Supplementary data for assessing the discriminative potential of 3D-based measures to aid species delimitation of Acropora corals

Data and scripts from the submitted manuscript: C. Ramírez-Portilla, I. Bieger, R. G. Belleman, T. Wilke, J.-F. Flot, A. H. Baird, S. Harii, F. Sinniger, J. A. Kaandorp (2022). Quantitative three-dimensional morphological analysis supports species discrimination in complex-shaped and taxonomically challenging corals. Frontiers in Marine Science.

All the information in this repository corresponds to the supplementary information for the manuscript. To see a detailed description per item, check the corresponding README file in each folder:

   3D-based_measures_estimation/
After 3D models were rendered and processed, meshes were then exported as triangulated mesh files (either .stl or .obj) for downstream analyses derived either from triangulated polygon meshes, medial axis skeleton graphs or a combination of both.

   Statistic_analyses_3D-based_measures/
To provide a quantitative assessment of the estimated morphological variables, both univariate values and distributions were analysed using R v4.1.0 (R Core Team, 2018) through the Rstudio console v1.4.1103 (RStudio Team, 2017). The three species previously delineated in this data set (Ramírez-Portilla et al., 2022), were used as a three-level factor for all the subsequent analyses.

Schematic representation | 3D model rendering and skeletonization from a coral specimen
Morphology of irregularly shaped organisms (from both living tissue and skeleton specimens) can be analysed using 3D scanning. Downstream processing renders three-dimensional models as either a triangulated polygon mesh or a medial axis skeleton from which variables such as curvature, branch length, width, spacing, and angle can be estimated.