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Putting phylogeny into the analysis of biological traits: A methodological approach
Authors:Thibaut Jombart  Sandrine Pavoine  Dominique Pontier
Affiliation:a MRC Centre for Outbreak Analysis & Modelling, Department of Infectious Disease Epidemiology, Imperial College London, Faculty of Medicine, Norfolk Place, London W2 1PG, UK
b Museum National d’Histoire Naturelle, Département Ecologie et Gestion de la Biodiversité, UMR 7204 MNHN-CNRS-UPMC, CRBPO, 61 rue Buffon, 75005 Paris, France
c Université de Lyon, Université Lyon 1, CNRS, UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, 43 boulevard du 11 novembre 1918, Villeurbanne F-69622, France
Abstract:Phylogenetic comparative methods have long considered phylogenetic signal as a source of statistical bias in the correlative analysis of biological traits. However, the main life-history strategies existing in a set of taxa are often combinations of life history traits that are inherently phylogenetically structured. In this paper, we present a method for identifying evolutionary strategies from large sets of biological traits, using phylogeny as a source of meaningful historical and ecological information. Our methodology extends a multivariate method developed for the analysis of spatial patterns, and relies on finding combinations of traits that are phylogenetically autocorrelated. Using extensive simulations, we show that our method efficiently uncovers phylogenetic structures with respect to various tree topologies, and remains powerful in cases where a large majority of traits are not phylogenetically structured. Our methodology is illustrated using empirical data, and implemented in the adephylo package for the free software R.
Keywords:Phylogenetic principal component analysis   pPCA   Multivariate   Comparative method   Phylogenetic signal
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