An agent‐based model to optimize transboundary management for the walleye pollock (Gadus chalcogrammus) fishery in the Gulf of Alaska

Abstract

AbstractBecause fish stocks often straddle state, national, and international boundaries, there is a need to coordinate fishery management across jurisdictions. This is particularly important when the abundance or spatial distribution of the stock varies through time. This is best achieved when management objectives and strategies align, and there is coordinated decision‐making and catch accounting among jurisdictions such that each fish stock is managed over its full geographic range. However, legal constraints or differing management objectives may not permit such coordinated decision making and policy development. This study introduces a framework for effectively simulating fleet dynamics, fishery quota allocation, and the implications of alternative management strategies while allowing for determination of economically optimal management approaches at the community level. As a case study, an agent‐based model (ABM) was developed to examine the interplay between transboundary management scenarios on the economic viability of a nascent Alaska state‐waters trawl fishery for walleye pollock (Gadus chalcogrammus) in the Gulf of Alaska, given a longstanding federally managed fishery. Under conditions characteristic of the recent past, the management strategy that produced the best overall improvements, relative to status quo, involved a scenario that allows for community‐based cooperatives in federal‐waters and an open access strategy in state‐waters. This case study allows us to demonstrate more generally how using an ABM allows for quantifying the impacts of and informing managers on anticipated, and novel, results of alternative management strategies for complex socioecological systems before implementation.Recommendations for Resource Managers Agent‐based modeling provides a method to realistically simulate fleet behavior within a fishery. The approach enables a quantitative analysis of the effects of alternative management scenarios under consideration by policymakers. “Best practices” for fishery management should include simulation analysis of management alternatives before selection of the preferred alternative for real‐world implementation.