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Taking full advantage of the diverse assemblage of data at hand to produce time series of abundance. A case study on Atlantic salmon populations of Brittany
Abstract : Estimation of abundance with wide spatio-temporal coverage is essential to the assessment and management of wild populations. But, in many cases, data available to estimate abundance time series have diverse forms, variable quality over space and time and they stem from multiple data collection procedures. We developed a Hierarchical Bayesian Modelling (HBM) approach that take full advantage of the diverse assemblage of data at hand to estimate homogeneous time series of abundances irrespective of the data collection procedure. We apply our approach to the estimation of adult abundances of 18 Atlantic salmon populations of Brittany (France) from 1987 to 2017 using catch statistics, environmental covariates and fishing effort. Additional data of total or partial abundance collected in 4 closely monitored populations are also integrated into the analysis. The HBM framework allows the transfer of information from the closely monitored populations to the others. Our results reveal no clear trend in the abundance of adult returns in Brittany over the period studied.
https://hal-agrocampus-ouest.archives-ouvertes.fr/hal-03401246
Contributor : Catherine Cliquet Connect in order to contact the contributor
Submitted on : Monday, October 25, 2021 - 12:21:49 PM
Last modification on : Friday, May 20, 2022 - 9:04:52 AM
Contributor : Catherine Cliquet Connect in order to contact the contributor
Submitted on : Monday, October 25, 2021 - 12:21:49 PM
Last modification on : Friday, May 20, 2022 - 9:04:52 AM
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