to sampling from mixtures of migrating populations. In our study, structure analysis and significant Fst in all sampling sites reveal at least three populations are genetically differentiated and not part of a single panmigric population. In fact, in the great majority of cases, the Fst is low, because the effect of polymorphism (due to mutations) drastically deflates Fst expectations (Balloux et al. 2002). In fish species, a negative correlation has been demonstrated between Fst values and dispersal capability (Waples 1987). According to this, feeding and spawning migrations at this fish are the result of a continuous movement from one part of the sea to another (Keyvan 2003). However, the loss of genetic variability might also be caused by sampling errors. Additionally, released fingerlings with hatcheryorigin that return to rivers to spawn may contribute to the loss of regional genetic differentiation (Vasemägi et al. 2005). Shaklee et al. (1982) and Thorpe and Sol-Cave (1994) showed that the Nei (1972) genetic distance values averaged 0.05 (range: ) for con-specific populations and 0.30 (range: ) for con-generic species. The distance value obtained in the present study (Table 4) falls within the average value of con-generic species, which indicates that the genetic difference among the studied populations was pronounced. In summary, this study provides preliminary evidence for the existence of at least three differentiated populations in the Caspian Sea, including the Ural, Volga, Sefidrud and Gorganrud populations. Probably in each river more than one population exists, suggesting that more samples from each river should be investigated. Characterizing the genetic structure of A. stellatus currently being used in the aquaculture industry will aid for future breed stock development and will improve management plans aimed at conserving diversity and minimizing inbreeding in artificial propagation. Acknowledgments We thank all those support provided by Iranian Fishery Research Organization (Project Cod ); Molecular Genetic Lab of the International Sturgeon Research Institute, Rasht. References Balloux F., Lugon-Moulin N. (2002). The estimate of population diffraction with microsatellite markers. Molecular Ecology 11, Chistiakov D. A., Hellemans B., Haley C. S., Law A. S., Tsigenopoulos C. S., Kotoulas G., Bertotto D., Libertini A., Volckaert F. A., A microsatellite linkage map of the European sea bass Dicentrarchus labrax L. Genetics, 170: Cornuet, J. M., Luikart G. (1996). Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics 144, Cui J.Z, Shen X.Y., Yang G.P., Gong Q.L., Gu Q.Q. (2005). Characterization of microsatellite DNAs in Takifugu rubripes genome and their utilization in the genetic diversity analysis of T. rubripes and T. pseudommus. Aquaculture 250, Excoffier L., Lischer H.E.L. (2010) Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology Resource 10, Keyvan A. (2003). Iranian sturgeons in the Caspian Sea. Iranian Fisheries Company. pp McQuown E., Sloor B.L., Sheehen R.J., May B. (2000). Microsatellite analysis of genetic variation in sturgeon: new primer sequences for Scaphyrhinchus and Acipenser. American Fisheries Society 129, McQuown E., Krueger C.C., Kincaid H.L., Gall A.E., May B. (2003). Genetic comparison of Lake Sturgeon population: Differentiation based on allelic frequencies at seven microsatellite loci. Journal of Great Lakes Research 29, May B., Charles C., Krueger C., Kincaid L. (1997). Genetic variation at Microsatellite loci in sturgeon primer sequence homology in Acipenser and Scaphirhenchus. Canadian Journal of Fisheries and Aquatic Sciences 54, Nei M. (1972). Genetic distance between populations. American Naturalist 106, Peakall R., Smouse P.E. (2005). GenAlEx 6: Genetic Analysis in Excel. Population genetic software for teaching and research. The Australian National University Canberra Australia. Available at: 437

438 Pourkazemi M., Skibinski D.O.F., Beardmore J.A. (1999). Application of mtdnad-loop region for the study of Russian sturgeon population structure from Iranian coastline of the Caspian Sea. Journal of Applied Ichthyology 15, Pourkazemi M. (2006). Caspian Sea sturgeon conservation and fisheries past, present and future. Journal of Applied Ichthyology 22 (suppl.1): 1-4. Rodzen J.A., May B. (2002). Inheritance of microsatellite loci in the polyploid white sturgeon (Acipenser transmontanus). Genome 54, Shabani A., Pourkazemi M., Rezvani S. (2006). Study of mtdna variation of stellate sturgeon (Acipenser stellatus) population from the north (Volga River) and South (Sefidrud River) Caspian Sea using RFLP analysis of PCR Amplified ND 5/6 gene regions. Journal of agricultural science and natural resources 12, (In Persian). Sekar M., Suresh E., Kumar N.S., Nayak S.K., Balakrishna C. (2009). Microsatellite DNA markers, a fisheries perspective Part 1: The nature of microsatellites. Aquaculture Asia Magazine. pp Shaklee J.B., Tamaru CS, Waples R.S. (1982). Speciation and evolution of marine fishes studied by electrophoretic analysis of proteins. Pacific Science 36, Thorpe JP, Sole-Cava A.M. (1994). The use of allozyme electrophoresis in invertebrate systematics. Zoologica Scripta 23, Vasemägi A.M., Gross R., Paavo T., Koljonen M.L., Nilsson J. (2005). Extensive immigration from compensatory hatchery releases into wild Atlantic salmon populations in the Baltic sea: spatio-temporal analysis over 18 years. Heredity 95, Velikova V.N., Shaudanov A.K., Gasimov A., Korshenko A., Abdoli A., Morozov B., Katunin D. N., Mammadov E., Bokova E. B., Emadi H., Annachariyeva J., Isbekov K., Akhundov M., Milchakova, N., Muradov O., Khodorevskaya R., Shahifar R., Shiganova, T., Zarbaliyeva T. S., Mammadli T., Velikova, V., Barale, V., Kim Y. (2012). Review of the environment and bioresources in the Caspian Sea ecosystem CaspEco Report, pp 423. Waples R.S. (1987). A multispecies approach to the analysis of gene flow in marine shore fishes. Evolution 41, Welsh A., May B. (2006). Development and standardization of disomic microsatellite markers for lake sturgeon genetic studies. Journal of Applied Ichthyology 22, Zhao N., Ai W., Shao Z.l., Zhu B., Brosse S., Chang J. (2005). Microsatellites assessment of Chinese sturgeon (Acipenser sinensis Gray) genetic variability. Journal of Applied Ichthyology 21, Wright S. (1965). The interpretation of population structure by F-Statistics with special regard to systems of mating. Evolutionary 19,

439 FISHERMEN AND SEA TURTLE INTERACTION IN A PROTECTED AREA Konstas S. 1*, Katsikatsou M. 1, Deligiannaki M. 2 1 Amvrakikos Wetlands Management Body, Dimotiko Katastima Anezas, Aneza Arta, Greece 2 The sea turtle Protection Society of Greece ARCHELON, Solomou Athens, Greece Abstract The Amvrakikos Wetlands National Park is a Protected Area, in which a variety of threatened species live together with stakeholders that exploit the natural resources. This investigation deals with the antagonistic action between the fishermen and the loggerhead turtle Caretta caretta. A semi-structured questionnaire, which was used for the investigation, has shown that this antagonistic action is related to the decline of the fish stocks (encouraging the abuser-victim relation) and the seasonal fishing bans of some commercial species, i.e. the local shrimp Melicertus kerathurus (encouraging the unreported fishing). Keywords: fisheries, sea turtle,amvrakikos *Corresponding author: Konstas Spiros (foreas_amvrakikou@yahoo.gr) ΑΛΛΖΛΔΠΗΓΡΑΖ ΑΛΗΔΧΝ ΚΑΗ ΘΑΛΑΗΧΝ ΥΔΛΧΝΧΝ Δ ΜΗΑ ΠΡΟΣΑΣΔΤΟΜΔΝΖ ΠΔΡΗΟΥΖ Κψλζηαο. 1*, Καηζηθάηζνπ Μ. 1, Γειεγηαλλάθε Μ. 2 1 Φμνέαξ Γζαπείνζζδξ Τβνμηυπςκ Αιαναηζημφ, Γδιμηζηυ Καηάζηδια Ακέγαξ, Ακέγα Άνηαξ, Δθθάδα 2 φθθμβμξ βζα ηδκ Πνμζηαζία ηδξ Θαθάζζζαξ Υεθχκαξ ΑΡΥΔΛΧΝ, μθςιμφ Αεήκα, Δθθάδα Πεξίιεςε Σμ Δεκζηυ Πάνημ Τβνμηυπςκ Αιαναηζημφ απμηεθεί ιζα Πνμζηαηεουιεκδ Πενζμπή, ζηδκ μπμία ζοκοπάνπμοκ ιζα πμζηζθία απεζθμφιεκςκ εζδχκ ηαοηυπνμκα ιε έκα ιςζασηυ πνήζεςκ. Ζ ένεοκα αοηή αββίγεζ εέιαηα ακηαβςκζζηζηήξ δνάζδξ ηςκ αθζέςκ ιε ηδ εαθάζζζα πεθχκα Caretta caretta. φιθςκα ιε ημ διζ-δμιδιέκμ ενςηδιαημθυβζμ πμο πνδζζιμπμζήεδηε, ιπμνμφιε κα ζοιπενάκμοιε υηζ μ ακηαβςκζζιυξ αθζέα-εαθάζζζαξ πεθχκαξ ζπεηίγεηαζ ιε ηδ ιείςζδ ηςκ ζπεοαπμεειάηςκ (μπυηε εκεαννφκεηαζ δ ζπέζδ εφηδ-εφιαημξ) ηαζ ιε ηδκ επμπζηή απαβυνεοζδ αθίεοζδξ ηάπμζςκ ειπμνζηχκ εζδχκ, υπςξ δ κηυπζα γαξίδα Melicertus kerathurus (μπυηε εκεαννφκεηαζ δ θαεναία αθζεία). Λέξειρ κλειδιά: αιηεία, ζαιάζζηα ρειώλα, Ακβξαθηθόο οββναθέαξ επζημζκςκίαξ: Κχκζηαξ πφνμξ (foreas_amvrakikou@yahoo.gr) 1. Δηζαγσγή Ο εαθάζζζμξ πχνμξ ημο Αιαναηζημφ Κυθπμο ζοιπενζθαιαάκεζ 256 km αηημβναιιήξ ηαζ ειπίπηεζ ζημ Δεκζηυ Πάνημ Τβνμηυπςκ Αιαναηζημφ. Ο Αιαναηζηυξ Κυθπμξ απμηεθεί ιζα ηθεζζηή εαθάζζζα έηηαζδ 405 km 2 πενίπμο, ζηδκ μπμία ημ οδαηζηυ ζζμγφβζμ ελανηάηαζ απυ ηα δφμ ιεβάθα πμηάιζα πμο εηαάθθμοκ ζε αοηυκ, 439

440 ημ Λμφνμ ηαζ ημκ Άναπεμ. Αοηά ηα πμηάιζα είκαζ ηαεμνζζηζηά βζα ηδκ οδνμβναθία ηδξ πενζμπήξ ηαζ δδιζμφνβδζακ ηζξ πανάηηζεξ θζικμεάθαζζεξ (πενζζζυηενεξ απυ 20) ηαζ ζπάκζμοξ οβνυημπμοξ, πμο απμηεθμφκ μζηυημπμοξ πνμηεναζυηδηαξ ημο δζηηφμο NATURA2000. Ζ θεζημονβία ηςκ πμηαιχκ ηαεμνίγεζ ηα παναηηδνζζηζηά ηδξ εαθάζζζαξ έηηαζδξ ημο Αιαναηζημφ, δδθαδή ηα νεφιαηα, ηδ εενιμηναζία, ηδκ αθαηυηδηα ηαζ άθθα θοζζημπδιζηά ηαζ ςηεακμβναθζηά ζημζπεία ηδξ ζηήθδξ ημο κενμφ ημο. Σμ αάεμξ ημο Αιαναηζημφ αββίγεζ πενίπμο ηα 65 ιέηνα ημ ιέβζζημ, ςζηυζμ ιεβάθμ πμζμζηυ ηςκ πανάηηζςκ πενζμπχκ ηοιαίκεηαζ απυ 0 έςξ 5 ιέηνα αάεμξ. Ζ εαθάζζζα πεθχκα πνμζηαηεφεηαζ απυ εθθδκζηή, εονςπασηή ηαζ δζεεκή κμιμεεζία, εκχ παναηηδνίγεηαζ ςξ είδμξ απεζθμφιεκμ αάζεζ ηδξ ηυηηζκδξ θίζηαξ ηδξ IUCN. οβηεηνζιέκα, ημ είδμξ ακαθένεηαζ ζηζξ οιαάζεζξ ηδξ Οοάζζκβηημκ βζα ημ δζεεκέξ ειπυνζμ ηςκ απεζθμφιεκςκ εζδχκ (CITES), ηδξ Βένκδξ (πμο εκανιμκίζηδηε ιε ημ Νυιμ 1335/1983), ηδξ Βυκκδξ βζα ηδκ πνμζηαζία ηςκ ιεηακαζηεοηζηχκ εζδχκ, ηδξ Βανηεθχκδξ (UNEP πμο εκανιμκίζηδηε ιε ημ Νυιμ 1634/1986). ημ εθθδκζηυ δίηαζμ ακαθένεηαζ ημ Π.Γ. 617 (ΦΔΚ 163A/ ), πμο απαβμνεφεζ ηδκ αθζεία, ηδκ ηαηαζηνμθή ηςκ αοβχκ ηαζ ηδ ζοθθμβή κεμζζχκ ηαζ ημ Π.Γ 67 (ΦΔΚ 23A/ ηαζ 43A/ ) πμο παναηηδνίγεζ ηδκ Caretta caretta, Chelonia mydas, Dermochelys coriacea ςξ πνμζηαηεουιεκα είδδ πακίδαξ ηαζ απαβμνεφεζ ηδ εακάηςζδ, ηαημπμίδζδ, ειπμνία, ηαημπή, ηθπ.. ημ Δεκζηυ Πάνημ Τβνμηυπςκ Αιαναηζημφ οπάνπεζ έκα ιςζασηυ πνήζεςκ ηςκ θοζζηχκ πυνςκ, μζ μπμίεξ θαιαάκμκηαζ οπυρδ ηαηά ηδ δζαπείνζζδ. Οζ δζάθμνεξ πνήζεζξ θαιαάκμοκ πχνα ηυζμ ζημ πενζαίμ, υζμ ηαζ ζημ οδάηζκμ ηιήια ηδξ Πνμζηαηεουιεκδξ Πενζμπήξ. Οζ ηονζυηενεξ πνήζεζξ πμο απακηχκηαζ ζηδκ πενζμπή είκαζ δ βεςνβία, δ ηηδκμηνμθία ηαζ δ αθζεία. Οζ ηάημζημζ ημο ηυπμο αζπμθμφκηαζ ζε ιεβάθμ ααειυ ιε ημκ πνςημβεκή ημιέα ηαζ δεοηενεουκηςξ ιε ηδ ιεηαπμίδζδ ηςκ πνμσυκηςκ αοηχκ. Καηά ηδκ εκαζπυθδζή ημοξ μζ κηυπζμζ ιε ηδκ αθζεία ζε ιζα πενζμπή ιε ηέημζμ θοζζηυ πθμφημ, ένπμκηαζ ζοπκά ακηζιέηςπμζ ιε ακηαβςκζζηζηά άβνζα είδδ. Έκα ηέημζμ είδμξ είκαζ εαθάζζζα πεθχκα Caretta caretta, δ μπμία δε βεκκά ζημκ Αιαναηζηυ αθθά έπεζ έκημκδ πανμοζία ηαζ ηνέθεηαζ ζηδκ πενζμπή. Ο ακηαβςκζζιυξ ηδξ εαθάζζζαξ πεθχκαξ ιε ημοξ αθζείξ έβηεζηαζ ηονίςξ ζημ βεβμκυξ υηζ ηαζ μζ δφμ ράπκμοκ ηδκ ίδζα θεία. Φανεφμκηαξ ηα ίδζα πνάβιαηα ηαοημπνυκςξ οπάνπεζ ζοπκά ηαηαζηνμθή ηςκ αθζεοηζηχκ ενβαθείςκ απυ ηζξ εαθάζζζεξ πεθχκεξ. Δζδζηά βζα ηζξ μζηναημηαθθζένβεζεξ πμο είκαζ ζηαεενέξ εβηαηαζηάζεζξ, δ εαθάζζζα πεθχκα ανίζηεζ ανηεηή δζαεέζζιδ ηνμθή ζηζξ ανιαεζέξ ηζξ μπμίεξ ηαηαζηνέθεζ. Ζ ζφβηνμοζδ αοηή μλφκεηαζ ηαηά ηδκ ηαθμηαζνζκή πενίμδμ, υηακ δ πανμοζία ημο είδμοξ αολάκεηαζ. Σδκ ηαθμηαζνζκή πενίμδμ ακαβκςνίγμκηαζ ηαζ ηα πενζζζυηενα ηνμφζιαηα ρυθζςκ πεθςκχκ πμο λεανάγμκηαζ ζηζξ αηηέξ ηδξ Πνμζηαηεουιεκδξ Πενζμπήξ. Σμ εέια αοηυ είκαζ ιείγμκ βζα ηδ δζαηήνδζδ ηδξ άβνζαξ γςήξ, ηαεχξ πμθθμί απυ ημοξ πνήζηεξ εακαηχκμοκ ή ηαημπμζμφκ ηζξ πεθχκεξ αοηέξ, εεςνχκηαξ υηζ εα ιεζςεεί μ ανζειυξ ημοξ ή απυ εηδίηδζδ εθυζμκ δεκ έπμοκ πνμζηαζία απυ ηδκ Πμθζηεία. Σμ γήηδια αοηυ δζενεοκήεδηε υπςξ θαίκεηαζ παναηάης. 440

