title: Putting phylogeny into the analysis of biological traits: a methodological approach.
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.
authors.affiliation: Department of Infectious Disease Epidemiology, Faculty of Medicine, Imperial College London, MRC Centre for Outbreak Analysis & Modelling, Norfolk Place, London W2 1PG, UK. t.jombart@imperial.ac.uk
authors.forename: Thibaut
authors.initials: T
authors.lastname: Jombart
authors.forename: Sandrine
authors.initials: S
authors.lastname: Pavoine
authors.forename: Sébastien
authors.initials: S
authors.lastname: Devillard
authors.forename: Dominique
authors.initials: D
authors.lastname: Pontier
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D049810:Genetic Speciation; D006801:Humans; D008957:Models, Genetic; D010802:Phylogeny; D025341:Principal Component Analysis / Q000379:methods*; D012984:Software