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Evolutionary Demography

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Data-driven Modelling of Structured Populations

Abstract

Patterns of survival and reproduction determine fitness and so it should come as no surprise that there is a rich body of theory linking demography with evolution. Here we provide an overview of these methods showing how evolutionary dynamics and selection can be understood using IPMs. We show how selection can be approximated using sensitivities and how this leads to an approximation for trait dynamics. The endpoints of evolution – what we expect to see in nature – are explored using ideas from Adaptive Dynamics, the key methods based on Evolutionarily Stable Strategies and Convergence Stability. Efficient methods for finding ESS are presented. We then extend these ideas to cover stochastic environments and function-valued traits. For function-valued traits we model the entire function rather than the underlying parameters, and so we are not tied to a specific fitted function.

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Notes

  1. 1.

    One last time: or any other continuously varying trait or traits.

  2. 2.

    The corresponding function for Windows is parLapply in the parallel package, which works a bit differently.

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Authors and Affiliations

  1. Ecology and Evolutionary Biology, Cornell University, Corson Hall, Ithaca, NY, USA

    Stephen P. Ellner

  2. Animal and Plant Sciences, University of Sheffield, Yorkshire, UK

    Dylan Z. Childs & Mark Rees

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  1. Stephen P. Ellner
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  2. Dylan Z. Childs
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  3. Mark Rees
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Ellner, S.P., Childs, D.Z., Rees, M. (2016). Evolutionary Demography. In: Data-driven Modelling of Structured Populations. Lecture Notes on Mathematical Modelling in the Life Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-28893-2_9

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