An Introduction to Phylogenetically Based Statistical Methods, with a New Method for Confidence Intervals on Ancestral Values

Abstract

Interspecific comparisons have played a prominent role in evolutionary biology at least since the time of Charles Darwin. Since 1985, the “comparative method” has been revitalized by new analytical techniques that use phylogenetic information and by increased availability of phytogenies (often from molecular data sets). Because species descend from common ancestors in a hierarchical fashion, related species tend to resemble each other (elephants look like elephants); therefore, cross-species data sets generally do not comprise independent and identically distributed data points. Phylogenetically based statistical methods attempt to account for this fact. Phylogenetic methods allow traditional topics in comparative and ecological physiology to be addressed with greater rigor, including the form of allometric relationships and whether physiological phenotypes vary predictably in relation to behavior, ecology or environmental characteristics, which provides evidence about adaptation. They can also address new topics, such as whether rates of physiological evolution have differed among lineages (clades), and where and when a phenotype first evolved. We present brief overviews of three phylogenetically based statistical methods: phylogenetically independent contrasts, Monte Carlo computer simulations to obtain null distributions of test statistics, and phylogenetic autocorrelation. In a new result, we show analytically how to use independent contrasts to estimate ancestral values and confidence intervals about them. These confidence intervals often exceed the range of variation observed among extant species, which points out the relatively great uncertainty inherent in such inferences. The use of phytogenies should become as common as the use of body size and scaling relationships in the analysis of physiological diversity.