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A Bayesian Approach for Inferring the Impact of a Discrete Character on Rates of Continuous-Character Evolution in the Presence of Background-Rate Variation.
May, Michael R; Moore, Brian R.
Afiliação
  • May MR; Department of Evolution and Ecology, University of California, Davis, Storer Hall, One Shields Avenue, Davis, CA 95616, USA.
  • Moore BR; Department of Evolution and Ecology, University of California, Davis, Storer Hall, One Shields Avenue, Davis, CA 95616, USA.
Syst Biol ; 69(3): 530-544, 2020 05 01.
Article em En | MEDLINE | ID: mdl-31665487
ABSTRACT
Understanding how and why rates of character evolution vary across the Tree of Life is central to many evolutionary questions; for example, does the trophic apparatus (a set of continuous characters) evolve at a higher rate in fish lineages that dwell in reef versus nonreef habitats (a discrete character)? Existing approaches for inferring the relationship between a discrete character and rates of continuous-character evolution rely on comparing a null model (in which rates of continuous-character evolution are constant across lineages) to an alternative model (in which rates of continuous-character evolution depend on the state of the discrete character under consideration). However, these approaches are susceptible to a "straw-man" effect the influence of the discrete character is inflated because the null model is extremely unrealistic. Here, we describe MuSSCRat, a Bayesian approach for inferring the impact of a discrete trait on rates of continuous-character evolution in the presence of alternative sources of rate variation ("background-rate variation"). We demonstrate by simulation that our method is able to reliably infer the degree of state-dependent rate variation, and show that ignoring background-rate variation leads to biased inferences regarding the degree of state-dependent rate variation in grunts (the fish group Haemulidae). [Bayesian phylogenetic comparative methods; continuous-character evolution; data augmentation; discrete-character evolution.].
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Filogenia / Classificação Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Syst Biol Assunto da revista: BIOLOGIA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Filogenia / Classificação Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: Syst Biol Assunto da revista: BIOLOGIA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Estados Unidos