The structure of species discrimination signals across a primate radiation

Abstract

Discriminating between conspecifics and heterospecifics potentially challenging for closely related sympatric species. The guenons, a recent primate radiation, exhibit high degrees of sympatry and form multi-species groups in which hybridization is possible but rare in most populations. Guenons have species-specific colorful face patterns hypothesized to function in species discrimination. Here, we apply a novel machine learning approach to identify the face regions most essential for correct species classification across fifteen guenon species. We then demonstrate the validity of these computational results using experiments with live guenons, showing that facial traits identified as critical for accurate classification do indeed influence selective attention toward con- and heterospecific faces. Our results suggest variability among guenon species in reliance on single-trait-based versus holistic facial characteristics when discriminating between species, and differences in behavioral responses to faces can be linked to whether discrimination is based on a single trait or whole-face pattern. Our study supports the hypothesis that guenon face patterns function to promote species discrimination and provides novel insights into the relationship between species interactions and phenotypic diversity.