441 Δζηυκα 1: Θαθάζζζα πεθχκα Caretta caretta λεαναζιέκδ ζηδκ αηηή ζε πνμπςνδιέκδ ζήρδ 2. Τιηθά θαη Μέζνδνη Ζ δζενεφκδζδ έβζκε ιε ζοκεκηεφλεζξ διζ-δμιδιέκμο ενςηδιαημθμβίμο (Γεθδβζακκάηδ 2013), πμο πενζεθάιαακε ενςηήζεζξ ακμζπημφ ηαζ ηθεζζημφ ηφπμο. Σμ δείβια ηςκ ρανάδςκ ήηακ ηυζμ επαββεθιαηίεξ υζμ ηαζ εναζζηέπκεξ (9% ηςκ ενςηδεέκηςκ). Γζεκενβήεδηακ 45 ζοκεκηεφλεζξ ζε 20 πενζμπέξ ημο Δεκζημφ Πάνημο Τβνμηυπςκ Αιαναηζημφ. Ζ επζθμβή ημο δείβιαημξ έβζκε ιε βκχιμκα ηδκ ηάθορδ δζαθυνςκ ημιέςκ ςξ πνμξ ηα ενβαθεία/ιεευδμοξ αθζείαξ, ηφπμοξ ζηάθμοξ, δθζηία, έηδ άζηδζδξ ημο επαββέθιαημξ, ηφπμξ αθζεοηζηήξ άδεζαξ. Κονίανπα εέιαηα πμο άββζγε ημ ενςηδιαημθυβζμ ήηακ ηα αθζεοηζηά ενβαθεία ηαζ ζηάθδ πμο πνδζζιμπμζμφκ μζ ρανάδεξ πμο ενςηήεδηακ, ηα αθζεφιαηα πμο παβζδεφμοκ ιε αοηά ηαζ μζ ηάζεζξ αφλδζδξ ή ιείςζδξ πμο αθέπμοκ ζηα ζπεοαπμεέιαηα δζαθυνςκ εζδχκ (ειπμνζηχκ ηαζ ιδ ειπμνζηχκ). Οζ αθζείξ νςηήεδηακ βζα ηζξ πενζμπέξ ηαζ ηζξ επμπέξ πμο δναζηδνζμπμζμφκηαζ, ηί είδδ αθζεφμοκ ζοκήεςξ ηαζ πμφ/πυηε εκημπίγμοκ ηζξ πενζζζυηενεξ εαθάζζζεξ πεθχκεξ. Δπίζδξ, ζδιακηζηά ήηακ ηα ζημζπεία πμο πνμέηορακ βζα ηδκ ειπεζνία ηςκ ρανάδςκ βζα ηδκ πνμζηαζία ηαζ ηδκ μζημθμβία ηςκ εαθάζζζςκ πεθςκχκ, πχξ ηζξ ακηζιεηςπίγμοκ ηαζ ηί γδημφκ απυ ηδκ Πμθζηεία ζε ζπέζδ ιε ηδκ ηαηαζηνμθή ηςκ αθζεοηζηχκ ημοξ ενβαθείςκ. Σέθμξ, ημ ενςηδιαημθυβζμ πενζείπε ανζειδηζηέξ ενςηήζεζξ πνμηεζιέκμο κα δζαπζζηςεεί ακ μ ενςηδεείξ απακημφζε ιε αηνίαεζα ζηζξ ενςηήζεζξ ή ακ ήηακ αδζάθμνμξ πνμξ αοηέξ ηαζ απακημφζε απθχξ βζα κα πενάζεζ ημ πνυκμ ημο ή βζα κα ζηνεαθχζεζ ηδκ εζηυκα ηδξ ένεοκαξ. 3. Απνηειέζκαηα Σμ δθζηζαηυ πνμθίθ ημο δείβιαημξ ηςκ αθζέςκ πμο ζοιιεηείπακ ζηδκ ένεοκα ήηακ ηαηά ιέζμ υνμ 47 εηχκ (απυ 23 έςξ 80 εηχκ). Σα έηδ εκαζπυθδζδξ ηςκ αθζέςκ ήηακ ηαηά ιέζμ υνμ 23 πνυκζα εκαζπυθδζδξ ιε ηδκ αθζεία (απυ 2 έςξ 62 πνυκζα). Σα αθζεοηζηά ενβαθεία πμο ακαθένεδηακ ζηδκ ένεοκα είκαζ ζηαηζηά ενβαθεία βζα ηδκ άζηδζδ ηδξ πανάηηζαξ αθζείαξ ηαζ άθθα ενβαθεία νίρδξ. Γζα ηδκ πανάηηζα αθζεία ακαθένεδηακ ζπεομπαβίδεξ (αμθημί, κηαμφθζα), δίπηοα (ιακζςιέκα, απθάδζα, ζφκεεηα), παναβάδζα ηαζ άθθα ενβαθεία νίρδξ (πεγυαμθμξ).. Σα ενβαθεία αοηά πνδζζιμπμζμφκηαζ εονφηαηα ζηδκ πενζμπή απυ ηδκ πθεζμρδθία ηςκ ρανάδςκ ηαζ είκαζ ακηζπνμζςπεοηζηά. Σα ζηάθδ πμο ακαθένεδηακ υηζ πνδζζιμπμζμφκηαζ απυ ημοξ αθζείξ είκαζ ιζηνά αθζεοηζηά ζηάθδ, υπςξ είκαζ ηα πνζάνζα ηαζ μζ βαΐηεξ, ηα μπμία είκαζ αηανίκςηα παναδμζζαηά ζηάθδ ηδξ πενζμπήξ πμο πνδζζιμπμζμφκηαζ εονφηαηα βζα ηα αααεή. Δπίζδξ, ακαθένεδηακ ηαζ ιεβαθφηενα αθζεοηζηά ζηάθδ, υπςξ είκαζ μζ ηνάηεξ ηαζ ηα ηνεπακηήνζα. Σα είδδ ρανζχκ πμο αθζεφμκηαζ ζηδκ πενζμπή είκαζ ηεθαθμεζδή, ηζζπμφνα, ημοηζμιμφνα, ζανδέθα. Δπίζδξ, ζημκ Αιαναηζηυ Κυθπμ αθζεφμκηαζ πέθζα, βανίδα ηαζ ηεθαθυπμδα (ζμοπζέξ, πηαπυδζα). Ζ ιεβάθδ πθεζμρδθία (91%) ηςκ ρανάδςκ βκςνίγεζ υηζ δ πεθχκα Caretta caretta πνμζηαηεφεηαζ, αθθά δε ζοιθςκμφκ ιε 441

442 αοηυ, ηαεχξ δδθχκμοκ υηζ «έπεζ αολδεεί ηα ηεθεοηαία πνυκζα έκακηζ ηδξ πνάζζκδξ πεθχκαξ (Chelonia mydas) ηαζ δε πνήγεζ ζδζαίηενδξ πνμζηαζίαξ». Πμθθμί ρανάδεξ (42%) βκςνίγμοκ πςξ δ εαθάζζζα πεθχκα Caretta caretta πνδζζιμπμζεί ηδκ πενζμπή ςξ πεδίμ ηνμθμθδρίαξ, εκχ ανηεημί (34%) δεκ λένμοκ ημ θυβμ βζα ημκ μπμίμ δ εαθάζζζα πεθχκα είκαζ πανμφζα ζηδκ πενζμπή. Τπάνπεζ επίζδξ έκα ιζηνυ πμζμζηυ (10%) πμο δδθχκεζ υηζ ηζξ πεθχκεξ Caretta caretta «ηάπμζμζ ηζξ έθενακ ζημκ Αιαναηζηυ Κυθπμ», εκχ παθζυηενα δεκ οπήνπακ ζηδκ πενζμπή. Γζα ηζξ δζαηνμθζηέξ ζοκήεεζεξ ηςκ εαθάζζζςκ πεθςκχκ μζ αθζείξ απακημφκ υηζ ηνχκε ηα ράνζα ιαζχκηαξ ηα ζημ δίπηο αθήκμκηαξ ηνφπεξ ζημ δίπηο. Πμθθμί απακημφκ πςξ δ πεθχκα έπεζ πνμηίιδζδ ζηδκ ημοηζμιμφνα, έκακηζ ηςκ άθθςκ ρανζχκ πμο ανίζημοκ ζηα δίπηοα. Χζηυζμ, πμθθμί αθζείξ δδθχκμοκ πςξ δ εαθάζζζα πεθχκα έπεζ πνμηίιδζδ ζηα ράνζα πμο μζ ίδζμζ αθζεφμοκ. Σέθμξ, ηα αθζεοηζηά ενβαθεία ζηα μπμία πζάκμκηαζ μζ εαθάζζζεξ πεθχκεξ αθμνμφκ ηονίςξ δίπηοα 87%, δεοηενεουκηςξ ηαθάιζα/πεημκζέξ 7%, κηαθζάκζα 3% ηαζ παναβάδζα 3%. Πάκηςξ, ζδιακηζηυ πμζμζηυ ηςκ ρανάδςκ ζοιθςκεί υηζ ηα αθζεφιαηα θείκμοκ, ακηακαηθχκηαξ ηδκ παβηυζιζα ηάζδ ηςκ αθζεοηζηχκ πυνςκ. Έθενακ: Αβηίζηνζ Πεημκζά πμζκί Σναφια ζημ ηεθάθζ Σναφια ζημ ηααμφηζ Σναφια ζημ πηενφβζμ Άθθμ αίηζμ Πίλαθαο 1: Δκπινθή ζε αιηεπηηθά εξγαιεία θαη ηξαχκαηα πνπ έθεξαλ νη ζαιάζζηεο ρειψλεο Caretta caretta πνπ παξαηεξήζεθαλ ζην πεδίν θαηά ηε δηάξθεηα ηνπ θαινθαηξηνχ ηνπ 2013 Σξαπκαηηζκέλεο ρειψλεο Caretta caretta (20 απφ 131 πνπ καξθαξίζηεθαλ) θμζ μζ αθζείξ (100%) πμο νςηήεδηακ απάκηδζακ πςξ μζ ίδζμζ πνμζςπζηά ή ηάπμζμζ ηνίημζ έπμοκ ακηζιεηςπίζεζ πνμαθήιαηα ιε ηζξ εαθάζζζεξ πεθχκεξ. Ζ ζοκηνζπηζηή πθεζμρδθία ημοξ (69%) απακηά υηζ πνυηεζηαζ βζα ιεβάθδξ ηθίιαηαξ πνμαθήιαηα ζηα αθζεοηζηά ενβαθεία, ζδίςξ θίβα θεπηά ιεηά ημ λδιένςια. ηδκ ενχηδζδ πχξ ακηζιεηςπίγμοκ μζ ίδζμζ ηδκ πενίπηςζδ εβηθςαζζιμφ ζηα αθζεοηζηά ενβαθεία ημ 91% απάκηδζε πςξ ηζξ εθεοεενχκεζ εθυζμκ είκαζ αηυια γςκηακή, ημ 4% δεκ απάκηδζε, εκχ 2 αθζείξ (4%) απάκηδζακ υηζ ηζξ ζημηχκμοκ. Πανυθα αοηά υηακ νςηήεδηακ ακ λένμοκ βζα άθθμοξ αθζείξ υηζ αθάπημοκ εαθάζζζεξ πεθχκεξ, ημ 67% ηςκ ενςηδεέκηςκ απάκηδζε υηζ έπεζ αημφζεζ ζζημνίεξ υηζ άθθμζ ρανάδεξ ζημηχκμοκ ηζξ εαθάζζζεξ πεθχκεξ. Ακ ηαζ ακδζοπδηζηή, δ έιιεζδ αοηή πθδνμθμνία δεκ επζηνέπεζ πμζμηζηέξ εηηζιήζεζξ. Ζ άιεζδ παναηήνδζδ ηαζ ηαηαβναθή ημο ανζειμφ ηςκ κεηνχκ ή ηναοιαηζζιέκςκ γχςκ ηαζ μζ δζαπνμκζηέξ ηάζεζξ ημο παναιέκεζ δ πζμ απμδμηζηή ιέεμδμξ. 442

