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Adaptational lag to temperature in valley oak (Quercus lobata) can be mitigated by genome-informed assisted gene flow

Climate change over the next century is predicted to cause widespread maladaptation in natural systems. This prediction, as well as many sustainable management and conservation practices, assumes that species are adapted to their current climate. However, this assumption is rarely tested. Using a la...

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Autores principales: Browne, Luke, Wright, Jessica W., Fitz-Gibbon, Sorel, Gugger, Paul F., Sork, Victoria L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6911187/
https://www.ncbi.nlm.nih.gov/pubmed/31767740
http://dx.doi.org/10.1073/pnas.1908771116
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author Browne, Luke
Wright, Jessica W.
Fitz-Gibbon, Sorel
Gugger, Paul F.
Sork, Victoria L.
author_facet Browne, Luke
Wright, Jessica W.
Fitz-Gibbon, Sorel
Gugger, Paul F.
Sork, Victoria L.
author_sort Browne, Luke
collection PubMed
description Climate change over the next century is predicted to cause widespread maladaptation in natural systems. This prediction, as well as many sustainable management and conservation practices, assumes that species are adapted to their current climate. However, this assumption is rarely tested. Using a large-scale common garden experiment combined with genome-wide sequencing, we found that valley oak (Quercus lobata), a foundational tree species in California ecosystems, showed a signature of adaptational lag to temperature, with fastest growth rates occurring at cooler temperatures than populations are currently experiencing. Future warming under realistic emissions scenarios was predicted to lead to further maladaptation to temperature and reduction in growth rates for valley oak. We then identified genotypes predicted to grow relatively fast under warmer temperatures and demonstrated that selecting seed sources based on their genotype has the potential to mitigate predicted negative consequences of future climate warming on growth rates in valley oak. These results illustrate that the belief of local adaptation underlying many management and conservation practices, such as using local seed sources for restoration, may not hold for some species. If contemporary adaptational lag is commonplace, we will need new approaches to help alleviate predicted negative consequences of climate warming on natural systems. We present one such approach, “genome-informed assisted gene flow,” which optimally matches individuals to future climates based on genotype–phenotype–environment associations.
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spelling pubmed-69111872019-12-18 Adaptational lag to temperature in valley oak (Quercus lobata) can be mitigated by genome-informed assisted gene flow Browne, Luke Wright, Jessica W. Fitz-Gibbon, Sorel Gugger, Paul F. Sork, Victoria L. Proc Natl Acad Sci U S A Biological Sciences Climate change over the next century is predicted to cause widespread maladaptation in natural systems. This prediction, as well as many sustainable management and conservation practices, assumes that species are adapted to their current climate. However, this assumption is rarely tested. Using a large-scale common garden experiment combined with genome-wide sequencing, we found that valley oak (Quercus lobata), a foundational tree species in California ecosystems, showed a signature of adaptational lag to temperature, with fastest growth rates occurring at cooler temperatures than populations are currently experiencing. Future warming under realistic emissions scenarios was predicted to lead to further maladaptation to temperature and reduction in growth rates for valley oak. We then identified genotypes predicted to grow relatively fast under warmer temperatures and demonstrated that selecting seed sources based on their genotype has the potential to mitigate predicted negative consequences of future climate warming on growth rates in valley oak. These results illustrate that the belief of local adaptation underlying many management and conservation practices, such as using local seed sources for restoration, may not hold for some species. If contemporary adaptational lag is commonplace, we will need new approaches to help alleviate predicted negative consequences of climate warming on natural systems. We present one such approach, “genome-informed assisted gene flow,” which optimally matches individuals to future climates based on genotype–phenotype–environment associations. National Academy of Sciences 2019-12-10 2019-11-25 /pmc/articles/PMC6911187/ /pubmed/31767740 http://dx.doi.org/10.1073/pnas.1908771116 Text en Copyright © 2019 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Browne, Luke
Wright, Jessica W.
Fitz-Gibbon, Sorel
Gugger, Paul F.
Sork, Victoria L.
Adaptational lag to temperature in valley oak (Quercus lobata) can be mitigated by genome-informed assisted gene flow
title Adaptational lag to temperature in valley oak (Quercus lobata) can be mitigated by genome-informed assisted gene flow
title_full Adaptational lag to temperature in valley oak (Quercus lobata) can be mitigated by genome-informed assisted gene flow
title_fullStr Adaptational lag to temperature in valley oak (Quercus lobata) can be mitigated by genome-informed assisted gene flow
title_full_unstemmed Adaptational lag to temperature in valley oak (Quercus lobata) can be mitigated by genome-informed assisted gene flow
title_short Adaptational lag to temperature in valley oak (Quercus lobata) can be mitigated by genome-informed assisted gene flow
title_sort adaptational lag to temperature in valley oak (quercus lobata) can be mitigated by genome-informed assisted gene flow
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6911187/
https://www.ncbi.nlm.nih.gov/pubmed/31767740
http://dx.doi.org/10.1073/pnas.1908771116
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