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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ALPACA: A fast and accurate computer vision approach for automated landmarking of three‐dimensional biological structures
Landmark‐based geometric morphometrics has emerged as an essential discipline for the quantitative analysis of size and shape in ecology and evolution. With the ever‐increasing density of digitized landmarks, the possible development of a fully automated method of landmark placement has attracted considerable attention. Despite the recent progress in image registration techniques, which could provide a pathway to automation, three‐dimensional (3D) morphometric data are still mainly gathered by trained experts. For the most part, the large infrastructure requirements necessary to perform image‐based registration, together with its system specificity and its overall speed, have prevented its wide dissemination. Here, we propose and implement a general and lightweight point cloud‐based approach to automatically collect high‐dimensional landmark data in 3D surfaces (Automated Landmarking through Point cloud Alignment and Correspondence Analysis). Our framework possesses several advantages compared with image‐based approaches. First, it presents comparable landmarking accuracy, despite relying on a single, random reference specimen and much sparser sampling of the structure's surface. Second, it can be efficiently run on consumer‐grade personal computers. Finally, it is general and can be applied at the intraspecific level to any biological structure of interest, regardless of whether anatomical atlases are available. Our validation procedures indicate that the method can recover intraspecific patterns of morphological variation that are largely comparable to those obtained by manual digitization, indicating that the use of an automated landmarking approach should not result in different conclusions regarding the nature of multivariate patterns of morphological variation. The proposed point cloud‐based approach has the potential to increase the scale and reproducibility of morphometrics research. To allow ALPACA to be used out‐of‐the‐box by users with no prior programming experience, we implemented it as a SlicerMorph module. SlicerMorph is an extension that enables geometric morphometrics data collection and 3D specimen analysis within the open‐source 3D Slicer biomedical visualization ecosystem. We expect that convenient access to this platform will make ALPACA broadly applicable within ecology and evolution.
- Award ID(s):
- 1759883
- NSF-PAR ID:
- 10448422
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Methods in Ecology and Evolution
- Volume:
- 12
- Issue:
- 11
- ISSN:
- 2041-210X
- Page Range / eLocation ID:
- p. 2129-2144
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Synopsis Urbanization, despite its destructive effects on natural habitats, offers species an opportunity to colonize novel niches. Previous research found that urban Anolis lizards in Puerto Rico had increased adhesive toepad area and more ventral toepad scales, traits that are likely adaptive and genetically based. We further investigated these phenotypic changes using geometric morphometrics to measure differences in toe shape, toepad shape, and lamellar morphology. Our results indicate that the increased toepad area of urban Anolis cristatellus lizards in Puerto Rico is not simply an isometric increase in toe size. Toes of urban populations exhibit multiple disproportional changes compared to forest lizards, with a larger proportion of the toe length covered in adhesive toepad. In addition, the toepads of urban lizards increase more in length than width. Lastly, lizards in urban populations exhibit both increased number of lamellae as well as increased spacing between individual lamellae. We also observed regional variation, with urban specimens having significantly more disparity, suggesting similar processes of urban adaptation are likely happening in parallel across the island, yet with region-specific idiosyncrasies, possibly generating more variation in toepad morphology across urban specimens as compared to forest specimens. Considering the use of geometric morphometrics, we found that specimen preparation, specifically how flat and straight toes are during imaging, to be an important factor affecting our data, more so than specimen size or any other meaningful morphological variation. In addition, we found that landmark and semilandmark data can be used to directly estimate toepad area, offering the opportunity to streamline future studies. In conclusion, our results highlight the value of considering toepad morphology in more detail beyond adhesive pad area or number of lamellae. Geometric morphometrics tools may be employed to elucidate subtle differences in shape to better allow researchers to connect changes in morphology to ecology and adhesive performance.
