Keith R. Criddle

Because 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.

A simultaneous‐equation equilibrium model of domestic and international markets for fillets, surimi, and roe of Alaska pollock (i.e., Walleye Pollock Gadus chalcogrammus) is used to examine the combined effect of variability in landings and changes in product mix on first wholesale prices and revenues. From the commencement of Americanization in the mid‐1970s through the joint venture era of the 1980s and following full Americanization in early 1990s, U.S. producers of Alaska pollock focused mainly on selling surimi and roe to Japan. Passage of the American Fisheries Act of 1998 (AFA) unleashed an economic transformation that more than doubled fishery revenues without increasing exploitation rates or catches. The increased value came about because freedom from the race for fish allowed fishers and processors to increase product quality, improve product recovery rates, diversify their mix of product forms, and develop new markets in the USA and Europe. Despite the size and importance of the Alaska pollock fishery—among U.S. fisheries, it consistently ranks number one by volume and in the top five by value—little attention has been given to the development of a formal model of Alaska pollock markets or the market impacts of the AFA. The results of the model indicate that first wholesale revenues are maximized when harvests are maximized, but the value of the harvest is particularly sensitive to changes in the demand for Alaska pollock harvested in Russian waters, price differentials between fillet and surimi, and Japanese inventories of Alaska pollock products. Comparative static simulations comparing pre‐ and post‐AFA fishery product recovery rates and product mix indicate revenues would have increased by 62% from 1998 to 2007. Received June 21, 2013; accepted July 1, 2014

Killer whale (Orcinus orca) depredation (whales stealing or damaging fish caught on fishing gear) adversely impacts demersal longline fisheries for sablefish (Anoplopoma fimbria), Pacific halibut (Hippoglossus stenolepis) and Greenland turbot (Reinhardtius hippoglossoides) in the Bering Sea, Aleutian Islands and Western Gulf of Alaska. These interactions increase direct costs and opportunity costs associated with catching fish and reduce the profitability of longline fishing in western Alaska. This study synthesizes National Marine Fisheries Service observer data, National Marine Fisheries Service sablefish longline survey and fishermen-collected depredation data to: 1) estimate the frequency of killer whale depredation on longline fisheries in Alaska; 2) estimate depredation-related catch per unit effort reductions; and 3) assess direct costs and opportunity costs incurred by longliners in western Alaska as a result of killer whale interactions. The percentage of commercial fishery sets affected by killer whales was highest in the Bering Sea fisheries for: sablefish (21.4%), Greenland turbot (9.9%), and Pacific halibut (6.9%). Average catch per unit effort reductions on depredated sets ranged from 35.1–69.3% for the observed longline fleet in all three management areas from 1998–2012 (p<0.001). To compensate for depredation, fishermen set additional gear to catch the same amount of fish, and this increased fuel costs by an additional 82% per depredated set (average $433 additional fuel per depredated set). In a separate analysis with six longline vessels in 2011and 2012, killer whale depredation avoidance measures resulted in an average additional cost of $494 per depredated vessel-day for fuel and crew food. Opportunity costs of time lost by fishermen averaged $522 per additional vessel-day on the grounds. This assessment of killer whale depredation costs represents the most extensive economic evaluation of this issue in Alaska to date and will help longline fishermen and managers consider the costs and benefits of depredation avoidance and alternative policy solutions.