Topological Phenotypes Constitute a New Dimension in the Phenotypic Space of Leaf Venation Networks
Fig 2
a Plot of the whole dataset consisting of 186 leaf networks depending on the unweighted nesting number iu and mean topological length. One leaf of Protium grandifolium (Dalbergia miscolobium) is marked by a circle (triangle) with black border as well as shown in e (f). The smaller circles (triangles) in the same color show the two nearest neighbors according to the statistical distance DKS. The specimen belonging to the most abundant genera in the dataset are marked in order to assess predictive accuracy at a higher taxonomic level. The specimen belong to Protium (98 specimen), Bursera (21 specimen) and Parkia (8 specimen). b Weights of the 8 metrics, in the first two principal components of the dataset. Component 1 contains mostly geometry (σ, a, A, ρA, d), Component 2 mostly topology (Ltop, iu, iw), see also S1 Text. c Results of leaf identification from fragments using Linear Discriminant Analysis (LDA). Accuracy scores were obtained using 10-fold stratified cross-validation. The plot shows histograms of the resulting accuracy scores. Accuracy of identification is significantly improved when using both geometrical and topological information as opposed to only geometry. (Welch’s t(15.6) = 15.8, p < 0.001). d Summary results of pairwise leaf identification from fragments. All pairs of leaves were classified individually using LDA. Again, using topological traits significantly improves the summary result (see S1 Text). e, f Images of the same leaves as those specially marked in A and their nesting numbers iu, together with their nearest two neighbors 1, 2. All images except for f-1 show a 1cm × 1cm gray-scaled and contrast-enhanced crop of the original scan. Image f-1 was zoomed in by a factor of 2 to show the nesting structure more clearly.