Application of pre-fishery abundance modelling and Bayesian hierarchical stock and recruitment analysis to the provision of precautionary catch advice for Irish salmon (Salmo salar L.) fisheries

  • N. Ó Maoiléidigh
  • , P. McGinnity
  • , E. Prévost
  • , E. C.E. Potter
  • , P. Gargan
  • , W. W. Crozier
  • , P. Mills
  • , W. Roche

Research output: Contribution to journalArticlepeer-review

Abstract

Ireland has one of the last remaining commercial salmon driftnet fisheries in the North Atlantic, with recent catches averaging 162 000 salmon (1997-2003), approximately 20% of the total landings of salmon in the entire North Atlantic. Since 2001, the Irish commercial salmon fishery has been managed on the basis of Total Allowable Catch (TAC) in each of 17 salmon fishing districts. This has been made possible by applying a number of new and innovative techniques to the estimation of conservation limits (CLs) and pre-fishery abundance (PFA) for combined stocks in each district. Stock and recruitment parameters from well-monitored European rivers were "transported" to all Irish rivers using a Bayesian hierarchical stock and recruitment (BHSRA) model. This provided the posterior probability distributions of the model parameters and related reference points, including individual river CLs. District PFA and the number of spawners were estimated for a baseline period of 1997-2003, using district catch data, estimates of unreported catch, and exploitation rate. Harvest guidelines were established on the basis of surplus of spawning fish over the CL for the baseline period. In line with scientific advice, the commercial fishery has been reduced from 212 000 fish in 2002 to 182 000 in 2003. In 2004, a total catch (including the rod catch) of approximately 160 000 wild salmon was advised.

Original languageEnglish
Pages (from-to)1370-1378
Number of pages9
JournalICES Journal of Marine Science
Volume61
Issue number8
DOIs
Publication statusPublished - Dec 2004
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 14 - Life Below Water
    SDG 14 Life Below Water

Keywords

  • Bayesian
  • conservation limit
  • salmon
  • stock and recruitment

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