443 Πίλαθαο 2: Απεηιέο γηα ηελ Caretta caretta ζε ζηεξηά θαη ζάιαζζα ζηελ πεξηνρή ηνπ Δζληθνχ Πάξθνπ θαη πξνηεξαηφηεηα αληηκεηψπηζεο ΑΠΔΗΛΔ Δζθεκκέλε ζλεζηκόηεηα/ηξαπκαηηζκνί Υηοπήιαηα ζε ηεθάθζ ηαζ ηααμφηζ, ηναφιαηα ζε πηενφβζα Με εζθεκκέλε ζλεζηκόηεηα Καηάπμζδ παβίδεοζδ ζε αβηίζηνζα ηαζ πεημκζέξ Παβίδεοζδ ζε δίπηοα Σναφιαηα ζε ηεθάθζ ηαζ ηααμφηζ απυ πνμζηνμφζεζξ ζε ζηάθδ ΠΡΟΣΔΡΑΗΟΣΖΣΑ ΑΝΣΗΜΔΣΧΠΗΖ Τρδθή Μέζδ (Ακάβηδ δζενεφκδζδξ) Μέζδ (Ακάβηδ δζενεφκδζδξ) Τρδθή 4.πδήηεζε Καηά ηδ δζελαβςβή ηδξ ένεοκαξ θάκδηε υηζ μζ ρανάδεξ έπμοκ έκα ακηζηεζιεκζηυ πνυαθδια, πμο ζπεηίγεηαζ ιε ηζξ γδιίεξ πμο πνμηαθμφκηαζ ζηα αθζεοηζηά ημοξ ενβαθεία υηακ μζ εαθάζζζεξ πεθχκεξ ειπθαημφκ ζε αοηά. Οζ έιπεζνμζ αθζείξ δζαπζζηχκμοκ ζε ιεβάθμ πμζμζηυ ηδκ ιείςζδ ηςκ ζπεοαπμεειάηςκ ζε ζπέζδ ιε ημ πανεθευκ, ηάηζ ημ μπμίμ ιενζημί απυ αοημφξ ζπεφδμοκ κα ημ απμδχζμοκ ηαζ ζηζξ εαθάζζζεξ πεθχκεξ Caretta caretta. εκχ ηαοηυπνμκα δεκ είκαζ ανκδηζημί πνμξ ηζξ πνάζζκεξ πεθχκεξ Chelonia mydas, πμο δδθχκμοκ πςξ ήηακ μζ ιυκεξ πανμφζεξ παθζυηενα ζηδκ πενζμπή. οιπεναζιαηζηά, απυ ηδκ ένεοκα ηαζ απυ ζημζπεία πνμδβμφιεκςκ εηχκ πνμηφπηεζ υηζ, πανυθα ηα πνμαθήιαηα πμο δδιζμονβμφκ μζ εαθάζζζεξ πεθχκεξ Caretta Caretta ζηα αθζεοηζηά ενβαθεία ηςκ αθζέςκ, δ εζηειιέκδ εακάηςζδ ηςκ πεθςκχκ απυ ημοξ αθζείξ έπεζ ηδκ ηάζδ κα πενζμνίγεηαζ.. Δκδεζηηζηυ είκαζ υηζ πμθθμί αθζείξ οπμζηήνζλακ θζθμπενζααθθμκηζηέξ εέζεζξ ηαζ έδεζλακ εοαζζεδζία βζα ηζξ εαθάζζζεξ πεθχκεξ, ακαβκςνίγμκηαξ ηδ ζδιαζία ημοξ βζα ημ μζημζφζηδια ημο Αιαναηζημφ Κυθπμο. οκεπχξ μζ ιαηνμπνυκζεξ πνμζπάεεζεξ εκδιένςζδξ ηαζ εοαζζεδημπμίδζδξ θαίκεηαζ κα απμδίδμοκ. Σμ θαζκυιεκμ ηδξ εζηειιέκδξ εακάηςζδξ ηςκ εαθαζζίςκ πεθςκχκ ζπεηίγεηαζ άιεζα ιε ηδ θαεναία αθζεία (ππ. δίπηοα, ζονυιεκα ενβαθεία), υπςξ δείπκμοκ ηα δεθηία εηεαθάζζςζδξ εαθάζζζςκ πεθςκχκ (φθθμβμξ βζα ηδκ Πνμζηαζία ηδξ Θαθάζζζαξ Υεθχκαξ ΑΡΥΔΛΧΝ). Γζα πανάδεζβια, μζ εηεαθαζζχζεζξ ηαημπμζδιέκςκ εαθάζζζςκ πεθςκχκ αολάκμκηαζ ηδκ ηαθμηαζνζκή πενίμδμ, υηακ δ πανμοζία ηδξ εαθάζζζαξ πεθχκαξ αολάκεηαζ ηαζ λεηζκά δ απαβυνεοζδ ηδξ αθίεοζδξ ηδξ βάιπανδξ (Melicertus kerathurus). Ο πενζμνζζιυξ ηδξ θαεναθζείαξ εα ζοκεζζθένεζ ζδιακηζηά ζηδκ πνμζηαζία ημο είδμοξ πενζμνίγμκηαξ ημοξ δεεθδιέκμοξ ηναοιαηζζιμφξ ή εακαηχζεζξ. Μζα αηνζαέζηενδ πενζβναθή ηαζ εηηίιδζδ ηςκ αημοζίςκ ηναοιαηζζιχκ εα ιπμνμφζε κα αμδεήζεζ ζημκ πενζμνζζιυ ηαζ αοημφ ημο θαζκμιέκμο. Γζα ηδκ ακηζιεηχπζζδ ηςκ ζοιαάκηςκ αοηχκ, είκαζ απαναίηδηδ ιζα ιαηνμπνυεεζιδ εηζηναηεία εκδιένςζδξ ιε ζημπυ ηδκ αθθαβή ηδξ ζηάζδξ ηςκ πνδζηχκ έκακηζ ηςκ εζδχκ ηδξ άβνζαξ πακίδαξ. Με ηδκ εηζηναηεία εκδιένςζδξ πνμηείκεηαζ πανάθθδθα κα βίκεζ εκδιένςζδ βζα ηδκ μζημθμβία ηςκ εζδχκ ηδξ άβνζαξ πακίδαξ. διακηζηή ηνίκεηαζ δ ζοζπέηζζδ ηςκ αθζεοηζηχκ ενβαθείςκ, ηςκ εακάηςκ ηςκ πεθςκχκ ηαζ ηδξ πνυηθδζδξ γδιζχκ ζημοξ αθζείξ απυ ηζξ εαθάζζζεξ πεθχκεξ, δ μπμία απαζηεί δζαθμνεηζηή ιεεμδμθμβία (Laurent et al. 2001, Margaritoulis et al. 2003, Deflorio et al. 2005, FISH/2005/28A Final Report to the the Directorate- General for Fisheries and Maritime Affairs 2008) ιε ελεζδζηεοιέκμ ζπεδζαζιυ βζα ηδ ζοθθμβή ηςκ δεδμιέκςκ ηαζ δνάζεζξ υπςξ: πανμοζία ενεοκδηχκ (onboard-observers) ζε αθζεοηζηά ζηάθδ βζα ηδκ επζηυπμο ηαηαβναθή ημο θαζκμιέκμο, εεεθμκηζηή ηαηαβναθή απυ ζοκενβαγυιεκμοξ αθζείξ, ένεοκα ιε ενςηδιαημθυβζα, δζαηναηζηή ζοκενβαζία ηθπ. Ζ ένεοκα δζελήπεδ ζηα πθαίζζα ημο Γζαζοκμνζαημφ Πνμβνάιιαημξ Δδαθζηήξ οκενβαζίαξ «Δθθάδα- Ηηαθία » PRO.ACT.NATURA2000 ηαζ εκηάζζεηαζ ζημκ Άλμκα πνμηεναζυηδηαξ 3 «Βεθηίςζδ ηδξ πμζυηδηαξ γςήξ, πνμζηαζία ημο πενζαάθθμκημξ ηαζ ακάπηολδ ηδξ ημζκςκζηήξ ηαζ πμθζηζζηζηή ζοκμπήξ» ηυπμξ 3.2: Πνμχεδζδ ηαζ αεθηίςζδ ηδξ απυ ημζκμφ πνμζηαζίαξ ηαζ δζαπείνζζδξ ηςκ θοζζηχκ πυνςκ, πνυθδρδ ηςκ θοζζηχκ ηαζ ηεπκμθμβζηχκ ηζκδφκςκ βζα ημ Φμνέα Γζαπείνζζδξ Τβνμηυπςκ Αιαναηζημφ. 443

444 Βηβιηνγξαθία Φμνέαξ Γζαπείνζζδξ Τβνμηυπςκ Αιαναηζημφ (2014). Γνάζεζξ Δλςηενζηήξ Δλεζδίηεοζδξ ηαζ Τπδνεζζχκ (External Expertise and Services). European Territorial Cooperation Programme, Greece Italy , Investing in our Future. Deflorio M., Aprea A., Corriero A., Santamaria N., De Metrio G. (2005). Incidental captures of sea turtles by swordfish and albacore longlines in the Ionian sea. Fisheries Science 71: Κεθάιαην ζε βηβιίν Γεθδβζακκάηδ Μανίκα (2013). Πνςημβεκή δεδμιέκα Δνςηδιαημθυβζα ένεοκαξ. Φμνέαξ Γζαπείνζζδξ Τβνμηυπςκ Αιαναηζημφ. Γνάζεζξ Δλςηενζηήξ Δλεζδίηεοζδξ ηαζ Τπδνεζζχκ (External Expertise and Services). European Territorial Cooperation Programme, Greece Italy , Investing in our Future. Laurent L., Camiñas J.A., Casale P., Deflorio M., DeMetrio G., Kapantagakis A., Margaritoulis D., Politou C.Y., Valeiras J. (2001). Assessing marine turtle bycatch in European drifting longline and trawl fisheries for identifyiong fishing regulations. Project EC-DG Fisheries Joint project of BioInsight, IEO, IMBC, STPS and University of Bari. Villeurbanne, France. 267 pp. Margaritoulis D., Argano R., Baran I., Bentivegna F., Bradai M.N., Caminas J.A., Casale P., De Metrio G., Demetropoulos A., Gerosa G., Godley B.J., Haddoud D.A., Houghton J., Laurent L., Lazar B. (2003). Loggerhead turtles in the Mediterranean Sea: Present knowledge and conservation perspectives. Pages in Loggerhead Sea Turtles (editors: A.B. Bolten and B.E. Witherington). Smithsonian Books, Washington DC. 319 pp. Ζιεθηξνληθή Βηβιηνγξαθία φθθμβμξ βζα ηδκ Πνμζηαζία ηδξ Θαθάζζζαξ Υεθχκαξ ΑΡΥΔΛΧΝ. Γεθηίμ εηεαθάζζςζδξ εαθάζζζςκ πεθςκχκ (Πνυζααζδ ) Φμνέαξ Γζαπείνζζδξ Τβνμηυπςκ Αιαναηζημφ (Πνυζααζδ ) FISH/2005/28A Service Contract SI Assessment of turtle bycatch. Final Report to the the Directorate-General for Fisheries and Maritime Affairs, February (2008) (Πνυζααζδ ) 444

445 GENETIC STRUCTURE OF GOLDEN MULLET, Liza aurata, USING MICROSATELLITE MARKERS Behruz M. 1, Norouzi M. 1 *, Amirjanati A. 1 1 Department of Marine Biology and Fisheries Sciences, Tonekabon Branch, Islamic Azad University, Tonekabon, Iran. ABSTRACT Genetic structure of golden mullet, Liza aurata, investigated in the Fereydoon-Kenar and Raamsar costs (south Caspian Sea, Iran) using 6 microsatellite markers designed for gray mullet (Mugil cephalus) and hand mullet (M. soiuy). Totally 60 samples of adult golden mullet were collected from these regions. All primer sets as polymorphic loci were used to analyze the genetic variation. Analyses revealed that average of alleles (Na) per locus was 6.2 (range 3 to 9 alleles). All sampled regions contained private alleles. The average estimates of inbreeding coefficient (Fis) values of 6 microsatellites were positive. The average observed and expected heterozygosity was and respectively. Deviations from Hardy-Weinberg equilibrium were in all cases (P<0.001). F-statistics (Fst) and gene flow (Nm) estimates in allele frequencies were and 2.9 respectively. Rst and Fst estimates in AMOVA indicated significant genetic differentiation among regions (P<0.01). Genetic distance was 0.679, indicating that the genetic difference among the studied populations is pronounced. The data generated in this study provides the genetic variation and differentiation in populations of golden mullet in the southern Caspian Sea (Mazandaran province). Keywords: golden mullet, Liza aurata, population genetic, microsatellite, Caspian Sea *Corresponding author: Mehrnoush Norouzi (mnoroozi@toniau.ac.ir) Introduction Golden grey mullet, Liza aurata (Risso, 1810) is a typical marine schooling fish. It was introduced into the Caspian from the Black Sea (targeted acclimatization) and spread widely within the Caspian Sea, except for the estuarine sea areas. Golden grey mullet is found in the southern part of the sea throughout the year; in the Middle Caspian it appears in spring and migrates back to the south in autumn. It is rarely caught in the northern part of the sea, except in Mangyshlak area. In early March, following the rise in water temperature, it starts migration from the southern feeding grounds. In April, it appears in the Middle Caspian. During migration, it feeds intensively, preferring shallow coastal areas (Velikova et al., 2012). Golden mullet is a euryhaline fish, sensitive to a decrease in water temperature. Age of maturity 3-4 years old. Spawning takes place in the open sea, at great depths ( m) and upon available aquatic vegetation. The species winters in the southern part of the Caspian. The fish is concentrated mostly in the sectors with rich marine vegetation and in areas with muddy bottoms. During the south-east winds, it moves off the shoreline notably and its concentration reduces. During the north - east winds and in still weather, the density of fish in the coastal zone increases significantly. Golden mullet is a valuable commercial fish. The second mullet species introduced from the Black Sea to the Caspian is Liza saliens Popov, The two Caspian mullet species are not separated (itemized) in fishery statistics; however, golden mullet prevails (up to 1.5 thousand tons) in the total mullet catches (Velikova et al., 2012). 445

446 Among molecular techniques, microsatellite markers are seen as the best way to identify the population structures of pelagic marine fishes because they are abundantly distributed across the genome, demonstrate high levels of allele polymorphism and can easily be amplified with PCR (Sekar et al., 2009). Microsatellite genotypes are particularly helpful in the detection of structure in closely related populations, regardless of whether they are in evolutionary equilibrium. Additionally, primers designed for one species can often be used in other related species (Chistiakov et al., 2005). So, the objectives of the present study are to investigate the genetic structure of the Golden grey mullet and test the hypothesis that the Golden mullet has an identical population in different regions of the South Caspian Sea (Mazandaran province). 2. Materials and Methods The fishes were caught from two different regions, including 30 samples from Fereydoon-Kenar and 30 samples from Raamsar costs (south Caspian Sea, Iran) (Figure.1). Fin tissue samples were prepared from 60 fishes of each location and preserved in 95% ethanol and stored at room temperature. Genomic DNA was extracted from fin tissue using a high pure PCR Template preparation kit (Roach, Germany) according to the manufacturer s instructions. The quality and concentration of DNA were assessed by 1% agarose gel electrophoresis and spectrophotometry (CECIL model CE2040) and then stored at -20 C until use. The nuclear DNA was amplified using 6 microsatellite primers designed for M. cephalus (Muce-55, 37, Xu et al., 2010) and M. soiuy (Muso10, 16, 19, 22, Xu et al., 2009). PCR products were electrophoresed on 10% polyacrylamide gels (29:1 acrylamide: bis-acrylamide; 1X TBE buffer) and followed by silver-staining. Gels were run at 40 ma for 14h. Alleles were sized using Uvitec software, and each gel contained an allelic ladder (100bp) to assist with consistent scoring of alleles. Allelic frequencies, observed and expected heterozygosities (Ho and He), genetic distance (Nei, 1972), genetic identity, Fst and Rst value, Nm, Hardy-Weinberg (HW) tests of equilibrium, and AMOVA were computed in GeanAlex 6.0 software (Peakall and Smouse, 2006). AMOVA calculations and allelic richness (AR) were performed on Arlequin 3.5 (Excoffier & Lischer 2010) using 10,000 permutations in each case. The Cornuet and Luikart (1996) programme BOTTLENECK ver was used to detect recent effective population size reduction (to assess the impact of population decline) using data from the microsatellites under the more suitable two-phased model (TPM). Figure 1. Map showing sampling locations of populations of L. aurata: Fereydoon-Kenar and Raamsar costs. 446

447 3. Results All primer sets as polymorphic loci were used to analyze the genetic variation. All microsatellite primers that were able to produce DNA bands displayed a characteristic disomic banding pattern (Figures 2, 3). The allele frequencies at all loci are given in Table 1. The average number of alleles found per site was 6.2, and the number of alleles in Muso10 ranged from 4 to 6 (AR=8), in Muso16 from 3 to 7 (AR=6), in Muso19 from 9 to 9 (AR=8), in Muso22 from 9 to 9 (AR=11), in Muce-37 from 5 to 9 (AR=9), in Muce-55 from 8 to 5 (AR=8). Out of 53 observed alleles, 21 alleles occurred at frequencies of less than 0.05 in all samples. All the populations sampled contained private alleles at a significant level (P < 0.05). The observed and expected heterozygosity averaged and , respectively; the observed heterozygosity ranged from in Raamsar to in Fereydoon-Kenar (Table 1). Bottleneck analysis of golden mullet was in Fereydoon-Kenar and in Raamsar. Estimates of inbreeding coefficient or Fis values were between at Muso -37 and at Muso-10 (mean Fis= 0.483; Table 2), and positive Fis values a relative dearth of heterozygotes. To test the departures from Hardy-Weinberg equilibrium were significant (P< 0.01) (Table 1). The Fst, Rst, and gene flow, as analyzed with AMOVA, showed a significant genetic differentiation among sites (P< 0.01), which suggested that the populations diverged from each other. The genetic distance and genetic identify computed by Nei (1972) between populations was and respectively. Figure 2. Microsatellite banding profile of L. aurata using primer pair Muso10. Figure 3. Microsatellite banding profile of L. aurata using primer pair Muso

448 Table 1. Numbers of allelles observed within 2 sampling sites using 6 sets of microsatellite primers. Number of studied samples (n), Observed (Ho) and expected (He) heterozygosities, number of alleles (Na), effective allele (Ne) at 6 loci in two sampling sites. Loci in accordance with H-W equilibrum *P < 0.05; **P < 0.01; ***P < 0.001; ns= not significant. Loci Regions Touchdown protocol Raamsar Fereydoon-Kenar F is Actual size (bp) Muso10 Na/Ne 6/ / / o C/ 30 Ho/He 0.167*** / *** / Muso16 Na/Ne 3/ / / o C/ 30 Ho/He 0.167***/ *** / Muso19 Na/Ne 9/ / / o C/ 30 Ho/He 0.267*** / *** / Muso22 Na/Ne 5/ / o C/ 40 Ho/He 0***/ *** / Muce-37 Na/Ne 9/ / / o C/ 25 Ho/He 1*** / ***/ Muce-55 Na/Ne 5/ / / o C/ 40 Ho/He 0.700***/ ** / Average Na/Ne 6.167/ / /483 Ho/He / / Discussion The results of the study on golden mullet fish shows that the obtained allelic average in this study (9.5) is less than the declared range (19.9±6.6) for saltwater fish (Dewoody and Avis, 2000). Also, in this study some allele have been observed with low frequency. This may be due to overfishing of this species in recent years. In previous years, due to overfishing of mullet, whose average weight was only 210 g, its resources have been damaged severely. In general, low number of alleles is a sign of genetic bottleneck which perhaps is occurred in wild population condition due to the isolation of population or a great reduction in its effective size. Since golden mullet fish is not indigenous to Caspian Sea, it is likely that the small founder population which first came to Caspian Sea from Black Sea is the cause of reduction in allelic variation. The results of this study confirm this because many alleles with low frequency are the sign of genetic bottleneck or the result of inbreeding. Average of inbreeding coefficient (Fis) which is positive for these two regions also supports this idea. The average heterozygosity observed in this study (0.394±0.1) is less than the declared amount for marine water fish (0.77±0.22) (Dewoody and Avis, 2000). In both sampling regions there have been places in which the 448

