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

Puttick, Mark N.; O’Reilly, Joseph; Oakley, Derek; Tanner, Alistair R.; Fleming, James F.; Clark, James W.; Holloway, Lucy; Lozano‐Fernandez, Jesus; Parry, Luke A.; Tarver, James E.; Pisani, Davide; Donoghue, Philip C. J.

doi:10.1098/rspb.2017.1636

Cited by 20 publications

(17 citation statements)

References 8 publications

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“…The number of such trees was highly correlated to the MP-BI topological distance (R 2 = 0.17, P < 0.01). These results corroborate most recent analyses of simulated data which reported that probabilistic methods (BI and maximum likelihood) are more accurate than MP in recovering the true phylogeny, although the precision of BI is diminished (O'Reilly et al 2016;Brown et al 2017;Puttick et al, 2017a). Interestingly, we have not found a negative association between the matrix length and the topological distance.…”

Section: Discussionsupporting

confidence: 92%

“…; Brown et al . ; Puttick et al ., ). Interestingly, we have not found a negative association between the matrix length and the topological distance.…”

Section: Discussionmentioning

confidence: 97%

“…The poor precision of Bayesian analysis of morphological data, which has been frequently reported (Brown et al 2017;Puttick et al 2017a), may be explained by features of the Mk model, by issues associated with the approximation of the posterior distribution of parameters via MCMC or both. The basic assumptions of continuous time Markov models, such as independence of characters and equilibrium of character states, are very arguably violated in discrete morphological data (Wiens, 2004).…”

Section: Discussionmentioning

confidence: 99%

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Comparative evaluation of maximum parsimony and Bayesian phylogenetic reconstruction using empirical morphological data

Schrago

Aguiar

Mello

2018

J of Evolutionary Biology

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The use of discrete morphological data in Bayesian phylogenetics has increased significantly over the last years with the proposal of total evidence analysis and the treatment of fossils as terminal taxa in Bayesian molecular dating. Both approaches rely on the assumption that probabilistic Markov models reasonably accommodate all the complexity of morphological evolution of discrete traits. The performance of such morphological models used in Bayesian phylogenetics has been thoroughly investigated, but conclusions so far were based mostly on simulated data. In this study, we have surveyed MorphoBank and obtained a large number of morphological matrices to evaluate Bayesian phylogenetic inference (BI) under Lewis' Mk model in comparison with the maximum parsimony (MP) algorithm. We found that trees estimated by both methods frequently differed and that BI generated a larger amount of polytomic tree topologies. The number of trees contained in the 95% Bayesian credibility interval was significantly greater than the number of equally parsimonious trees. We also investigated which factors mostly influenced the topological difference between maximum parsimony and Bayesian tree topologies and found that the number of terminals in morphological matrices was the variable with the highest association with the topological distance between trees inferred by BI and MP. Surprisingly, we show that differences between both approaches were not influenced by increasing sample size. Our results, which were based on a large set of empirical matrices, corroborate recent findings that BI is less precise than MP.

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Section: Discussionsupporting

confidence: 92%

“…; Brown et al . ; Puttick et al ., ). Interestingly, we have not found a negative association between the matrix length and the topological distance.…”

Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

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Comparative evaluation of maximum parsimony and Bayesian phylogenetic reconstruction using empirical morphological data

Schrago

Aguiar

Mello

2018

J of Evolutionary Biology

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“…Previous studies have advocated accuracy as the sole criterion by which to select a method [5][6][7][8][9][10][11]. Congreve & Lamsdell [9] ( problematically [2]) define the most accurate tree as the one that bears the fewest incorrect splits.…”

Section: Introductionmentioning

confidence: 99%

Bayesian and parsimony approaches reconstruct informative trees from simulated morphological datasets

Smith

2019

Biol. Lett.

104

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Phylogenetic analysis aims to establish the true relationships between taxa. Different analytical methods, however, can reach different conclusions. In order to establish which approach best reconstructs true relationships, previous studies have simulated datasets from known tree topologies, and identified the method that reconstructs the generative tree most accurately. On this basis, researchers have argued that morphological datasets should be analysed by Bayesian approaches, which employ an explicit probabilistic model of evolution, rather than parsimony methods—with implied weights parsimony sometimes identified as particularly inaccurate. Accuracy alone, however, is an inadequate measure of a tree's utility: a fully unresolved tree is perfectly accurate, yet contains no phylogenetic information. The highly resolved trees recovered by implied weights parsimony in fact contain as much useful information as the more accurate, but less resolved, trees recovered by Bayesian methods. By collapsing poorly supported groups, this superior resolution can be traded for accuracy, resulting in trees as accurate as those obtained by a Bayesian approach. By contrast, equally weighted parsimony analysis produces trees that are less resolved and less accurate, leading to less reliable evolutionary conclusions.

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“…The Mk is thus a general, data-independent version of the classic Jukes-Cantor model of nucleotide evolution (Jukes & Cantor, 1969). Adoption of the Mk model in probabilistic analysis of morphology remains controversial, as doubts were cast on whether such a simple framework can accurately account for the intricacies of phenotypic evolution (Brown, Parins-Fukuchi, Stull, Vargas, & Smith, 2017;Dávalos, Velazco, Warsi, Smits, & Simmons, 2014;Puttick, O'Reilly, Oakley et al, 2017;Schrago, Aguiar, & Mello, 2018). A fundamental criticism rests on the assumption that morphological characters evolve under a common mechanism, that is, the rate of evolution at each branch is linearly correlated among characters (Goloboff, Pittman, Pol, & Xu, 2018;Tuffley & Steel, 1997); therefore, if a given character evolves faster in some lineage, it is expected that another unrelated character will also evolve relatively faster in this same lineage.…”

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confidence: 99%

Data partitioning and correction for ascertainment bias reduce the uncertainty of placental mammal divergence times inferred from the morphological clock

Caldas

Schrago

2019

Ecology and Evolution

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Bayesian estimates of divergence times based on the molecular clock yield uncertainty of parameter estimates measured by the width of posterior distributions of node ages. For the relaxed molecular clock, previous works have reported that some of the uncertainty inherent to the variation of rates among lineages may be reduced by partitioning data. Here we test this effect for the purely morphological clock, using placental mammals as a case study. We applied the uncorrelated lognormal relaxed clock to morphological data of 40 extant mammalian taxa and 4,533 characters, taken from the largest published matrix of discrete phenotypic characters. The morphologically derived timescale was compared to divergence times inferred from molecular and combined data. We show that partitioning data into anatomical units significantly reduced the uncertainty of divergence time estimates for morphological data. For the first time, we demonstrate that ascertainment bias has an impact on the precision of morphological clock estimates. While analyses including molecular data suggested most divergences between placental orders occurred near the K‐Pg boundary, the partitioned morphological clock recovered older interordinal splits and some younger intraordinal ones, including significantly later dates for the radiation of bats and rodents, which accord to the short‐fuse hypothesis.

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

Cited by 20 publications

References 8 publications

Comparative evaluation of maximum parsimony and Bayesian phylogenetic reconstruction using empirical morphological data

Comparative evaluation of maximum parsimony and Bayesian phylogenetic reconstruction using empirical morphological data

Bayesian and parsimony approaches reconstruct informative trees from simulated morphological datasets

Data partitioning and correction for ascertainment bias reduce the uncertainty of placental mammal divergence times inferred from the morphological clock

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