Contributors: Laboratoire d'Ecologie Alpine (LECA ); Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA); University of Vermont Burlington; Department of Plant Biology; Station biologique de Roscoff = Roscoff Marine Station (SBR); Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS); Centre de Biologie pour la Gestion des Populations (UMR CBGP); Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD France-Sud )-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier; Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM); Faculty of Mathematics, Natural Sciences and Information Technologies (FAMNIT); University of Primorska; Faculty of Agriculture Zagreb (UNIZG); University of Zagreb; Parco Nazionale dello Stelvio; Partenaires INRAE; ERSAF LOMBARDIA ITA; Partenaires IRSTEA; Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA); University of Freiburg Freiburg; Fondazione Edmund Mach - Edmund Mach Foundation Italie (FEM); Landscape Ecology Group ETH Zürich; Institute of Terrestrial Ecosystems (ITES); Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology Zürich (ETH Zürich)-Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology Zürich (ETH Zürich); Swiss Federal Institute for Forest, Snow and Landscape Research WSL; The research benefited from the support of AnaBM (USMB) and AEEM (UGA) laboratory facilities and we are grateful to the Roscoff Bioinformatics platform ABiMS (http://abims.sb-roscoff.fr). LP was supported by the Swiss National Science Foundation grant (N° 310030_188550), and GY received funding from the IDEX UGA (Université Grenoble Alpes, ANR-15-IDEX-0002).; ANR-15-IDEX-0002,UGA,IDEX UGA(2015)
نبذة مختصرة : Data availability: Raw reads are available under the NCBI bioproject “PRJNA813419” (Accession number for BioSamples: SAMN26501511 - SAMN26502071 and SRA: SRR18252263-SRR18252823). ; International audience ; Climate projections predict major changes in alpine environments by the end of the 21st century. To avoid climate-induced maladaptation and extinction, many animal populations will either need to move to more suitable habitats or adapt in situ to novel conditions. Since populations of a species exhibit genetic variation related to local adaptation, it is important to incorporate this variation into predictive models to help assess the ability of the species to survive climate change. Here, we evaluate how the adaptive genetic variation of a mountain ungulate-the Northern chamois (Rupicapra rupicapra)-could be impacted by future global warming. Based on genotype-environment association analyses of 429 chamois using a ddRAD sequencing approach, we identified genetic variation associated with climatic gradients across the European Alps. We then delineated adaptive genetic units and projected the optimal distribution of these adaptive groups in the future. Our results suggest the presence of local adaptation to climate in Northern chamois with similar genetic adaptive responses in geographically distant but climatically similar populations. Furthermore, our results predict that future climatic changes will modify the Northern chamois adaptive landscape considerably, with various degrees of maladaptation risk.
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