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Fluctuations in lifetime selection in an autocorrelated environment
Olivier Cotto1, Luis-Miguel Chevin2
1Centre d'Ecologie Fonctionnelle et Evolutive Unité Mixte de Recherche 5175, Centre National de la Recherche Scientifique-Université de Montpellier, Université Paul-Valéry Montpellier, École Pratique des Hautes Études, 1919 route de Mende, 34293 Montpellier, Cedex 5, France; Department of Mathematics and Statistics, and Department of Biology, Queen's University, Jeffery Hall, Kingston, Ontario, Canada, K7L 3N6.
None:
Most natural environments vary stochastically and are temporally autocorrelated. Previous theory investigating the effects of environmental autocorrelation on evolution mostly assumed that total fitness resulted from a single selection episode. Yet organisms are likely to experience selection repeatedly along their life, in response to possibly different environmental states. We model the evolution of a quantitative trait in organisms with non-overlapping generations undergoing several episodes of selection in a randomly fluctuating and autocorrelated environment. We show that the evolutionary dynamics depends not directly on fluctuations of the environment, but instead on those of an effective phenotypic optimum that integrates the effects of all selection episodes within each generation. The variance and autocorrelation of the integrated optimum shape the variance and predictability of selection, with substantial qualitative and quantitative deviations from previous predictions considering a single selection episode per generation. We also investigate the consequence of multiple selection episodes per generation on population load. In particular, we identify a new load resulting from within-generation fluctuating selection, generating the death of individuals without significance for the evolutionary dynamics. Our study emphasizes how taking into account fluctuating selection within lifetime unravels new properties of evolutionary dynamics, with crucial implications notably with respect to responses to global changes.
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