“…We then calculated a body condition index by applying a principal component analysis (PCA) to length, height, and weight (as e.g., in Fusani, Cardinale, Carere, & Goymann, and Kocovsky, Sullivan, Knight, & Stepien, ), which was then used for further analyses (Section ). PCA is a multivariate statistical approach that reduces the dimensionality of the dataset by replacing multiple inter‐related original variables with a few, new uncorrelated component variables called “factors.” In our case, it served to reduce multiple testing to a single variable, instead of three (for a detailed description see Giuliani et al., ; Giuliani, Zbilut, Conti, Manetti, & Miccheli, ; Carere et al., ; Mojekwu & Anumudu, ). The morphometric characteristics of the three sampling groups are shown in Table , together with those of the three groups as pooled; PCA results are shown in Table .…”