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Using Connectivity To Identify Climatic Drivers Of Local Adaptationuse asterix (*) to get italics
Stewart L. Macdonald, John Llewelyn, Ben PhillipsPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"
2017
Despite being able to conclusively demonstrate local adaptation, we are still often unable to objectively determine the climatic drivers of local adaptation. Given the rapid rate of global change, understanding the climatic drivers of local adaptation is vital. Not only will this tell us which climate axes matter most to population fitness, but such knowledge is critical to inform management strategies such as translocation and targeted gene flow. While simple assessments of geographic trait variation are useful, geographic variation (and its associations with environment) may represent plastic, rather than evolved, differences. Additionally, the vast number of trait–environment combinations makes it difficult to determine which aspects of the environment populations adapt to. Here we argue that by incorporating a measure of landscape connectivity as a proxy for gene flow, we can differentiate between trait–environment relationships underpinned by genetic differences versus those that reflect phenotypic plasticity. By doing so, we can rapidly shorten the list of trait– environment combinations that may be of adaptive significance. We demonstrate how this reasoning can be applied using data on geographic trait variation in a lizard species from Australia’s Wet Tropics rainforest. Our analysis reveals an overwhelming signal of local adaptation for the traits and environmental variables we investigated. Our analysis also allows us to rank environmental variables by the degree to which they appear to be driving local adaptation. Although encouraging, methodological issues remain: we point to these issue in the hope that the community can rapidly hone the methods we sketch here. The promise is a rapid and general approach to identifying the environmental drivers of local adaptation.
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local adaptation, climate, connectivity, gene flow
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Adaptation, Evolutionary Applications
e.g. John Doe john@doe.com
No need for them to be recommenders of PCIEvolBiol. Please do not suggest reviewers for whom there might be a conflict of interest. Reviewers are not allowed to review preprints written by close colleagues (with whom they have published in the last four years, with whom they have received joint funding in the last four years, or with whom they are currently writing a manuscript, or submitting a grant proposal), or by family members, friends, or anyone for whom bias might affect the nature of the review - see the code of conduct
e.g. John Doe john@doe.com
2017-06-06 13:06:54
Ruth Arabelle Hufbauer
Thomas Lenormand