Stock assessment models overstate sustainability of the world’s fisheries

Effective fisheries management requires accurate estimates of stock biomass and trends; yet, assumptions in stock assessment models generate high levels of uncertainty and error. For 230 fisheries worldwide, we contrasted stock biomass estimates at the time of assessment with updated hindcast estimates modeled for the same year in later assessments to evaluate systematic over- or underestimation. For stocks that were overfished, low value, or located in regions with rising temperatures, historical biomass estimates were generally overstated compared with updated assessments. Moreover, rising trends reported for overfished stocks were often inaccurate. With consideration of bias identified retrospectively, 85% more stocks than currently recognized have likely collapsed below 10% of maximum historical biomass. The high uncertainty and bias in modeled stock estimates warrants much greater precaution by managers.

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Publication Details

Journal
Science
Published
2024-08-22
DOI
https://doi.org/10.1126/science.adl6282
Citations
56
Primary Topic
Marine and fisheries research
Type
article
Field-Weighted Citation Impact
15.83
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article

Stock assessment models overstate sustainability of the world’s fisheries

Christopher J. Brown, Rick D. Stuart‐Smith, Graham J. Edgar, Nils C. Krueck et al.
56 citations
Science
Marine and fisheries research
15.83
article

Stock assessment models overstate sustainability of the world’s fisheries

Christopher J. Brown, Rick D. Stuart‐Smith, Graham J. Edgar, Nils C. Krueck, Susan C. Baker, Amanda E. Bates
article en
56 citations

Abstract

Effective fisheries management requires accurate estimates of stock biomass and trends; yet, assumptions in stock assessment models generate high levels of uncertainty and error. For 230 fisheries worldwide, we contrasted stock biomass estimates at the time of assessment with updated hindcast estimates modeled for the same year in later assessments to evaluate systematic over- or underestimation. For stocks that were overfished, low value, or located in regions with rising temperatures, historical biomass estimates were generally overstated compared with updated assessments. Moreover, rising trends reported for overfished stocks were often inaccurate. With consideration of bias identified retrospectively, 85% more stocks than currently recognized have likely collapsed below 10% of maximum historical biomass. The high uncertainty and bias in modeled stock estimates warrants much greater precaution by managers.

ScienceVol. 385(6711)
University of Tasmania (AU), University of Victoria (CA), Centre for Marine Socioecology (AU)
Openalex Percentile: Top 0%
Marine and fisheries research
15.83
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