Management strategy evaluation operating model conditioning: a swordfish case study

Daniela Rosa*, Iago Mosqueira, Dan Fu, Rui Coelho

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Evaluation of fish stock status is a key step for fisheries management. Tuna Regional Fisheries Management Organizations (t-RFMOs) are moving towards management strategy evaluation (MSE), a process that combines science and policy and depends on technical aspects, developed by scientists, designed to meet management objectives established by managers and other stakeholders. In the Indian Ocean, the current management advice for swordfish (Xiphias gladius) is based on an ensemble of 24 models considering four areas of uncertainty about the stock dynamics. There is an ongoing MSE process for swordfish, and this paper describes the methodology being applied for the conditioning of the operating model (OM), including model selection and validation. In the MSE, nine sources of uncertainty were considered, each being characterized by 2–3 levels. A partial factorial design was employed to reduce the number of models from a full factorial design to those needed to encompass the overall uncertainty. A selection and validation process was carried out, filtering models that converged, showed good predictive skills, and provided plausible estimates. Overall, the estimated spawning stock biomass (SSB) relative to SSB at maximum sustainable yield (MSY), and fishing mortality (F) relative to FMSY encompasses the estimates of the stock assessment ensemble at the most optimist area of the distribution. The MSE for swordfish is an ongoing process that is expected to provide more robust management advice in the future. Further developments to the OM can still occur, but the methods presented herein can be applied to this, or other species, MSE processes.

Original languageEnglish
Pages (from-to)1189-1207
JournalReviews in Fish Biology and Fisheries
Volume34
Issue number3
Early online date23 Jun 2024
DOIs
Publication statusPublished - 2024

Keywords

  • Diagnostics
  • Filtering
  • Indian Ocean
  • Model validation
  • t-RFMO
  • Xiphias gladius

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