Methodology for the Analysis of Fishery Management Policies, with an Example of the North Carolina Brown Shrimp Fishery

摘要

Since the passage of the Fisheries Conservation and Management Act in 1976 there has been increasing attention to the problems associated with managing marine resources. The paper is a response to this call. It presents a methodology for the analysis of fishery management policies and for the identification of policies that approximate optimal policies. The methodology applies the techniques of sequential decision processes to a stochastic simulation model of a fishery. The use of Monte Carlo sampling techniques enables one to characterize fisheries more comprehensively than techniques that require models with analytical solutions. Furthermore, an application of sequential techniques to the Monte Carlo sample provides the analyst with the ability to approximate optimal policies in this more comprehensive setting. To demonstrate the approach the authors illustrate how the model works using data from the North Carolina brown shrimp (Penaeus aztecus) fishery of Pamlico Sound.