Evidence map›Paper›PMID 42157438›Full record

SynthesisBiological reviews of the Cambridge Philosophical Society2026

Building phenotypic character matrices for phylogenetic inference: exploration of 35 years of practice.

Melanie J Hopkins, Mark C Nikolic, James D Holmes, Daniela S Monti, Ernesto E Vargas-Parra, Russell D C Bicknell, Gregory D Edgecombe, Katherine Jordan-Burmeister, John R Paterson, Shravya Srivastava-Losey

Abstract readSystematic Review
In one paragraph

Synthesis in Biological reviews of the Cambridge Philosophical Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Melanie J HopkinsDivision of Paleontology (Invertebrates), American Museum of Natural History, Central Park West at 79th Street, New York, NY, 10024, USA.ORCID https://orcid.org/0000-0002-3580-2172
Mark C NikolicDivision of Paleontology (Invertebrates), American Museum of Natural History, Central Park West at 79th Street, New York, NY, 10024, USA.
James D HolmesDepartment of Earth Sciences, Palaeobiology, Uppsala University, Villavägen 16, Uppsala, 752 36, Sweden.ORCID https://orcid.org/0000-0001-8804-2149
Daniela S MontiInstituto de Ecología, Genética y Evolución de Buenos Aires, CONICET-UBA, Facultad de Ciencias Exactas y Naturales, UBA, Intendente Güiraldes 2160, Ciudad Universitaria, Buenos Aires, C1428EGA, Argentina.
Ernesto E Vargas-ParraDivision of Paleontology (Invertebrates), American Museum of Natural History, Central Park West at 79th Street, New York, NY, 10024, USA.ORCID https://orcid.org/0000-0002-4773-6811
Russell D C BicknellDivision of Paleontology (Invertebrates), American Museum of Natural History, Central Park West at 79th Street, New York, NY, 10024, USA.
Gregory D EdgecombeThe Natural History Museum, Cromwell Road, London, SW7 5BD, UK.
Katherine Jordan-BurmeisterDepartment of Earth, Environmental, and Planetary Sciences, University of Tennessee-Knoxville, Knoxville, TN, 37996, USA.
John R PatersonPalaeoscience Research Centre, School of Environmental and Rural Science, University of New England, Armidale, NSW, 2351, Australia.
Shravya Srivastava-LoseyDepartment of Earth and Planetary Sciences, University of California, Riverside, CA, 92521, USA.

Funding

National Science Foundation 1848145
6 · The paper itself

Abstract

Recent methodological development in phylogenetic inference has focused predominantly on molecular data. However, renewed interest in other data types, particularly morphological data, has followed from the increased recognition of the power of total evidence and tip-dating approaches, including fossil data, for inference of time-scaled trees and rates of evolution. However, attention has largely focused on the improvement of models of morphological evolution and other analytical tools with much less discussion about data acquisition itself. Here we review past and current practice for describing and collecting morphological data for phylogenetic inference. We present a systematic review of 164 phylogenetic analyses conducted over the last 35 years and focused on a diverse group of extinct arthropods: trilobites. Trends in increasing matrix size, data type, and coding strategy are evident. Where present, polymorphic characters have been predominantly derived from discretized continuous characters, although increasingly practitioners are utilizing alternative approaches for the treatment of quantitative characters. Not surprisingly, traditional indices that describe character consistency are highly correlated with matrix size but show surprising variation at different taxonomic scales. More recent attempts to describe data quality using information theory imply that characters can have high information content even if data are missing for many tips, providing support against the exclusion of characters because of missing data. In consideration of this, as well as advances in the study of developmental biology and variational complexity, we identify several avenues for increasing the quality and quantity of morphological data going forward.

Indexed as

ArthropodsPhenotypePhylogenyAnimalsBiological EvolutionFossilsBayesian analysisfossilsmorphologyparsimonytrilobites

Identifiers

PMID42157438
PMCPMC13542364

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.