## 2 Materials and Methods
### Methodology  
#### 2.2.1 Geometric Morphometrics  
The GM tool kit was used to characterize and analyze the carnivore tooth scores on the basis of the extracted cross-sections. GM is a method based on the use of landmarks (homologous points across specimens) that contain morphological information in the form of Cartesian coordinates [31; 32; 33; 34] and that enable the study of shape and form (shape and size) variance and co-variance [35; 36; 37]. While shape can be studied after standardization procedures that remove the effects in the orientation, location, and size of the elements under study, form requires the omission of the scaling step, so that size (or centroid size as it is commonly known in GM) can be considered alongside shape. In addition to landmarks, semilandmarks have been introduced in GM studies to register areas that lack clear homologous points [32; 38], long curves, or surfaces. The use of semilandmarks has thus allowed the detailed quantification of 2D and 3D geometries. In order to be able to combine semilandmarks with fixed landmarks, semilandmarks need to be transformed into homologous points through the application of sliding algorithms [39] by ensuring the correspondence of the semilandmarks and the avoidance of arbitrary location. The process of sliding semilandmarks aims to minimize shape differences between each slid specimen (targets) and the template (usually a mean shape) through the repetitive sliding of all the semilandmarks at the same time. The application of this technique based on the Thin-Plate-Spline (TPS) formalism accounts for local shape deformation using a mathematical model that interpolates the space found between two sets of homologous landmarks as smoothly as possible [38]. Landmarking procedures were performed using an automated procedure programmed in the R programming language [40; 41], while sliding was performed using functions from the _geomorph_ R library [42]. First, 7 2D fixed landmarks were collected for each score cross-section following the guidelines established in [PERSON] et al. [30] and [PERSON] et al. [19] (Figure 1). Additionally, we tested the use of semilandmarks to characterize score cross-sections at 50% of the total length and at the most conspicuous U-shaped score profile by generating different models (Figure 1) that included; 10 (Figure 1b), 25 (Figure 1c), and 50 (Figure 1d) 2D semilandmarks slid along a single curve; and 10 (Figure 1e), 20 (Figure 1f), and 30 (Figure 1g) semilandmarks slid along 2 curves defined by the lateral limits on the score cross-section and its deepest point, meaning the latter models include three additional fixed landmarks. Landmarking was performed by two authors ([PERSON] and [PERSON]) in different sessions and interchanging the carnivore groups. This allowed the analysis of inter and intra-observer error, as in previous studies [20; 22], by assessing the significance of the differences observed between the landmark configurations obtained from the same dataset, using multivariate analyses of variance (MANOVAs). The confirmation of the method replicability, based on the obtention of non-significant differences (\(p>0.05\)) between the carnivore group means (e.g., the lion sample landmarked by [PERSON] versus the lion sample landmarked by [PERSON]), opened the way for the performance of the present study. The analysis of landmark configurations requires the use of a previous standardization method, such as general Procrustes analysis (GPA), a technique that normalizes the morphological information by translating, rotating, and scaling the landmark configurations. This step is usually followed by dimensionality reduction techniques such as the one provided by principal component analyses (PCA), which also enables the observation of the sample variance distribution space and the visualization of the changes in shape and form (excluding the scaling process) with the aid of transformation grids, which minimize the bending between specimens to express changes in the relative position of points along the outline [43].