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Detecting Non-Brownian Trait Evolution in Adaptive Radiations

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  • Robert P Freckleton
  • Paul H Harvey

Abstract

Many phylogenetic comparative methods that are currently widely used in the scientific literature assume a Brownian motion model for trait evolution, but the suitability of that model is rarely tested, and a number of important factors might affect whether this model is appropriate or not. For instance, we might expect evolutionary change in adaptive radiations to be driven by the availability of ecological niches. Such evolution has been shown to produce patterns of change that are different from those modelled by the Brownian process. We applied two tests for the assumption of Brownian motion that generally have high power to reject data generated under non-Brownian niche-filling models for the evolution of traits in adaptive radiations. As a case study, we used these tests to explore the evolution of feeding adaptations in two radiations of warblers. In one case, the patterns revealed do not accord with Brownian motion but show characteristics expected under certain niche-filling models. Two diagnostic tests reveal when traditional phylogenetic comparative methods relying on a Brownian motion model of trait evolution are not appropriate, and these can help identify underlying ecological mechanisms of adaptation.

Suggested Citation

  • Robert P Freckleton & Paul H Harvey, 2006. "Detecting Non-Brownian Trait Evolution in Adaptive Radiations," PLOS Biology, Public Library of Science, vol. 4(11), pages 1-8, November.
    • Handle: RePEc:plo:pbio00:0040373
    DOI: 10.1371/journal.pbio.0040373
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    References listed on IDEAS

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    1. Mark Pagel, 1999. "Inferring the historical patterns of biological evolution," Nature, Nature, vol. 401(6756), pages 877-884, October.
    2. Jonathan Silvertown & Mike E. Dodd & David J. G. Gowing & J. Owen Mountford, 1999. "Hydrologically defined niches reveal a basis for species richness in plant communities," Nature, Nature, vol. 400(6739), pages 61-63, July.
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    1. Piotr Zwiernik & Caroline Uhler & Donald Richards, 2017. "Maximum likelihood estimation for linear Gaussian covariance models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(4), pages 1269-1292, September.

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