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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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WHERE’S YOUR HEAD AT: EXPLORATION AND EVALUATION OF EURYPTERID MORPHOSPACE
Natural History collections contain primary data spanning the history of life on Earth. Much of these data remain understudied and therefore has not been integrated into our current understanding of paleontology. One such collection is the eurypterid collection at the University of Michigan Museum of Paleontology (UMMP). Last summer this material was digitized and preliminary morphometrics work was conducted. Here, we leverage the work we completed to include material from other previously published studies on eurypterid morphometrics. Specifically, we are interested in evaluating landmark placement between studies and comparing results of the two studies separately and combined. 130 specimens from the UMMP possess intact prosoma and were landmarked in the StereoMorph package in R. Four fixed landmarks and two sets of sliding landmarks along curves of the prosoma were employed. The data were analyzed using a Principal Components Analysis(PCA) and results were visualized in R using ggplot2. Previous work utilized more landmarks, which were unobtainable with the UMMP dataset. So for a viable comparison, approximately 115 specimens (those used in Bicknell and Amati 2021) from the New York State Museum and Yale Peabody were landmarked using our smaller landmark set. This allows us to examine the efficacy of different amounts and types of landmarks (fixed versus curves) and the resulting distribution in morphospace. The resulting morphospace shows a broad occupation of the genus Eurypterus, which supports previous studies. Additionally, there is a difference in distance between groups in the combined morphospace compared to previous work. This is likely due to the variation in landmarks used to capture specific aspects of the prosoma. This case study in landmark variation provides evidence that landmark selection, research question, and reproducibility should be carefully considered. Furthermore, targeted digitization of museum collections will increase mobilization of primary datasets.
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- Award ID(s):
- 1943082
- PAR ID:
- 10503832
- Publisher / Repository:
- Geological Society of America Abstracts with Programs
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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