Literature DB >> 17849325

Estimating a binary character's effect on speciation and extinction.

Wayne P Maddison1, Peter E Midford, Sarah P Otto.   

Abstract

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.

Mesh:

Year:  2007        PMID: 17849325     DOI: 10.1080/10635150701607033

Source DB:  PubMed          Journal:  Syst Biol        ISSN: 1063-5157            Impact factor:   15.683


  249 in total

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Review 8.  Evolving entities: towards a unified framework for understanding diversity at the species and higher levels.

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Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-06-12       Impact factor: 6.237

9.  Equilibrium speciation dynamics in a model adaptive radiation of island lizards.

Authors:  Daniel L Rabosky; Richard E Glor
Journal:  Proc Natl Acad Sci U S A       Date:  2010-12-06       Impact factor: 11.205

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Authors:  Luke J Matthews; Christian Arnold; Zarin Machanda; Charles L Nunn
Journal:  Proc Biol Sci       Date:  2010-10-13       Impact factor: 5.349

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