Simple vs. complex stock assessment models: a comparison of their utility for managing fisheries

University Of Alaska Fairbanks Campus, Fairbanks AK

Investigators

Abstract

Both scholars and practitioners use fisheries stock assessments to estimate fish abundance and to calculate fisheries harvest quotas. These assessments have evolved towards complex models involving hundreds of parameters. Their implementation is time-consuming and limited to highly trained technical staff. Additionally, this complexity makes these models completely opaque to decision makers and stakeholders. A recent study of a simplistic simulated salmon fishery showed that assessments based on simpler models could outperform those using more complex models, even if the more complex models were correct and even if their use allowed the incorporation of additional relevant information. This research extends this analysis by simulating the Eastern Bering Sea pollock stock and its fishery. The results of this analysis will demonstrate whether simpler models can provide reliable estimates. The pollock fishery is the largest U.S. fishery, with harvests averaging over a million tons per year, and the stock is also a major component of the Bering Sea ecosystem. The findings of this research will improve the economic and conservation performance of management of this fishery. The results are likely to inform stock assessment procedures in a wide range of fisheries in the U.S. and elsewhere.