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The effect of migration on local adaptation in a coevolving host–parasite system

Author

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  • Andrew D. Morgan

    (University of Oxford)

  • Sylvain Gandon

    (UMR CNRS/IRD 2724, IRD)

  • Angus Buckling

    (University of Oxford)

Abstract

Antagonistic coevolution between hosts and parasites in spatially structured populations can result in local adaptation of parasites1,2,3,4,5; that is, the greater infectivity of local parasites than foreign parasites on local hosts1. Such parasite specialization on local hosts has implications for human health and agriculture. By contrast with classic single-species population-genetic models6,7, theory indicates that parasite migration between subpopulations might increase parasite local adaptation, as long as migration does not completely homogenize populations8,9,10,11. To test this hypothesis we developed a system-specific mathematical model and then coevolved replicate populations of the bacterium Pseudomonas fluorescens and a parasitic bacteriophage with parasite only, with host only or with no migration. Here we show that patterns of local adaptation have considerable temporal and spatial variation and that, in the absence of migration, parasites tend to be locally maladapted. However, in accord with our model, parasite migration results in parasite local adaptation, but host migration alone has no significant effect.

Suggested Citation

  • Andrew D. Morgan & Sylvain Gandon & Angus Buckling, 2005. "The effect of migration on local adaptation in a coevolving host–parasite system," Nature, Nature, vol. 437(7056), pages 253-256, September.
  • Handle: RePEc:nat:nature:v:437:y:2005:i:7056:d:10.1038_nature03913
    DOI: 10.1038/nature03913
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    Cited by:

    1. Iritani, Ryosuke & Iwasa, Yoh, 2014. "Parasite infection drives the evolution of state-dependent dispersal of the host," Theoretical Population Biology, Elsevier, vol. 92(C), pages 1-13.
    2. Vuilleumier, S. & Goudet, J. & Perrin, N., 2010. "Evolution in heterogeneous populations: From migration models to fixation probabilities," Theoretical Population Biology, Elsevier, vol. 78(4), pages 250-258.

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