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Updated: May 29, 2025

A Practical Guide to Phylogenetics for Nonexperts
Published on: February 5, 2014
Accuracy of phylogenetic reconstructions from continuous characters analysed under parsimony and its parametric
Victor A Tagliacollo1, Mario de Pinna2, Junior Chuctaya1
1Instituto de Biologia, Universidade Federal de Uberlândia, Rua Ceará - S/N, Umuarama, Minas Gerais, Brazil.
Abstract:
Quantitative traits are a source of evolutionary information often difficult to handle in cladistics. Tools exist to analyse this kind of data without subjective discretization, avoiding biases in the delimitation of categorical states. Nonetheless, our ability to accurately infer relationships from continuous characters is incompletely understood, particularly under parsimony analysis. This study evaluates the accuracy of phylogenetic reconstructions from simulated matrices of continuous characters evolving under alternative evolutionary processes and analysed by parsimony. We sampled 100 empirical trees to simulate 9000 matrices, each containing between 25 and 50 taxa, and 50 and 150 continuous characters evolving under three evolutionary processes: Brownian motion, Ornstein-Uhlenbeck and early burst with variable parametrizations. Our cladogram comparisons revealed that continuous character matrices, when properly coded and analysed by parsimony in TNT, carry phylogenetic signals from which species relationships can be inferred, regardless of the evolutionary models and parameterization schemes. Interestingly, implementing equal weighting or implied weighting with varying penalization strengths against homoplasies did not affect cladogram reconstructions based on continuous characters. Finally, the accuracy of continuous characters in resolving species relationships is skewed towards apical nodes of the recovered trees. Our findings provide general insights of the utility of quantitative traits in cladistics and demonstrate that their effectiveness in estimating shallower nodes is independent of the underlying evolutionary model, parameters and weighting schemes.
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