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Data from: Phylogenetic analysis using Lévy processes: finding jumps in the evolution of continuous traits

Citation

Landis, Michael J.; Schraiber, Joshua G.; Liang, Mason (2012), Data from: Phylogenetic analysis using Lévy processes: finding jumps in the evolution of continuous traits, Dryad, Dataset, https://doi.org/10.5061/dryad.0n761

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.

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