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Wynd, B. M.

Publications and source records attributed to Wynd, B. M..

2 recordsLinked to original sources

Incorporating continuous characters in joint estimation of dicynodont phylogeny

Continuous characters have received comparatively little attention in Bayesian phylogenetic estimation. This is predominantly because they cannot be modeled by a standard phylogenetic Q-matrix approach due to their non-discrete nature. In this paper, we explore the use of continuous traits under two Brownian motion models to estimate a phylogenetic tree for Dicynodontia, a well-studied group of early synapsids (stem mammals) in which both discrete and continuous characters have been extensively used in parsimony-based tree reconstruction. We examine the differences in phylogenetic signal between a continuous trait partition, a discrete trait partition, and a joint analysis with both types of characters. We find that continuous and discrete traits contribute substantially different signal to the analysis, even when other parts of the model (clock and tree) are held constant. Tree topologies resulting from the new analyses differ strongly from the established phylogeny for dicynodonts, highlighting continued difficulty in incorporating truly continuous data in a Bayesian phylogenetic framework.

evolutionary biology↗

Modeling of Rate Heterogeneity in Datasets Compiled for Use With Parsimony

AO_SCPLOWBSTRACTC_SCPLOWIn recent years, there has been an increased interest in modeling morphological traits using Bayesian methods. Much of the work associated with modeling these characters has focused on the substitution or evolutionary model employed in the analysis. However, there are many other assumptions that researchers make in the modeling process that are consequential to estimated phylogenetic trees. One of these is how among-character rate variation (ACRV) is parameterized. In molecular data, a discretized gamma distribution is often used to allow different characters to have different rates of evolution. Morphological data are collected in ways that fundamentally differ from molecular data. In this paper, we appraise the use of standard parameters for ACRV and provide recommendations to researchers who work with morphological data in a Bayesian framework.

paleontology↗