Dental topography of prosimian premolars predicts diet: A comparison in premolar and molar dietary classification accuracies.

OBJECTIVES: This study tests whether (1) premolar topography of extant "prosimians" (strepsirrhines and tarsiers) successfully predicts diet and (2) whether the combination of molar and premolar topography yields higher classification accuracy than using either tooth position in isolation. MATERIALS AND METHODS: Dental topographic metrics (ariaDNE, relief index, and orientation patch count rotated) were calculated for 118 individual matched-pairs of mandibular fourth premolars (P4) and second molars (M2). The sample represents 7 families and 22 genera. Tooth variables were analyzed in isolation (P4 only; M2 only), together (P4 and M2), and combined (PC1 scores of bivariate principal component analyses of P4 and M2 for each metric). Discriminant function analyses were conducted with and without a measure of size (two-dimensional surface area). RESULTS: When using topography only, "prosimian" P4 shape predicts diet with a success rate that is slightly higher than that of M2 shape. When absolute size is included, premolars and molars perform comparably well. Including both premolar and molar topography (separately or combined) improves classification accuracy for every analysis beyond considering either in isolation. Classification accuracy is highest when premolar and molar topography and size are included. DISCUSSION: Our findings indicate that molar teeth incompletely summarize the functional requirements of oral food breakdown for a given diet, and that the mechanism selecting for premolar form is more varied than what is expressed by molar teeth. Finally, our findings suggest that fossil P4s (in isolation or with the M2) can be used for meaningful dietary reconstruction of extinct primates.

Increasing the impact of vertebrate scientific collections through 3D imaging: The openVertebrate (oVert) Thematic Collections Network.

The impact of preserved museum specimens is transforming and increasing by three-dimensional (3D) imaging that creates high-fidelity online digital specimens. Through examples from the openVertebrate (oVert) Thematic Collections Network, we describe how we created a digitization community dedicated to the shared vision of making 3D data of specimens available and the impact of these data on a broad audience of scientists, students, teachers, artists, and more. High-fidelity digital 3D models allow people from multiple communities to simultaneously access and use scientific specimens. Based on our multiyear, multi-institution project, we identify significant technological and social hurdles that remain for fully realizing the potential impact of digital 3D specimens.