Quantifying exchanges of Allis shads between river catchments by combining otolith microchemistry and abundance indices in a Bayesian model - Archive ouverte HAL
Article Dans Une Revue ICES Journal of Marine Science Année : 2018

Quantifying exchanges of Allis shads between river catchments by combining otolith microchemistry and abundance indices in a Bayesian model

M. Randon
  • Fonction : Auteur
Françoise Daverat
Philippe Jatteau
J. Martin
  • Fonction : Auteur
Hilaire Drouineau

Résumé

Similar to many diadromous fish species, dramatic declines were observed for Allis shad, an anadromous Clupeidae, since the beginning of the 2000s. The knowledge of population and metapopulation dynamics is a key issue for the management of migratory species. Although homing behaviour is dominant in Allis shad, staying causes exchanges between populations of each river catchment. Currently, the management of Allis shad is applied at the population scale, without accounting for a potential metapopulation structure. Herein we propose a method to estimate the exchanges flux between rivers and a method to identify source and sink rivers. We used otolith microchemistry within a Bayesian model of reallocation coupled with abundance estimates of spawners per watershed. Results showed a metapopulation dynamic with several rivers acting as sources and other as sinks. However, the lack of precision and homogeneity in abundance data resulted in large credibility intervals, which calls for a better standardization in the acquisition of abundance data. Nevertheless, this method should provide an overview of the metapopulation dynamics of other anadromous species with management concerns. © International Council for the Exploration of the Sea 2017. All rights reserved.

Dates et versions

hal-01710428 , version 1 (15-02-2018)

Identifiants

Citer

M. Randon, Françoise Daverat, Gilles Bareille, Philippe Jatteau, J. Martin, et al.. Quantifying exchanges of Allis shads between river catchments by combining otolith microchemistry and abundance indices in a Bayesian model. ICES Journal of Marine Science, 2018, 75 (1), pp.9-21. ⟨10.1093/icesjms/fsx148⟩. ⟨hal-01710428⟩
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