449 observed heterozygosity was less than the expected amount. However, the observed reduced heterozygosity compared to expectable heterozygosity, reduction in allelic variation and also existence of alleles with low frequency can be due to reasons like overfishing and environmental causes like pollutants which reduce the natural breeding of this fish. Undoubtedly, the golden mullet stock in the Caspian Sea is in a critical condition and is suffering more damage every year. Recently, unfavorable hydrological conditions related to climate change have had a negative impact on the sustainability of exploitable yield of golden mullet; the thermal structure of the upper layers of the sea has been detrimental to the species, and there has also been poor vertical mixing of surface and deeper water (Velikova et al., 2012). Reduction in genetic variation increases the possibility of becoming ill and other selective factors and as a result it decreases size of population (Shen and Gong, 2004). Since in this study the average of inbreeding coefficient was positive, It is possible that first parents were selected from one or two places near to each other in Black Sea or genetic variation of this species is low in Black Sea,and it may also be related to sampling from Admixture of stocks due to specific feeding grounds or nursery areas for reproduction, sufficient information on location of the harvest is not available (Ghodsi et al., 2011). Considering Hardy-Weinberg equilibrium, all places in every location were out of equilibrium (p<0.001). The cause of deviation from equilibrium was sample mixing, population combination and sampling error (since the populations were small and samples were low in number). Fst based on allelic frequency was which shows average genetic differentiation (Balloux et al. 2002). Genetic flow was calculated to be 2.9. Fst and Rst via AMOVA for Codominant data in all sampling site were significant (P 0.01). So the populations are separated from each other, suggesting that at least two populations are genetically differentiated and do not represent a single panmictic population. High capacity of dispersion which is probably due to lack of physical or ecological barriers in south coast of Caspian Sea, leads to high contact in sub-populations when they migrate and this is the reason of the average population structure for this species. Shaklee (1982), Thorpe and Sole-Cava (1994) showed that the Nei (1972) genetic distance for separation of populations is said to be 0.3 in average (from 0.03 to 0.61) which is compatible to the observed genetic distance and confirms genetic differentiation among observed populations. This study shows the preliminary results and reasons for the existence of different populations of golden mullet fish in two regions of Fereydoon-Kenar and Raamsar costs. The existence private alleles and significant Fst and Rst confirm that different populations in two regions. The losses of genetic diversity may increase with bottlenecking for this species in Caspian Sea. The small founder population which first came to Caspian Sea, overfishing and environmental pollution of the sea are the causes of reduction in population size which leads to reduction in allelic variation of the fish. Also, inbreeding is the reason of allelic variation reduction in every sampling location. It is possible that members of the same family were sampled or it is because of low genetic variation in mullet fries who first came from Black Sea to Caspian Sea. Private alleles, difference in frequency of dominant alleles in every sampling location and the index of significant differentiation show that different populations exist in south of Caspian Sea in coast of Mazandaran. Acknowledgments The study was supported by Islamic Azad University, Tonekabon Branch and was performed in Molecular Genetic Lab. We would like to thank Dr. Nazemi (Dept. of Biology). 449

450 References Balloux F., Lugon-Moulin N. (2002). The estimate of population diffraction with microsatellite markers. Molecular Ecology 11, Chistiakov D.A., Hellemans B., Haley C.S., Law A.S., Tsigenopoulos C.S., Kotoulas G., Bertotto D., Libertini A., Volckaert F.A. (2005). A microsatellite linkage map of the European sea bass Dicentrarchus labrax L. Genetics. 170, Cornuet, J. M., Luikart G. (1996). Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics 144, Excoffier L., Lischer H.E.L. (2010) Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology Resource 10, Ghodsi Z., Shabani A., Shabanpur B. (2011). Genetic diversity of Liza aurata (Risso, 1810) in the coastal regions of Golstan province, using microsatellite marker. Taxonomy and Biosystematics. 6, Nei M. (1972). Genetic distance between populations. American Naturalist 106, Peakall R., Smouse P.E. (2006). GenAlEx 6: Genetic Analysis in Excel. Population genetic software for teaching and research. The Australian National University Canberra Australia. Available at: Sekar M., Suresh E., Kumar N.S., Nayak S.K., Balakrishna C. (2009). Microsatellite DNA markers, a fisheries perspective Part 1: The nature of microsatellites. Aquaculture Asia Magazine. pp Shaklee J.B., Tamaru CS, Waples R.S. (1982). Speciation and evolution of marine fishes studied by electrophoretic analysis of proteins. Pacific Science. 36, Thorpe JP, Sole-Cava A.M. (1994). The use of allozyme electrophoresis in invertebrate systematics. Zoologica Scripta. 23, Velikova V.N., Shaudanov A.K., Gasimov A., Korshenko A., Abdoli A., Morozov B., Katunin D. N., Mammadov E., Bokova E. B., Emadi H., Annachariyeva J., Isbekov K., Akhundov M., Milchakova, N., Muradov O., Khodorevskaya R., Shahifar R., Shiganova, T., Zarbaliyeva T. S., Mammadli T., Velikova, V., Barale, V., Kim Y. (2012). Review of the environment and bioresources in the Caspian Sea ecosystem CaspEco Report, 423P. Welsh A., May B Development and standardization of disomic microsatellite markers for lake sturgeon genetic studies. Journal of Applied Ichthyology. 22, Xu, G., Shao, Ch., Liao, X., Tian, Y., and Chen, S Isolation and characterization of polymorphic microsatellite loci from so-iuy mullet (Mugil soiuy Basilewsky 1855). ConservationGenetetics 10: Xu, T.-j., Sun, D.-Q.,Shi,G, Wang, R-X., Devlopment and characterization of polymorphic microsatellite markers in the gray mullet (Mugil cephalus), Gentics and Molecular Research. 9,

451 CONTENTS OF Cu AND Zn IN BOGUE, Boops boops AND PICAREL, Spicara smaris FROM THE KISSAMOS GULF, CRETE Skordas K.,* Korakaki D., Kosmidis D., Nikolaou M., Neofitou N., Panagiotaki P. Department of Ichthyology and Aquatic Environment, School of Agricultural Sciences, University of Thessaly, Fytokou St, N. Ionia, 38446, Volos, Greece Abstract This preliminary study deals with the contents of copper and zinc in muscle tissue of Boops boops and Spicara smaris, the two most commercial species caught in the Kissamos Gulf in Crete. The metal contents in muscle were determined using the USEPA Method Determinations of copper (Cu) and zinc (Zn) contents were carried out using a flame atomic absorption spectrometer (Flame AAS). The mean content of copper in B. boops was 9.60 ± 3.65 ιg kg -1 and the mean figure for zinc was ± 5.36 mg kg -1, while in S. smaris were 6.98 ± 2.46 ιg kg -1 and ± 3.24 mg kg -1 respectively. The estimated daily intake of copper and zinc was calculated and an assessment of the health risk to consumers was made. Σhe heavy metal contents in the edible part (muscle) of fish caught in the Kissamos Gulf did not exceed permissible limits and therefore their consumption should be considered safe for human health. Key words: Copper, Zinc, Boops boops, Spicara smaris, Eastern Mediterranean *Corresponding author: Konstantinos Skordas (kskord@apae.uth.gr) 1. Introduction Many fish species are widely used as indicators of pollution of the aquatic environment (Marks et al. 1980) and they play an important role in environmental research (Evans et al. 1993). Metals, such as Fe, Zn, Cu, Se and Mn are essential for metabolic functioning in fish but become toxic for the organism when their contents are excessive, also causing problems for human health when fishes are consumed (Prego & Cobelo-Garcia 2003; Vlahogianni et al. 2007; Mayor & Solan 2011). Heavy metals are considered to be among the most dangerous pollutants of the marine environment because they do not degrade and thus they remain unchanged in the aquatic environment (McIntyre 1995). Consequently they represent a long-term selective pressure depending on their chemical form and bioavailability (Cukrov et al. 2011). Furthermore, bio-accumulated heavy metals can be bio-magnified via the food chain, resulting in health risks when finally assimilated by human consumers (Agah et al. 2009). In aquatic ecosystems metals are found in low contents. Since they do not degrade in water, and cannot be deposited in sediments or digested (Abdel-Baki et al. 2011), heavy metals bio-accumulate in aquatic organisms and they may become toxic when their contents reach high levels (Huang 2003). The determination of heavy metal contents in fish provides useful information on their suitability as food for humans, as well as contributing to an overall assessment of pollution in the environment (Forstner & Wittman 1983). The purpose of this preliminary study was to examine the content of copper and zinc in B. boops and S. smaris which are the two most commercially important species intended for human consumption that are caught in the Gulf of Kissamos in Crete. In addition, the study gives an estimation of the degree of risk to humans from heavy metals in these two species. The results of this study give a complete picture of the content of the two metals in the two most commercial species and the degree of risk to the consumer. 2. Materials and methods Sampling of B. Boops and S. smaris was carried out on catches by professional fishermen during September 2012 in the Kissamos Gulf. For this study, a total of 30 individuals of each species were selected (n=60). To avoid any possible variability due to the growth stage of the fish, the specimens chosen were of approximately the same age and size (commercial size). Immediately after collection the fish were killed on ice and then transferred to the laboratory in insulated boxes full of ice to avoid any contamination. After sample collection, total length (TL) and fork length 451

452 Contents of Cu (κg kg -1 ) HydroMedit 2014, November 13-15, Volos, Greece (FL), accurate to 0.1 cm, and total weight (TW) to the nearest 0.01 g were recorded (B. boops: n = 30, TW = g, TL = cm and S. smaris: n = 30, TW = g, TL = cm). Metal contents were determined using USEPA Method 3052 (1996) for microwave-assisted acid digestion of siliceous and organically based matrices. All samples of fish muscle tissue were homogenised and stored in a dry environment until digestion. For total dissolution, 9 ml of concentrated HNO 3 were added to 0.5 g of muscle tissue in acid-cleaned Teflon vessels. The vessels were sealed and placed in a closed, high-pressure microwave system (Multiwave 3000, Anton Paar, Austria). After digestion, the samples were diluted with ultrapure water in 50 ml volumetric flasks and stored in polypropylene sample bottles at 4 ºC until further analysis. Quantitative determinations of copper (Cu) were carried out with a graphite furnace atomic absorption spectrometer (GF AAS), while for zinc (Zn) they were carried out with a flame atomic absorption spectrometer (Flame AAS), using standard addition methods. The estimation of human health risk from consumption of wild fish from the Kissamos Gulf in Greece was assessed according to Onsanit et al. (2010). The human health risk was assessed and then comparisons of mean metal contents with internationally established food safety standards for edible fish tissues were made. 3. Results Figures 1.1 and 1.2 show the results for contents of copper and zinc in muscle tissue separately for each species. The average content of copper in B. boops was 9.60 ιg kg -1 and the average figure for zinc was mg kg -1, while in S. smaris the contents were 6.98 ιg kg -1 and mg kg -1 respectively B. boops S. Smaris Figure 1.1: Mean ± SD contents of copper in muscle tissue of B. Boops and S. smaris (κg kg -1 dry wt). 452

453 Contents of Zn (mg kg -1 ) HydroMedit 2014, November 13-15, Volos, Greece B. boops S. Smaris Figure 1.2: Mean ± SD contents of zincnin muscle tissue of B. Boops and S. smaris. The estimation of human health risk from consumption of wild fish from the Kissamos Gulf in Greece was assessed according to Onsanit et al. (2010). An average adult body weight of 70 kg in the general population and an average consumption of g/d of wild fish were the figures used to calculate estimated daily intake (EDI; ιg/kg bw/d) of analytes (FAO, 2010; Stirling Institute of Aquaculture, 2004). Comparisons of mean analyte contents with permitted limits for edible fish tissues were made. The estimated daily intake (EDI, ιg/kg bw/d) of copper and zinc was calculated (Table 1) and compared with the Allowed Daily Intake (ADI) and with Reference Doses (RfD). The daily intake (ιg/kg bw/day) was calculated using the following equation: EDI = C fish *[ dc fish /bw] Where C fish = average trace element content in fish muscle (κg/g wet weight), dc fish = daily fish consumption (g/day) per capita as recorded by the FAO (2008) and bw = average body weight (kg) of the target population. The hazard quotient (HQ) was calculated by dividing the estimated daily intake (EDI) by the established RfD to assess the health risk from fish consumption. There would be no obvious risk if the HQ were less than 1. For an average consumer in Greece, the estimated daily intake of copper and zinc from the consumption of wild B. boops and S. smaris is lower than the Allowed Daily Intake (ADI) and the Reference Doses (RfD) of these metals (JECFA 2003, Ikem & Egilla 2008, Onsanit et al. 2010, USEPA 2012) (Table 1). The hazard quotient (HQ) for both species is less than 1 in all cases. Table 1: Daily intake of trace elements by Greeks through consumption of marine fish. Estimated daily intake (EDI, κg/kg bw/d) of wild fish (n = 60) caught in the Kissamos Gulf, allowed daily intake (ADI), ADI 1 is calculated from the provisional tolerance weekly intake set by the JECFA (2003) while ADI 2 is calculated from Ikem & Egilla (2008), and reference doses (RfD, ιg/kg bw/d) of trace elements as established by the United States Environmental Protection Agency (2012). Species Copper Zinc EDI B. boops S. smaris ADI ADI RfD

454 4. Disscussion Comparing the average contents of copper and zinc in the muscle tissue of the two species caught in this area, higher contents of the metals were observed in B. boops. Levels of heavy metals in the environment, size (weight - length) of individuals and stage of development are all considered to be important factors affecting the content of metals in aquatic organisms. Type of fish also seems to be a very important factor for the accumulation of elements in fish tissues. This could be due to differences in physiology between the two species (Kalantzi et al. 2013). In assessing health risks for human consumption of these fish, a comparison with limits for copper and zinc in edible parts of fish which have been established by various national or international authorities showed that both species had lower contents than the values set for safety standards. Furthermore, a comparison of estimated daily intake (EDI) with allowed daily intake and reference doses (RfD) demonstrates that there is no obvious risk for human health from copper and zinc through consumption of B. boops and S. smaris caught in this area of Greece. In almost all cases the contents of the metals in the muscle tissue of both species studied were lower than the various permitted limits for copper and zinc of 30 mg kg -1 (FAO 1983), 20 mg kg -1 (Usero et al. 2003), 30 mg kg -1 (Kalantzi et al. 2013) and 100 mg kg -1 (Canadian Food Standards), with the exception of Zinc in B. boops which was marginally above the figure of 20 mg kg -1 given by Usero et al. (2003). The results of this study showed that the contents of copper and zinc in wild fish caught in the Kissamos Gulf are at safe levels in comparison with permissible established limits. References Abdel-Baki A.S., Dkhil M.A., Al-Quraishy S. (2011). Bioaccumulation of some heavy metals in tilapia fish relevant to their concentration in water and sediment of, Wadi Hanifah, Saudi Arabia. African Journal of Biotechnology 10, Agah H., Leemarkers M., Elskens M., Rez Fatemi S. M., Baeyens W. (2009). Accumulation of trace metals in the muscle and liver tissues of five fish species from the Persian Gulf. Environmental Monitoring and Assessment 157, Canadian Food Standards URL: (Accessed on: ). Cukrov N., Franĉišković-Bilinski S., Hlaĉa B., Barišić D. (2011). A recent history of metal accumulation in the sediments of Rijeka harbour, Adriatic Sea, Croatia. Marine Pollution Bulletin 62, Evans D.W., Dodoo D.K., Hanson P.J. (1993). Trace elements concentrations in fish livers. Implications of variations with fish size in pollution monitoring. Marine Pollution Bulletin, 26(6), Food and Agricultural Organization (FAO) (1983). Compilation of legal limits for hazardous substances in fish and fishery products. FAO fishery circular 464, Food and Agricultural Organization (FAO) (2008). Food Security Statistics: Food Consumption. Statistics Division, Food and Agricultural Organization of the United Nations. URL: (Accessed on: ). Food and Agricultural Organization (FAO) (2010). National Aquaculture Sector Overview. Greece. National Aquaculture Sector Overview Fact Sheets. Text by Christo Filogiannis, P. In: FAO Fisheries and Aquaculture Department [online]. Rome. URL: (Accessed on: ). Forstner U., Wittmann G.T.W. (1983). Metal pollution in the aquatic environment. Springel-Verlag, Berlin, pp 486. Huang, B.W. (2003). Heavy metal concentrations in the common benthic fishes caught from the coastal waters of Eastern Taiwan. Journal of Food and Drug Analysis, 11, Ikem A., Egilla J. (2008). Trace element content of fish feed and bluegill sunfish (Lepomis macrochirus) from aquaculture and wild source in Missouri. Food Chemistry 110, Joint Food and Agriculture Organization/World Health Organization Expert Committee on Food Additives (JECFA) (2003) Summary and Conclusions of the 61 st Meeting of the Joint FAO/ WHO Expert Committee of Food Additives. JECFA/61/Sc, Rome, Italy pp

