PS 106-267
Managing bycatch with individual bycatch quotas: results from a game-theoretic analysis

Friday, August 14, 2015
Exhibit Hall, Baltimore Convention Center
Evelyn H. Strombom, Biology, University of Pennsylvania, Philadelphia, PA
Erol Ak├žay, Department of Biology, University of Pennsylvania
James R. Watson, College of Earth, Ocean and Atmospheric Sciences, Oregon State University

Bycatch is estimated at 40% of global marine catch, around 38.5 million tons, and is a significant challenge for managing sustainable marine systems.  Bycatch can be reduced by setting a total bycatch quota and closing the fishery when the bycatch limit is reached, but doing so could limit target species catch and revenue. To avoid premature closure of their fishing season, fishers can try to avoid bycatch independently or by cooperating with other fishers.  However, there is a conflict of interest for each fisher: does one act cooperatively and limit one’s bycatch, or, knowing that others are trying to do the same, does one act selfishly and disregard how much bycatch is caught? This is the classic free rider problem.  Transferrable individual bycatch quotas (IBQs) can in principle make fishers internalize the cost of bycatch. However, a rich set of social and economic arrangements in which fishers share or trade quotas can complicate matters. Here we present a game-theoretic model to understand when cooperative bycatch avoidance behavior can be attained under different management regimes and cooperation rules among the fishers. 


We identify the conditions when cooperative arrangements between fishers are vulnerable to cheating, and whether cheating fishers can completely unravel cooperation or can coexist with cooperative ones in a fishery. We also examine how cooperation or cheating among fishers affects risk of early season closure, and how the social and fishing outcomes respond to environmental variables, especially spatial heterogeneity and spatial correlation between target and bycatch species.  Last, we make comparisons between globally optimal solutions, the arrangement of cooperative and selfish behaviors that maximize the whole fishing fleet’s revenue, and non-cooperative equilibria where individuals optimize their revenue. We frame these results in the context of several real-world fishery examples and explain how our theoretical results will contribute to new forms of management that efficiently minimize the impact of fishing on marine systems.