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Stacked distribution models predict climate-driven loss of variation in leaf phenology at continental scales

Climate change is having profound effects on species distributions and is likely altering the distribution of genetic variation across landscapes. Maintaining population genetic diversity is essential for the survival of species facing rapid environmental change, and variation loss will further ecol...

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Detalles Bibliográficos
Autores principales: Bayliss, Shannon L. J., Mueller, Liam O., Ware, Ian M., Schweitzer, Jennifer A., Bailey, Joseph K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9649771/
https://www.ncbi.nlm.nih.gov/pubmed/36357488
http://dx.doi.org/10.1038/s42003-022-04131-z
Descripción
Sumario:Climate change is having profound effects on species distributions and is likely altering the distribution of genetic variation across landscapes. Maintaining population genetic diversity is essential for the survival of species facing rapid environmental change, and variation loss will further ecological and evolutionary change. We used trait values of spring foliar leaf-out phenology of 400 genotypes from three geographically isolated populations of Populus angustifolia grown under common conditions, in concert with stacked species distribution modeling, to ask: (a) How will climate change alter phenological variation across the P. angustifolia species-range, and within populations; and (b) will the distribution of phenological variation among and within populations converge (become more similar) in future climatic conditions? Models predicted a net loss of phenological variation in future climate scenarios on 20-25% of the landscape across the species’ range, with the trailing edge population losing variation on as much as 47% of the landscape. Our models also predicted that population’s phenological trait distributions will become more similar over time. This stacked distribution model approach allows for the identification of areas expected to experience the greatest loss of genetically based functional trait variation and areas that may be priorities to conserve as future genetic climate refugia.