PRELIMINARY ANALYSIS OF CATCH RATES OF ATLANTIC BONITO (SARDA SARDA) CAUGHT BY MOROCCAN ARTISANAL GILL NET FISHERY IN THE ATLANTIC,
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1 SCRS/2012/179 COLLECT. VOL. SCI. PAP. ICCAT, 69(5): (2013) PRELIMINARY ANALYSIS OF CATCH RATES OF ATLANTIC BONITO (SARDA SARDA) CAUGHT BY MOROCCAN ARTISANAL GILL NET FISHERY IN THE ATLANTIC, N. Abid 1, A. Faraj 2, F. El Omrani 3 and K.Ouakka 4 SUMMARY Nominal CPUE of Atlantic bonito (Sarda sarda) from Moroccan artisanal gill net fishery operating in the Atlantic during the period were analyzed by GLM approach assuming a log normal error distribution. The preliminary standardized annual abundance index didn t show any clear trend over the considered period RÉSUMÉ La CPUE nominale de la bonite à dos rayé de l Atlantique (Sarda sarda) en provenance de la pêcherie artisanale marocaine opérant au filet maillant dans l'océan Atlantique entre 2004 et 2010 a été analysée par une approche GLM postulant une distribution d'erreur lognormale. L'indice d'abondance annuel préliminaire standardisé n'a dégagé aucune tendance claire au cours de la période considérée. RESUMEN Se analizó la CPUE nominal del bonito del Atlántico (Sarda sarda) de la pesquería artesanal de redes de enmalle marroquíes que operó en el Atlántico durante el periodo mediante un enfoque GLM y asumiendo una distribución de error lognormal. El índice de abundancia anual preliminarmente estandarizado no mostró ninguna tendencia clara durante el periodo considerado. KEY WORDS Atlantic Bonito, GLM, nominal CPUE, artisanal Gill net fishery Introduction The Atlantic bonito (Sarda sarda) is one of the main small tuna species caught in the Moroccan waters. The annual average catches of this species during the last 5 years was about 1136TM, which represent nearly 53% of the total small tuna s catches. In the Moroccan Atlantic coast, this species is mainly caught by an artisanal fleet using gillnet. The main fishing area is comprised between 22 and 25 N latitude and 15 and 17 W longitude (Figure1). This paper aimed to carry out a preliminary analysis of the catches of Atlantic bonito per trip related to this fishery from 2004 to Material and Methods The total catch (in weight) data from 3345 positive trips carried out by the Moroccan artisanal fleet operating in the Atlantic waters during the period , were collected from the fish market in the Dakhla port located in south of Morocco. 1 Institut National de Recherche Halieutique (INRH), Regional Centre of Tangier, Morocco. 2 Institut National de Recherche Halieutique (INRH), Head of Fisheries Department, Casablanca, Morocco. 3 Institut National de Recherche Halieutique (INRH), Regional Centre of Dakhla, Morocco. 4 Institut National de Recherche Halieutique (INRH), Regional Centre of Laayoune, Morocco. 2156
2 The nominal CPUE, expressed as the total catch in weight per trip, was analyzed by General Linear Model (GLM) approach (McCullagh and Nelder, 1989), assuming a lognormal error distribution to compute the annual standardized index. In this analysis, the vessels were classified arbitrary according to their GRT into four classes: Class 1: Tx; Class 2: Tx Class 3: Class 4: 65 Tx The factors considered in the initial model are as follow: Log (CPUE w ) = µ + Y + Q + GRT class+ Y*Q +Y*GRT class+ Q*GRT class+ e Log(CPUEw): natural logarithm of nominal CPUE in weight µ: intercept Y: year effect Q: Quarter effect GRT class: Gross tonnage class effect Y*Q: interaction Year and quarter effect Y*GRT class: interaction Year and Gross tonnage class Q*GRT class: interaction Quarter and Gross tonnage class e: error The step AIC analysis was performed for the evaluation of the factors in the model. Only factors explaining at least 5% of the total deviance were selected in the final model to compute the annual standardized abundance index. 2. Results and Discussion 2.1 Description of the fishery The fleet targeting Atlantic bonito is made up of about 60 vessels. It is on average 28 GRT, 14m and 180HP. Other tuna species such as the little tunny (Euthunnus alletteratus), the plane bonito (Orcynopsis unicolor) and skipjack (Katsuwonus pelamis) are also caught by this fleet in small quantities. However, the Atlantic bonito remains the dominating species in the catches, with more than 80% in weight. The fishing activity takes place over the year, with higher intensity during the last quarter of the year. The size data from this fishery are still not available. Currently there are no management measures at the national level for small tuna s species. 2.2 CPUE analysis The number of observation for each factor levels combination is summarized in the Table 1. In general, the number of trips by year, quarter and GRT class seems to be satisfactory. The distribution of Log nominal CPUE by year, quarter and GRT class is illustrated by the Figure 2. Some differences are noticeable for each factor levels. The results of the deviance analysis are presented in the Table 2. Both factors Year, Quarter and their interaction explain 25% of the total variability in the response variable. These factors are selected in the final model to compute the standardized index. The diagnostic plots (residuals vs fitted values and QQ plots) for the final model are illustrated by the Figure 3. In overall, the selected model fit well the observed data, as the residual don t show any clear trend. The Table 3 summarizes the nominal CPUE, the annual standardized index, and the corresponding standard error and the coefficient of variation (CV). The trend in the annual nominal and standardized CPUE index is shown by the Figure
3 More data related to the fleet characteristics and the size data from this fishery will be collected in the future to take into account in the future analysis of CPUE. References Mccullagh, P. and J.A. Nelder Generalized linear models. Second Edition. Chapman & Hall. University Press. Cambridge. 511pp. N. Abid, S. Benchoucha, A. Lamatai, C. El fanichi, F. El omrani, J. Bensbai, M. El Orch et M. Bougharioun Pêcherie des grands pélagiques. Rapport national interne de l INRH. 66 p 2158
4 Table 1. Number of observations by year, quarter and GRT class considered in the GLM analysis. GRT class/quarter Total Grand Total
5 Table 2. Deviance analysis results. Δ deviance refers to change in deviance; % deviance: percentage of deviance explained with respect to the null model. Residual Residual Model factors Df Deviance Null Δ deviance % deviance P(> Chi ) Year % 6.17E-55 Year+Quarter % 1.68E-116 Year+Quarter+GRT class % 8.84E-07 Year+Quarter+GRT class+year:quarter % 8.09E-57 Year+Quarter+GRT class+year:quarter+year:grt class % 1.47E-02 Year+Quarter+GRT class+year:quarter+year:grt class +Quarter:GRTclass % 1.87E-01 Table 3. GLM estimated standardized annual abundance index and the corresponding standard errors and coefficient of variation (CV %). Year Nominal Std.Index Scaled Std.Index Std. Error CV(%) % % % % % % % Figure 1. The main fishing area for the Moroccan artisanal gillnet fishery targeting small tunas. 2160
6 a b c Figure 2. Distribution of Log nominal CPUE by year (a), GRT class (b) and by quarter (c). Figure 3. Diagnostic plots: residual vs fitted values and QQ plot. 2161
7 CPUE(Kg/trip) Std.CPUE Upper CPUE Lower CPUE Nominal CPUE Figure 4. Trend in nominal and standardized annual abundance index and corresponding % confidence limits. 2162
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