The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Assessing Trait Covariation and Morphological Integration on Phylogenies Using Evolutionary Covariance Matrices
Open accessAbstract
Morphological integration describes the degree to which sets of organismal traits covary with one another. Morphological covariation may be evaluated at various levels of biological organization, but when characterizing such patterns across species at the macroevolutionary level, phylogeny must be taken into account. We outline an analytical procedure based on the evolutionary covariance matrix that allows species-level patterns of morphological integration among structures defined by sets of traits to be evaluated while accounting for the phylogenetic relationships among taxa, providing a flexible and robust complement to related phylogenetic independent contrasts based approaches. Using computer simulations under a Brownian motion model we show that statistical tests based on the approach display appropriate Type I error rates and high statistical power for detecting known levels of integration, and these trends remain consistent for simulations using different numbers of species, and for simulations that differ in the number of trait dimensions. Thus, our procedure provides a useful means of testing hypotheses of morphological integration in a phylogenetic context. We illustrate the utility of this approach by evaluating evolutionary patterns of morphological integration in head shape for a lineage of Plethodon salamanders, and find significant integration between cranial shape and mandible shape. Finally, computer code written in R for implementing the procedure is provided.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Phylogenies and the Comparative Method
Felsenstein, J. (1985) · The American Naturalist · doi:10.1086/284325 · Cited by 9,793
The Comparative Method in Evolutionary Biology
Harvey, P. H., & Pagel, M. D. (1991) · doi:10.1093/oso/9780198546412.001.0001 · Cited by 4,337
Extensions of the procrustes method for the optimal superimposition of landmarks
Rohlf, F. J., & Slice, D. (1990) · Systematic Zoology · doi:10.2307/2992207 · Cited by 4,289
Stabilizing selection and the comparative analysis of adaptation
Hansen, T. F. (1997) · Evolution · doi:10.1111/j.1558-5646.1997.tb01457.x · Cited by 1,361
Adams, D. C. (2014) · Systematic Biology · doi:10.1093/sysbio/syu030 · Cited by 653
Self-citationThe evolutionary role of modularity and integration in the Hominoid cranium
Mitteroecker, P., & Bookstein, F. (2008) · Evolution · doi:10.1111/j.1558-5646.2008.00321.x · Cited by 267
Adams, D. C. (2014) · Systematic Biology · doi:10.1093/sysbio/syt105 · Cited by 207
Self-citationCranial integration and modularity: insights into evolution and development from morphometric data
(2013) · Bollettino del CILEA (CILEA) · doi:10.4404/hystrix-24.1-6367 · Cited by 199
Cited by
The ancestral flower of angiosperms and its early diversification
Sauquet, H., von Balthazar, M., Magallón, S., Doyle, J. A., Endress, P. K., Bailes, E. J., Barroso de Morais, E., Bull-Hereñu, K., Carrive, L., Chartier, M., et al. (2017) · Nature Communications · doi:10.1038/ncomms16047 · Cited by 336
Adams, D. C. (2014) · Evolution · doi:10.1111/evo.12463 · Cited by 286
Self-citationAdams, D. C. (2016) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.12511 · Cited by 257
Self-citationGoswami, A., & Finarelli, J. A. (2016) · Evolution · doi:10.1111/evo.12956 · Cited by 99
Morphological consequences of artificial cranial deformation: Modularity and integration
Püschel, T. A., Friess, M., & Manríquez, G. (2020) · PLOS ONE · doi:10.1371/journal.pone.0227362 · Cited by 22
Metadata
- Authors
- Adams, D. C., & Felice, R. N.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2014-04-11
- Volume
- 9
- Issue
- 4
- Pages
- e94335
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W2172186016
- Cited by
- 211
- References
- 8
- FWCI
- 22.08
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Assessing Trait Covariation and Morphological Integration on Phylogenies Using Evolutionary Covariance Matrices. https://app.cochat.ai/papers/10.1371/journal.pone.0094335
- The paper
- Adams, D. C., & Felice, R. N. (2014). Assessing Trait Covariation and Morphological Integration on Phylogenies Using Evolutionary Covariance Matrices. PLoS ONE. https://doi.org/10.1371/journal.pone.0094335
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.