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

Title
Building phenotypic character matrices for phylogenetic inference: exploration of 35 years of practice
Publication Date
2026-10
Author(s)
Hopkins, Melanie J
Nikolic, Mark C
Holmes, James D
( author )
OrcID: https://orcid.org/0000-0001-8804-2149
Email: jholme28@une.edu.au
UNE Id une-id:jholme28
Monti, Daniela S
Vargas‐Parra, Ernesto E
Bicknell, Russell D C
( author )
OrcID: https://orcid.org/0000-0001-8541-9035
Email: rbickne2@une.edu.au
UNE Id une-id:rbickne2
Edgecombe, Gregory D
Jordan‐Burmeister, Katherine
Paterson, John R
( author )
OrcID: https://orcid.org/0000-0003-2947-3912
Email: jpater20@une.edu.au
UNE Id une-id:jpater20
Srivastava‐Losey, Shravya
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
Wiley-Blackwell Publishing Ltd
Place of publication
United Kingdom
DOI
10.1002/brv.70183
UNE publication id
une:1959.11/74888
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.

Link
Citation
Biological Reviews, 101(5), p. 2379-2407
ISSN
1469-185X
1464-7931
Start page
2379
End page
2407
Rights
Attribution-NonCommercial 4.0 International

Files:

NameSizeformatDescriptionLink