title: Plausibility of inferred ancestral phenotypes and the evaluation of alternative models of limb evolution in scincid lizards.
abstract: Phylogenetic approaches to inferring ancestral character states are becoming increasingly sophisticated; however, the potential remains for available methods to yield strongly supported but inaccurate ancestral state estimates. The consistency of ancestral states inferred for two or more characters affords a useful criterion for evaluating ancestral trait reconstructions. Ancestral state estimates for multiple characters that entail plausible phenotypes when considered together may reasonably be assumed to be reliable. However, the accuracy of inferred ancestral states for one or more characters may be questionable where combined reconstructions imply implausible phenotypes for a proportion of internal nodes. This criterion for assessing reconstructed ancestral states is applied here in evaluating inferences of ancestral limb morphology in the scincid lizard clade Lerista. Ancestral numbers of digits for the manus and pes inferred assuming the models that best fit the data entail ancestral digit configurations for many nodes that differ fundamentally from configurations observed among known species. However, when an alternative model is assumed for the pes, inferred ancestral digit configurations are invariably represented among observed phenotypes. This indicates that a suboptimal model for the pes (and not the model providing the best fit to the data) yields accurate ancestral state estimates.
authors.affiliation: School of Earth and Environmental Sciences, The University of Adelaide, Adelaide, SA 5005, Australia. adam.skinner@adelaide.edu.au
authors.forename: Adam
authors.initials: A
authors.lastname: Skinner
authors.forename: Michael S Y
authors.initials: MS
authors.lastname: Lee
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D005075:Biological Evolution; D005121:Extremities / Q000033:anatomy & histology; D008116:Lizards / Q000033:anatomy & histology / Q000235:genetics*; D008954:Models, Biological; D010641:Phenotype; D010802:Phylogeny