Document Detail


Predicting demographically sustainable rates of adaptation: can great tit breeding time keep pace with climate change?
MedLine Citation:
PMID:  23209174     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Populations need to adapt to sustained climate change, which requires micro-evolutionary change in the long term. A key question is how the rate of this micro-evolutionary change compares with the rate of environmental change, given that theoretically there is a 'critical rate of environmental change' beyond which increased maladaptation leads to population extinction. Here, we parametrize two closely related models to predict this critical rate using data from a long-term study of great tits (Parus major). We used stochastic dynamic programming to predict changes in optimal breeding time under three different climate scenarios. Using these results we parametrized two theoretical models to predict critical rates. Results from both models agreed qualitatively in that even 'mild' rates of climate change would be close to these critical rates with respect to great tit breeding time, while for scenarios close to the upper limit of IPCC climate projections the calculated critical rates would be clearly exceeded with possible consequences for population persistence. We therefore tentatively conclude that micro-evolution, together with plasticity, would rescue only the population from mild rates of climate change, although the models make many simplifying assumptions that remain to be tested.
Authors:
Phillip Gienapp; Marjolein Lof; Thomas E Reed; John McNamara; Simon Verhulst; Marcel E Visser
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
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:  20120289     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Adaptation, Biological*
Animals
Biological Evolution
Breeding*
Climate Change*
Female
Forecasting
Genetic Fitness
Models, Biological
Ovum / physiology
Passeriformes / genetics,  physiology*
Phenotype
Population Dynamics
Seasons
Temperature
Time Factors
Comments/Corrections

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


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