A molar microwear texture analysis of pitheciid primates.
Anna J RagniMark F TeafordPeter S UngarPublished in: American journal of primatology (2017)
Dental microwear textures have been examined for a broad range of extant primates to assess their efficacy for reconstructing diets of fossil species. To date though, no dental microwear texture data have been published for pitheciid molars, despite reported variation in degree of sclerocarpy and, by extension, the fracture properties of foods these platyrrhines eat. While all pitheciids eat hard or tough seeds, Chiropotes and Pithecia have been documented to consume more than Callicebus. In this study, we explored whether measures of molar microwear texture complexity discriminate taxa following variation in reliance upon seeds, and whether dispersion among variables is greatest in Callicebus, which has the most variable diet. Here we report results for a study of microwear textures on M2 "Phase II" facets of Ch. satanas (N = 14), P. irrorata (N = 8), and Ca. moloch (N = 24) from the Brazilian Amazon (Oriximina, UHE Samuel, and Taperinha, respectively). Textures examined using a scanning confocal profiler showed significant differences in central tendencies for three measures: mean dale area (Sda), anisotropy (Str), and heterogeneity (HAsfc9 ). Ten measures showed significant differences in dispersion, with Callicebus being significantly more variable in eight of those ten. These results demonstrate that the pitheciids with different morphological adaptations and dietary reliance on seeds differ in their dental microwear textures, though less than initially hypothesized. Measures of dispersion, especially, show potential for identifying dietary variability.
Keyphrases
- phase ii
- oral health
- clinical trial
- contrast enhanced
- weight loss
- physical activity
- single cell
- magnetic resonance
- high intensity
- high resolution
- computed tomography
- magnetic resonance imaging
- big data
- risk assessment
- climate change
- study protocol
- artificial intelligence
- data analysis
- electron microscopy
- meta analyses