Weighted parsimony outperforms other methods of phylogenetic inference under models appropriate for morphology

One of the lasting controversies in phylogenetic inference is the degree to which specific evolutionary models should influence the choice of methods. Model‐based approaches to phylogenetic inference (likelihood, Bayesian) are defended on the premise that without explicit statistical models there is...

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Veröffentlicht in:	Cladistics Jg. 34; H. 4; S. 407 - 437
Hauptverfasser:	Goloboff, Pablo A., Torres, Ambrosio, Arias, J. Salvador
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Hoboken Wiley Subscription Services, Inc 01.08.2018
Schlagworte:	Bayesian analysis Branches DNA Evolution Mathematical models Morphology Nucleotide sequence nucleotide sequences Phylogenetics Phylogeny Sampling techniques Statistical analysis statistical models
ISSN:	0748-3007, 1096-0031, 1096-0031
Online-Zugang:	Volltext
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Abstract	One of the lasting controversies in phylogenetic inference is the degree to which specific evolutionary models should influence the choice of methods. Model‐based approaches to phylogenetic inference (likelihood, Bayesian) are defended on the premise that without explicit statistical models there is no science, and parsimony is defended on the grounds that it provides the best rationalization of the data, while refraining from assigning specific probabilities to trees or character‐state reconstructions. Authors who favour model‐based approaches often focus on the statistical properties of the methods and models themselves, but this is of only limited use in deciding the best method for phylogenetic inference—such decision also requires considering the conditions of evolution that prevail in nature. Another approach is to compare the performance of parsimony and model‐based methods in simulations, which traditionally have been used to defend the use of models of evolution for DNA sequences. Some recent papers, however, have promoted the use of model‐based approaches to phylogenetic inference for discrete morphological data as well. These papers simulated data under models already known to be unfavourable to parsimony, and modelled morphological evolution as if it evolved just like DNA, with probabilities of change for all characters changing in concert along tree branches. The present paper discusses these issues, showing that under reasonable and less restrictive models of evolution for discrete characters, equally weighted parsimony performs as well or better than model‐based methods, and that parsimony under implied weights clearly outperforms all other methods.
AbstractList	One of the lasting controversies in phylogenetic inference is the degree to which specific evolutionary models should influence the choice of methods. Model‐based approaches to phylogenetic inference (likelihood, Bayesian) are defended on the premise that without explicit statistical models there is no science, and parsimony is defended on the grounds that it provides the best rationalization of the data, while refraining from assigning specific probabilities to trees or character‐state reconstructions. Authors who favour model‐based approaches often focus on the statistical properties of the methods and models themselves, but this is of only limited use in deciding the best method for phylogenetic inference—such decision also requires considering the conditions of evolution that prevail in nature. Another approach is to compare the performance of parsimony and model‐based methods in simulations, which traditionally have been used to defend the use of models of evolution for DNA sequences. Some recent papers, however, have promoted the use of model‐based approaches to phylogenetic inference for discrete morphological data as well. These papers simulated data under models already known to be unfavourable to parsimony, and modelled morphological evolution as if it evolved just like DNA, with probabilities of change for all characters changing in concert along tree branches. The present paper discusses these issues, showing that under reasonable and less restrictive models of evolution for discrete characters, equally weighted parsimony performs as well or better than model‐based methods, and that parsimony under implied weights clearly outperforms all other methods. One of the lasting controversies in phylogenetic inference is the degree to which specific evolutionary models should influence the choice of methods. Model-based approaches to phylogenetic inference (likelihood, Bayesian) are defended on the premise that without explicit statistical models there is no science, and parsimony is defended on the grounds that it provides the best rationalization of the data, while refraining from assigning specific probabilities to trees or character-state reconstructions. Authors who favour model-based approaches often focus on the statistical properties of the methods and models themselves, but this is of only limited use in deciding the best method for phylogenetic inference-such decision also requires considering the conditions of evolution that prevail in nature. Another approach is to compare the performance of parsimony and model-based methods in simulations, which traditionally have been used to defend the use of models of evolution for DNA sequences. Some recent papers, however, have promoted the use of model-based approaches to phylogenetic inference for discrete morphological data as well. These papers simulated data under models already known to be unfavourable to parsimony, and modelled morphological evolution as if it evolved just like DNA, with probabilities of change for all characters changing in concert along tree branches. The present paper discusses these issues, showing that under reasonable and less restrictive models of evolution for discrete characters, equally weighted parsimony performs as well or better than model-based methods, and that parsimony under implied weights clearly outperforms all other methods.One of the lasting controversies in phylogenetic inference is the degree to which specific evolutionary models should influence the choice of methods. Model-based approaches to phylogenetic inference (likelihood, Bayesian) are defended on the premise that without explicit statistical models there is no science, and parsimony is defended on the grounds that it provides the best rationalization of the data, while refraining from assigning specific probabilities to trees or character-state reconstructions. Authors who favour model-based approaches often focus on the statistical properties of the methods and models themselves, but this is of only limited use in deciding the best method for phylogenetic inference-such decision also requires considering the conditions of evolution that prevail in nature. Another approach is to compare the performance of parsimony and model-based methods in simulations, which traditionally have been used to defend the use of models of evolution for DNA sequences. Some recent papers, however, have promoted the use of model-based approaches to phylogenetic inference for discrete morphological data as well. These papers simulated data under models already known to be unfavourable to parsimony, and modelled morphological evolution as if it evolved just like DNA, with probabilities of change for all characters changing in concert along tree branches. The present paper discusses these issues, showing that under reasonable and less restrictive models of evolution for discrete characters, equally weighted parsimony performs as well or better than model-based methods, and that parsimony under implied weights clearly outperforms all other methods.
Author	Torres, Ambrosio Goloboff, Pablo A. Arias, J. Salvador
Author_xml	– sequence: 1 givenname: Pablo A. surname: Goloboff fullname: Goloboff, Pablo A. email: pablogolo@yahoo.com.ar organization: CONICET – sequence: 2 givenname: Ambrosio surname: Torres fullname: Torres, Ambrosio organization: CONICET – sequence: 3 givenname: J. Salvador surname: Arias fullname: Arias, J. Salvador organization: CONICET
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ContentType	Journal Article
Copyright	The Willi Hennig Society 2017 2018 The Willi Hennig Society The Willi Hennig Society 2017.
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SubjectTerms	Bayesian analysis Branches DNA Evolution Mathematical models Morphology Nucleotide sequence nucleotide sequences Phylogenetics Phylogeny Sampling techniques Statistical analysis statistical models
Title	Weighted parsimony outperforms other methods of phylogenetic inference under models appropriate for morphology
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