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Projection of current and future distribution of adaptive genetic units in an alpine ungulate

Heredity volume 132, pages 54–66 (2024)Cite this article

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Abstract

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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Fig. 1: Map of the study area illustrating the location of Northern chamois (Rupicapra rupicapra) sampled individuals.
Fig. 2: Adaptive landscape of the Northern chamois along the European Alps and Dinaric Mts.
Fig. 3: Delineation of adaptive and global genetic units.
Fig. 4: Projection of the four adaptive genetic units.
Fig. 5: Projection of shift in distribution of adaptive genetic units.
Fig. 6: Projection of genetic offset.

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Data availability

Raw reads are available under the NCBI bioproject “PRJNA813419” (Accession number for BioSamples: SAMN26501511 - SAMN26502071 and SRA: SRR18252263-SRR18252823).

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Acknowledgements

We thank Philippe Auliac, Aurélie Barboiron, Bruno Bassano, François Biollaz, Glauco Camenisch, Marie Canut, Jérôme Cavailhès, Mathieu Garel, Veronika Grünschachner-Berger, Marie Heuret, Ludovic Imberdis, Martina Just, Christine Lettl, Laura Martinelli, Radka Poláková, Elias Pesenti, Davide Righetti, Christine Saint-Andrieux, Federico Tettamanti, Roberto Viganò, Barbora Rolečková, Barbora Zemanová, and IVB Genetic Bank (Czech Academy of Sciences) for providing help to collect samples. We acknowledge Maya Guegen, Julien Renaud, and Flurin Leugger for answering our questions on the bioclimatic variable selection. We thank Delphine Rioux, Nadine Curt Grand-Gaudin, Nathalie Tissot and Sophie Tissot for assistance with ddRADseq library preparation in the laboratory. We warmly thank the associate editor as well as three anonymous reviewers for their insightful comments on the manuscript. 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 – Initiatives de Recherche Stratégiques (IRS) – Université Grenoble Alpes.

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Authors and Affiliations

  1. Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LECA, 38000, Grenoble, France

    Amélie Hoste, Thibaut Capblancq, Laure Denoyelle & Glenn Yannic

  2. Department of Plant Biology, University of Vermont, Burlington, VT, 05405, USA

    Thibaut Capblancq

  3. CNRS, Sorbonne Université, UMR 7144, Station Biologique de Roscoff, Place Georges Teissier, 29680, Roscoff, France

    Thomas Broquet

  4. UMR CBGP, INRAE, CIRAD, IRD, Institut Agro, Université Montpellier, Montpellier, France

    Charles Perrier

  5. Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, 6000, Koper, Slovenia

    Elena Buzan

  6. Faculty of Environmental Protection, Trg mladosti 7, 3320, Velenje, Slovenia

    Elena Buzan

  7. Department of Fisheries, Apiculture, Wildlife Management and Special Zoology, Faculty of Agriculture, University of Zagreb, Svetošimunska 25, 10000, Zagreb, Croatia

    Nikica Šprem

  8. Stelvio National Park – ERSAF Lombardia, Via De Simoni 42, 23032, Bormio, Italy

    Luca Corlatti

  9. Chair of Wildlife Ecology and Management, University of Freiburg, Tennenbacher Straße 4, 79106, Freiburg, Germany

    Luca Corlatti

  10. Conservation Genomics Unit, Research and Innovation Centre, Fondazione E. Mach, Via E. Mach 1, 38098 S, Michele all’Adige, TN, Italy

    Barbara Crestanello & Heidi Christine Hauffe

  11. Landscape Ecology, Department of Environmental Systems Science, Institute of Terrestrial Ecosystems, ETH Zrich, Zurich, Switzerland

    Loïc Pellissier

  12. Swiss Federal Institute for Forest, Snow and Landscape Research, Birmensdorf, Switzerland

    Loïc Pellissier

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  1. Amélie Hoste
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Contributions

GY and LP coordinated the project. GY and TC designed the study and supervised AH. EB, LC, BC, HCH, and NS contributed to the sample collection. TB and GY performed the bioinformatic analysis. AH analyzed the data with TC and GY. AH, TC, and GY interpreted the results with contribution from TB, CP, and LD. AH, TC and GY wrote the manuscript with comments and editing of all authors. The final version of the manuscript has been read and approved by all authors.

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Correspondence to Glenn Yannic.

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Hoste, A., Capblancq, T., Broquet, T. et al. Projection of current and future distribution of adaptive genetic units in an alpine ungulate. Heredity 132, 54–66 (2024). https://doi.org/10.1038/s41437-023-00661-2

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