Mieux comprendre la dynamique des populations sauvages de saumon atlantique pour optimiser leur gestion. L'apport des modèles hiérarchiques Bayésiens - Archive ouverte HAL Access content directly
Other Publications Year : 2014

Mieux comprendre la dynamique des populations sauvages de saumon atlantique pour optimiser leur gestion. L'apport des modèles hiérarchiques Bayésiens

Abstract

This deliverable is the French version of the NGO stakeholder paper for the Atlantic salmon case study. The paper is planned to be published in the French journal Sciences Eaux et Territoires (www.set-revue.fr). The modelling approach developed during the Ecoknows project in collaboration with the ICES Working Group on North Atlantic Salmon is reviewed. Models are being developed that provide improvement to the stock assessment models currently used by the ICES WGNAS and paves the way toward harmonizing the stock assessment models used in the Baltic (WGBAST) and in the North Atlantic (WGNAS). A life cycle model has been successfully developed in the Hierarchical Bayesian framework that brings a substantial contribution to A. salmon stock assessment on a broad ocean scale. The model captures the joint dynamics of all the populations considered by ICES for stock assessment in the five regions of the South Eastern-North Atlantic Ocean: France, England and Wales, Ireland and Northern Ireland, Scotland and Iceland. Results show that marine survival, has fluctuated markedly through time with a clear shift in 1990. Maturing probability after decades of increase is now slightly decreasing, indicating some fundamental changes in stocks biology or in their environment.Temporal fluctuations in key population dynamic parameters and abundances are quite synchronous across stocks and reinforce the hypothesis of a response to large scale environmental forcing during the marine phase of the life cycle.
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Dates and versions

hal-01210267 , version 1 (05-06-2020)

Identifiers

  • HAL Id : hal-01210267 , version 1
  • PRODINRA : 295115

Cite

Etienne Rivot, Félix Massiot-Granier, Etienne Prévost, J. White, G. Chaput, et al.. Mieux comprendre la dynamique des populations sauvages de saumon atlantique pour optimiser leur gestion. L'apport des modèles hiérarchiques Bayésiens : Ecoknows deliverable 7.1. NGO Stakeholder paper; Case study Atlantic salmon. 2014, 20 p. ⟨hal-01210267⟩
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