Testing character evolution models in phylogenetic paleobiology: a case study with Cambrian echinoderms

Macroevolutionary inference has historically been treated as a two-step process, involving the inference of a tree, and then inference of a macroevolutionary model using that tree. Newer models blend the two steps. These methods make more complete use of fossils than the previous generation of Bayes...

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Bibliographic Details
Main Authors: Wright, April M. ca. 20./21. Jh (Author), Wagner, Peter J. 1964- (Author), Wright, David F. 1985- (Author)
Format: Electronic eBook
Language:English
Published: Cambridge Cambridge University Press 2021
Series:Cambridge elements
Subjects:
Links:https://doi.org/10.1017/9781009049016
https://doi.org/10.1017/9781009049016
https://doi.org/10.1017/9781009049016
Summary:Macroevolutionary inference has historically been treated as a two-step process, involving the inference of a tree, and then inference of a macroevolutionary model using that tree. Newer models blend the two steps. These methods make more complete use of fossils than the previous generation of Bayesian phylogenetic models. They also involve many more parameters than prior models, including parameters about which empiricists may have little intuition. In this Element, we set forth a framework for fitting complex, hierarchical models. The authors ultimately fit and use a joint tree and diversification model to estimate a dated phylogeny of the Cincta (Echinodermata), a morphologically distinct group of Cambrian echinoderms that lack the fivefold radial symmetry characteristic of extant members of the phylum. Although the phylogeny of cinctans remains poorly supported in places, this Element shows how models of character change and diversification contribute to understanding patterns of phylogenetic relatedness and testing macroevolutionary hypotheses
Item Description:Title from publisher's bibliographic system (viewed on 20 Jul 2021)
Physical Description:1 Online-Ressource (42 Seiten)
ISBN:9781009049016
DOI:10.1017/9781009049016

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