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Quantitative three-dimensional morphological analysis supports species discrimination in complex-shaped and taxonomically challenging corals
Ramirez-Portilla, C.; Bieger, I.M.; Belleman, R.G.; Wilke, T.; Flot, J.-F.; Baird, A.H.; Harii, S.; Sinniger, F.; Kaandorp, J.A. (2022). Quantitative three-dimensional morphological analysis supports species discrimination in complex-shaped and taxonomically challenging corals. Front. Mar. Sci. 9: 955582.
In: Frontiers in Marine Science. Frontiers Media: Lausanne. e-ISSN 2296-7745, more
Peer reviewed article  

Available in  Authors 

Author keywords
    species delimitation; quantitative morphology; phenotypic variation; 3D scanning; skeletonization algorithms; feature selection; surface curvature

Authors  Top 
  • Ramirez-Portilla, C., more
  • Bieger, I.M.
  • Belleman, R.G.
  • Wilke, T.
  • Flot, J.-F., more
  • Baird, A.H.
  • Harii, S.
  • Sinniger, F.
  • Kaandorp, J.A.

    Morphological characters play an important role in species descriptions and are essential for a better understanding of the function, evolution and plasticity of an organism’s shape. However, in complex-shaped organisms lacking characteristic features that can be used as landmarks, quantifying morphological traits, assessing their intra- and interspecific variation, and subsequently delineating phenotypically distinct groups continue to be problematic. For such organisms, three-dimensional morphological analysis might be a promising approach to differentiate morphogroups and potentially aid the delineation of species boundaries, though identifying informative features remains a challenge. Here, we assessed the potential of 3D-based quantitative morphology to delineate a priori and/or to discriminate a posteriori morphogroups of complex-shaped and taxonomically challenging organisms, such as corals from the morphologically diverse genus Acropora. Using three closely related coral taxa previously delimited using other lines of evidence, we extracted a set of variables derived from triangulated polygon meshes and medial axis skeletons of the 3D models. From the resulting data set, univariate and multivariate analyses of 3D-based variables quantifying overall shape including curvature, branching, and complexity were conducted. Finally, informative feature selection was performed to assess the discriminative power of the selected variables. Results revealed significant interspecific differences in the means of a set of 3D-based variables, highlighting potentially informative characters that provide sufficient resolution to discriminate morphogroups congruent with independent species identification based on other lines of evidence. A combination of representative features, remarkably represented by curvature, yielded measures that assisted in differentiating closely related species despite the overall morphospaces overlap. This study shows that a well-justified combination of 3D-based variables can aid species discrimination in complex-shaped organisms such as corals and that feature screening and selection is useful for achieving sufficient resolution to validate species boundaries. Yet, the significant discriminative power displayed by curvature-related variables and their potential link to functional significance need to be explored further. Integrating informative morphological features with other independent lines of evidence appears therefore a promising way to advance not only taxonomy but also our understanding of morphological variation in complex-shaped organisms.

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