This interdisciplinary project combines comparative analyses of face guenon faces with techniques from computer vision, cognitive psychology, and behavioral ecology to understand the evolution of guenon face morphology. Our comparative analyses have demonstrated evidence for character displacement in guenon face patterns – guenon faces have evolved to be specifically distinctive from those species they are sympatric with. Our new studies include: computational reconstructions of phylogeographic scenarios for the evolution of guenons and the role of face patterns in either the initial speciation or maintenance of the tribe; machine learning algorithms and other methods developed in computer vision research to quantify variation in face patterns, and identify face regions of high information content; experiments in which guenon face images are presented as stimulus pairs to captive guenons to monitor their responses to determine how signal content influences guenon visual biases and mating decisions; behavioral studies of inter-specific interactions between sympatric guenon species in the wild.

 

Example of guenon facial variation
(Credit: James Higham)