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Diversification of animal vocalizations plays a key role in behavioral evolution and speciation. Vocal organ morphology represents an important source of acoustic variation, yet its small size, complex shape, and absence of homologous landmarks pose major challenges to comparative analyses. Here, we use a geometric morphometric approach based on geometrically homologous landmarks to quantify shape variation of laryngeal cartilages of four rodent genera representing three families. Reconstructed cartilages of the larynx from contrast-enhanced micro-CT images were quantified by variable numbers of three-dimensional landmarks placed on structural margins and major surfaces. Landmark sets were superimposed using generalized Procrustes analysis prior to statistical analysis. Correlations among pairwise Procrustes distances were used to identify the minimum number of landmarks necessary to fully characterize shape variation. We found that the five species occupy distinct positions in morphospace, with variation explained in part by phylogeny, body size, and differences in vocal production mechanisms. Our findings provide a foundation for quantifying the contribution of vocal organ morphology to acoustic diversification.
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High-Density Morphometric Analysis of Shape and Integration: The Good, the Bad, and the Not-Really-a-Problem
Abstract The field of comparative morphology has entered a new phase with the rapid generation of high-resolution three-dimensional (3D) data. With freely available 3D data of thousands of species, methods for quantifying morphology that harness this rich phenotypic information are quickly emerging. Among these techniques, high-density geometric morphometric approaches provide a powerful and versatile framework to robustly characterize shape and phenotypic integration, the covariances among morphological traits. These methods are particularly useful for analyses of complex structures and across disparate taxa, which may share few landmarks of unambiguous homology. However, high-density geometric morphometrics also brings challenges, for example, with statistical, but not biological, covariances imposed by placement and sliding of semilandmarks and registration methods such as Procrustes superimposition. Here, we present simulations and case studies of high-density datasets for squamates, birds, and caecilians that exemplify the promise and challenges of high-dimensional analyses of phenotypic integration and modularity. We assess: (1) the relative merits of “big” high-density geometric morphometrics data over traditional shape data; (2) the impact of Procrustes superimposition on analyses of integration and modularity; and (3) differences in patterns of integration between analyses using high-density geometric morphometrics and those using discrete landmarks. We demonstrate that for many skull regions, 20–30 landmarks and/or semilandmarks are needed to accurately characterize their shape variation, and landmark-only analyses do a particularly poor job of capturing shape variation in vault and rostrum bones. Procrustes superimposition can mask modularity, especially when landmarks covary in parallel directions, but this effect decreases with more biologically complex covariance patterns. The directional effect of landmark variation on the position of the centroid affects recovery of covariance patterns more than landmark number does. Landmark-only and landmark-plus-sliding-semilandmark analyses of integration are generally congruent in overall pattern of integration, but landmark-only analyses tend to show higher integration between adjacent bones, especially when landmarks placed on the sutures between bones introduces a boundary bias. Allometry may be a stronger influence on patterns of integration in landmark-only analyses, which show stronger integration prior to removal of allometric effects compared to analyses including semilandmarks. High-density geometric morphometrics has its challenges and drawbacks, but our analyses of simulated and empirical datasets demonstrate that these potential issues are unlikely to obscure genuine biological signal. Rather, high-density geometric morphometric data exceed traditional landmark-based methods in characterization of morphology and allow more nuanced comparisons across disparate taxa. Combined with the rapid increases in 3D data availability, high-density morphometric approaches have immense potential to propel a new class of studies of comparative morphology and phenotypic integration.
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- Award ID(s):
- 1839250
- PAR ID:
- 10170993
- Date Published:
- Journal Name:
- Integrative and Comparative Biology
- Volume:
- 59
- Issue:
- 3
- ISSN:
- 1540-7063
- Page Range / eLocation ID:
- 669 to 683
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1093/icb/icz120
