Bayesian estimation of species relative abundances and habitat preferences using opportunistic data |
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Authors: | Camille?Coron mailto:camille.coron@math.u-psud.fr" title=" camille.coron@math.u-psud.fr" itemprop=" email" data-track=" click" data-track-action=" Email author" data-track-label=" " >Email author http://orcid.org/---" itemprop=" url" title=" View OrcID profile" target=" _blank" rel=" noopener" data-track=" click" data-track-action=" OrcID" data-track-label=" " >View author s OrcID profile,Clément?Calenge,Christophe?Giraud,Romain?Julliard |
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Affiliation: | 1.Laboratoire de Mathématiques d’Orsay, Univ. Paris-Sud, CNRS,Université Paris-Saclay,Orsay,France;2.Office National de la Chasse et de la Faune Sauvage,Le Perray en Yvelines,France;3.CESCO, UMR CNRS 7204, Muséum National d’Histoire Naturelle,Paris,France |
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Abstract: | We develop a new statistical procedure to monitor relative species abundances and their respective preferences for different habitat types, using opportunistic data. Following Giraud et al. (Biometrics 72(2):649–658, 2015), we combine the opportunistic data with some standardized data in order to correct the bias inherent to the opportunistic data collection. Species observations are modeled by Poisson distributions whose parameters quantify species abundances and habitat preferences, and are estimated using Bayesian computations. Our main contributions are (i) to tackle the bias induced by habitat selection behaviors, (ii) to handle data where the habitat type associated to each observation is unknown, (iii) to estimate probabilities of selection of habitat for the species. As an illustration, we estimate common bird species habitat preferences and abundances in the region of Aquitaine (France). |
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