Estimating a Binary Character's Effect on Speciation and Extinction

• Published in: Systematic biology Vol. 56; no. 5; pp. 701 - 710
• Main Authors: Maddison, Wayne P., Midford, Peter E., Otto, Sarah P.
• Format: Journal Article
• Language: English
• Published: England Society of Systematic Zoology 01.10.2007; Taylor & Francis; Oxford University Press
• Subjects: Birth-death process; branching process; cladogenesis; Computer Simulation; Differential equations; Evolution; Evolutionary biology; Extinct species; Extinction; Extinction, Biological; Genetic Speciation; key innovation; Likelihood Functions; macroevolution; Mathematical models; Models, Biological; Null hypothesis; Parametric models; Phylogenetics; Phylogeny; Plant roots; Speciation; Species extinction; speciose; statistical inference; Taxonomy; key innovation; extinction; Birth-death process; branching process; macroevolution; phylogeny; statistical inference; cladogenesis; speciose; speciation
• ISSN: 1063-5157; 1076-836X
• DOI: 10.1080/10635150701607033

Determining whether speciation and extinction rates depend on the state of a particular character has been of long-standing interest to evolutionary biologists. To assess the effect of a character on diversification rates using likelihood methods requires that we be able to calculate the probability that a group of extant species would have evolved as observed, given a particular model of the character's effect. Here we describe how to calculate this probability for a phylogenetic tree and a two-state (binary) character under a simple model of evolution (the “BiSSE” model, binary-state speciation and extinction). The model involves six parameters, specifying two speciation rates (rate when the lineage is in state 0; rate when in state 1), two extinction rates (when in state 0; when in state 1), and two rates of character state change (from 0 to 1, and from 1 to 0). Using these probability calculations, we can do maximum likelihood inference to estimate the model's parameters and perform hypothesis tests (e.g., is the rate of speciation elevated for one character state over the other?). We demonstrate the application of the method using simulated data with known parameter values.