中国水产科学2018，Vol.25Issue(3)：621-631,11.DOI:10.3724/SP.J.1118.2018.17280
应用贝叶斯生物量动态模型评估印度洋黄鳍金枪鱼资源
Assessment of the Indian Ocean yellowfin tuna (Thunnus albacares) using a Bayesian biomass dynamic model
摘要
Abstract
The aim of the present study was to assess the Indian Ocean yellowfin tuna (Thunnus albacares) using a Bayesian biomass dynamic model and to analyze the impacts of two standardized longline CPUE (catch per unit effort) series from Japan and Taiwan and the prior distributions of intrinsic rate of increase (r) on the results of the assessments. (1) The models fit the standardized CPUE from Japan better than that from Taiwan, and the results indicated that the stock was overfished and subject to overfishing when the standardized CPUE from Japan was singly used in the models. The opposite might be achieved using the standardized CPUE from Taiwan. Further-more, when both standardized CPUEs were used, the weighting of the model-estimated Japan standardized CPUE was greater than that of the Taiwan standardized CPUE, and the results were similar for models where only the Japan standardized CPUE was used. (2) If uninformative prior was assigned to r, the estimate of the parameters seemed unreasonable because the r was likely to be underestimated, and the carrying capacity (K) was overesti-mated. If informative prior was used for r, the estimates of r and k seemed more reasonable. Because there is often a strong negative correlation between r and K in biomass dynamics models, it is difficult to correctly estimate r and K simultaneously, especially under data-poor situations. However, by using informative priors, estimates of parameters of biomass dynamics models can be improved. (3) Deviance information criterion (DIC) and mean square error (MSE) were used to evaluate model fitness, and model S8 was selected as the best model for assessing stock status. According to model S8, Indian ocean yellowfin tuna are overfished and subject to overfishing, which was identical to the results based on Stock Synthesis.关键词
印度洋/黄鳍金枪鱼/贝叶斯/生物量动态模型/资源评估Key words
Indian Ocean/Thunnus albacares/Bayesian/biomass dynamic model/stock assessment分类
农业科技引用本文复制引用
官文江,朱江峰,田思泉..应用贝叶斯生物量动态模型评估印度洋黄鳍金枪鱼资源[J].中国水产科学,2018,25(3):621-631,11.基金项目
国家自然科学基金联合基金重点项目(U1609202) （U1609202）
大洋渔业资源可持续开发省部共建教育部重点实验室开放基金项目(A1-0203-00-2009-2). （A1-0203-00-2009-2）
