中国水产科学2023，Vol.30Issue(9)：1142-1154,13.DOI:10.12264/JFSC2023-0168
利用贝叶斯动态产量模型评估印度洋长鳍金枪鱼资源状态
Status assessment of Thunnus alalunga resources in the Indian Ocean using a Bayesian biomass dynamic model
摘要
Abstract
There is relatively little information on the biology of Indian Ocean albacore tuna(Thunnus alalunga);further,many problems with the fishery data result in a large uncertainty in its stock assessment results and affect fishery management.In this study,based on the fishery catch,standardized Catch Per Unit Effort(CPUE)data,and relevant stock hypotheses of Indian Ocean albacore tuna,a Bayesian biomass dynamic model was used to conduct a stock assessment.The results showed that:(1)The observation error of catch has an important influence on the estimation of model parameters,judgment of resource status,and fishery management,and an increase in catch observation error increases the probability of overfishing assessed by the model,which leads to a decrease in Total Allowable Catch(TAC);(2)The shape parameters of biomass dynamic model,prior distribution of r,and choice of resource abundance index affect the quality of stock assessment,and this study shows that the stock assessment results of the Fox model are more reasonable than those of the Schaefer model,the increase in the range of r priori distribution makes the resource state assessed by the model better,and the assessment results are relatively better when using the standardized CPUE of the southwest waters;(3)Setting a range of resource proportions(φ、P2017)for certain years can help improve the quality of fishery stock assessment under the lack data;(4)The probability of overfished and overfishing for albacore tuna in the Indian Ocean are 34％and 50％,respectively,and the probability of both occurring simultaneously is 32％,and the species is at risk of overfishing.The projection analysis showed that the probability of not overfishing for Indian Ocean albacore tuna after 10 years was greater than 60％when the TAC was controlled below 32658 t(i.e.,90％of the final five-year average catch).The Bayesian biomass dynamic model,as a data-limited fishery stock assessment model,is applicable to Indian Ocean albacore tuna,and it can better consider the effects of parameter inputs and uncertainty factors on the quality of stock assessment and the estimation of TAC,providing a scientific basis for an in-depth study of the stock status and management of Indian Ocean albacore tuna.关键词
印度洋/长鳍金枪鱼/贝叶斯动态产量模型/资源评估与管理Key words
the Indian Ocean/Thunnus alalunga/Bayesian biomass dynamics model/stock assessment and management分类
农业科技引用本文复制引用
安康,官文江..利用贝叶斯动态产量模型评估印度洋长鳍金枪鱼资源状态[J].中国水产科学,2023,30(9):1142-1154,13.基金项目
国家自然科学基金项目(32072981). （32072981）