455 Kalantzi I., Black K.D., Pergantis S.A., Shimmield T.M., Papageorgiou N., Sevastou K., Karakassis I. (2013). Metals and other elements in tissues of wild fish from fish farms and comparison with farmed species in sites with oxic and anoxic sediments, Food Chemistry 141, Mayor DJ, Solan M (2011). Complex interactions mediate the effects of fish farming on benthic chemistry within a region of Scotland. Environmental Research 111, Marks P.J., Plaskett D., Potter I.C., Bradley J.S. (1980) Relationship between Concentration of Heavy Metals in Muscle Tissue and Body Weight of Fish from the Swan-Avon Estuary, Western Australia. Australian Journal of Marine & Freshwater Research 31, McIntyre A.D. (1995). Human impact on the oceans: The 1990s and beyond. Marine Pollution Bulletin 31: Onsanit S., Ke C., Wang X., Wang K.J., Wang W.X. (2010). Trace elements in two marine fish cultured in fish cages in Fujian province, China. Environmental Pollution 158, Prego R., Cobelo-García A. (2003). Twentieth century overview of heavy metals in the Galician Rias (NW Iberian Peninsula). Environmental Pollution 121, Stirling Institute of Aquaculture (2004). Study of the market for aquaculture produced lubina y dorada species. Report to the European Commission, DG Fisheries. United States Environmental Protection Agency (USEPA) (1996) Method 3052: Microwave assisted acid digestion of sediments, sludges, soils and oils, in Test Methods for Evaluating Solid Waste, Physical/Chemical Methods - SW-846. USEPA, Washington DC. United States Environmental Protection Agency (USEPA) (2012). Fish Tissue Screening Levels. U.S. EPA, Region 3, Philadelphia, PA. URL (Accessed on: ). Usero J., Izquierdo C., Morillo J., Gracia I. (2003). Heavy metals in fish (Solea vulgaris, Anguila Anguilla and Liza aurata) from salt marshes on the southern Atlantic coast of Spain. Environment International 29, Vlahogianni T., Dassenakis M., Scoullos M.J., Valavanidis A. (2007). Integrated use of biomarkers (superoxide dismutase, catalase and lipid peroxidation) in mussels Mytilusgalloprovincialis for assessing heavy metals pollution in coastal areas from the Saronikos Gulf of Greece Marine Pollution Bulletin 54,

456 EVALUATING THE SENSITIVITY OF CERTAIN EVENNESS INDICES TO SPECIES RARITY IN SIMULATED MACROBENTHIC COMMUNITIES OF DIFFERENT STRUCTURE Lolas A.*, Vafidis D. Laboratory of Benthic Ecology, Department of Ichthyology & Aquatic Environment, University of Thessaly, Fytoko Street, , Volos, Greece Abstract The sensitivity of 8 commonly used evenness indices to species rarity and differences in community structure, was evaluated using a set of simulated communities, generated from data of existing macrobenthic communities modified in a controlled way. Three transformations were applied to the original sets of data and replicated 100 times, in order to modify i) the community structure into random sets, ii) the abundance of rare species and iii) the abundance of dominant species. A total of different communities were generated and the sensitivity of the given indices was evaluated by means of the Coefficient of Variation, between-indices relationships were assessed by the Spearman rank correlation and a Hierarchical Cluster Analysis. Pielou s Evenness Index appeared to be sensitive to the abundance of dominant and McInthosh s Index to the abundance of rare species, whereas Hurlbert s Index proved quite sensitive to all the transformation. Key words: Pielou, Hurlbert, McIntosh, upper sublittoral *Corresponding author: Lolas Alexios (allolas@uth.gr) ΑΞΗΟΛΟΓΖΖ ΔΤΑΗΘΖΗΑ ΣΧΝ ΓΔΗΚΣΧΝ ΟΜΟΗΟΜΟΡΦΖ ΚΑΣΑΝΟΜΖ ΣΖ ΠΑΝΗΟΣΖΣΑ ΣΧΝ ΔΗΓΧΝ ΜΔΑ ΑΠΟ ΠΡΟΟΜΟΗΧΖ ΣΖ ΓΗΑΦΟΡΔΣΗΚΖ ΤΣΑΖ ΜΑΚΡΟΒΔΝΘΗΚΧΝ ΚΟΗΝΟΣΖΣΧΝ Λφιαο Α.*, Βαθείδεο Γ. Δνβαζηήνζμ Βεκεζηήξ Οζημθμβίαξ, Σιήια Γεςπμκίαξ Ηπεομθμβίαξ ηαζ Τδάηζκμο Πενζαάθθμκημξ, Πακεπζζηήιζμ Θεζζαθίαξ, Οδυξ Φοηυημο, , Βυθμξ, Δθθάδα Περίληψη ηδ ζοβηεηνζιέκδ ιεθέηδ, αλζμθμβήεδηε δ επίδναζδ ηδξ ζπακζυηδηαξ ηςκ εζδχκ ζηδ ζοιπενζθμνά 8 εονέςξ πνδζζιμπμζμφιεκςκ δεζηηχκ μιμζυιμνθδξ ηαηακμιήξ, ιέζα απυ ηδκ πνμζμιμίςζδ ηδξ δζαθμνεηζηήξ ζφζηαζδξ ιαηνμαεκεζηχκ ημζκμηήηςκ. Δθανιυζηδηακ 3 ζοβηεηνζιέκμζ ιεηαζπδιαηζζιμί ζε πναβιαηζηά δεδμιέκα απυ οθζζηάιεκεξ αζμημζκυηδηεξ ημο Παβαζδηζημφ ηυθπμο, ιε ζηυπμ κα εκζζπφζμοκ ακηίζημζπα, ηδκ ηοπαζυηδηα ζηδκ ηαηακμιή ηαζ ηδκ πανμοζία ηςκ ζπάκζςκ ηαζ ηςκ ηονίανπςκ εζδχκ ζηδ ζοκεεζδ ηςκ κέςκ, εζημκζηχκ ημζκμηήηςκ. οκμθζηά δδιζμονβήεδηακ εζημκζηέξ αζμημζκυηδηεξ βζα ηάεε ιεηαζπδιαηζζιυ ηαζ δ εοαζζεδζία ηςκ δεζηηχκ αλζμθμβήεδηε ιέζς ηδξ ζοιπενζθμνάξ ημο οκηεθεζηή Παναθθαηηζηυηδηαξ (CV), ηδξ ζοζπέηζζδξ ιεηαλφ ημοξ ιε αάζδ ημκ ζοκηεθεζηή Spearman ηαζ ηδξ ηαηάηαλήξ ημοξ ιε αάζδ ηδκ Ηενανπζηή Ακάθοζδ Οιάδςκ (ΖCA). O δείηηδξ Οιμζυιμνθδξ Καηακμιήξ Pielou έδεζλε εοαζζεδζία ζηδκ αθεμκία ηςκ ηονίανπςκ ηαζ μ δείηηδξ McIntosh ζηδκ αθεμκία ηςκ ζπάκζςκ εζδχκ, εκχ μ δείηηδξ Hurlbert έδεζλε κα επδνεάγεηαζ ηαζ απυ ημοξ 3 ιεηαζπδιαηζζιμφξ. Λέξειρ κλειδιά: Pielou, Hurlbert, McIntosh, αλώηεξε ππνπαξαιηαθή *οββναθέαξ επζημζκςκίαξ: Λυθαξ Αθέλζμξ (allolas@uth.gr) 456

457 1. Δηζαγσγή Ο πζμ ημζκυξ ηνυπμξ εηηίιδζδξ ηδξ αζμπμζηζθυηδηαξ είκαζ δ ιέηνδζδ ημο ανζειμφ ηςκ εζδχκ ζε έκα ζοβηεηνζιέκμ ηυπμ, ιζα δεδμιέκδ πνμκζηή ζηζβιή, αοηυ δδθαδή πμο μκμιάγεηαζ «πθμφημξ εζδχκ» (species richness) ηαζ μοζζαζηζηά, απμηεθεί ηδκ πζμ εονέςξ απμδεηηή ενιδκεία ηδξ έκκμζαξ «ιέηνδζδ ηδξ αζμπμζηζθυηδηαξ» (Hubbell 2001). Aοηή δ πθδνμθμνία, υιςξ, δεκ επανηεί βζα κα πενζβνάρεζ ηδ δμιή ιζαξ αζμημζκυηδηαξ, αθμφ δ αθεμκία ηάεε είδμοξ δζαθένεζ, ηυζμ ζημ πχνμ υζμ ηαζ ζημ πνυκμ. Γζ αοηυ ημ θυβμ, έπμοκ ακαπηοπεεί ιζα ζεζνά απυ δείηηεξ (Magurran 2004), μζ μπμίμζ εηηζιμφκ ηδκ πμζηζθυηδηα θαιαάκμκηαξ οπυρδ ηα δφμ ηφνζα ζοζηαηζηά πμο ηδ ζοκεέημοκ, ημκ «πθμφημ» (richness) ηαζ ηδκ «μιμζυιμνθδ ηαηακμιή» (evenness) ηςκ εζδχκ (Pielou 1966). Κάεε έκαξ απυ ημοξ δείηηεξ πμο έπμοκ πνμηαεεί, δίκεζ πενζζζυηενδ αανφηδηα ζε έκα απυ ηα δφμ παναπάκς ζημζπεία ηδξ πμζηζθυηδηαξ. ιςξ, αηυιδ δεκ έπεζ ανεεεί έκαξ δείηηδξ πμο κα πενζβνάθεζ μθμηθδνςιέκα ηαζ ηα δφμ αοηά ζημζπεία. Αοηυ έπεζ ςξ απμηέθεζια, κα οπάνπεζ πθέμκ πθδεχνα δεζηηχκ πμζηζθυηδηαξ, αθθά δ επζθμβή ημο ηαηαθθδθυηενμο κα είκαζ ιζα δφζημθδ οπυεεζδ, αθμφ δε θαίκεηαζ λεηάεανα ακ ηαζ πυζμ επδνεάγμκηαζ απυ ηδ ζοιιεημπή ζπάκζςκ ή ηονίανπςκ εζδχκ ζηδ ζφκεεζδ ηδξ αζμημζκυηδηαξ πμο πνμζπαεμφκ κα πενζβνάρμοκ (Smith & Wilson 1996, Gotelli & Colwell 2001). ηδ ζοβηεηνζιέκδ ιεθέηδ, έβζκε ιζα πνμζπάεεζα κα αλζμθμβδεεί δ επίδναζδ πμο αζηεί δ ζπακζυηδηα ηςκ εζδχκ πμο ζοκεέημοκ ιζα αζμημζκυηδηα αεκεζηχκ αζπυκδοθςκ ζηδ ζοιπενζθμνά ηςκ δεζηηχκ μιμζυιμνθδξ ηαηακμιήξ πμο πνδζζιμπμζμφκηαζ εονφηενα ζηδ αζαθζμβναθία. 2. Τιηθά θαη Μέζνδνη Σα δεδμιέκα ζηα μπμία εθανιυζηδηακ μζ 8 δείηηεξ πμο ηεθζηά επζθέπεδηακ (Πίκαηαξ 1) πνμήθεακ απυ ηζξ δεζβιαημθδρίεξ πεδίμο πμο πενζβνάθμοκ μζ Lolas & Vafidis (2013). Οοζζαζηζηά, πνυηεζηαζ βζα ηδ ζφκεεζδ ηςκ ιαηνμαεκεζηχκ ημζκμηήηςκ ζηδκ ακχηενδ οπμπαναθζαηή γχκδ ημο Παβαζδηζημφ Κυθπμο, απυ 4 ζηαειμφξ δεζβιαημθδρίαξ, ιεηά απυ 5 επμπζηέξ δεζβιαημθδρίεξ Πναβιαημπμζήεδηε ιζα ζεζνά απυ πνμζμιμζχζεζξ, πμο είπακ ςξ ζηυπμ κα δδιζμονβήζμοκ ιε ιαεδιαηζηυ ηνυπμ, δείβιαηα απυ «εζημκζηέξ αζμημζκυηδηεξ», έπμκηαξ ςξ πνυηοπμ ηδ ζφκεεζδ ηςκ αζμζημζκμηήηςκ πμο πνμέηορακ απυ ηδκ ιεθέηδ ηςκ Lolas & Vafidis (2013). Οοζζαζηζηά, αοηέξ μζ «εζημκζηέξ αζμημζκυηδηεξ» ακηζηαημπηνίγμοκ ηζξ ακηίζημζπεξ πναβιαηζηέξ αζμημζκυηδηεξ πμο εα ιπμνμφζακ, εκδεπμιέκςξ, κα πνμηφρμοκ απυ ηάπμζμ άθθμ ενεοκδηή, ζημ πθαίζζμ ιζαξ άθθδξ ιεθέηδξ ή αηυια ηαζ απυ ημκ ίδζμ ενεοκδηή ηάης απυ δζαθμνεηζηέξ ζοκεήηεξ ή ζε δζαθμνεηζηέξ πενζμπέξ (Clifford & Casey 1992, Kerans et al. 1992). Πίλαθαο 4. Ολνκαζία, καζεκαηηθή δηαηχπσζε θαη βηβιηνγξαθηθή αλαθνξά ησλ θπξηφηεξσλ Γεηθηψλ Οκνηνκνξθίαο, πνπ εμεηάζηεθαλ Α/Α Ονομαςία Κωδικόσ Αναφορά 1 Ομοιόμορφθ κατανομι τθσ Pielou Pielou Pielou Ομοιόμορφθ κατανομι του Hurlbert Hulbert Hurlbert Ομοιόμορφθ κατανομι του McIntosh McIntosh McIntosh Ομοιόμορφθ κατανομι του Heip Heip Heip Παραλλαγι τθσ κυριαρχίασ του Simpson 1-D Smith & Wilson Παραλλαγι τθσ κυριαρχίασ του Simpson 1/D Smith & Wilson Παραλλαγι τθσ κυριαρχίασ του Simpson -lnd Smith & Wilson Παραλλαγι τθσ ομοιόμορφθσ κατανομισ του Hill F2,1 Alatalo

