Leveraging scientific uncertainty in fisheries management for estimating among-assessment variation in overfishing limits
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Leveraging scientific uncertainty in fisheries management for estimating among-assessment variation in overfishing limits

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  • Journal Title:
    ICES Journal of Marine Science
  • Personal Author:
  • NOAA Program & Office:
    OAR (Oceanic and Atmospheric Research)
  • Description:
    Fisheries management systems can utilize probability-based harvest control rules to incorporate scientific uncertainty and manager risk tolerance when setting catch limits. A precautionary buffer that scales with scientific uncertainty is used to calculate the acceptable biological catch from the overfishing limit (OFL) for US West Coast groundfish and coastal pelagic species. A previous analysis formed the basis for estimating scientific uncertainty as the among-assessment variation in estimates of historical spawning biomass time-series. This “historical biomass” approach may underestimate scientific uncertainty, because the OFL is a function of estimated exploitable biomass and fishing mortality. We developed a new approach that bases the calculation of scientific uncertainty on projected spawning biomass (SSB) and OFLs, accounting for uncertainty in recruitment and among-assessment variation. OFL projections yielded a higher estimate of uncertainty than SSB (0.502 vs. 0.413 for 25-year projections and 0.562 vs. 0.384 for a 1-year projection, assuming a deterministic stock-recruitment relationship). Assuming a stochastic stock-recruitment relationship produced smaller estimates of uncertainty (0.436, 25-year OFL projections; 0.452, 1-year OFL projections; 0.360, 25-year SSB projections; 0.318, 1-year SSB projections). The projection-based approach presented herein is applicable across stocks and regions that conduct assessments with sufficient and consistent outputs for calculating an OFL.
  • Keywords:
  • Source:
    ICES Journal of Marine Science, 77(2), 515-526
  • DOI:
  • ISSN:
    1054-3139;1095-9289;
  • Format:
    PDF
  • Publisher:
    Oxford University Press (OUP)
  • Document Type:
    Journal Article
  • Funding:
    Grant no. NA10OAR4320148
  • Rights Information:
    Other
  • Compliance:
    Library
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