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Hierarchical Bayesian modelling of Atlantic salmon egg to smolt time series from monitored rivers of eastern Canada to define and transport reference points / G. Chaput ... [et al.].: Fs70-5/2015-075E-PDF

This paper presents analyses of the available time series of Atlantic salmon (Salmo salar) spawner to smolt data from fourteen monitored rivers in eastern Canada. A freshwater life history model is presented using a hierarchical Bayesian modelling framework to estimate and transfer reference points for Atlantic salmon. The results show that the stock and recruitment dynamic of Atlantic salmon within the freshwater portion of the life cycle is highly variable within and among rivers with consequence that the stock and recruitment parameters are uncertain. These uncertainties propagate into the estimation of reference points for management.

Permanent link to this Catalogue record:
publications.gc.ca/pub?id=9.809302&sl=0

Publication information
Department/Agency
  • Canada. Department of Fisheries and Oceans.
  • Canadian Science Advisory Secretariat.
TitleHierarchical Bayesian modelling of Atlantic salmon egg to smolt time series from monitored rivers of eastern Canada to define and transport reference points / G. Chaput ... [et al.].
Variant title
  • Modélisation bayésienne hiérarchique de séries chronologiques du stade d’œuf au stade de saumoneau du saumon de l’Atlantique dans les rivières surveillées de l’est du Canada, pour définir et transposer des points de référence
Series title
  • Canadian Science Advisory Secretariat research document, 1919-5044 ; 2015/075, Gulf, Maritimes, Newfoundland and Labrador Regions
Publication typeMonograph - View Master Record
Language[English]
FormatDigital text
Electronic document
Note(s)
  • "December 2015."
  • Includes bibliographic references (p. 16-17).
Publishing information
  • Ottawa : Fisheries and Oceans Canada, 2015.
Author / Contributor
  • Chaput, Gerald J.
Descriptionv, 84 p. : fig., graphs, maps, tables.
Catalogue number
  • Fs70-5/2015-075E-PDF
Subject terms
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