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On the evolution of specialization with a mechanistic underpinning in structured metapopulations

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  • Nurmi, Tuomas
  • Parvinen, Kalle

Abstract

We analyze the evolution of specialization in resource utilization in a discrete-time metapopulation model using the adaptive dynamics approach. The local dynamics in the metapopulation are based on the Beverton–Holt model with mechanistic underpinnings. The consumer faces a trade-off in the abilities to consume two resources that are spatially heterogeneously distributed to patches that are prone to local catastrophes. We explore the factors favoring the spread of generalist or specialist strategies. Increasing fecundity or decreasing catastrophe probability favors the spread of the generalist strategy and increasing environmental heterogeneity enlarges the parameter domain where the evolutionary branching is possible. When there are no catastrophes, increasing emigration diminishes the parameter domain where the evolutionary branching may occur. Otherwise, the effect of emigration on evolutionary dynamics is non-monotonous: both small and large values of emigration probability favor the spread of the specialist strategies whereas the parameter domain where evolutionary branching may occur is largest when the emigration probability has intermediate values. We compare how different forms of spatial heterogeneity and different models of local growth affect the evolutionary dynamics. We show that even small changes in the resource dynamics may have outstanding evolutionary effects to the consumers.

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  • Nurmi, Tuomas & Parvinen, Kalle, 2008. "On the evolution of specialization with a mechanistic underpinning in structured metapopulations," Theoretical Population Biology, Elsevier, vol. 73(2), pages 222-243.
    • Handle: RePEc:eee:thpobi:v:73:y:2008:i:2:p:222-243
    DOI: 10.1016/j.tpb.2007.12.002
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    References listed on IDEAS

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    Cited by:

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    4. Chaianunporn, Thotsapol & Hovestadt, Thomas, 2012. "Concurrent evolution of random dispersal and habitat niche width in host-parasitoid systems," Ecological Modelling, Elsevier, vol. 247(C), pages 241-250.

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