A likelihood approach to estimating phylogeny from discrete morphological character data
Abstract
Evolutionary biologists have adopted simple likelihood models for purposes of estimating ancestral states and evaluating character independence on specified phylogenies; however, for purposes of estimating phylogenies by using discrete morphological data, maximum parsimony remains the only option. This paper explores the possibility of using standard, well-behaved Markov models for estimating morphological phylogenies (including branch lengths) under the likelihood criterion. An important modification of standard Markov models involves making the likelihood conditional on characters being variable, because constant characters are absent in morphological data sets. Without this modification, branch lengths are often overestimated, resulting in potentially serious biases in tree topology selection. Several new avenues of research are opened by an explicitly model-based approach to phylogenetic analysis of discrete morphological data, including combined-data likelihood analyses (morphology + sequence data), likelihood ratio tests, and Bayesian analyses.
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Singular and unreplicated evolutionary events are incompatible with models typically used to describe change over time, such as Brownian motion or the Mk model.
“Their singular and unreplicated nature seems incompatible with models that we typically use to describe change over time, such as Brownian motion (BM; Felsenstein 1973) or the Mk model (Pagel 1994;Lewis 2001).”
From Rethinking phylogenetic comparative methods (2018) · cites this paper as Lewis 2001
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- Authors
- Lewis, P. O.
- Affiliations
- University of Connecticut (US)
- Corresponding author
- Lewis, Paul O.
- ORCID
- Lewis, Paul O.
- Venue
- Systematic Biology
- Publisher
- Oxford University Press (OUP)
- Published
- 2001-11-01
- Volume
- 50
- Issue
- 6
- Pages
- 913-925
- ISSN
- 1063-5157 (ISSN-L)
- 1076-836X
- OpenAlex
- W2122082385
- Cited by
- 2,929
- References
- 2
- Citations by year
- 2026: 167 · 2025: 216 · 2024: 180 · 2023: 173 · 2022: 153 · 2021: 196 · 2020: 228 · 2019: 172 · 2018: 177 · 2017: 141 · 2016: 116 · 2015: 119 · 2014: 140 · 2013: 100 · 2012: 95
- FWCI
- 6.42
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Systematic Biology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Smithsonian Institution
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Earth and Planetary Sciences › Paleontology › Evolution and Paleontology Studies
- Life Sciences › Agricultural and Biological Sciences › Ecology, Evolution, Behavior and Systematics › Plant Diversity and Evolution
- Keywords
- morphological phylogeny, Markov model, likelihood estimation, branch length estimation, likelihood ratio test, Bayesian phylogenetics
- MeSH terms
- Biometry, Markov Chains, Models, Genetic, Phylogeny, Likelihood Functions
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