GSA Annual Meeting in Seattle, Washington, USA - 2017

Paper No. 272-61
Presentation Time: 9:00 AM-6:30 PM

A SIMULATION REVIEW OF METHODS FOR ESTIMATING MACROEVOLUTIONARY RATES USING FOSSIL DATA


SOUL, Laura C. and HUNT, Gene, Department of Paleobiology, Smithsonian Institution, National Museum of Natural History, NHB MRC 121, P.O. Box 37012, Washington, DC 20013-7012, SoulL@si.edu

A large number of studies use paleontological data in order to make estimates of speciation, extinction, sampling, and net diversification rates through geological time. These estimates have been used to make inferences about a variety of macroevolutionary patterns, including the influence of one clade’s diversification on another, the occurrence of adaptive radiations, and relationships between morphological evolution and diversification, among others. These rate estimates therefore play a very important role in modern paleobiological research. When methods to estimate these rates are initially presented, they often include validation of the method using simulation. However, simulation studies that compare the accuracy and precision of the outcomes from each method to one another, and under different and realistic evolutionary scenarios, have been lacking. Here we compare the success of rate estimation methods that have been used in macroevolutionary studies in the last five years, including both occurrence based and phylogenetic approaches. Simulated fossil records were designed to resemble carnivoran, dinosaurian and molluscan clades, and evolutionary scenarios including mass extinction, radiation, and stochastic variation, among others. The methods tested include: Alroy’s gap-filler and three-timer; Foote’s likelihood and boundary-crosser, with and without phylogenetic range extensions; capture-mark-recapture; Sakamoto et al’s Bayesian phylogenetic approach; and PyRate. Initial results show that several estimators tend to overestimate evolutionary rates, and that the best choice of method depends on the clade and time period under investigation. We hope that this comprehensive assessment of the methods currently available to estimate evolutionary rates provides a useful guide to those wishing to implement these analyses.