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Background Comparative morphology fundamentally relies on the orientation and alignment of specimens. In the era of geometric morphometrics, point-based homologies are commonly deployed to register specimens and their landmarks in a shared coordinate system. However, the number of point-based homologies commonly diminishes with increasing phylogenetic breadth. These situations invite alternative, often conflicting, approaches to alignment. The bivalve shell (Mollusca: Bivalvia) exemplifies a homologous structure with few universally homologous points—only one can be identified across the Class, the shell ‘beak’. Here, we develop an axis-based framework, grounded in the homology of shell features, to orient shells for landmark-based, comparative morphology. Methods Using 3D scans of species that span the disparity of shell morphology across the Class, multiple modes of scaling, translation, and rotation were applied to test for differences in shell shape. Point-based homologies were used to define body axes, which were then standardized to facilitate specimen alignment via rotation. Resulting alignments were compared using pairwise distances between specimen shapes as defined by surface semilandmarks. Results Analysis of 45 possible alignment schemes finds general conformity among the shape differences of ‘typical’ equilateral shells, but the shape differences among atypical shells can change considerably, particularly those with distinctive modes of growth. Each alignment corresponds to a hypothesis about the ecological, developmental, or evolutionary basis of morphological differences, but we suggest orientation via the hinge line for many analyses of shell shape across the Class, a formalization of the most common approach to morphometrics of shell form. This axis-based approach to aligning specimens facilitates the comparison of approximately continuous differences in shape among phylogenetically broad and morphologically disparate samples, not only within bivalves but across many other clades.more » « less
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Abstract Large‐scale digitization projects such as
#ScanAllFishes andoVert are generating high‐resolution microCT scans of vertebrates by the thousands. Data from these projects are shared with the community using aggregate 3D specimen repositories like MorphoSource through various open licenses. We anticipate an explosion of quantitative research in organismal biology with the convergence of available data and the methodologies to analyse them.Though the data are available, the road from a series of images to analysis is fraught with challenges for most biologists. It involves tedious tasks of data format conversions, preserving spatial scale of the data accurately, 3D visualization and segmentations, and acquiring measurements and annotations. When scientists use commercial software with proprietary formats, a roadblock for data exchange, collaboration and reproducibility is erected that hurts the efforts of the scientific community to broaden participation in research.
We developed SlicerMorph as an extension of 3D Slicer, a biomedical visualization and analysis ecosystem with extensive visualization and segmentation capabilities built on proven python‐scriptable open‐source libraries such as Visualization Toolkit and Insight Toolkit. In addition to the core functionalities of Slicer, SlicerMorph provides users with modules to conveniently retrieve open‐access 3D models or import users own 3D volumes, to annotate 3D curve and patch‐based landmarks, generate landmark templates, conduct geometric morphometric analyses of 3D organismal form using both landmark‐driven and landmark‐free approaches, and create 3D animations from their results. We highlight how these individual modules can be tied together to establish complete workflow(s) from image sequence to morphospace. Our software development efforts were supplemented with short courses and workshops that cover the fundamentals of 3D imaging and morphometric analyses as it applies to study of organismal form and shape in evolutionary biology.
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Abstract Sensory systems perform fitness‐relevant functions, and specialized sensory structures allow organisms to accomplish challenging tasks. However, broad comparative analyses of sensory morphologies and their performance are lacking for diverse mammalian radiations.
Neotropical leaf‐nosed bats (Phyllostomidae) are one of the most ecologically diverse mammal groups; including a wide range of diets and foraging behaviours, and extreme morphological variation in external sensory structures used in echolocation (nose leaf and pinnae).
We coupled 3D geometric morphometrics and acoustic field recordings under a phylogenetic framework to investigate the mechanisms underlying the diversification of external sensory morphologies in phyllostomids, and explored the potential implications of sensory morphological diversity to functional outputs and dietary ecology.
We found that the nose leaf consists of two evolutionary modules—spear and horseshoe—suggesting that modularity enabled morphological and functional diversification of this structure.
We found a significant association between some aspects of nose leaf shape and maximum frequency and bandwidth of echolocation calls, but not between pinnae shape and echolocation call parameters. This may be explained by the use of multiple sensory modes across phyllostomids and plasticity of some echolocation call parameters.
Species with different diets significantly differed in nose leaf shape, specifically in spear breadth, presence of a midrib, and cupping and anterior rotation of the horseshoe. This may relate to different levels of prey type specificity within each diet. Pinnae shape significantly differed between species that consume non‐mobile, non‐evasive prey (broad rounded, cupped pinnae) and mobile, evasive prey (flattened pinnae with a sharp tapering apex). This may reflect the use of different sound cues to detect prey.
Our results give insight into the morphological evolution of external sensory structures in bats, and highlight new links between morphological diversity and ecology.
A free
Plain Language Summary can be found within the Supporting Information of this article.
