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Updated: Nov 28, 2025

Systematic Assessment of Mammalian Skull Specimens for Dental and Temporomandibular Joint Pathology
Published on: August 22, 2022
Assessing complexity in hominid dental evolution: Fractal analysis of great ape and human molars
Hugo Cano-Fernández1,2, Aida Gómez-Robles3,4,5
1Universidad Autónoma de Barcelona, Barcelona, Spain.
Objectives:
Molar crenulation is defined as the accessory pattern of grooves that appears on the occlusal surface of many mammalian molars. Although frequently used in the characterization of species, this trait is often assessed qualitatively, which poses unavoidable subjective biases. The objective of this study is to quantitatively test the variability in the expression of molar crenulation in primates and its association with molar size and diet.
Methods:
The variability in the expression of molar crenulation in hominids (human, chimpanzee, gorilla, and orangutan) was assessed with fractal analysis using photographs of first, second and third upper and lower molars. After this, representative values for 29 primate species were used to evaluate the correlation between molar complexity, molar size, and diet using a phylogenetic generalized least squares regression.
Results:
Results show that there are statistically significant differences in fractal dimensions across hominid species in all molars, with orangutan molars presenting higher values of occlusal complexity. Our results indicate that there is no significant association between molar complexity and molar size or diet.
Discussion:
Our results show higher levels of occlusal complexity in orangutans, thus supporting previously published observations. Our analyses, however, do not indicate a clear association between molar complexity and molar size or diet, pointing to other factors as the major drivers of complexity. To our knowledge, our study is the first one to use fractal analysis to measure occlusal complexity in primates. Our results show that this approach is a rapid and cost-effective way to measure molar complexity.
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