458 Γζα ηδ δδιζμονβία ηςκ «εζημκζηχκ αζμημζκμηήηςκ», επζθεβυηακ ανπζηά έκαξ ηοπαίμξ ανζειυξ εζδχκ απυ ηδκ ανπζηή ζφκεεζδ, ιε ηδκ πνμτπυεεζδ δ κέα ζφκεεζδ κα ιδκ έπεζ πμηέ θζβυηενα απυ 5 είδδ. ηδ ζοκέπεζα, εθανιμγυκηακ 2 επζπθέμκ ιεηαζπδιαηζζιμί, ιε ζηυπμ κα εηηζιδεεί δ εοαζζεδζία ηςκ δεζηηχκ ζε ζπέζδ ιε ηδ ζπακζυηδηα ηςκ εζδχκ. Γζα κα εκζζποεεί δ επίδναζδ ηςκ ζπάκζςκ εζδχκ (ανζειυξ αηυιςκ < 4), δ κέα ζφκεεζδ, ανπζηά, ειπθμοηζγυηακ ιε έκακ ηοπαίμ ανζειυ εζδχκ ιεηαλφ 0 ηαζ 2κ, υπμο κ μ ανζειυξ ηςκ ζπάκζςκ εζδχκ. ηδ ζοκέπεζα, ζηα κέα αοηά είδδ, απμδίδμκηακ έκαξ ηοπαίμξ πθδεοζιυξ ιεηαλφ 1 ηαζ 3 αηυιςκ (Beisel et al. 1996). Γζα κα εκζζποεεί δ επίδναζδ ηςκ ηονίανπςκ εζδχκ (πεηζηή Κονζανπία > 5%), μζ πθδεοζιμί ημοξ ιεηααάθθμκηακ ηοπαία ιε έκα ζοκηεθεζηή ιεηαλφ 0,75 ηαζ 1,25 (Beisel et al. 1996). Γζα ηάεε ιία απυ ηζξ 20 ιαηνμπακζδζηέξ ζοκεέζεζξ, πναβιαημπμζήεδηακ 100 πνμζμιμζχζεζξ βζα ηάεε ιεηαζπδιαηζζιυ ηαζ οπμθμβίζηδηακ μζ ζοβηεηνζιέκμζ δείηηεξ βζα ηάεε ιία απυ αοηέξ. ηδ ζοκέπεζα, οπθμβίζηδηε μ οκηεθεζηήξ Παναθθαηηζηυηδηαξ βζα ηάεε δείηηδ ηαζ δ δζαδζηαζία επακαθήθεδηε 10 θμνέξ, χζηε κα δδιζμονβδεμφκ ζοκμθζηά ηοπαίεξ δζαθμνεηζηέξ ζοκεέζεζξ. Γζα ηδ ζφβηνζζδ ηςκ δζάθμνςκ δεζηηχκ ηαζ ημκ εκημπζζιυ ηςκ πζεακχκ μιμζμηήηςκ ιεηαλφ ημοξ, επζθέπεδηε μ ζοκηεθεζηήξ ζοζπέηζζδξ Spearman ηαζ δ Ηενανπζηή Ακάθοζδ Οιάδςκ (Hierarchical Cluster Analysis). Γζα ηδκ εηηίιδζδ ηδξ εοαζζεδζίαξ ζε ηάεε πνμζμιμίςζδ ηαζ ηδ ζφβηνζζδ ιεηαλφ ηςκ δεζηηχκ, πνδζζιμπμζήεδηε μ οκηεθεζηήξ Παναθθαηηζηυηδηαξ (Coefficient of Variation, CV). Ζ δδιζμονβία ηςκ «εζημκζηχκ αζμημζκμηήηςκ» ηαζ μζ οπμθμβζζιμί ηςκ δεζηηχκ πναβιαημπμζήεδηακ ιε ηδ πνήζδ ιαηνμεκημθχκ ημο θμβζζιζημφ επελενβαζίαξ θμβζζηζηχκ θφθθςκ Microsoft Excel 2003 ηαζ ηχδζηα ζηδ βθχζζα πνμβναιιαηζζιμφ Microsoft Visual Basic for Applications (VBA). θεξ μζ ακαθφζεζξ πναβιαημπμζήεδηακ ζημ ζηαηζζηζηυ παηέημ STATGRAPHICS Centurion (έηδμζδ ). 3. Απνηειέζκαηα πδήηεζε ημκ Πίκαηα 2 ηαηαβνάθμκηαζ ηα πμζμηζηά παναηηδνζζηζηά ηδξ δζαηφιακζδξ ηςκ ηζιχκ ηάεε δείηηδ, υπςξ οπμθμβίζηδηε βζα ηάεε ιεηαζπδιαηζζιυ. Ζ δζαηφιαζκδ ημο οκηεθεζηή Παναθθαηηζηυηδηαξ ηαζ δ μιαδμπμίδζδ ηςκ δεζηηχκ, ζφιθςκα ιε ηδκ Ηενανπζηή Ακάθοζδ Οιάδςκ, απμδίδεηαζ ζημ πήια 1. Απυ ηα απμηεθέζιαηα ηδξ ακάθοζδξ ηδξ εοαζζεδζίαξ ηςκ δεζηηχκ, θάκδηε υηζ δ απυηνζζή ημοξ ζημοξ δζάθμνμοξ ιεηαζπδιαηζζιμφξ ήηακ λεπςνζζηή βζα ηάεε δείηηδ, εκχ έδεζλε κα επδνεάγεηαζ απυ ηα πμζμηζηά παναηηδνζζηζηά ηςκ ιεηαζπδιαηζζιχκ. Πζμ ζοβηεηνζιέκα, μ δείηηδξ ημο Hurlbert θάκδηε πςξ είκαζ μ πενζζζυηενμ ακελάνηδημξ απυ υθμοξ, ηαεχξ έδεζλε ζδιακηζηή εοαζζεδζία ζε ηάεε ιεηαζπδιαηζζιυ. Ακηίεεηα, δ επίδναζδ ηδξ αθεμκίαξ ηςκ ζπάκζςκ εζδχκ θάκδηε κα επδνεάγεζ ζδιακηζηά ημκ δείηηδ ημο McIntosh, ηαεχξ υπςξ θάκδηε, μ ζοβηεηνζιέκμξ δείηηδξ πανμοζίαζε ηδ ιεβαθφηενδ εοαζζεδζία ζημκ ζοβηεηνζιέκμ ιεηαζπδιαηζζιυ. Δλίζμο ζδιακηζηή επίδναζδ είπε δ αθεμκία ηςκ ηονίανπςκ εζδχκ ζημκ δείηηδ Pielou, μ μπμίμξ έδεζλε πμθφ ιεβαθφηενδ εοαζζεδζία ζημκ ζοβηεηνζιέκμ ιεηαζπδιαηζζιυ ζε ζφβηνζζδ ιε ημοξ άθθμοξ δφμ. Πίλαθαο 5. πληειεζηήο Παξαιιαθηηθφηεηαο (CV), Διάρηζηε, Μέγηζηε θαη Μέζε ηηκή (± Σππηθή Απφθιηζε) γηα θάζε δείθηε νκνηφκνξθεο θαηαλνκήο θαη γηα θάζε κεηαζρεκαηηζκφ Δείκτησ CV Ελάχιςτη Μζγιςτη Μζςη Επίδραςη Συχαίασ φνθεςησ Pielou 8,83% 0,310 0,900 0,815 ± 0,072 Hurlbert 7,76% 0,302 0,898 0,812 ± 0,063 McIntosh 9,49% 0,190 0,953 0,875 ± 0,083 Heip 18,28% 0,203 0,704 0,476 ± 0,087 1-D 18,72% 0,232 0,991 0,951 ± 0,178 1/D 31,83% 0,184 0,627 0,333 ± 0,106 -lnd 12,04% 0,153 0,861 0,714 ± 0,086 F 2,1 15,10% 0,450 0,871 0,649 ± 0,098 Επίδραςη πάνιων Ειδϊν Pielou 9,73% 0,424 0,92 0,781 ± 0,076 Hulbert 9,81% 0,404 0,92 0,775 ± 0,076 McIntosh 9,27% 0,353 0,96 0,852 ± 0,079 Heip 25,42% 0,202 0,77 0,413 ± 0,105 1-D 13,25% 0,415 0,99 0,936 ± 0,

459 1/D 42,03% 0,127 0,78 0,295 ± 0,124 -lnd 15,17% 0,269 0,87 0,679 ± 0,103 F 2,1 16,93% 0,402 0,95 0,644 ± 0,109 Επίδραςη Κυρίαρχων Ειδϊν Pielou 9,64% 0,426 0,92 0,799 ± 0,077 Hulbert 9,94% 0,414 0,91 0,795 ± 0,079 McIntosh 12,35% 0,356 0,94 0,850 ± 0,105 Heip 20,90% 0,194 0,85 0,469 ± 0,098 1-D 20,49% 0,471 0,99 0,932 ± 0,191 1/D 36,83% 0,167 0,82 0,334 ± 0,123 -lnd 15,17% 0,247 0,86 0,692 ± 0,105 F 2,1 17,62% 0,464 0,9 0,647 ± 0,114 ρήκα 6. Γηαθχκαλζε ηνπ ζπληειεζηή παξαιιαθηηθφηεηαο (CV) φπσο ππνινγίζηεθε απφ ηηο ηηκέο ησλ δεηθηψλ νκνηφκνξθεο θαηαλνκήο (Α), Ηεξαξρηθή θαηάμε θαη νκαδνπνίεζε ησλ δεηθηψλ, κε βάζε ηελ νκνηφηεηα ηνπο (Β), γηα θάζε έλαλ απφ ηνπο 3 κεηαζρεκαηηζκνχο δεδνκέλσλ πνπ εθαξκφζηεθαλ. ε ακηίζημζπδ ιεθέηδ ηδξ εοαζζεδζίαξ μνζζιέκςκ δεζηηχκ Οιμζυιμνθδξ Καηακμιήξ ζηζξ ιεηααμθέξ ηδξ αθεμκίαξ, πμο πναβιαημπμίδζακ μζ Boyle et al. (1990), ακ ηαζ πνδζζιμπμίδζακ δζαθμνεηζηή ιαεδιαηζηή πνμζέββζζδ ζημκ ηνυπμ πμο ιεηαζπδιάηζζακ ηα δεδμιέκα ημοξ, ηαηέθδλακ ζε πανυιμζα ζοιπενάζιαηα. 459

460 οβηεηνζιέκα, ηαηέθδλακ ζημ ζοιπέναζια υηζ μ δείηηδξ ημο McIntosh έδεζλε ζδιακηζηή εοαζζεδζία ζε ιζηνέξ ιεηααμθέξ ηδξ αθεμκίαξ ηαζ ηυκζζακ υηζ εεςνείηαζ πζμ ηαηάθθδθμξ βζα εηηζιήζεζξ, υηακ οπάνπμοκ ανηεηά ζπάκζα είδδ. Ακηίεεηα μ δείηηδξ ηδξ Pielou, έδεζλε κα επδνεάγεηαζ απυ ιεβάθεξ ηζιέξ αθεμκίαξ ηαζ αοηυξ είκαζ μ θυβμξ πμο είκαζ πζμ ηαηάθθδθμξ ζε δείβιαηα πμο οπάνπμοκ ηονίανπα είδδ. Σέθμξ, βζα ημκ δείηηδ ημο Hurlbert, μζ ζοβηεηνζιέκμζ ενεοκδηέξ ηυκζζακ υηζ είκαζ ζπεηζηά ακελάνηδημξ απυ ηζξ ηζιέξ ηδξ αθεμκίαξ, ακ ηαζ θάκδηε πςξ είπε πενζζζυηενδ εοαζζεδζία ζηζξ παιδθυηενεξ ηζιέξ. Λίβμ δζαθμνεηζηή ήηακ δ άπμρδ ηςκ Beisel et al. (1996), ακ ηαζ ζηδ δζηή ημοξ ιεθέηδ μζ δείηηεξ πμο εηηζιήεδηακ ήηακ 4 ηαζ απυ αοημφξ, ιυκμ μ δείηηδξ Simpson ηαζ McIntosh ήηακ ημζκμί ιε ηδκ πανμφζα ιεθέηδ. Πανυθα αοηά, αλίγεζ κα ζδιεζςεεί πςξ μζ ζοββναθείξ, ζοιπένακακ πςξ μζ δείηηεξ Simpson ηαζ McIntosh είπακ ηδ ιεβαθφηενδ ζοζπέηζζδ, αθθά μ δείηηδξ McIntosh είπε ηδ ιεβαθφηενδ εοαζζεδζία ζηα ηονίανπα είδδ ηαζ θίβμ ιζηνυηενδ ζημοξ οπυθμζπμοξ ιεηαζπδιαηζζιμφξ. Θεχνδζακ υιςξ υηζ αοηή δ δζαθμνά ήηακ ιζηνή ηαζ ημκ πνυηεζκακ ςξ ημκ πζμ ηαηάθθδθμ απυ ημοξ 4 δείηηεξ πμο είπακ ζοβηνίκεζ. Απυ ηδκ πανμφζα ιεθέηδ, πνμηφπηεζ πςξ μ δείηηδξ Hurlbert (1971) είκαζ ανηεηά αλζυπζζημξ ζε ηάεε απυπεζνα εηηίιδζδξ ηδξ μιμζμιμνθίαξ ηδξ ηαηακμιήξ ιζαξ αεκεζηήξ αζμημζκςκίαξ. Ακ υιςξ οπάνπεζ θυβμξ κα δμεεί έιθαζδ ζηα ζπάκζα είδδ, ηυηε μ δείηηδξ McIntosh (1967) είκαζ πζμ ηαηάθθδθμξ, εκχ ζηδκ πενίπηςζδ ηςκ ηονίανπςκ εζδχκ, πνμηείκεηαζ δ πνήζδ ημο δείηηδ ηδξ Pielou (1966). Δπεζδή υιςξ δ αζμθμβζηή πμζηζθυηδηα ειπενζέπεζ ηαζ ηδκ αθεμκία ηαζ ημκ πθμφημ ηςκ εζδχκ (Magurran 2004), ηακέκαξ δείηηδξ Οιμζυιμνθδξ Καηακμιήξ δεκ πνέπεζ κα ελεηάγεηαζ ιυκμξ ημο. Ακηίεεηα, είκαζ ηαθφηενα κα πνδζζιμπμζείηαζ ζε ζοκδοαζιυ ιε ηάπμζμκ απυ ημοξ δείηηεξ πμζηζθυηδηαξ, έηζζ χζηε δ ενιδκεία ηςκ απμηεθεζιάηςκ κα είκαζ πζμ εφζημπδ. Βηβιηνγξαθία Alatalo R.V. (1981). Problems in the measurement of evenness in ecology. Oikos 37, Beisel J.N., Moreteau J.C. (1997). A simple formula for calculating the lower limit of Shannon's diversity index. Ecological Modelling 99, Beisel J.N., Thomas S, Usseglio-Polatera P., Moreteau J.C. (1996). A sensitivity analysis of indices summarizing community structure. Journal of Freshwater Ecology 11, Boyle T.P., Smillie G.M., Anderson J.C., Beeson D.R. (1990). A sensitivity analysis of nine diversity and seven similarity indices. Research Journal of the Water Pollution Control Federation 62, Clifford H.F., Casey R.J. (1992). Differences between operators in collecting quantitative samples of stream macroinvertebrates. Journal of Freshwater Ecology 7, Heip C. (1974). A new index measuring evenness. Journal of the Marine Biological Association of the United Kingdom 54, Hubbell S.P. (2001). The Unified Neutral Theory of Biodiversity and Biogeography. Princeton, Princeton University Press, pp 448. Hurlbert S.H. (1971). The nonconcept of species diversity: a critique and alternative parameters. Ecology 52, Kerans B.L., Karr J.R., Ahlstedt S.A. (1992). Aquatic invertebrate assemblages: spatial and temporal differences among sampling protocols. Journal of the North American Benthological Society 11, Lolas A. Vafidis D. (2013). Population dynamics of two caprellid species (Crustaceae: Amphipoda: Caprellidae) from shallow hard bottom assemblages. Marine Biodiversity 43, Magurran A.E. (2004). Measuring Biological Diversity. Blackwell Publishing, Oxford, pp 260. McIntosh R.P. (1967). An index of diversity and the relation of certain concepts to diversity. Ecology 48, Pielou E.C (1966). The measurement of diversity in different types of biological collections. Journal of Theoretical Biology 13, Shannon C.E. (1948). A mathematical theory of communication. Bell System Technical Journal 27, Simpson E.H. (1949). Measurement of diversity. Nature 163, 688. Smith B., Wilson J.B. (1996). A consumer s guide to evenness indices. Oikos 76, Gotelli N.J., Colwell R.K. (2001). Quantifying biodiversity: Procedures and pitfalls in the measurement and comparison of species richness. Ecology Letters 4,

