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Beyond species distribution modeling: a landscape genetics approach to investigating range shifts under future climate change

Beyond species distribution modeling: a landscape genetics approach to investigating range shifts under future climate change
Beyond species distribution modeling: a landscape genetics approach to investigating range shifts under future climate change
Understanding 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.
1574-9541
250-256
Razgour, Orly
107f4912-304a-44d5-99f8-cdf2a9ce6f14
Razgour, Orly
107f4912-304a-44d5-99f8-cdf2a9ce6f14

Razgour, Orly (2015) Beyond species distribution modeling: a landscape genetics approach to investigating range shifts under future climate change. Ecological Informatics, 30, 250-256. (doi:10.1016/j.ecoinf.2015.05.007).

Record type: Article

Abstract

Understanding 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.

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Accepted/In Press date: 18 May 2015
e-pub ahead of print date: 5 June 2015
Published date: November 2015
Organisations: Environmental

Identifiers

Local EPrints ID: 394296
URI: http://eprints.soton.ac.uk/id/eprint/394296
ISSN: 1574-9541
PURE UUID: 78513ba6-420f-4649-8700-6b8bf28e4077
ORCID for Orly Razgour: ORCID iD orcid.org/0000-0003-3186-0313

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Date deposited: 13 May 2016 10:58
Last modified: 15 Mar 2024 00:20

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Author: Orly Razgour ORCID iD

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