Parsimony and maximum-likelihood phylogenetic analyses of morphology do not generally integrate uncertainty in inferring evolutionary history: a response to Brown et al.

Our recent study evaluated the performance of parsimony and probabilistic models of phylogenetic inference based on categorical data [1]. We found that a Bayesian implementation of a probabilistic Markov model produced more accurate results than either of the competing parsimony approaches (the main method currently employed), and the maximum-likelihood implementation of the same model. This occurs principally because the results of Bayesian analyses are less resolved (less precise) as a measure of topological uncertainty is intrinsically recovered in this MCMC-based approach and can be used to construct a majority-rule consensus tree that reflects this. Of the three main methods, maximum likelihood performed theworst of all as a single exclusively bifurcating tree is estimated in this framework which does not integrate an intrinsic measure of support.

Bibliographic Details

Main Authors:	Puttick, Mark N., O'Reilly, Joseph E., Oakley, Derek, Tanner, Alistair R., Fleming, James F., Clark, James, Holloway, Lucy, Lozano Fernández, Jesús, Parry, Luke A., Tarver, James E., Pisani, Davide, Donoghue, Philip C. J.
Format:	artículo biblioteca
Language:	English
Published:	Royal Society (Great Britain) 2017-10-11
Subjects:	Taxonomy and systematics, Evolution, Palaeontology,
Online Access:	http://hdl.handle.net/10261/217174
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