An exploration of character traits and linear measurements for sexing mountain gazelle (Gazella gazella) skeletons

The skeletal elements of mountain gazelle (Gazella gazella) have proven difficult to sex with statistical confidence due to wide overlap in the body size of the two sexes. We studied a sample of 53 modern mountain gazelle skeletons to determine which character traits and metric measurements best predict sex. The success of the character traits was determined using blind tests while the metrics were examined using discriminant function analysis. The most useful elements include the previously identified horn core, pubis and atlas, but also some new bone portions that preserve well in the archaeological record (e.g., distal tibia, distal metacarpal and metatarsal, and second phalanx). Surprisingly, two elements commonly used in sexing analyses (distal humerus and astragalus) were not among the most effective elements. Although cutting points and discriminant functions for sexing gazelle bone portions are presented here, they do not account for potential body size change and thus are not suited for direct application to archaeological assemblages. Instead, we provide guidelines for application to archaeological gazelle assemblages, most importantly a regression analysis that considers the sex ratios obtained from multiple measurements to predict the sex ratio of archaeological gazelle populations.     

Three statistical methods for sex determination in extant and fossil caprines: assessment of the Rupicapra long bones

Sex determination of fossil remains in archeopaleontological contexts is a necessary step in order to gain insights in archaeological and paleobiological parameters such as prey selection and sexual dimorphism. Species with higher sexual dimorphism are more reliably sexed while the sex determination of less dimorphic animals is not attempted. In this study, we compared the accuracy of three different methods in the sex determination of a modern known-sex sample of chamois (Rupicapra pyrenaica parva) from the Cantabrian range (Northern Iberian Peninsula), which is a small-sized ungulate with low sexual dimorphism when compared to other animals in which sex determination has been attempted (i.e., Ursus spelaeus, Capra pyrenaica). The three methods applied were mixture analysis (MA), cluster analysis (CA) and principal component analysis (PCA). Within CA we applied three different analysis: one agglomerative hierarchical method (AH) and two optimal partitioning methods (k-means and robust k-means); and within PCA we applied normal and robust variants of the analysis.