461 NEW PRACTICES IMPROVING BREEDING SELECTION PROGRAMMES FOR EUROPEAN SEA BASS (Dicentrarchus labrax) AND GILTHEAD SEA BREAM (Sparus aurata) Papaharisis L. 1*, Pavlidis M. 2, Chatziplis D. 3, Kottaras E. 1, Dimitroglou A. 1, Samaras A. 2, Loukovitis D. 3, Tsigenopoulos C.S. 4 1 Nireus Aquaculture S.A., Greece 2 Department of Biology, University of Crete, Greece 3 Laboratory of Agrobiotechnology and Agricultrural Products Inspection, Dept. of Agricultural Technology, School of Agricultural Technology, Food Technology and Nutrition, Alexander Technological Educational Institute of Thessaloniki, Greece 4 Institute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Centre for Marine Research (HCMR), Heraklion, Greece Abstract The European sea bass and the gilthead sea bream have the biggest contribution (110,000 tons/year) in the aquaculture of Greece. Integrated scientific program for genetic selection have recently started and the first results appear very promising. However, proper breeding selection programmes should incorporate the new scientific evidences and not based merely on classical growth characteristics. The aim of the two research initiatives, recently funded by the Hellenic Republic, is the application of selective breeding programmes in NIREUS S.A. for the genetic improvement of European sea bass (BASSGEN) and the gilthead sea bream (BREAMIMPROVE) production traits based on molecular markers (MAS, Marker Assisted Selection) in combination with classical selection techniques. Selection will be based on microsatellite markers which, according to research studies, are linked to quantitative trait loci (QTL) controlling commercially important traits, such as body weight and stress response. In addition, a new QTL detection study will be carried out in each species aiming at more precise and detailed mapping of existing QTL for the implementation of future breeding programs. BASSGEN aims to develop and evaluate an innovative selection breeding program based on performance, immunological and endocrine parameters, while BREAMIMPROVE is focused on introducing new techniques in the selection of breeding candidates based both on phenotypic measurements and molecular markers. It is worth mentioning, that these programmes based on molecular genetic markers will be carried out for the first time in Greek aquaculture, highlighting the potential of innovative molecular methods in rapid improvement of economically important productive traits. Keywords: Selection program, Stress response, Bodyweight, Quantitative Trait Loci * Contact author: Leonidas Papaharisis, l.papaharisis@nireus.com 1. Introduction The European sea bass Dicentrarchus labrax together with the gilthead sea bream Sparus aurata constitute the two main export products of Greece in the sector of animal foods of high alimentary value. With an annual production at the order of 110,000 tons, these two species contribute considerably in the consolidation of Greece as the first country in Europe to produce Mediterranean marine fishes. Until today, however, breeding is based on the production of eggs from broodstocks that have not been genetically characterized and from the producers' empirical choice. Integrated scientific programmes for genetic selection have recently started and the first results appear very promising. The methodology of genetic selection is based on the continuous choice of candidate fish that present better response to production indicators such as the higher growing rate, disease resistance, lower deposition of fat etc. compared to the remainder individuals of the population. Then, there is controlled reproduction between the candidate fish, with concrete restrictions to avoid inbreeding and produce descendants that will present improved production traits. 461

462 However, proper breeding selection programmes should incorporate the new scientific evidences and not based merely on classical growth characteristics. The aim of the two research initiatives, recently funded by the Hellenic Republic, is the application of selective breeding programmes in NIREUS S.A. for the genetic improvement of European sea bass (BASSGEN) and the gilthead sea bream (BREAMIMPROVE) production traits based on molecular markers (MAS, Marker Assisted Selection) in combination with selection techniques based on phenotypic values of economically important productive traits. 2. Materials and Methods Selection will be based on microsatellite markers which, according to research studies, are linked to quantitative trait loci (QTL) controlling commercially important traits, such as body weight and stress response. The genetic gain from the utilization of marker information is expected to be 15-25% higher compared to selection based only upon phenotype. Simulation studies have shown that selection through MAS is expected to increase average body weight of first generation progeny to a percentage of 5-15%, decreasing at the same time the duration of production cycle (from months to months) and, finally, reducing production costs. However, selection for desirable characters can often be accompanied from other less desirable traits as the stress sensitivity and/or the aggressive behavior. The stress sensitivity most times is connected with immunological, reproductive and/or behavioral disturbances as well as with decreased performance and robustness. Therefore, this parameter should be seriously taken into consideration in the modern programs of genetic selection. The progress that has been made recently in the field of molecular genetics has made feasible the introduction of new information from genetic markers to estimate hereditary values and its exploitation into animal breeding schemes. In addition, a new QTL detection study will be carried out in each species aiming at more precise and detailed mapping of existing QTL for the implementation of future breeding programs. 3. Results BASSGEN programme (Increase Greek fish farm competitiveness through innovative breading selection programme for European sea bass, Dicentrarchus labrax), aims to develop and evaluate an innovative selection breeding programme based on performance, immunological and endocrine (stress resistance) parameters. Preliminary data demonstrate, for the first time in European sea bass families, a consistency in the stress response report with the presence of individuals that show consistent high or low cortisol plasma concentrations following exposure to standardized acute stressor (Figure 1). These results are of importance and could contribute to the improvement of breeding as alternative selection criteria other than the ordinary ones, and consequently could potentially grow the number of fish in the nucleus population. 462

463 Cortisol (ng ml -1 ) HydroMedit 2014, November 13-15, Volos, Greece Consistency in the stress response 1st Sampling 2nd Sampling 3rd Sampling 4th Sampling HR Groups LR Figure 1: Presence of high cortisol responders (HR) and low cortisol responders (LR) in European sea bass, following exposure to acute stressors for four consecutive months. Blood samples were taken 0.5 hours post-stress. BREAMIMPROVE programme (Development and application of innovative biotechnological methods utilizing molecular genetic markers, for the genetic improvement of farmed gilthead seabream, Sparus aurata), aims to introduce new techniques in the selection of breeding candidates based both on phenotypic measurements and molecular markers (M.A.S.), for the genetic improvement of seabream productive traits (i.e. body weight, body shape and fat accumulation). Preliminary results verify the segregation of QTL affecting bodyweight within a breeding population (Figure 2). The segregation of four previously reported QTL affecting bodyweight (Linkage Groups 1, 9, 21 and 23; Loukovitis et al. 2012) has been verified in a broodstock line of a breeding population. Fine mapping of the detected QTL is underway as well as their incorporation in the genetic evaluations of the breeding program. 463

464 P - VALUES LOD SCORES HydroMedit 2014, November 13-15, Volos, Greece QTL detected on Linkage Group 1 P VALUES LOD SCORE Distance (cm) 0 Figure 2. Lod scores and P-values of QTL affecting bodyweight, detected in Linkage Group 1 of the gilthead seabream 4. Discussion It is worth mentioning, that these genetic selection programmes in both species based on molecular genetic markers and in the same company will be carried out for the first time in Greek aquaculture, highlighting the potential of innovative molecular methods in rapid improvement of economically important productive traits. Acknowledgements Financial support for this study has been provided by the General Secretariat for Research and Technology (GSRT), Ministry of Education and Religious Affairs, under the National Programme for Competitiveness & Entrepreneurship (EPAN II) funded by National sources and the European Regional Development Fund" for the gilthead sea bream and by the Ministry of Rural Development and Food under the European Fisheries Fund and Programme for Public Investments for the European sea bass. References D. Loukovitis, E. Sarropoulou, C. Batargias, A. P. Apostolidis, G. Kotoulas, C. S. Tsigenopoulos and D. Chatziplis (2012) Quantitative Trait Loci for Body Growth and Sex Determination in the Hermaphrodite Teleost Fish Sparus aurata L. Animal Genetics doi: /j

465 THEMATIC FIELD: INLAND AQUATIC RESOURCES & FISHERIES ECONOMICS 465

466 GROWTH, AGE AND SIZE STRUCTURE OF THE ROUND GOBY (Neogobius melanostomus) FROM ITS MAIN HABITATS IN BULGARIAN WATERS Velkov B.*, Vassilev M., Apostolou A. Department of Aquatic Ecosystems, Institute for Biodiversity and Ecosystem Research Base 2, Bulgarian Academy of Sciences, 2 Gagarin Street, 1113 Sofia, Bulgaria Abstract The growth, age and size structure of the round goby (Neogobius melanostomus) inhabiting different types of water bodies in Bulgaria were investigated. The species is a Ponto - Caspian benthophillic species, which lives both in fresh and in brackish waters (large rivers, estuaries, sublittoral zones in the sea bays). Despite its wide distribution and high numbers, so far there are no profound investigations on the growth of the species along the Bulgarian Black Sea coast. Moreover, despite the evidence for differences in growth of gobies living in fresh, brackish and salt waters there are no data on the Bulgarian waters, which are part of the native area of the species. Variable life histories as evidences of ecological plasticity are discussed at the background of varying ecological conditions. There were significant differences between mean back-calculated sizes of same age males at all ages among the three populations. The age structure, size structure and growth of the three populations were different. Considering age and size structure, the riverine and lacustrine populations demonstrated much more similarities as opposed to population from the sea. Key words: Round goby, growth, invasive species, Bulgarian ichthyofauna, fish ecology *Corresponding author: Velkov Boris (boris.velkov@gmail.com) 1. Introduction The round goby (Neogobius melanostomus) is a Ponto-Caspian benthophillic species, originally inhabiting mainly fresh and brackish waters (large rivers, estuaries) and the coastal areas of Black, Azov and Caspian Seas (Georgiev 1966, Pinchuk et al. 2003). In Bulgarian waters the round goby occurs along the entire Black sea coast, the entire stretch of Danube River, lower stretches of all Danube and Black Sea tributaries, seaside lakes and lagoons. In its native area it is an important species for the artisanal and commercial fishery (Moskalkova 1996) and together with other gobiids is an important component of sublittoral fish communities. Despite its wide distribution and its significant ecological role, so far there are no investigations on growth, age and size structure of the round goby in Bulgaria. The only published information available is based on personal communication (Corkum et al. 2004). In the period since 1990, the round goby has extended widely its spread through Europe and even North America (Pinchuk et al. 2003, Corkum et al. 2004, Sapota 2004). The success of the species as an invader has been attributed mainly to its ecological plasticity. The latter includes variable life histories and is coupled with varying growth, size and age structure. Growth and size structure of round goby populations have been investigated recently, mainly in novel habitats (Macinnis & Corkum 2000, Simonović et al. 2001, Pliszka 2002, Corkum et al. 2004, French & Black 2009, Shemonaev &Kirilenko 2009). Most of the authors point out at differences of growth of the fish, age and size structure of novel populations, compared to native ones. These differences generally include schemes with lower number of age groups, lower growth and earlier maturation of fish in invasive (recently introduced) populations. In the recent years however new papers appeared, describing new populations which are excluded of the above mentioned scheme (Sokołowska & Fey 2011). These results demonstrate the dynamics of the round goby population and its plasticity, and are reminders that a population is a constantly changing system which cannot only be viewed on the native introduced axis. The objective of our study was to describe growth, age and age structure of three isolated native populations of the round goby, which represent the three main habitats of the species in Bulgaria: Danube River, Black sea and seaside lakes. These water bodies differ in terms of basic hydrology and features, like water current, depth, substratum and salinity. We assumed the possible differences will reflect the natural response of the round goby to variable environmental conditions and their analysis will reveal more information on the population dynamics of this highly invasive species. 2. Material and Methods 466

467 Three populations were samples from 2009 to The Lake sample was collected from Durankulak Lake (North-Eastern Bulgaria, N, E). The Marine sample-was collected near Primorsko city-southeastern Bulgaria ( N, E). The River sample was collected in Danune River near Belene city ( N, E, May 2010). Specimens were fixed in formole (10% formaldehyde 38%) for further analysis. The standard length (SL) of each fish was measured to the nearest 1 mm and body weight measured to 0,1g. Scales were collected and observed under stereomicroscope with 3X magnification. After the annuli were determined the distance from the scale center to each annulus and to the edge of the scale was measured. The longest distance on the oral radius was used. Linear equation of SL on scale radius was calculated and used to back calculate the size at each age, based on the scale readings. The relative rate of increase in length was calculated according to Ricker (1975). According to this scheme, the relative rate of increase for the first year is 100%. The rate in the each following year is calculated as: ((L t -L t-1 )/L t-1 )*100, where L t is the length at given year and L t-1 is the length at previous year. Mann-Whitney U Test was used to compare the differences in size at given age between same sex of different populations and between different sex within the same population. The size corresponded to the time formation of the last two annuli was used. For example, to obtain values for size at age 1, the fish aged 1+ and 2+ years were used in order to increase the sample size. Age structure was expressed as the number and the proportions of the age groups. 3. Results The number of individuals sampled from each population was 86 gobies for Lake population, 174 for marine population and 48 for the River population. The age composition varied between the three populations. No difference was found for the number of age groups according to sex. The Lake population consisted of four groups but mainly of fish aged one year (1+, 63 %, 2+: 25.9%, 3+: 7.4% and 4+: 3.7%). The Marine population consisted of 5 groups but mainly of fish aged 2+ and 3+ years (1+: 4%, 2+: 34.5%, 3+: 44.8%, 4+: 9.2%, 5+: 7.5%). The River population consisted of three groups but mainly of fish aged 1+ years (1+:42.5%, 2+: 37.5% and 3+: 20%). The length ranged from 34 to 133 mm in Lake population (mean length: 62.6mm, g) from mm (mean length 101.4mm, 3-114g) in marine population and from 25 to 117mm (mean 66.4mm) in River population. A higher percentage of large fish was seen in Marine population. Table 1. Mean back calculated length (SL, mm) of male and female round gobies from Marine, Lake and River populations (in parenthesis, the standard deviation values) Population (Location) Age Male Female Marine (± 8.3) 57.1 (± 7.5) (Black Sea) (± 11.6) 78.6 (± 7.9) (± 14.3) 93.7 (± 7.2) (± 12.1) (± 6.1) (± 14.0) (± 5.6) Lake (± 7.7) 43.5 (± 7.6) (Durankulak) (± 6.9) 55.6 (± 7.9) (± 8.3) 67.3 (± 5.9) (± 14.9) River (± 6.2) 58.5 (± 8.9) (Belene) (± 9.3) 73.1 (± 11.4) (± 11.7) 84.3 (± 11.8) There were significant differences between mean back-calculated sizes of same age males at all ages among the three populations (Table 1). Black Sea had the largest males at all ages, though at age 1 the difference with males from Danube was not significant. At age 2 and age 3 the Marine males were significantly larger than males of the other populations and at age 4 larger than the Riverine males (no age 4 males were present in the lacustrine population). There were differences between the two freshwater populations too. Riverine males were larger than lacustrine males at all ages. Differences have been also noticed between female fish. At age 1 to age 3 sizes of Marine females were not significantly different than River females and were significantly larger than Lake females. At age 4 there was no difference between Marine and Lake females (no similar age in Danube). At age 1 the only significant difference between back calculated size was found in the Lake population, with males 467

468 being larger than females (47.5 vs. 43.5mm). At age 2 the Marine males were significantly larger than females (87.2 vs. 78.6mm) and no differences were found within the Lake and the River populations. The male fish were longer than Marine females at age 3 (108.1 vs. 93.7mm) and Lake females (82.5mm vs. 67.3mm) and no difference were found for the River population. At age 4 Marine males were larger than Marine females (123.6 vs mm) and no significant differences were found between the Lake males and females. Marine population was the only one, where five years old fish were found. Males were significantly larger than females (140.2 vs mm, Figure 1). Both marine female and male fish sustained higher level of growth compared to freshwater populations during their 2 nd year of life. The respective values were 53% and 41% for males and females of Marine sample, 29% and 28% for the males and females of lacustrine sample, and 37% and 30% for the males and females of Danube population (Figure 2). Figure 1. Back calculated length of round goby from Black Sea, Danube River, Durankulak Lake Figure 2. Mean relative rate of size increase of round goby from Black Sea, Danube River, Durankulak Lake Significant decline of growth rate in sea fish occurred after age 2. At age 3 the growth rate of male sea gobies dropped to 27% and the female to 20%. At older age the decline continued, however at lower rate. At all ages the fish from marine population demonstrated higher rate of increase, compared to the lacustrine and riverine populations and in all populations the males had higher rate of increase, compared to females of the same age except the sea fish during their fifth year. 4. Discussion The age structure, size structure and growth of the three populations were different. Considering age and size structure, the riverine and lacustrine populations demonstrated much more similarities as opposed to population from the sea. Among them were smaller number of age groups and higher proportion of younger individuals. We found five age groups ( ) in the Back Sea population, four ( ) in the Durankulak Lake population and only three ( ) in the Danube River. The lower number of age groups of the two freshwater populations resembled the age structure of previously investigated freshwater populations both in Europe (Simonović et al. 2001, Shemonaev & Kirilenko 2008) and in North America (Charlebois et al. 1997, Macinnis & Corkum 2000, French & Black 2009).. The Danube population in our study was composed of only three age groups, similar to the upper Detroit River ( , Macinnis & Corkum 2000) and the upper Danube (0+ to 2+, Simonović et al. 2001). Macinnis & Corkum (2000) found age 1 to be the most abundant group in Detroit River, followed by age two, which is similar to the composition of our riverine and lacustrine but not the marine population. Freshwater habitats were suggested as containing smaller, earlier maturing fish previously (Corkum et al. 2004). On the other hand the running waters were reported as being avoided by the round goby (at least compared to other representatives of genus 468

