Document Detail

Evolutionary rescue beyond the models.
MedLine Citation:
PMID:  23209173     Owner:  NLM     Status:  MEDLINE    
Laboratory model systems and mathematical models have shed considerable light on the fundamental properties and processes of evolutionary rescue. But it remains to determine the extent to which these model-based findings can help biologists predict when evolution will fail or succeed in rescuing natural populations that are facing novel conditions that threaten their persistence. In this article, we present a prospectus for transferring our basic understanding of evolutionary rescue to wild and other non-laboratory populations. Current experimental and theoretical results emphasize how the interplay between inheritance processes and absolute fitness in changed environments drive population dynamics and determine prospects of extinction. We discuss the challenge of inferring these elements of the evolutionary rescue process in field and natural settings. Addressing this challenge will contribute to a more comprehensive understanding of population persistence that combines processes of evolutionary rescue with developmental and ecological mechanisms.
Richard Gomulkiewicz; Ruth G Shaw
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Review    
Journal Detail:
Title:  Philosophical transactions of the Royal Society of London. Series B, Biological sciences     Volume:  368     ISSN:  1471-2970     ISO Abbreviation:  Philos. Trans. R. Soc. Lond., B, Biol. Sci.     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2012-12-04     Completed Date:  2013-05-07     Revised Date:  2014-01-23    
Medline Journal Info:
Nlm Unique ID:  7503623     Medline TA:  Philos Trans R Soc Lond B Biol Sci     Country:  England    
Other Details:
Languages:  eng     Pagination:  20120093     Citation Subset:  IM    
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MeSH Terms
Adaptation, Physiological
Angiosperms / genetics,  physiology*
Biological Evolution*
Empirical Research
Extinction, Biological
Genetic Variation
Models, Biological
Seeds / physiology
Selection, Genetic
Stress, Physiological

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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