Refining Fisheries Advice With Stock-Specific Ecosystem Information

Jacob W. Bentley, Mathieu G. Lundy, Daniel Howell, Steven E. Beggs, Alida Bundy, Francisco De Castro, Clive J. Fox, Johanna J. Heymans, Christopher P. Lynam, Debbi Pedreschi, Pia Schuchert, Natalia Serpetti, Johnny Woodlock, David G. Reid

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)
44 Downloads (Pure)


Although frequently suggested as a goal for ecosystem-based fisheries management, incorporating ecosystem information into fisheries stock assessments has proven challenging. The uncertainty of input data, coupled with the structural uncertainty of complex multi-species models, currently makes the use of absolute values from such models contentious for short-term single-species fisheries management advice. Here, we propose a different approach where the standard assessment methodologies can be enhanced using ecosystem model derived information. Using a case study of the Irish Sea, we illustrate how stock-specific ecosystem indicators can be used to set an ecosystem-based fishing mortality reference point (FECO) within the “Pretty Good Yield” ranges for fishing mortality which form the present precautionary approach adopted in Europe by the International Council for the Exploration of the Sea (ICES). We propose that this new target, FECO, can be used to scale fishing mortality down when the ecosystem conditions for the stock are poor and up when conditions are good. This approach provides a streamlined quantitative way of incorporating ecosystem information into catch advice and provides an opportunity to operationalize ecosystem models and empirical indicators, while retaining the integrity of current assessment models and the FMSY-based advice process.
Original languageEnglish
Article number602072
Number of pages19
JournalFrontiers in Marine Science
Publication statusPublished - 9 Apr 2021


  • strategic advice
  • ecosystem approach to fisheries management
  • FECO
  • Ecopath with Ecoism
  • indicators


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