Adaptive landscapes have served as fruitful guides to evolutionary research for nearly a century. Current methods guided by landscape frameworks mostly utilize evolutionary modelling (for example, fitting data to Ornstein-Uhlenbeck models) to make inferences about adaptive peaks. Recent alternative methods utilize known relationships between phenotypes and functional performance to derive information about adaptive landscapes; this information can then help explain the distribution of species in phenotypic space and help infer the relative importance of various functions for guiding diversification. Here, data on performance for three turtle shell functions – strength, hydrodynamic efficiency, and self-righting ability – are used to develop a set of predicted performance optima in shell shape space. The distribution of performance optima shows significant similarity to the distribution of existing turtle species and helps explain the absence of shells in otherwise anomalously-empty regions of morphospace. The method outperforms modelling-based approaches in inferring the location of reasonable adaptive peaks and in explaining the shape of the phenotypic distributions of turtle shells. Performance surface-based methods allow researchers to more directly connect functional performance with macroevolutionary diversification, and to explain the distribution of species (including presences and absences) across phenotypic space.
Supplementary File 1 - Phylogeny
Supplementary File 1 – Phylogeny used for evolutionary analyses; taken from Stayton et al. 2018.
Stayton2018_SupplementaryFile01.nexus
Supplementary File 2 - Full-shell morphospace
Supplementary File 2 – Morphospace plot of all hard-shelled species utilized in this study, calculated from full shell data generated by reflecting all non-midsagittal landmarks across the midsagittal plane. Data are color-coded by Family. Wireframe images outside of the corners of plots indicate shapes associated with those regions of morphospace (e.g., images outside the upper right corner indicate shapes associated with high PC1 and PC2 scores). The matrix correlation between species’ scores on the first two PCs of the half-shell analysis and species’ scores on the first two PCs of the whole-shell analysis was 0.926. The matrix correlation between Procrustes distance matrices for the half-shell and whole-shell analyses (with distances in each matrix calculated between species) was 0.982.
Stayton2018_SupplementaryFile02.pdf
Supplementary File 3 - Phylogenetic MANOVA results on shape-ecology relationships
Supplementary File 3 – Results of phylogenetic MANOVAs on increasingly-restricted sets of the first 12 PC axes for turtle shell shape, with species grouped by ecology.
Stayton2018_SupplementaryFile03.docx
Supplementary File 4 – Phylogenetic ANOVA results on shape-ecology relationships
Supplementary File 4 – Results of phylogenetic ANOVAs on each of the first 12 PC axes for turtle shell shape, with species grouped by ecology.
Stayton2018_SupplementaryFile04.docx
Supplementary File 5 – Phylogenetic discriminant function results for ecology
Supplementary File 5 – Loadings for each of the first 12 PCs in the equation produced by a phylogenetic discriminant function analysis to differentiate aquatic and terrestrial species.
Stayton2018_SupplementaryFile05.docx
Supplementary File 6 – Base finite element model
Supplementary File 6 – Glyptemys muhlenbergii finite element model used as a base for transformations and mechanical strength assessment, in Strand7 (Strand7 2007) text format.
Stayton2018_SupplementaryFile06.txt
Supplementary File 7 – All loading schemes used in mechanical analyses
Supplementary File 7 – Locations of all loads (“x” symbols) and restraints (“+” symbols) used in finite element analyses illustrated on the base Glyptemys muhlenbergii model in dorsal (top) and ventral (bottom) views.
Stayton2018_SupplementaryFile07.pdf
Supplementary File 8 – Closed surface used as a base for hydrodynamics testing
Supplementary File 8 – Closed Glyptemys muhlenbergii model used as a base for transformations and analyses of drag, in .stl format.
Stayton2018_SupplementaryFile08.stl
Supplementary File 9 – All drag measurements
Supplementary File 9 – Drag coefficient measurements and locations along shape PC axes 1 and 2 of 20 3D printed models used to assess hydrodynamic performance.
Stayton2018_SupplementaryFile09.xlsx
Supplementary File 10 – Performance data used to build performance surfaces
Supplementary File 10 – All performance data for shell strength (average maximum von Mises stress assessed across 12 load cases), hydrodynamics (interpolated drag coefficient) and self-righting (F-index) for all combinations of 17 PC1 and 15 PC2 scores evenly distributed across turtle shell shape space.
Stayton2018_SupplementaryFile10.xlsx