FISHERIES STOCK ASSESSMENT AND DECISION-ANALYSIS - THE BAYESIAN-APPROACH

The Bayesian approach to stock assessment determines the probabilities of alternative hypotheses using information for the stock in question and from inferences for other stocks/species. These probabilities are essential if the consequences of alternative management actions are t o be evaluated through a decision analysis. Using the Bayesian approac h to stock assessment and decision analysis it becomes possible to adm it the full range of uncertainty and use the collective historical exp erience of fisheries science when estimating the consequences of propo sed management actions. Recent advances in computing algorithms and po wer have allowed methods based on the Bayesian approach to be used eve n for fairly complex stock assessment models and to be within the reac h of most stock assessment scientists. However, to avoid coming to ill -founded conclusions, care must be taken when selecting prior distribu tions. In particular, selection of priors designed to be noninformativ e with respect to quantities of interest to management is problematic. The arguments of the paper are illustrated using New Zealand's wester n stock of hoki, Macruronus novaezelandiae (Merlucciidae) and the Beri ng-Chukchi-Beaufort Seas stock of bowhead whales as examples.