Stock assessment for Atlantic yellowfin tuna based on extended surplus production model considering life history |
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| Authors: | Zhipan Tian Fei Wang Siquan Tian Qiuyun Ma |
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| Institution: | 1.College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China2.National Distant-water Fisheries Engineering Research Center, Shanghai 201306, China3.Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China4.Fisheries College, Zhejiang Ocean University, Zhoushan 316022, China |
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| Abstract: | The modern fishery stock assessment could be conducted by various models, such as Stock Synthesis model with high data requirement and complicated model structure, and the basic surplus production model, which fails to incorporate individual growth, maturity, and fishery selectivity, etc. In this study, the Just Another Bayesian Biomass Assessment (JABBA) Select which is relatively balanced between complex and simple models, was used to conduct stock assessment for yellowfin tuna (Thunnus albacares) in the Atlantic Ocean. Its population dynamics was evaluated, considering the influence of selectivity patterns and different catch per unit effort (CPUE) indices on the stock assessment results. The model with three joint longline standardized CPUE indices and logistic selectivity pattern performed well, without significant retrospective pattern. The results indicated that the stock is not overfished and not subject to overfishing in 2018. Sensitivity analyses indicated that stock assessment results are robust to natural mortality but sensitive to steepness of the stock-recruitment relationship and fishing selectivity. High steepness was revealed to be more appropriate for this stock, while the fishing selectivity has greater influence to the assessment results than life history parameters. Overall, JABBA-Select is suitable for the stock assessment of Atlantic yellowfin tuna with different selectivity patterns, and the assumptions of natural mortality and selectivity pattern should be improved to reduce uncertainties. |
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| Keywords: | population dynamics selectivity tropical tuna fishery management |
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