A DECISION-THEORY CASE-STUDY - CHOOSING A SEASON OPENING FOR A SPINY LOBSTER (PANULIRUS-ARGUS L.) FISHERY

The present work illustrates a robust rational approach to making deci sions under uncertainty. The optimal opening for the Turks and Caicos Islands lobster season is estimated using Bayesian decision theory. In formation from a variety of sources is combined to obtain posterior pr obability distributions for two uncertain parameters used in a simple bioeconomic utility model. A moult rate parameter posterior probabilit y distribution is obtained from a subjective prior updated with size f requency and tagging data. A natural mortality posterior is obtained f rom a prior derived from published estimates and a fitted catch-effort model. In the case of the size-frequency and catch-effort models, the parameter likelihoods are generated using a Bayesian bootstrap techni que which does not assume any particular likelihood model. (C) 1998 El sevier Science B.V. All rights reserved.