Article,
Phylogenetic analysis using Lévy processes: finding jumps in the evolution of continuous traits
Syst Biol, 62 (2): 193-204 (March 2013)
DOI: 10.1093/sysbio/sys086
Abstract
Gaussian processes, a class of stochastic processes including Brownian motion and the Ornstein-Uhlenbeck process, are widely used to model continuous trait evolution in statistical phylogenetics. Under such processes, observations at the tips of a phylogenetic tree have a multivariate Gaussian distribution, which may lead to suboptimal model specification under certain evolutionary conditions, as supposed in models of punctuated equilibrium or adaptive radiation. To consider non-normally distributed continuous trait evolution, we introduce a method to compute posterior probabilities when modeling continuous trait evolution as a L\é\vy process. Through data simulation and model testing, we establish that single-rate Brownian motion (BM) and L\é\vy processes with jumps generate distinct patterns in comparative data. We then analyzed body mass and endocranial volume measurements for 126 primates. We rejected single-rate BM in favor of a L\é\vy process with jumps for each trait, with the lineage leading to most recent common ancestor of great apes showing particularly strong evidence against single-rate BM.
