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Dissection, MicroCT Scanning and Morphometric Analyses of the Baculum

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Published on: March 19, 2017

Assessing the application of landmark-free morphometrics to macroevolutionary analyses.

James M Mulqueeney^1,2, Thomas H G Ezard³, Anjali Goswami⁴

¹School for Ocean & Earth Science, National Oceanography Centre Southampton, University of Southampton Waterfront Campus, Southampton, UK. j.m.mulqueeney@soton.ac.uk.

BMC Ecology and Evolution

|April 27, 2025

Summary

Automated, landmark-free shape analysis shows promise for large-scale evolutionary studies. While efficient, these methods require further refinement for broad adoption across diverse taxa.

Keywords:

Geometric morphometrics Landmark-free morphometrics Macroevolution Mammalia Morphometrics Shape

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Area of Science:

Evolutionary biology
Morphometrics
Computational anatomy

Background:

3D geometric morphometrics revolutionized phenotypic evolution studies.
Manual landmarking is time-consuming, operator-dependent, and limits cross-taxa comparisons.
Automated, landmark-free methods offer potential but are underexplored for macroevolutionary analyses.

Purpose of the Study:

To evaluate automated, landmark-free approaches for macroevolutionary analyses.
To compare Deterministic Atlas Analysis (DAA) with high-density geometric morphometrics.
To assess the utility of these methods across diverse mammalian taxa.

Main Methods:

Applied Large Deformation Diffeomorphic Metric Mapping (LDDMM) via DAA.
Utilized a dataset of 322 mammals from 180 families.
Standardized mixed-modality scan data (CT and surface scans) using Poisson surface reconstruction.

Main Results:

Standardization improved DAA-manual landmarking correspondence, though differences persisted for specific taxa (Primates, Cetacea).
Both DAA and manual methods yielded comparable, yet varying, estimates for phylogenetic signal, morphological disparity, and evolutionary rates.
DAA demonstrated potential for large-scale, cross-taxa studies due to enhanced efficiency.

Conclusions:

Landmark-free methods like DAA offer efficiency gains for macroevolutionary morphometrics.
Challenges remain, particularly regarding accuracy across morphologically disparate taxa.
Further research and methodological improvements are needed for widespread adoption of landmark-free analyses.