Document Detail


Evolutionary rescue by beneficial mutations in environments that change in space and time.
MedLine Citation:
PMID:  23209164     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
A factor that may limit the ability of many populations to adapt to changing conditions is the rate at which beneficial mutations can become established. We study the probability that mutations become established in changing environments by extending the classic theory for branching processes. When environments change in time, under quite general conditions, the establishment probability is approximately twice the 'effective selection coefficient', whose value is an average that gives most weight to a mutant's fitness in the generations immediately after it appears. When fitness varies along a gradient in a continuous habitat, increased dispersal generally decreases the chance a mutation establishes because mutations move out of areas where they are most adapted. When there is a patch of favourable habitat that moves in time, there is a maximum speed of movement above which mutations cannot become established, regardless of when and where they first appear. This critical speed limit, which is proportional to the mutation's maximum selective advantage, represents an absolute constraint on the potential of locally adapted mutations to contribute to evolutionary rescue.
Authors:
Mark Kirkpatrick; Stephan Peischl
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.    
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:  20120082     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Adaptation, Biological
Biological Evolution*
Computer Simulation
Ecosystem*
Extinction, Biological
Genetic Fitness
Genetics, Population / methods
Models, Genetic*
Mutation*
Population Density
Quantitative Trait, Heritable
Selection, Genetic
Spatio-Temporal Analysis
Time Factors
Comments/Corrections

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


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