Procedures for the Analysis of Comparative Data Using Phylogenetically Independent Contrasts

Abstract

We discuss and clarify several aspects of applying Felsenstein's (1985, Am. Nat. 125: 1-15) procedures to test for correlated evolution of continuous traits. This is one of several available comparative methods that maps data for phenotypic traits onto an existing phylogenetic tree (derived from independent information). Application of Felsenstein's method does not require an entirely dichotomous topology. It also does not require an assumption of gradual, clocklike character evolution, as might be modeled by Brownian motion. Almost any available information can be used to estimate branch lengths (e.g., genetic distances, divergence times estimated from the fossil record or from molecular clocks, numbers of character changes from a cladistic analysis). However, the adequacy for statistical purposes of any proposed branch lengths must be verified empirically for each phylogeny and for each character. We suggest a simple way of doing this, based on graphical analysis of plots of standardized independent contrasts versus their standard deviations (i.e., the square roots of the sums of their branch lengths). In some cases, the branch lengths and/or the values of traits being studied will require transformation. An example involving the scaling of mammalian home range area is presented. Once adequately standardized, sets of independent contrasts can be analyzed using either linear or nonlinear (multiple) regression. In all cases, however, regressions (or correlations) must be computed through the origin. We also discuss ways of correcting for body size effects and how this relates to making graphical representations of relationships of standardized independent contrasts. We close with a consideration of the types of traits that can be analyzed with independent contrasts procedures and conclude that any (continuous) trait that is inherited from ancestors is appropriate for analysis, regardless of the mechanism of inheritance (e.g., genetic or cultural). [Allometry; body size; branch lengths; comparative method; evolutionary rates; functional morphology; home range; statistics.] SYSTEMATIC BIOLOGY

Laboratory endurance capacity predicts variation in field locomotor behaviour among lizard species

“…As in my analysis of the data for 57 species, branch lengths in units of estimated divergence times yielded negative relationships in diagnostic plots of the absolute values of the standardized contrasts versus their standard deviations (Garland et al 1992). Such relationships can lead to inflated type I error rates (Díaz-Uriarte & Garland 1998).…”

“…This is the best understood and most widely used of available phylogenetically based statistical methods (e.g. Losos 1990a, b;Harvey & Pagel 1991;Garland et al 1992Garland et al , 1999Garland & Adolph 1994;Irschick et al 1996;Martins 1996;Zani 1996;Díaz-Uriarte & Garland 1998) and was used in my previous analysis of endurance . I used the PDTREE program (available for free from the author; latest version 5.0 described in Garland et al 1999).…”

Endocranial volumes of primate species: scaling analyses using a comprehensive and reliable data set

“…Contrasts were generated using the PDAP:PDTree package (Garland et al, 1992) of the Mesquite computer program (Maddison and Maddison, 2005). The appropriateness of branch length estimations was then tested using CONTINUOUS (Pagel, 1994).…”

“…The likelihood ratio test revealed that the Null hypothesis of equal branch lengths should be rejected (ln-likelihood ratio = 75.09, df = 1, p = <0.0001). Independent contrasts were analyzed using least-squares regressions constrained to pass through the origin (Garland et al, 1992).…”

Higher Allocation to Low Cost Chemical Defenses in Invasive Species of Hawaii

“…Our phylogenetic hypothesis was based on the conservative megatree, where unresolved nodes were included as soft politomies. We employed programs in the PDAP package (Garland et al, 1993) to transform the phylogenetic tree into a matrix of phylogenetic distances, and assessed whether the studied traits showed significant phylogenetic signal-i.e., the tendency of closely related species to resemble each other due to shared ancestryemploying the randomization procedure in the PHYSIG module developed by Blomberg et al (2003). This test consists in comparing the variance in phylogenetic independent contrasts observed in the real dataset against a null distribution obtained after the phenotypic data were randomized across the tips of the phylogeny (i.e., breaking any pattern of phylogenetic resemblance between relatives).…”