Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/25785
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dc.contributor.authorRazgour, Orlyen_UK
dc.contributor.authorTaggart, Johnen_UK
dc.contributor.authorManel, Stephanieen_UK
dc.contributor.authorJuste, Javieren_UK
dc.contributor.authorIbanez, Carlosen_UK
dc.contributor.authorRebelo, Hugoen_UK
dc.contributor.authorAlberdi, Anttonen_UK
dc.contributor.authorJones, Garethen_UK
dc.contributor.authorPark, Kirstyen_UK
dc.date.accessioned2018-02-18T05:12:44Z-
dc.date.available2018-02-18T05:12:44Z-
dc.date.issued2018-01en_UK
dc.identifier.urihttp://hdl.handle.net/1893/25785-
dc.description.abstractClimate change is a major threat to global biodiversity that will produce a range of new selection pressures. Understanding species responses to climate change requires an interdisciplinary perspective, combining ecological, molecular and environmental approaches. We propose an applied integrated framework to identify populations under threat from climate change based on their extent of exposure, inherent sensitivity due to adaptive and neutral genetic variation and range shift potential. We consider intraspecific vulnerability and population-level responses, an important but often neglected conservation research priority. We demonstrate how this framework can be applied to vertebrates with limited dispersal abilities using empirical data for the bat Plecotus austriacus. We use ecological niche modelling and environmental dissimilarity analysis to locate areas at high risk of exposure to future changes. Combining outlier tests with genotype–environment association analysis, we identify potential climate-adaptive SNPs in our genomic data set and differences in the frequency of adaptive and neutral variation between populations. We assess landscape connectivity and show that changing environmental suitability may limit the future movement of individuals, thus affecting both the ability of populations to shift their distribution to climatically suitable areas and the probability of evolutionary rescue through the spread of adaptive genetic variation among populations. Therefore, a better understanding of movement ecology and landscape connectivity is needed for predicting population persistence under climate change. Our study highlights the importance of incorporating genomic data to determine sensitivity, adaptive potential and range shift potential, instead of relying solely on exposure to guide species vulnerability assessments and conservation planning.en_UK
dc.language.isoenen_UK
dc.publisherWiley-Blackwellen_UK
dc.relationRazgour O, Taggart J, Manel S, Juste J, Ibanez C, Rebelo H, Alberdi A, Jones G & Park K (2018) An integrated framework to identify wildlife populations under threat from climate change. Molecular Ecology Resources, 18 (1), pp. 18-31. https://doi.org/10.1111/1755-0998.12694en_UK
dc.rights© 2017 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.en_UK
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_UK
dc.subjectbatsen_UK
dc.subjectconservation genomicsen_UK
dc.subjectgenotype–environment associationsen_UK
dc.subjectglobal changeen_UK
dc.subjectlandscape geneticsen_UK
dc.subjectrange shiftsen_UK
dc.titleAn integrated framework to identify wildlife populations under threat from climate changeen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.1111/1755-0998.12694en_UK
dc.identifier.pmid28649779en_UK
dc.citation.jtitleMolecular Ecology Resourcesen_UK
dc.citation.issn1755-0998en_UK
dc.citation.issn1755-098Xen_UK
dc.citation.volume18en_UK
dc.citation.issue1en_UK
dc.citation.spage18en_UK
dc.citation.epage31en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.citation.date25/07/2017en_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.contributor.affiliationInstitute of Aquacultureen_UK
dc.contributor.affiliationParis Sciences and Letters Research Universityen_UK
dc.contributor.affiliationEstación Biológica de Doñanaen_UK
dc.contributor.affiliationEstación Biológica de Doñanaen_UK
dc.contributor.affiliationUniversity of Bristolen_UK
dc.contributor.affiliationUniversity of the Basque Countryen_UK
dc.contributor.affiliationUniversity of Bristolen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.identifier.isiWOS:000424112000003en_UK
dc.identifier.scopusid2-s2.0-85026328363en_UK
dc.identifier.wtid521526en_UK
dc.contributor.orcid0000-0002-3843-9663en_UK
dc.contributor.orcid0000-0001-6080-7197en_UK
dc.date.accepted2017-06-16en_UK
dc.date.filedepositdate2017-08-17en_UK
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