The Late Miocene development of faunas and environments in western Eurasia is well known, but the climatic and environmental processes that controlled its details are incompletely understood. Here we map the rise and fall of the classic Pikermian fossil mammal chronofauna between 12 and 4.2 Ma, using genus-level faunal similarity between localities. To directly relate land mammal community evolution to environmental change, we use the hypsodonty paleoprecipitation proxy and paleoclimate modeling. fossil mammals ͉ paleoclimate ͉ Pikermi ͉ similarity index

More than half a century ago, Percy Butler (1963: 4) wrote that we "need to study the functions of teeth more thoroughly so as to be in a position to assess the adaptive significance of observed variations and their possible selective value". There have been many advances in the study of dental functional morphology since that time. Here we review the various approaches to characterizing and comparing occlusal form that have been developed, especially dental topographic analysis. We also report on a new study of dental topography of platyrrhine primates (n = 341 individuals representing 16 species) with known differences in both dietary preferences and other food items eaten. Results indicate frugivores, gummivores, folivores, and seed eaters each have a unique combination of slope, relief, angularity, sharpness, and occlusal patch size and count values. Likewise, among frugivores, those that supplement their diets with hard objects, insects, leaves, and seeds, also each have a distinctive suite of topographic features. We conclude that both primary and secondary diet choices select for occlusal form, and that functional morphology more reflects the types of foods and mechanical challenges they pose rather than the frequencies in which they are eaten.

TABLE S2. Individual Proboscidean molar specimens with mean mesowear angles and δ 13 C values. Genus Species Locality Country/State Age Specimen Tooth MW angle δ 13 C Elephas maximus India Recent AMNH 113572

Different diets wear teeth in different ways and generate distinguishable wear and microwear patterns that have long been the basis of palaeodiet reconstructions. Little experimental research has been performed to study them together. Here, we show that an artificial mechanical masticator, a chewing machine, occluding real horse teeth in continuous simulated chewing (of 100 000 chewing cycles) is capable of replicating microscopic wear features and gross wear on teeth that resemble wear in specimens collected from nature. Simulating pure attrition (chewing without food) and four plant material diets of different abrasives content (at n ¼ 5 tooth pairs per group), we detected differences in microscopic wear features by stereomicroscopy of the chewing surface in the number and quality of pits and scratches that were not always as expected. Using computed tomography scanning in one tooth per diet, absolute wear was quantified as the mean height change after the simulated chewing. Absolute wear increased with diet abrasiveness, originating from phytoliths and grit. In combination, our findings highlight that differences in actual dental tissue loss can occur at similar microwear patterns, cautioning against a direct transformation of microwear results into predictions about diet or tooth wear rate.

Two separate subfamilies of Plio‐Pleistocene African pigs (suids) consecutively evolved hypsodont and horizodont molars with flat occlusal surfaces, commonly interpreted as an adaptive trait to a grazing diet, similar to that of the present warthogs (Phacochoerus spp.). To investigate this in detail, we studied the 3D‐dental topography of fossil specimens from the Turkana Basin, using geographic information systems‐based methods. To establish baselines for interpretation of the Turkana Basin suids, topography of third molars of extant suids with known diets were analyzed: grazing warthog (Phacochoerus africanus), herbivorous mixed‐feeder forest hog (Hylochoerus meinertzhageni), omnivorous generalist wild boar (Sus scrofa), omnivorous fruit and tuber eater bush pig (Potamochoerus spp.), and omnivorous fruit eater babirusa (Babyrousa spp.) In addition, we analyzed supposedly browsing Miocene suids, Listriodon spp. The same topographic measures were applied to Plio‐Pleistocene specimens from the Turkana Basin, Kenya: Notochoerus euilus, Notochoerus scotti, Kolpochoerus heseloni, and Metridiochoerus andrewsi. With some differences between techniques, 3D‐dental topography analysis of extant suid molars mostly predicts the dietary differences between the species correctly. The grazing P. africanus differs from both the omnivorous suids and the herbivorous mixed‐feeder H. meinertzhageni in all except one metrics. The omnivorous mostly tropical suids, Potamochoerus and Babyrousa, primarily differ from the generalist, S. scrofa, in the orientation patch count analysis, showing higher occlusal complexity in the latter. Although, there might be significant gaps between the morphological changes and the ecological changes, we conclude that based on comparison of dental topography with the present‐day suids, N. scotti and M. andrewsi were most likely highly specialized grazers, while N. euilus and K. heseloni retained more of their ancestral, omnivorous heritage, but consumed grasses more than the extant omnivorous suids. Research highlights Dental topography can predict different diets in present‐day wild pigs. The Plio‐Pleistocene pigs in the Turkana Basin had dental topography mostly similar to extant grazing warthog, although some species also had resemblances to omnivorous forest pigs.

The ability to analyze and classify three-dimensional (3D) biological morphology has lagged behind the analysis of other biological data types such as gene sequences. Here, we introduce the techniques of data mining to the study of 3D biological shapes to bring the analyses of phenomes closer to the efficiency of studying genomes. We compiled five training sets of highly variable morphologies of mammalian teeth from the MorphoBrowser database. Samples were labeled either by dietary class or by conventional dental types (e.g. carnassial, selenodont). We automatically extracted a multitude of topological attributes using Geographic Information Systems (GIS)-like procedures that were then used in several combinations of feature selection schemes and probabilistic classification models to build and optimize classifiers for predicting the labels of the training sets. In terms of classification accuracy, computational time and size of the feature sets used, non-repeated best-first search combined with 1-nearest neighbor classifier was the best approach. However, several other classification models combined with the same searching scheme proved practical. The current study represents a first step in the automatic analysis of 3D phenotypes, which will be increasingly valuable with the future increase in 3D morphology and phenomics databases.

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Objectives: There remain many idiosyncrasies among the values calculated for varying dental topography metrics arising from differences in software preferences among research groups.The aim of this work is to compare and provide potential conversion formulae for dental topography metrics calculated using differing software platforms. Methods: Three software packages: ArcGIS, Surfer Manipulator, and molaR were used to calculate orientation patch count rotated (OPCR), Dirichlet normal energy (DNE), occlusal relief (OR), slope (m), and angularity (a) on platyrrhine second upper molars. Values derived from the various software packages were compared for distributional consistency and correlation. Where appropriate, formulae for conversion between like measures calculated on different software platforms were developed.Results: When compared with the same measurement across software, OPCR, OR, and slope were all highly correlated. However, only OR demonstrated distributional consistency (i.e., nearly consistent mean, median, max, and min). Slope and OPCR were both higher when calculated by molaR as compared to Surfer Manipulator and ArcGIS calculations, conversion formulae are provided for these measures. DNE is only weakly correlated with angularity; but is correlated with orientation patch count across taxa. Discussion:We explore why there is variation in the dental topography values calculated among the various software packages. The conversion formulae provided in this work will make possible direct comparisons among studies conducted across multiple research groups.