The evolutionary time machine: forecasting how populations can adapt to changing environments using dormant propagules
Evolutionary changes are determined by a complex assortment of ecological, demographic and adaptive histories. Predicting how evolution will shape the genetic structures of populations coping with current (and future) environmental challenges has principally relied on investigations through space, i...
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ftpubmed:oai:pubmedcentral.nih.gov:3640660 2023-05-15T17:57:36+02:00 The evolutionary time machine: forecasting how populations can adapt to changing environments using dormant propagules Orsini, Luisa Schwenk, Klaus De Meester, Luc Colbourne, John K. Pfrender, Michael E. Weider, Lawrence J. 2013-02-08 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3640660 http://www.ncbi.nlm.nih.gov/pubmed/23395434 https://doi.org/10.1016/j.tree.2013.01.009 en eng http://www.ncbi.nlm.nih.gov/pmc/articles/PMC http://www.ncbi.nlm.nih.gov/pubmed/23395434 http://dx.doi.org/10.1016/j.tree.2013.01.009 © 2013 Elsevier Ltd. All rights reserved. Article Text 2013 ftpubmed https://doi.org/10.1016/j.tree.2013.01.009 2014-05-04T00:37:58Z Evolutionary changes are determined by a complex assortment of ecological, demographic and adaptive histories. Predicting how evolution will shape the genetic structures of populations coping with current (and future) environmental challenges has principally relied on investigations through space, in lieu of time, because long-term phenotypic and molecular data are scarce. Yet, dormant propagules in sediments, soils and permafrost are convenient natural archives of population-histories from which to trace adaptive trajectories along extended time periods. DNA sequence data obtained from these natural archives, combined with pioneering methods for analyzing both ecological and population genomic time-series data, are likely to provide predictive models to forecast evolutionary responses of natural populations to environmental changes resulting from natural and anthropogenic stressors, including climate change. Text permafrost PubMed Central (PMC) Trends in Ecology & Evolution 28 5 274 282 |
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Article Orsini, Luisa Schwenk, Klaus De Meester, Luc Colbourne, John K. Pfrender, Michael E. Weider, Lawrence J. The evolutionary time machine: forecasting how populations can adapt to changing environments using dormant propagules |
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Article |
description |
Evolutionary changes are determined by a complex assortment of ecological, demographic and adaptive histories. Predicting how evolution will shape the genetic structures of populations coping with current (and future) environmental challenges has principally relied on investigations through space, in lieu of time, because long-term phenotypic and molecular data are scarce. Yet, dormant propagules in sediments, soils and permafrost are convenient natural archives of population-histories from which to trace adaptive trajectories along extended time periods. DNA sequence data obtained from these natural archives, combined with pioneering methods for analyzing both ecological and population genomic time-series data, are likely to provide predictive models to forecast evolutionary responses of natural populations to environmental changes resulting from natural and anthropogenic stressors, including climate change. |
format |
Text |
author |
Orsini, Luisa Schwenk, Klaus De Meester, Luc Colbourne, John K. Pfrender, Michael E. Weider, Lawrence J. |
author_facet |
Orsini, Luisa Schwenk, Klaus De Meester, Luc Colbourne, John K. Pfrender, Michael E. Weider, Lawrence J. |
author_sort |
Orsini, Luisa |
title |
The evolutionary time machine: forecasting how populations can adapt to changing environments using dormant propagules |
title_short |
The evolutionary time machine: forecasting how populations can adapt to changing environments using dormant propagules |
title_full |
The evolutionary time machine: forecasting how populations can adapt to changing environments using dormant propagules |
title_fullStr |
The evolutionary time machine: forecasting how populations can adapt to changing environments using dormant propagules |
title_full_unstemmed |
The evolutionary time machine: forecasting how populations can adapt to changing environments using dormant propagules |
title_sort |
evolutionary time machine: forecasting how populations can adapt to changing environments using dormant propagules |
publishDate |
2013 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3640660 http://www.ncbi.nlm.nih.gov/pubmed/23395434 https://doi.org/10.1016/j.tree.2013.01.009 |
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permafrost |
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permafrost |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC http://www.ncbi.nlm.nih.gov/pubmed/23395434 http://dx.doi.org/10.1016/j.tree.2013.01.009 |
op_rights |
© 2013 Elsevier Ltd. All rights reserved. |
op_doi |
https://doi.org/10.1016/j.tree.2013.01.009 |
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Trends in Ecology & Evolution |
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28 |
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5 |
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274 |
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282 |
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1766166062201569280 |