469 Neogobius) - Harka & Bíró (2007). This suggests suboptimal conditions in running waters for the round goby. Running waters pose an obstacle to this sedentary fish by requiring more energy allocation. Existing literature on marine populations of the round goby demonstrates varying age characteristics. There are numerous investigations on the round goby populations of Black (Apanasenko 1973, Svetovidov 1964, Gümüs & Kurt 2009), Caspian (Azizova 1962, Stepanova 2001), as well as Azov Seas (Revina et al. 1971, Kostyuchenko 1961, Apanasenko 1973). The determined age compositions for Black Sea were from 5 age groups (Gümüs & Kurt 2009) to 8 ( , Apanasenko 1973). Azov Sea investigations revealed 3 ( , Apanasenko 1973) to 5 ( , Kostyuchenko 1961) age groups. Caspian populations consisted of 4-5 age groups, depending on the year and region (Azizova 1962, Stepanova 2001). Gümüs & Kurt (2009) reported age structure for a population of round goby in Southern Black sea. The number of age groups and the dominance of 2- and 3-years old fish resemble our own observations. Generally males attained larger size than females studying this study, which could be expected, based on previously published results (Bilko 1971, Macinnis & Corkum 2000, Shemonaev &Kirilenko 2009, Kornis et al. 2012). Differences in size between male and female fish appeared after age 1, except for the lacustrine population. The delay in size differentiation according to sex has already reported (Bilko 1971, Shemonaev & Kirilenko 2009) and could be explained by maturation terms. The lacustrine males were larger than females even earlier at age 1, which probably reflects the earlier maturation of lacustrine male fish. The riverine population had the least differences on growth between males and females. No significant difference was found at any age. The differences in growth of both sexes are backed up by the complex social structure of round goby. Hypothesis that 2 forms of males occur in some round goby populations (Marentette et a.l 2009) was not proven. Among the 3 investigated populations marine fish had the highest growth. On the opposite, the lacustrine fish had the lowest size at age and rate of increase. The round gobies from Danube demonstrated growth rates closer to the sea fish however significantly lower (except for age 1). Lower growth and size at age for freshwaters were reported previously (Corkum et al. 2004). Brackish waters were suggested as optimal for the round goby growth (Corcum et al. 2004) and running waters as less preferable to the species (Harka & Bíró 2007). Simonović et al. (2001) in their investigation on the round goby in Danube found that the length at various ages was smaller than the corresponding values of sea gobies (Caspian and Azov Seas). These results are similar to our survey, in addition with those of Polaĉik et al. (2008), who reported the size of round goby along the Bulgarian section of Danube to range between approximately 17 and 77 mm (median: 45mm). The round goby demonstrates highly variable growth even in the same water body, depending on the feeding conditions (Bilko 1971). Up until recently the higher growth was observed in populations inhabiting brackish sea waters of its native area (Berg 1949, Svetovidov 1964, Bilko 1971, Apanasenko 1973, Gümüs & Kurt 2009) compared to newly invaded areas (Macinnis & Corkum 2000, Simonović et al. 2001, Johnson et al. 2005, French & Black 2009). In recent years the Baltic Sea populations demonstrated growth, which is probably at the upper limit of all area of distribution (Sapota 2004, Sokołowska and Fey 2011). The authors addressed this rapid growth to the lack of predators and the high availability of food (Sapota 2004). Food availability is an important factor for round goby growth (Bilko 1971). The higher availability of potential food in the sea, compared to Durankulak Lake and Danube, probably results in higher growth rate. Usually the populations inhabiting Black Sea were reported as performing highest growth within the native area (Apanasenko 1973). Published data revealed freshwater populations as slower growing, especially in rivers. Compared to previous data the back calculated sizes of Black Sea round gobies of this study were intermediate. The highest growth was reported by Berg (1949) and Svetovidov (1964). They reported maximum size of approximately 250mm and Berg (1949) noted the size of 130mm for 1 year old males, which is approximately double the size we estimated. Later various papers, considering various regions of Black, Caspian and Azov Seas revealed the complex character of growth. Occurrence of local populations was proposed, which experience different growth, depending on feeding conditions (Bilko 1961). Later Apanasenko (1973) compared age and growth of populations in Azov and Black Seas and found that the Black Sea supports highest growth, larger size and most complex age structure for the round goby populations. Pollution, eutrophication and intensive fishing (Apanasenko, 1973) can shift growth, age and size structure. Within all three populations the highest growth occurred during the 1 st year of life, similarly to what has been reported by Bilko (1971) for Black sea populations. During the 2 nd year length rate decreased significantly for the freshwater populations but less for marine ones, which experienced their major decline during the 3 rd year. At older ages the length gain retains approximately at the similar levels. The variation of length of same age fish increased with age and was highest in lacustrine population. The highest rate of growth during the 1 st year of life and consecutive decrease with age was 469

470 observed previously (Shemonaev & Kirilenko 2009). Male fish of all populations retained higher growth during their 2 nd year compared to females. These results are in concordance with other observations (Bilko 1971, Kovtun et al. 1974, 1976) and are most probably related to the higher growth until maturity and earlier maturation of the female fish. The lack of significant difference in length between male and female round goby at age 1 and the higher rate (compared to the other two populations) rate of increase during their 2 nd year probably indicate that marine population reach maturity at later age. These differences were less pronounced in riverine population, where we found no significant difference between size of male and female fish at any age. The faster growth of males is observed in many fish with nest guarding males and is inherent to all round goby populations. Acknowledgements The manuscript has been prepared by the aims of the project DО /08 funded by the Bulgarian Scientific Research Fund. References Apanasenko M.K. (1973). Size-age composition of round goby Neogobius melanostomus Pallas from different areas of Azov and Black Seas. Biologia Morya 31, (in Russian). Azizova N.A. (1962). The possibility of a goby fishery in the Caspian. Rybnoe Khozyaistvo 3, 14 Berg L.S., (1949). Freshwater Fishes of the USSR and Adjacent Countries. Vol. III. pp Acad. Sci. USSR Zool. Inst. (Translated from Russian by the Israel Program for Scientific Translations, Jerusalem, 1965). Bilko V.P. (1971). Comparative description of the growth of gobies (Gobiidae) and Lee s phenomenon. Journal of Ichthyology 11, Charlebois P.M., Marsden J.E., Goettel R.G., Wolfe R.K., Jude D.J., Rudnika S. (1997). The Round Goby, Neogobius melanostomus (Pallas). A Review of European and North American Literature. Illinois Indiana Sea Grant Program and Illinois Natural History Survey, Illinois Natural History Survey Special Publication 20, Champaign, pp. 76. Corkum L.D., Sapota M.R., Skora K.E. (2004). The round goby, Neogobius melanostomus, a fish invader on both sides of the Atlantic Ocean. Biological Invasions 6, French J.R.P. III & Black, M. G. (2009). Maximum length and age of round gobies (Apollonia melanostomus) in Lake Huron. Journal of Freshwater Ecology 24, Georgiev J.M. (1966). Species composition and characteristics of the gobies (Gobiidae, Pisces) of Bulgaria. Izv. Nauchn. Izsled. Inst. Rib. Stop. Okeanogr. Varna, 7, Gümüs A. & Kurt, A. (2009). Age structure and growth by otolith interpretation of Neogobius melanostomus (Gobiidae) from southern Black Sea. Cybium 33, Harka A. & Bíró P. (2007). New patterns in danubian distribution of Ponto-Caspian gobies a result of global climatic change and/or canalization? Electronic Journal of Ichthyology, 1, Johnson T.B., Bunnell D.B., Knight C.T. (2005a). A potential new energy pathway in Central Lake Erie: the round goby connection. Journal of Great Lakes Research 31 (Suppl. 2), Kornis M.S., Mercado-Silva N., Vander Zanden M. J. (2012). Twenty years of invasion: a review of round goby Neogobius melanostomus biology, spread and ecological implications. Journal of Fish Biology, 80, Kostyuchenko A.A. (1961). Age and growth of the round goby N. melanostomus (Pallas) in the Azov Sea. Tr. Azov. Chernom. Nauchn. Izsled. Inst. Rybn. Khoz. Okeanogr. 19, (In Russian). Kovtun I.F., Nekrasova M. Ja., Revina N. I. (1974). On the diet of round goby (Neogobius melanostomus) and utilization of food supply in Azov Sea. Zool. Zh. 53, Kovtun I.F., Nekrasova M. Ya., Dombrovskiy Yu. A., Revina N. I. (1976). Application of regressionanalysis for forecasting the size of the round goby stock in the Sea of Azov. Hydrobiol. J. 12, (English translation of Gidrobiol. Zh. 12, 49-53) Moskalkova K.I. (1996). Ecological and morpho-physiologycal prerequisites for distribution expansion of the goby Neogobius melanostomus under conditions of anthropogenous pollution of water bodies. Vopr. Ikchthyol. 36 (5), Pinchuk V., Vasil eva E.D., Vasil ev V.P., Miller P.J. (2003). Neogobius melanostomus (Pallas, 1814). In: Miller P.J. ed. The Freshwater Fishes of Europe: 8(1), AULA-Verlag GmbH Wiebelsheim. Pliszka J. A. (2002). Morphology of otoliths, age and growth rate of round goby (Neogobius melanostomus) from the Vistula Lagoon. MSc Thesis, University of Gda nsk, Gdynia, Poland (in Polish). 470

471 Polaĉik M., Janáĉ M., Trichkova T., Vassilev M., Jurajda P. (2008): The distribution and abundance of the Neogobius fishes in their native range (Bulgaria) with notes on the non-native range in the Danube River. Large Rivers 18, Rass, T.S. (1992). Fish resources of the Black Sea and their changes. Okeanologiya 32: Revina N.I. (1971). The state of the Neogobius melanostomus stock in the Sea of Azov. Rybn. Khoz. Moskva, 10, 7-9. Shemonaev E. V. & Kirilenko E. V. (2009). Some Features of Biology of the Round Goby Neogobius melanostomus (Perciformes, Gobiidae) in Waters of Kuibyshev Reservoir. Journal of Ichthyology, Vol. 49, No. 6, Simonović P, Paunović M., Popović S. (2001) Morphology, feeding and reproduction of the round goby, Neogobius melanostomus (Pallas) in the Danube River basin, Yugoslavia. Journal of Great Lakes Research 27, Smirnov A.I. (1986). [Perciformes (Gobioidei), Scorpaeniformes, Pleuronectiformes, Lophiiformes]. Fauna Ukraini 8, (in Russian). Sokołowska E. & Fey D.P. (2011). Age and growth of the round goby Neogobius melanostomus in the Gulf of Gdansk several years after invasion. Is the Baltic Sea a new Promised Land? Journal of Fish Biology 78, Stepanova T.G. (2001). Some features of reproduction and growth of gobies in the Northern Caspian. In: Ecology of young fish and problems of Caspian fish reproduction. VNIRO Press pp Svetovidov A.N. (1964). Fishes of the Black Sea. Nauka, Moskow. pp

472 EFFECTS OF SODIUM BICARBONATE ON CRITICAL SWIMMING SPEED OF RAINBOW TROUT (Oncorhynchus mykiss) Atamanalp M. 1, Kocaman E.M., 1, Alak G. 2, Uçar A. 1, Arslan H. 1 1 Fisheries Faculty, Ataturk University, 25240, Erzurum, Turkey 2 Agriculture Faculty, Ataturk University, Erzurum, Turkey Abstract Swimming performance is considered a good means of evaluating sublethal effects and an important criterion for the quantification of the sublethal effects of toxicants on fish. In this study, Oncorhynchus mykiss were exposed to three difference doses (0.7 mg/lt, 1.4 mg/lt and 2.1 mg/lt) of sodium bicarbonate during 4 days. Critical swimming speed (U crit ) was investigated at the end of the trial period. The statistically analyses showed that differences between groups in critical swimming speed are not significant (p<0.05). Key words: Sodium bicarbonat, critical swimming speed, rainbow trout 1. Introduction Aquatic environments worldwide are suffering from accelerated rates of environmental degradation due to emissions of toxic compounds from anthropogenic sources (Van der Oost et al. 2003). Feed additive used in various areas from laboratories to feeding activities in line with various targets like anesthetic substance and a chemical compound whose sodium carbonate chemical formula is NaHCO 3 is one of the sodium salts. It has antacid feature. It is also used as baking powder. It is water soluble white solid crystal powder and it has soft alkaline taste resembling sodium carbonate. It is also used in saline solution composition (Kaplan et al. 2005). Sodium bicarbonate (NaHCO 3 ) known as baking soda, is white in color, dissolved in water easily and gives carbon dioxide when dissolved in water. Carbon dioxide gas is listed for anaesthetic purposes in cold, cool and warm water fishes and has been used primarily to sedate fish during transport or to allow handling of large numbers of fish (Bowser 2001). In fisheries researches and aquaculture, some applications such as weighing or transporting the fishes from pond to pond should be carried out in a short time. The decreasing of water temperature may cause stress on fishes. So the determining the effects of anaesthetics appearing on the fishes at their natural ambient water temperature is important (Altun et al. 2009) Swimming performance is one of the most important factors enabling the survival of many fish species in ecological environment. Swimming performance depends on the diversity of biological and physiological factors. The characteristic of the species, i.e. body shape, fin shape, muscle function, swimming mode and fish size, is effective in swimming performance. Environmental factors are ph, oxygen, photoperiod and various pollutants. (Wolter & Arlinghaus 2003). 472

473 In fish, swimming activities are categorized as sustainable (more than 200 minutes), prolonged (between 15 seconds and 200 minutes) and maximum swimming speed (the possible highest swimming speed). Sustainable swimming speed includes the speed that fish use in activities like immigration, slow movements without muscle tiredness and search for feed. Prolonged swimming speed is the speed that the fish can sustain between 14 seconds and 200 minutes. The energy required for this speed is provided from both red muscle fibers (oxygenic) and white muscle fibers (oxygen-free). Maximum swimming speed occurs anaerobically with the participation of all movement muscles. (Reidy et al. 2000; Özbilgin & Başaran 2005). The most common method in measuring swimming performance for fish and other aquatic species is critical swimming speed. Critical swimming speed is a measurement for determining the swimming capability of fish (Plaut 2001). In this method, fish is placed in a water tunnel and swimming capability against water flow at different speeds is evaluated. Fish needs to protect its position against current because of optomotor. Critical swimming speed which is a special part of prolonged swimming speed depends on many environmental and physical factors. These factors are temperature and seasonal difference, body size, feeding, saltiness and pollution (Beamish 1978). Numeral expression of this activity in fish is possible with the measurement of swimming performance. Because swimming activity consists of many physiological processes and systems, calculation of swimming performance becomes possible in a controlled environment created specially. Swimming performance used as a sensitive index in the determination of health and stress situations of fish varies depending on many factors such as fish species, size, living environment and style, water parameters like temperature and saltiness, water pollution, current velocity of the water, feeding style of the fish and energy situation. The aim of this study is to determine the effects of sodium bicarbonate applied in different dosages on critical swimming speed of rainbow trout. 2. Material and Metod 80 rainbow trout (165±25 g) (Oncorhynchus mykiss) obtained from Atatürk University Faculty of Aquaculture Inland Water Fish Application and Research Center and not exposed to any infection or toxicity before were placed in test tank found in Faculty of Aquaculture Toxicology Research Unit. Two of the tanks were determined as control groups and other four were determined as treatment groups. In every tank, 10 fish were places and there were 8 tanks (Atamanalp 2000). Critical swimming speed is accepted as the estimated value of the highest sustainable speed in the measurement of the swimming speed of fish. This system is based on measuring the swimming performance of fish against current by increasing the water speed gradually after the fish are placed in water tunnel whose speed can be controlled (Figure 2.1). In the measurement of critical swimming speed, the time of exhaustion and current velocity are used (Hammer 1995). 473

474 Figure.2.1.Swimming performance system At the end of the application, fish exposed to 3 different doses of sodium bicarbonate for 4 days were taken in swimming tunnel for the measurement of critical swimming speeds in swimming performance unit having the same water quality with the environment they were in. Swimming performance measurement system consists of the tunnel having 1 m length and 40 cm diameter found in the tank system with rounded edges and 14,65 cm perimeter. Water temperature was measured directly by the system and flow rates were measured with current meter device (pemsantaş ). The critical swimming speed at exhaustion was calculated in cm s-1 for each fish using the following formula: Ucrit = U i + (T i /T ii )U ii Ui is the highest velocity maintained for the whole interval (cm s-1), Uii is the velocity increment (cm s-1), Ti is the time spent at fatigue velocity (min), Tii is the interval length (min: Brett, 1964). 3. Results Swimming performance is considered a good means of evaluating sublethal effects and an important criterion for the quantification of the sublethal effects of toxicants on fish. In this study, Oncorhynchus mykiss were exposed to three difference doses (0.7 mg/lt, 1.4 mg/lt and 2.1 mg/lt) of sodium bicarbonate during 4 days. Critical swimming speed (U crit ) was investigated at the end of the trial period. The statistically analyses showed that differences between groups in critical swimming speed are not significant (p<0.05). 474