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Predicting phenolog...
Predicting phenology by integrating ecology, evolution and climate science
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Pau, Stephanie (author)
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Wolkovich, Elizabeth M. (author)
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Cook, Benjamin I. (author)
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Davies, T. Jonathan (author)
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Kraft, Nathan J. B. (author)
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- Bolmgren, Kjell (author)
- Lund University,Lunds universitet,Evolutionär ekologi,Biologiska institutionen,Naturvetenskapliga fakulteten,Evolutionary ecology,Department of Biology,Faculty of Science
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Betancourt, Julio L. (author)
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Cleland, Elsa E. (author)
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(creator_code:org_t)
- 2011-09-19
- 2011
- English.
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In: Global Change Biology. - : Wiley. - 1354-1013. ; 17:12, s. 3633-3643
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http://dx.doi.org/10...
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Abstract
Subject headings
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- Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology - the timing of life-history events. Phenology has well-demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species' reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.
Subject headings
- NATURVETENSKAP -- Biologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences (hsv//eng)
Keyword
- environmental filtering
- growing-degree day models
- niche conservatism
- photoperiod
- temperature sensitivity
- temporal niche
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