Blood from a stone: Performance of catch-only methods in estimating stock biomass status

Christopher M. Free, Olaf P. Jensen, Sean C. Anderson, Nicolas L. Gutierrez, Kristin M. Kleisner, Catherine Longo, Cóilín Minto, Giacomo Chato Osio, Jessica C. Walsh

Research output: Contribution to journalArticle

Abstract

Demand for data-limited stock assessment methods is increasing, and new methods are being developed rapidly. One class of these methods requires only catch time series and, in some cases, information about life history or fishery characteristics, to estimate stock status. These catch-only methods (COMs) range from statistical models trained on data-rich stocks to mechanistic population models that make assumptions about changes in fishing effort. We review 11 COMs, comparing performance through application to data-rich stocks and simulated fisheries. The catch-only methods evaluated here produce imprecise and biased estimates of B/BMSY, especially for stocks that are lightly exploited. They were also generally poor classifiers of stock status. While no method performed best across all stocks, ensembles of multiple COMs generally performed better than individual COMs. We advocate for testing new COMs using this common platform. We also caution that performance in estimating stock status is not sufficient for gauging the usefulness of COMs in managing fisheries. Greater use of management strategy evaluation is needed before COMs can be considered a reliable tool for management.

Original languageEnglish (US)
Article number105452
JournalFisheries Research
Volume223
DOIs
Publication statusPublished - Mar 2020

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All Science Journal Classification (ASJC) codes

  • Aquatic Science

Keywords

  • Catch-only methods
  • Data-limited fisheries
  • Data-poor fisheries
  • Ensemble methods
  • Stock assessment
  • Stock status

Cite this

Free, C. M., Jensen, O. P., Anderson, S. C., Gutierrez, N. L., Kleisner, K. M., Longo, C., ... Walsh, J. C. (2020). Blood from a stone: Performance of catch-only methods in estimating stock biomass status. Fisheries Research, 223, [105452]. https://doi.org/10.1016/j.fishres.2019.105452