Title

Bayesian Mixed Models And The Phylogeny Of Pitvipers (Viperidae: Serpentes)

Keywords

Bayesian phylogeny; Crotalinae; Data partitions; MCMC; Mixed models; Pitvipers; Posterior probability credibility; Viperidae

Abstract

The subfamily Crotalinae (pitvipers) contains over 190 species of venomous snakes distributed in both the Old and New World. We incorporated an extensive sampling of taxa (including 28 of 29 genera), and sequences of four mitochondrial gene fragments (2.3 kb) per individual, to estimate the phylogeny of pitvipers based on maximum parsimony and Bayesian phylogenetic methods. Our Bayesian analyses incorporated complex mixed models of nucleotide evolution that allocated independent models to various partitions of the dataset within combined analyses. We compared results of unpartitioned versus partitioned Bayesian analyses to investigate how much unpartitioned (versus partitioned) models were forced to compromise estimates of model parameters, and whether complex models substantially alter phylogenetic conclusions to the extent that they appear to extract more phylogenetic signal than simple models. Our results indicate that complex models do extract more phylogenetic signal from the data. We also address how differences in phylogenetic results (e.g., bipartition posterior probabilities) obtained from simple versus complex models may be interpreted in terms of relative credibility. Our estimates of pitviper phylogeny suggest that nearly all recently proposed generic reallocations appear valid, although certain Old and New World genera (Ovophis, Trimeresurus, and Bothrops) remain poly- or paraphyletic and require further taxonomic revision. While a majority of nodes were resolved, we could not confidently estimate the basal relationships among New World genera and which lineage of Old World species is most closely related to this New World group. © 2006 Elsevier Inc. All rights reserved.

Publication Date

4-1-2006

Publication Title

Molecular Phylogenetics and Evolution

Volume

39

Issue

1

Number of Pages

91-110

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.ympev.2005.12.014

Socpus ID

33645007877 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/33645007877

This document is currently not available here.

Share

COinS