Main Objective

1. Seasonal abundance with biomass and distribution patterns of European hake Merluccius merluccius (L.) in Izmir Bay (Turkey)Esin Yalcin, Rasit Gurbet, Okan Ozaydin, Erdem Sayin, Sencer Akalin, Semih Leblebiciesin.yalcin@mail.ege.edu.trEge University, Fisheries Faculty, Department of Fisheries and Processing Technology, İzmir/Turkey

2. Main Objective The hypothesis; main abiotic factors (e.g. temperature, salinity, water masses) and also oceanographic conditions (e.g. eddies, wind-driven circulation, thermohaline-driven, baroclinic circulation) may also influence fish-biomass fluctuations in Izmir Bay. Exhibition of relationship between monthly abundance and distribution patterns of stability in time and space with some important hydrographicconditions (e.g. temperature) by using GIS (Geographical Information System) tools and statistical techniques. This study deals with the monthly abundance (number/h) with biomass (kg/h) and distribution patterns of European hake (M. merluccius) in the Izmir Bay, Turkey. The goal of the present study is to learn more about the factors that might modulate the spatio-temporal aggregation patterns of species.

3. This study belongs to one of the TUBITAK (The Scientific and Technological Research Council of Turkey) project which name is “Investigation effects of abiotic environmental factors on commercially important demersal fish population in Izmir Bay” (2007-present). • PhD thesis: The effects of environmental variables on red mullet (Mullus barbatus) and European hake (Merluccius merluccius) populations in Izmir Bay.

4. Aegean Sea & Izmir Bay Aegean Sea, GFCM / GSA-22

5. Total Landings of European hake GSA-22 (Aegean Sea) Turkish Coast Site 1990-2007 TURKISH STATISTICAL INSTITUTE (TurkStat) Annual Fishery Statistics European hake (Merluccius merluccius) is one of the most important demersal target species of the commercial fisheries in the Aegean Sea (geographical sub-area 22).

6. Material & Methods • Use of trawl surveys seasonal data; 7 research trawl surveys performed between 2007 and 2008 (present) • Evaluations of abundance with swept area method; 10 bottom trawling by depth ranges of stations by km² • Use of oceanographic in situ data,10 hydrographic & 7 current meter stations (depth range 20-70 m) • Use of monthlymeteorological data,wind data sets of Izmir Bay from the Turkish State Meteorological Service • Evaluations of distribution patterns with GIS tools;Spatial Analysis extension of ArcGIS (ESRI) • Using statistical techniques to arrange data sets;One-Sample Kolmogorov-Smirnov Test and Bonferroni Test • Using flexible regression analysistoanalysis all data together;A GLM multifactor ANOVA was used for the dependent variable in relation to factors

7. GIS Tools • Withthe analytical tool contained in the Spatial Analyst extensionof Arc GIS 9.2 (ESRI, 2006) • Interpolations of temperature value was done using the krigging techniques. • The external limits of the areas (contours) occupied by each range of values. • Spatial distribution of abundance of species as kg/h & number/h exhibited by different colored fish symbol in each stations.

8. Fig.1. GIS Model

9. Fig.2. Bathymetry of Izmir Bay and hydrographic stations. Figure 1. Bathymetry of the Izmir Bay with the research stations. Figure 1. Bathymetry of the Izmir Bay with the research stations.

10. Prohibited Area, Izmir Bay Commercial fisheries annual circular 2006-2008. Prohibited time scale: 15 April-15 September

11. Fig. 3. Geographical distribution of abundance (kg/h) of European hake in autumn with temperature.

12. Fig. 4. Geographical distribution of abundance (numbers/h) of European hake in autumn with temperature.

13. Fig. 5. Geographical distribution of abundance (kg/h) of European hake in winter with temperature.

14. Fig. 6. Geographical distribution of abundance (numbers/h) of European hake in winter with temperature.

15. Fig. 7. Geographical distribution of biomass (kg/h) of European hake in spring with temperature.

16. Fig. 8. Geographical distribution of abundance (numbers/h) of European hake in spring with temperature. Figure 2. Geographical distribution of abundance (numbers/h) of European hake in spring with temperature.

17. Table.1. Factors available for inclusion in the analysis. Data Analysis

18. Statistical Analysis • The dependent variables were found to be app. log-normally distributed. They were log10-transformed to stabilize their variance by One-Sample Kolmogorov-Smirnov Test. • Abundance data were also incremented by 1 (data+1) to avoid censoring all zero sample sizes from subsequent transformations used to stabize data variances. • In descriptive statistics, a boxplot (box-and-whisker diagram) was used as a convenient way of graphically depicting groups of numerical data. • Adjustment for multiple comparisons by Bonferroni Test. • Significance level was set to α = 0,05 in statistical analysis.

19. Interaction plots of mean values Fig.9. Interaction plots of mean values expressed in months. Figure 9. Interaction plots of mean values expressed in months.

20. Boxplot (box-and-whisker diagram) Log10 (hake_kg/h+1) Log10 (hake_number/h+1) Fig.10. Differences between monthly abundance (number/h) and biomass (kg/h) by boxplot.

21. Statistical Model • A GLM (Generalized Linear Models) multifactor ANOVA was used for the dependent variable in relation to factors. • The dependent variable under examination was indices of fish density in number and biomass. • All factors (month, station, species, depth, temperature, salinity) were initially included in the model.

22. GLM multifactor ANOVA for European hake biomasslog (kg/h+1)by stations month WITH temperature & salinity & depth Fig.11. This test is based on the linearly independent pairwise comparisons among the estimated marginal means of month.

23. GLM multifactor ANOVA for European hake abundancelog (number/h+1)by stations month WITH temperature & salinity & depth Fig.12. This test is based on the linearly independent pairwise comparisons among the estimated marginal means of month.

24. European hake (Merluccius merluccius) Table.2. European hake Biomass (kg/km²) and CPUE (kg/HP) Autumn (October, November) and Summer (June, July, August) data will be collected in 2008 and in 2009.

25. RESULTS & DISCUSSION • European hake were higher exploited fish species in all fishing allowed area of the Izmir Bay. • European hake were mainly distributed in middle of the bay. • Significant differences among stations and temperature were observed in Izmir Bay by using flexible regression analysis; GLM and supported by GIS Model. • The mean regional density of hake was observed to vary monthly, being higher mainly abundance (number/h) of fish in autumn, biomass (kg/h) of fish in winter. It is supported by ArcGIS analysis. • European hake Biomass (kg/km²) and CPUE (kg/HP) mainly distributed higher in depth range of 30-50 m. The most high value displayed in September.

26. RESULTS & DISCUSSION • In view of the limited understanding of the dynamic ecology of European hake, it is necessary to consider all possible causes for the observed of fishery. • It is necessary to take all data for each month in a year to consider all possible effects on European hake distribution in study area. • Additional years of data would be useful in further testing the stability of the suggested distribution patterns. • Other oceanographic factors such as current, salinity, density, Dissolved Oxygen, pH, klorofil-a, etc. are also important and should evaluated with all season data. • All collected biological and population data should be evaluated when the project was finished.

27. Acknowledgements • This study was founded in TUBITAK (The Scientific and Technological Research Council of Turkey) project which name is “Investigation of effects of abiotic environmental factors on commercially important demersal fish population in Izmir Bay”. • The authors want to express their gratitude to all colleagues and volunteer students involved in the surveys and data processing. • Special thanks to Elizabeth Tunka Eronat, Gokay Aydogdu and S. Ahmet Özdemir.