Ambient occlusion and PCV (portion de ciel visible): A new dental topographic metric and proxy of morphological wear resistance.

Abstract

Recently, ambient occlusion, quantified through portion de ciel visible (PCV) was introduced as a method for quantifying dental morphological wear resistance and reconstructing diet in mammals. Despite being used to reconstruct diet and investigate the relationship between dental form and function, no rigorous analysis has investigated the correlation between PCV and diet. Using a sample of platyrrhine and prosimians M2s, we show average PCV was significantly different between most dietary groups. In prosimian, insectivores had the lowest PCV, followed by folivores, omnivores, frugivores, and finally hard-object feeders. In platyrrhines, omnivores had the lowest average PCV, followed by folivores, frugivores, and finally hard-object feeders. PCV was correlated to two topographic variables (Dirichlet normal energy, DNE, and relief index, RFI) but uncorrelated to three others (orientation patch count rotated, OPCR, tooth surface area, and tooth size). The OPCR values here differed greatly from previously published values using the same sample, showing how differences in data acquisition (i.e., using 2.5D vs. 3D surfaces) can lead to drastic differences in results. Compared to other popular topographic variables, PCV performed as well or better at predicting diet in these groups, and when combined with a metric for size, the percent of successful dietary classifications reached 90%. Further, using an ontogenetic series of hominin (Paranthropus robustus) M2s, we show that PCV correlates well with probability of wear, with PCV values being higher on the portions of the occlusal surface that experience more wear (e.g., cusps and crest tips, wear facets) than the portions of the tooth that experience less. This relationship is strongest once wear facets have begun to form on the occlusal surface. These results highlight the usefulness of PCV in quantifying morphological wear resistance and predicting diet in mammals.