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Phylogenetic Comparative Analysis: A Modeling Approach for Adaptive Evolution

The American Naturalist · 2004 · Vol. 164(6) · pp. 683–695
Marguerite A. ButlerAaron A. King

Abstract

Biologists employ phylogenetic comparative methods to study adaptive evolution. However, none of the popular methods model selection directly. We explain and develop a method based on the Ornstein-Uhlenbeck (OU) process, first proposed by Hansen. Ornstein-Uhlenbeck models incorporate both selection and drift and are thus qualitatively different from, and more general than, pure drift models based on Brownian motion. Most importantly, OU models possess selective optima that formalize the notion of adaptive zone. In this article, we develop the method for one quantitative character, discuss interpretations of its parameters, and provide code implementing the method. Our approach allows us to translate hypotheses regarding adaptation in different selective regimes into explicit models, to test the models against data using maximum-likelihood-based model selection techniques, and to infer details of the evolutionary process. We illustrate the method using two worked examples. Relative to existing approaches, the direct modeling approach we demonstrate allows one to explore more detailed hypotheses and to utilize more of the information content of comparative data sets than existing methods. Moreover, the use of a model selection framework to simultaneously compare a variety of hypotheses advances our ability to assess alternative evolutionary explanations.

Evolution and Paleontology StudiesGenetic diversity and population structureGenomics and Phylogenetic StudiesSelection (genetic algorithm)Computer sciencePhylogenetic comparative methodsModel selectionPhylogenetic treeAdaptation (eye)Variety (cybernetics)Process (computing)Machine learningArtificial intelligence
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