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Landscape genetics of a sub-alpine toad: climate change predicted to induce upward range shifts via asymmetrical migration corridors.
Maier, Paul A; Vandergast, Amy G; Ostoja, Steven M; Aguilar, Andres; Bohonak, Andrew J.
Afiliação
  • Maier PA; Department of Biology, San Diego State University, 5500 Campanile Dr., San Diego, CA, 92182, USA. paulm@genebygene.com.
  • Vandergast AG; FamilyTreeDNA, Gene by Gene, 1445 N Loop W, Houston, TX, 77008, USA. paulm@genebygene.com.
  • Ostoja SM; U.S. Geological Survey, Western Ecological Research Center, San Diego Field Station, San Diego, CA, 92101, USA.
  • Aguilar A; USDA California Climate Hub, Agricultural Research Service, John Muir Institute of the Environment, University of California, Davis, 1 Shields Ave., Davis, CA, 95616, USA.
  • Bohonak AJ; Department of Biological Sciences, California State University, Los Angeles, 5151 State University Dr., Los Angeles, CA, 90032, USA.
Heredity (Edinb) ; 129(5): 257-272, 2022 11.
Article em En | MEDLINE | ID: mdl-36076071
ABSTRACT
Climate change is expected to have a major hydrological impact on the core breeding habitat and migration corridors of many amphibians in the twenty-first century. The Yosemite toad (Anaxyrus canorus) is a species of meadow-specializing amphibian endemic to the high-elevation Sierra Nevada Mountains of California. Despite living entirely on federal lands, it has recently faced severe extirpations, yet our understanding of climatic influences on population connectivity is limited. In this study, we used a previously published double-digest RADseq dataset along with numerous remotely sensed habitat features in a landscape genetics framework to answer two primary questions in Yosemite National Park (1) Which fine-scale climate, topographic, soil, and vegetation features most facilitate meadow connectivity? (2) How is climate change predicted to influence both the magnitude and net asymmetry of genetic migration? We developed an approach for simultaneously modeling multiple toad migration paths, akin to circuit theory, except raw environmental features can be separately considered. Our workflow identified the most likely migration corridors between meadows and used the unique cubist machine learning approach to fit and forecast environmental models of connectivity. We identified the permuted modeling importance of numerous snowpack-related features, such as runoff and groundwater recharge. Our results highlight the importance of considering phylogeographic structure, and asymmetrical migration in landscape genetics. We predict an upward elevational shift for this already high-elevation species, as measured by the net vector of anticipated genetic movement, and a north-eastward shift in species distribution via the network of genetic migration corridors across the park.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Mudança Climática / Bufonidae Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals Idioma: En Revista: Heredity (Edinb) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Mudança Climática / Bufonidae Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals Idioma: En Revista: Heredity (Edinb) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos