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 Leblebici

esin.yalcin@mail.ege.edu.tr

Ege University, Fisheries Faculty, Department of Fisheries and Processing Technology, İzmir/Turkey

Main ObjectiveThe 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 hydrographic conditions (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.

• 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.

Aegean Sea & Izmir BayAegean Sea & Izmir Bay

Aegean Sea, GFCM / GSA-22

Total Landings of European hake

European hake (Merluccius merluccius)

0

2000

4000

6000

8000

10000

1990

1992

1994

1996

1998

2000

2002

2004

2006

year

tonnes

GSA-22 (Aegean Sea) Turkish Coast Site 1990-2007

TURKISH STATISTICAL INSTITUTE (TurkStat) Annual Fishery StatisticsEuropean hake (Merluccius merluccius) is one of the most important demersal target species of the commercial fisheries in the Aegean Sea (geographical sub-area 22).

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 monthly meteorological 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 analysis to analysis all data together; A

GLM multifactor ANOVA was used for the dependent variable in relation to factors

GIS Tools

• With the analytical tool contained in the Spatial Analyst extension of 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.

Fig.1. GIS Model

Fig.2. Bathymetry of Izmir Bay and hydrographic stations.

Prohibited Area, Izmir Bay

Commercial fisheries annual circular 2006-2008. Prohibited time scale: 15 April-15 September

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

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

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

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

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

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

Table.1. Factors available for inclusion in the analysis.

Factors Description

Dependent M. merluccius

Kg/hNumber/h

Categorical MonthStation

7 month (3 seasons)

10 station

Quantitative DepthTemperatureSalinity

mC°psu

Data Analysis

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.

Interaction plots of mean values

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

Boxplot (box-and-whisker diagram)

1 2 3 4 5 6 8 9 10 11

stations

0,00

1,00

2,00

3,00

log

_mm

er_

a

1 2 3 4 5 6 8 9 10 11

stations

0,00

0,50

1,00

1,50

2,00

log

_mm

er_

kg

Fig.10. Differences between monthly abundance (number/h) and biomass (kg/h) by boxplot.

Log10 (hake_kg/h+1) Log10 (hake_number/h+1)

• 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.

Statistical Model

Fig.11. This test is based on the linearly independent pairwise comparisons among the estimated marginal means of month.

GLM multifactor ANOVA for European hake biomasslog (kg/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.

GLM multifactor ANOVA for European hake abundance log (number/h+1) by stations month WITH temperature & salinity & depth

European hake (Merluccius merluccius)Biomass (kg/km²) CPUE (kg/HP)

Dep

<30 m 30-50 m

>50 m Total <30 m 30-50 m

>50 m Total

Sep

- 61029,24

47591,93

108621,17

- 131,81 102,79 234,60

Dec

3031,12 6,50 43808,84

46846,46 6,55 0,01 94,62 101,18

Jan 1515,56 13413,02

4851,60 19780,18 3,27 28,97 10,48 42,72

Feb

6314,84 17772,25

6894,77 30981,85 13,64 38,38 14,89 66,92

Mar

19852,48

25496,71

13271,45

62186,37 42,88 55,07 28,665 134,31

Apr

May

505,19 3267,03 27388,73

33603,75 1,09 7,06 59,15 72,58

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.

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.

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.

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.