Phylogenetic analysis using Lévy processes: Finding jumps in the evolution of continuous traits

Michael J. Landis, Joshua G. Schraiber, Mason Liang

Research output: Contribution to journalArticlepeer-review

84 Scopus citations

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 Lévy process. Through data simulation and model testing, we establish that single-rate Brownian motion (BM) and Lévy 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 Lévy 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. Continuous traits; saltational evolution; Lévy processes; Bayesian inference.

Original languageEnglish
Pages (from-to)193-204
Number of pages12
JournalSystematic Biology
Volume62
Issue number2
DOIs
StatePublished - Mar 2013

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