Estimating Steepness of Stock-Recruitment Relationship Using Bayesian Analysis

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 will use a Bayesian approach to re-estimate steepness of the Beverton-Holt S-R curve for the Pacific bluefin tuna (Thunnus orientalis). Previous steepness estimates for Pacific bluefin tuna seem too high to be plausible. Substantially, the effects of using an uninformative prior vs. an informative prior based on information from other studies on posteriors of steepness are investigated, and the influences of different steepness on yields are simulated. Consequently, this study shows small discrepancy between the two priors on their posteriors, and that different steepness estimates can have pronounced effects on the predicted yields, resulting in  different management decisions.