Geographical patterns of adaptation within a species’ range: interactions between drift and gene flow

Authors

  • M. ALLEAUME-BENHARIRA,

    1. Laboratoire Génétique et Environnement, Université de Montpellier II, Institut des Sciences de l’Évolution, Montpellier Cedex, France
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  • I. R. PEN,

    1. Laboratoire Génétique et Environnement, Université de Montpellier II, Institut des Sciences de l’Évolution, Montpellier Cedex, France
    2. Theoretical Biology Group, Centre for Ecological and Evolutionary Studies, University of Groningen, Kerklaan, The Netherlands
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  • O. RONCE

    1. Laboratoire Génétique et Environnement, Université de Montpellier II, Institut des Sciences de l’Évolution, Montpellier Cedex, France
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Mariane Alleaume-Benharira, Laboratoire Génétique et Environnement, CNRS UMR 5554, Université de Montpellier II, Institut des Sciences de l’Évolution, CC065, USTL, Place Eugène Bataillon, FR-34095, Montpellier Cedex 05, France.
Tel.: +33-4-67144718; fax: +33-4-67143622;
e-mail: alleaume@isem.univ-montp2.fr

Abstract

We use individual-based stochastic simulations and analytical deterministic predictions to investigate the interaction between drift, natural selection and gene flow on the patterns of local adaptation across a fragmented species’ range under clinally varying selection. Migration between populations follows a stepping-stone pattern and density decreases from the centre to the periphery of the range. Increased migration worsens gene swamping in small marginal populations but mitigates the effect of drift by replenishing genetic variance and helping purge deleterious mutations. Contrary to the deterministic prediction that increased connectivity within the range always inhibits local adaptation, simulations show that low intermediate migration rates improve fitness in marginal populations and attenuate fitness heterogeneity across the range. Such migration rates are optimal in that they maximize the total mean fitness at the scale of the range. Optimal migration rates increase with shallower environmental gradients, smaller marginal populations and higher mutation rates affecting fitness.

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