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Updated: Jun 10, 2025
12:27
Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
Published on: February 15, 2017
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Do morphometric data improve phylogenetic reconstruction? A systematic review and assessment
Emma J Holvast1, Mélina A Celik2, Matthew J Phillips2
1School of Archaeology and Anthropology, The Australian National University, Canberra, Australia. Emma.Holvast@anu.edu.au.
BMC Ecology and Evolution
|October 18, 2024
Summary
Geometric morphometric (GMM) data can improve phylogenetic inference, but current research shows it does not increase phylogenetic accuracy. More studies are needed to compare continuous and discrete morphological data for better phylogenetic reconstruction.
Area of Science:
- Evolutionary Biology
- Systematic Biology
- Phylogenetics
Background:
- Morphological data are vital for phylogenetics and molecular dating, but subjective character definitions introduce bias.
- Quantitative data, such as geometric morphometric (GMM) data, offer a more objective approach to integrating morphology into phylogenetic inference.
- This systematic review examines the use of continuous morphometric data for phylogenetic reconstruction and compares its efficacy against discrete characters.
Conclusions:
- Only twelve empirical studies using continuous morphometric data for phylogenetics were identified.
- The lack of direct comparisons between discrete and continuous data hinders understanding of continuous data's performance.
- Researchers are urged to conduct studies comparing discrete and continuous datasets with directly comparable properties (shape or size) to address this knowledge gap.
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