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Application of Bayesian surplus production model and traditional surplus production model on stock assessment of the southern Atlantic albacore (<i>Thunnus alalunga</i>)

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Title Application of Bayesian surplus production model and traditional surplus production model on stock assessment of the southern Atlantic albacore (Thunnus alalunga)
 
Creator Liao, Baochao
Zhang, Kui
Shan, Xiujuan
Chen, Xiao
Baset, Abdul
Memon, Khadim Hussain
Liu, Qun
 
Subject Bayesian model
Fox model
Thunnus alalunga
Southern Atlantic
Risk assessment
 
Description 922-928
Bayesian surplus Production model (BSP) and traditional surplus Production models (TSP) were used to evaluate the southern Atlantic albacore (Thunnusalalunga) stock. Population parameterswere estimated using CEDA (catch-effort data analysis) and ASPIC (a surplus-production model incorporate covariates) computer software packages. Performance of the BSP model and TSP model were compared by a Bayesian information criterion (BIC). Maximum sustainable yield (MSY) from the TSP model and BSP model were used to verify the MSY estimations by International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch of 2011 (24122 t) was higher than the MSY from BSP (21756t, 23408t), and the relative fishing mortality ratio (F2011/FMSY) of the stock was higher than 1.0, which shows thatthis stock over-exploited. Different harvest strategies were set to assess the risk for this stock, and these estimates were used topredict the biomass and catch in 2025 (B2025, C2025) and other five indexes (B2025 /BMSY, B2025 /K, P (B2025> B2012), P (B2025> BMSY), P (B2025< BMSY/4)). Evaluated biological reference points (BRPs) from Bayesian model were compared with the results from traditional modeling method on the southern Atlantic albacore (T. alalunga) stock, and results showed that the measures should be taken for the sustainable utilization of this fish stock, and the harvest rate of 0.15 seemed tobe the best management measures.
 
Date 2017-05-08T09:33:16Z
2017-05-08T09:33:16Z
2017-05
 
Type Article
 
Identifier 0975-1033 (Online); 0379-5136 (Print)
http://nopr.niscair.res.in/handle/123456789/41671
 
Language en_US
 
Rights CC Attribution-Noncommercial-No Derivative Works 2.5 India
 
Publisher NISCAIR-CSIR, India
 
Source IJMS Vol.46(05) [May 2017]