A COMPARATIVE METHOD FOR STUDYING ADAPTATION TO A RANDOMLY EVOLVING ENVIRONMENT

Authors

  • Thomas F. Hansen,

    1. Center for Evolutionary and Ecological Synthesis, Department of Biology, University of Oslo, PB 1066, Blindern, 0316 Oslo, Norway
    2. Department of Biological Sciences, Florida State University, Tallahassee, Florida 32306
    3. E-mail: thomas.hansen@bio.uio.no
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  • Jason Pienaar,

    Corresponding author
    1. Department of Biological Sciences, Florida State University, Tallahassee, Florida 32306
      Current address: Department of Zoology, University of Hawaii at Manoa, Honolulu, Hawaii 96822
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  • Steven Hecht Orzack

    1. Fresh Pond Research Institute, Cambridge, Massachusetts 02140
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Current address: Department of Zoology, University of Hawaii at Manoa, Honolulu, Hawaii 96822

Abstract

Most phylogenetic comparative methods used for testing adaptive hypotheses make evolutionary assumptions that are not compatible with evolution toward an optimal state. As a consequence they do not correct for maladaptation. The “evolutionary regression” that is returned is more shallow than the optimal relationship between the trait and environment. We show how both evolutionary and optimal regressions, as well as phylogenetic inertia, can be estimated jointly by a comparative method built around an Ornstein–Uhlenbeck model of adaptive evolution. The method considers a single trait adapting to an optimum that is influenced by one or more continuous, randomly changing predictor variables.

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