A new role for effort dynamics in the theory of harvested populations and data-poor stock assessment

James T. Thorson, Cóilín Minto, Carolina V. Minte-Vera, Kristin M. Kleisner, Catherine Longo

Research output: Contribution to journalArticlepeer-review

53 Citations (Scopus)

Abstract

Research shows that population status can be predicted using catch data, but there is little justification for why these predictions work or how they account for changes in fisheries management. We demonstrate that biomass can be reconstructed from catch data whenever fishing mortality follows predictable dynamics over time (called "effort dynamics"), and we develop a state-space catch only model (SSCOM) for this purpose. We use theoretical arguments and simulation modeling to demonstrate that SSCOM can, in some cases, estimate population status from catch data. Next, we use meta-analysis to estimate effort dynamics for US West Coast groundfishes before and after fisheries management changes in the mid-1990s. We apply the SSCOM using meta-analytic results to data for eight assessed species and compare results with stock assessment and data-poor methods. Results indicate general agreement among all three methods. We conclude that effort dynamics provides a theoretical basis for using catch data to reconstruct biomass and has potential for conducting data-poor assessments. However, we still recommend that index and compositional data be collected to allow application of data-rich methods.

Original languageEnglish
Pages (from-to)1829-1844
Number of pages16
JournalCanadian Journal of Fisheries and Aquatic Sciences
Volume70
Issue number12
DOIs
Publication statusPublished - Dec 2013

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