A Bayesian approach for detecting the impact of mass‐extinction events on molecular phylogenies when rates of lineage diversification may vary. Issue 8 (28th May 2016)

• Record Type: Journal Article
• Authors: May, Michael R.; Höhna, Sebastian; Moore, Brian R.
• Editors: Cooper, Natalie
• Is Part Of: Methods in ecology and evolution. Volume 7:Issue 8(2016:Aug.)
• Page Start: 947
• Page End: 959
• Publication Date: 2016-05-28
• Subjects: Bayesian inference -- birth‐death stochastic‐branching process -- compound Poisson process model -- lineage diversification rates -- mass extinction -- phylogeny -- speciation; Ecology -- Periodicals; Evolution -- Periodicals; 577
• DOI: 10.1111/2041-210X.12563
• Languages: English
• ISSNs: 2041-210X

Abstract

Summary: The paleontological record chronicles numerous episodes of mass extinction that severely culled the Tree of Life. Biologists have long sought to assess the extent to which these events may have impacted particular groups. We present a novel method for detecting the impact of mass‐extinction events on molecular phylogenies, even in the presence of tree‐wide diversification‐rate variation and in the absence of additional information from the fossil record. Our approach is based on an episodic stochastic‐branching process model in which rates of speciation and extinction are constant between events. We model three types of events: (i) instantaneous tree‐wide shifts in speciation rate; (ii) instantaneous tree‐wide shifts in extinction rate and (iii) instantaneous tree‐wide mass‐extinction events. Each type of event is modelled as an independent compound Poisson process (CPP), where the waiting times between events are exponentially distributed with event‐specific rate parameters. The magnitude of each event is drawn from an event‐specific prior distribution. Parameters of the model are then estimated in a Bayesian statistical framework using a reversible‐jump Markov chain Monte Carlo algorithm. This Bayesian approach enables us to distinguish between tree‐wide diversification‐rate variation and mass‐extinction events by specifying a biologically informed prior on the magnitude of mass‐extinction events and empirical hyperpriors on the diversification‐rate parameters. We demonstrate via simulation that this method has substantial power to detect the number of mass‐extinction events and provides unbiased estimates of the timing of mass‐extinction events, while exhibiting an appropriate (i.e. <5%) false‐discovery rate, even when background diversification rates vary. Finally, we provide an empirical demonstration of this approach, which reveals that conifers experienced a major episode of mass extinction ≈23 Ma. This new approach – the CPP on Mass‐Extinction Times (CoMET ) model – provides an effective tool for detecting the impact of mass‐extinction events on molecular phylogenies, even when the history of those groups includes temporal variation in diversification rates and when the fossil history of those groups is poorly known.