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Considering adaptive genetic variation in climate change vulnerability assessment reduces species range loss projections
Local adaptations can determine the potential of populations to respond to environmental changes, yet adaptive genetic variation is commonly ignored in models forecasting species vulnerability and biogeographical shifts under future climate change. Here we integrate genomic and ecological modeling a...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6535011/ https://www.ncbi.nlm.nih.gov/pubmed/31061126 http://dx.doi.org/10.1073/pnas.1820663116 |
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author | Razgour, Orly Forester, Brenna Taggart, John B. Bekaert, Michaël Juste, Javier Ibáñez, Carlos Puechmaille, Sébastien J. Novella-Fernandez, Roberto Alberdi, Antton Manel, Stéphanie |
author_facet | Razgour, Orly Forester, Brenna Taggart, John B. Bekaert, Michaël Juste, Javier Ibáñez, Carlos Puechmaille, Sébastien J. Novella-Fernandez, Roberto Alberdi, Antton Manel, Stéphanie |
author_sort | Razgour, Orly |
collection | PubMed |
description | Local adaptations can determine the potential of populations to respond to environmental changes, yet adaptive genetic variation is commonly ignored in models forecasting species vulnerability and biogeographical shifts under future climate change. Here we integrate genomic and ecological modeling approaches to identify genetic adaptations associated with climate in two cryptic forest bats. We then incorporate this information directly into forecasts of range changes under future climate change and assessment of population persistence through the spread of climate-adaptive genetic variation (evolutionary rescue potential). Considering climate-adaptive potential reduced range loss projections, suggesting that failure to account for intraspecific variability can result in overestimation of future losses. On the other hand, range overlap between species was projected to increase, indicating that interspecific competition is likely to play an important role in limiting species’ future ranges. We show that although evolutionary rescue is possible, it depends on a population’s adaptive capacity and connectivity. Hence, we stress the importance of incorporating genomic data and landscape connectivity in climate change vulnerability assessments and conservation management. |
format | Online Article Text |
id | pubmed-6535011 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-65350112019-06-03 Considering adaptive genetic variation in climate change vulnerability assessment reduces species range loss projections Razgour, Orly Forester, Brenna Taggart, John B. Bekaert, Michaël Juste, Javier Ibáñez, Carlos Puechmaille, Sébastien J. Novella-Fernandez, Roberto Alberdi, Antton Manel, Stéphanie Proc Natl Acad Sci U S A Biological Sciences Local adaptations can determine the potential of populations to respond to environmental changes, yet adaptive genetic variation is commonly ignored in models forecasting species vulnerability and biogeographical shifts under future climate change. Here we integrate genomic and ecological modeling approaches to identify genetic adaptations associated with climate in two cryptic forest bats. We then incorporate this information directly into forecasts of range changes under future climate change and assessment of population persistence through the spread of climate-adaptive genetic variation (evolutionary rescue potential). Considering climate-adaptive potential reduced range loss projections, suggesting that failure to account for intraspecific variability can result in overestimation of future losses. On the other hand, range overlap between species was projected to increase, indicating that interspecific competition is likely to play an important role in limiting species’ future ranges. We show that although evolutionary rescue is possible, it depends on a population’s adaptive capacity and connectivity. Hence, we stress the importance of incorporating genomic data and landscape connectivity in climate change vulnerability assessments and conservation management. National Academy of Sciences 2019-05-21 2019-05-06 /pmc/articles/PMC6535011/ /pubmed/31061126 http://dx.doi.org/10.1073/pnas.1820663116 Text en Copyright © 2019 the Author(s). Published by PNAS. http://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (http://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Biological Sciences Razgour, Orly Forester, Brenna Taggart, John B. Bekaert, Michaël Juste, Javier Ibáñez, Carlos Puechmaille, Sébastien J. Novella-Fernandez, Roberto Alberdi, Antton Manel, Stéphanie Considering adaptive genetic variation in climate change vulnerability assessment reduces species range loss projections |
title | Considering adaptive genetic variation in climate change vulnerability assessment reduces species range loss projections |
title_full | Considering adaptive genetic variation in climate change vulnerability assessment reduces species range loss projections |
title_fullStr | Considering adaptive genetic variation in climate change vulnerability assessment reduces species range loss projections |
title_full_unstemmed | Considering adaptive genetic variation in climate change vulnerability assessment reduces species range loss projections |
title_short | Considering adaptive genetic variation in climate change vulnerability assessment reduces species range loss projections |
title_sort | considering adaptive genetic variation in climate change vulnerability assessment reduces species range loss projections |
topic | Biological Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6535011/ https://www.ncbi.nlm.nih.gov/pubmed/31061126 http://dx.doi.org/10.1073/pnas.1820663116 |
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