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Optimizing selection for function-valued traits

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Abstract

We consider a function-valued trait z(t) whose pre-selection distribution is Gaussian, and a fitness function W that models optimizing selection, subject to certain natural assumptions. We show that the post-selection distribution of z(t) is also Gaussian, compute the selection differential, and derive an equation that expresses the selection gradient in terms of the parameters of W and of the pre-selection distribution. We make no assumptions on the nature of the ‘time–parameter t.

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Authors and Affiliations

  1. Department of Mathematical Sciences, University of Wisconsin, Milwaukee, WI, 53201, USA

    Jay H. Beder

  2. School of Biological Sciences and Department of Mathematics, Washington State University, P. O. Box 644236, Pullman, WA, 99164, USA

    Richard Gomulkiewicz

Authors
  1. Jay H. Beder
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  2. Richard Gomulkiewicz
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Correspondence to Jay H. Beder.

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Beder, J.H., Gomulkiewicz, R. Optimizing selection for function-valued traits. J. Math. Biol. 55, 861–882 (2007). https://doi.org/10.1007/s00285-007-0114-6

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  • DOI: https://doi.org/10.1007/s00285-007-0114-6

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