Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/21974
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dc.contributor.authorRazgour, Orlyen_UK
dc.date.accessioned2016-01-18T23:49:04Z-
dc.date.available2016-01-18T23:49:04Z-
dc.date.issued2015-11en_UK
dc.identifier.urihttp://hdl.handle.net/1893/21974-
dc.description.abstractUnderstanding how biodiversity will respond to future climate change is a major conservation and societal challenge. Climate change is predicted to force many species to shift their ranges in pursuit of suitable conditions. This study aims to use landscape genetics, the study of the effects of environmental heterogeneity on the spatial distribution of genetic variation, as a predictive tool to assess how species will shift their ranges to track climatic changes and inform conservation measures that will facilitate movement. The approach is based on three steps: 1) using Species Distribution Models (SDMs) to predict suitable ranges under future climate change, 2) using the landscape genetics framework to identify landscape variables that impede or facilitate movement, and 3) extrapolating the effect of landscape connectivity on range shifts in response to future climate change. I show how this approach can be implemented using the publicly available genetic dataset of the grey long-eared bat,Plecotus austriacus, in the Iberian Peninsula. Forest cover gradient was the main landscape variable affecting genetic connectivity between colonies. Forest availability is likely to limit future range shifts in response to climate change, primarily over the central plateau, but important range shift pathways have been identified along the eastern and western coasts. I provide outputs that can be directly used by conservation managers and review the viability of the approach. Using landscape genetics as a predictive tool in combination with SDMs enables the identification of potential pathways, whose loss can affect the ability of species to shift their range into future climatically suitable areas, and the appropriate conservation management measures to increase landscape connectivity and facilitate movement.en_UK
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.relationRazgour O (2015) Beyond species distribution modelling: A landscape genetics approach to investigating range shifts under future climate change. Ecological Informatics, 30, pp. 250-256. https://doi.org/10.1016/j.ecoinf.2015.05.007en_UK
dc.rightsThis item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. Accepted refereed manuscript of: Razgour O (2015) Beyond species distribution modelling: A landscape genetics approach to investigating range shifts under future climate change, Ecological Informatics, 30, pp. 250-256. DOI: 10.1016/j.ecoinf.2015.05.007 © 2015, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/en_UK
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_UK
dc.subjectChiropteraen_UK
dc.subjectClimate Changeen_UK
dc.subjectEcological Niche Modellingen_UK
dc.subjectGenetic Connectivityen_UK
dc.subjectLandscape Connectivityen_UK
dc.subjectPlecotus austriacusen_UK
dc.titleBeyond species distribution modelling: A landscape genetics approach to investigating range shifts under future climate changeen_UK
dc.typeJournal Articleen_UK
dc.rights.embargodate2016-11-06en_UK
dc.rights.embargoreason[Razgour_Accepted_Ecological Informatics_Beyond SDM.pdf] Publisher requires embargo of 12 months after formal publication.en_UK
dc.identifier.doi10.1016/j.ecoinf.2015.05.007en_UK
dc.citation.jtitleEcological Informaticsen_UK
dc.citation.issn1574-9541en_UK
dc.citation.volume30en_UK
dc.citation.spage250en_UK
dc.citation.epage256en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.author.emailOrly.Razgour@gmail.comen_UK
dc.citation.date05/06/2015en_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.identifier.isiWOS:000366876400031en_UK
dc.identifier.scopusid2-s2.0-84930806290en_UK
dc.identifier.wtid597088en_UK
dc.date.accepted2015-05-18en_UK
dcterms.dateAccepted2015-05-18en_UK
dc.date.filedepositdate2015-07-10en_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionAMen_UK
local.rioxx.authorRazgour, Orly|en_UK
local.rioxx.projectInternal Project|University of Stirling|https://isni.org/isni/0000000122484331en_UK
local.rioxx.freetoreaddate2016-11-06en_UK
local.rioxx.licencehttp://www.rioxx.net/licenses/under-embargo-all-rights-reserved||2016-11-05en_UK
local.rioxx.licencehttp://creativecommons.org/licenses/by-nc-nd/4.0/|2016-11-06|en_UK
local.rioxx.filenameRazgour_Accepted_Ecological Informatics_Beyond SDM.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source1574-9541en_UK
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