Estimating Steepness of Stock-Recruitment Relationship Using Bayesian Analysis

• Main Authors: Chun Chi Wu, 吳純綺
• Other Authors: 許建宗
• Format: Others
• Language: en_US
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/36966458032104718900

碩士 === 國立臺灣大學 === 海洋研究所 === 100 === To formulate the stock-recruitment (S-R) curve is one of the essential tasks in fishery stock assessment. Steepness is generally used to re-parameterize the S-R relationship thereby providing insight on resilience of a stock under exploitation. High steepness implies that a stock is relatively resilient. In this study, we use a Bayesian approach to re-estimate steepness of the Beverton-Holt S-R curve for the Pacific bluefin tuna (Thunnus orientalis) on the basis of the production model incorporating multiple fisheries. Previous steepness estimates (h ~ 1) for Pacific bluefin tuna seem too high to be plausible. Substantially, we evaluate the effects of using an uninformative prior vs. an informative prior based on information from other studies on posteriors of steepness. Our analysis shows small discrepancy between the two priors on their posteriors. The estimations of steepness (0.98 from vague-prior setting, and 0.94 from informative-prior setting) suggest that Pacific Bluefin tuna may be sensitive to variable environmental conditions.