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Adaptation, Plasticity, and Extinction in a Changing Environment: Towards a Predictive Theory
Adaptation, Plasticity, and Extinction in a Changing Environment: Towards a Predictive Theory
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Adaptation, Plasticity, and Extinction in a Changing Environment: Towards a Predictive Theory
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Adaptation, Plasticity, and Extinction in a Changing Environment: Towards a Predictive Theory
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Adaptation, Plasticity, and Extinction in a Changing Environment: Towards a Predictive Theory
Adaptation, Plasticity, and Extinction in a Changing Environment: Towards a Predictive Theory
Journal Article

Adaptation, Plasticity, and Extinction in a Changing Environment: Towards a Predictive Theory

2010
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Overview
Many species are experiencing sustained environmental change mainly due to human activities. The unusual rate and extent of anthropogenic alterations of the environment may exceed the capacity of developmental, genetic, and demographic mechanisms that populations have evolved to deal with environmental change. To begin to understand the limits to population persistence, we present a simple evolutionary model for the critical rate of environmental change beyond which a population must decline and go extinct. We use this model to highlight the major determinants of extinction risk in a changing environment, and identify research needs for improved predictions based on projected changes in environmental variables. Two key parameters relating the environment to population biology have not yet received sufficient attention. Phenotypic plasticity, the direct influence of environment on the development of individual phenotypes, is increasingly considered an important component of phenotypic change in the wild and should be incorporated in models of population persistence. Environmental sensitivity of selection, the change in the optimum phenotype with the environment, still crucially needs empirical assessment. We use environmental tolerance curves and other examples of ecological and evolutionary responses to climate change to illustrate how these mechanistic approaches can be developed for predictive purposes.