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Data from: Quantifying the effects of migration and mutation on adaptation and demography in spatially heterogeneous environments Débarre, Florence; Ronce, Ophélie; Gandon, Sylvain


How do mutation and gene flow influence population persistence, niche expansion, and local adaptation in spatially heterogeneous environments? In this article, we analyse a demographic and evolutionary model of adaptation to an environment containing two habitats in equal frequencies, and we bridge the gap between different theoretical frameworks. Qualitatively, our model yields four qualitative types of outcomes: (i) global extinction of the population (ii) adaptation to one habitat only, but also adaptation to both habitats with (iii) specialized phenotypes, or (iv) with generalized phenotypes; and we determine the conditions under which each equilibrium is reached. We derive new analytical approximations for the local densities and the distributions of traits in each habitat under a migration--selection--mutation balance, compute the equilibrium values of the means, variances and asymmetries of the local distributions of phenotypes, and contrast the effects of migration and mutation on the evolutionary outcome. We then check our analytical results by solving our model numerically, and also assess their robustness in the presence of demographic stochasticity. While increased migration results in a decrease in local adaptation, mutation in our model does not influence the values of the local mean traits. Yet, both migration and mutation can have dramatic effects on population size and even lead to metapopulation extinction when selection is strong. Niche expansion, the ability for the population to adapt to both habitats, can also be prevented by small migration rates and a reduced evolutionary potential characterised by rare mutation events of small effects; but niche expansion is otherwise the most likely outcome. Although our results are derived under the assumption of clonal reproduction, we finally show and discuss the links between our model and previous quantitative genetics models.; Usage notes
Debarre-etal_2013_JEB_CodesZipped folder containing R and Mathematica codes.

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