Open AccessThe Impact of dental wear on the analysis of morphological affinities based on dental non-metric traits
Author(s) -
Daniel Fidalgo,
Verônica Wesolowski,
Mark Hübbe
Publication year - 2021
Publication title -
dental anthropology
Language(s) - English
Resource type - Journals
eISSN - 2769-822X
pISSN - 1096-9411
DOI - 10.26575/daj.v34i2.328
Subject(s) - affinities , trait , context (archaeology) , tooth crown , tooth wear , crown (dentistry) , principal component analysis , divergence (linguistics) , scale (ratio) , dental anatomy , dentistry , orthodontics , medicine , biology , mathematics , geography , computer science , statistics , paleontology , cartography , biochemistry , linguistics , philosophy , programming language
Dental wear is described as a limitation to dental morphological studies, as it obscures important crown trait features, resulting in significant differences on trait frequencies, an essential component for estimating biodistances. However, the actual impact of dental wear on biological distances still requires further characterization. We explore the impact of dental wear on morphological affinities for Brazilian pre-colonial series in the context of worldwide reference series. Twenty crown traits were scored using the Arizona State University Dental Anthropological System, and dental wear was quantified as an ordinal scale between 1 (no wear) and 8 (crown eroded). Seven crown trait frequencies are significantly associated with dental wear (p<0.05), demonstrating its impact on their analysis. To explore this impact on biodistances, data was divided by wear categories (all teeth, low-wear, moderate/severe wear) and morphological affinities among series was compared through Euclidean distances, Mean Measure of Divergence, and Principal Component Analysis. Results show the impact of wear is only meaningful when a sample contains many wear-biased traits with only moderate/severe wear. We conclude despite the impact of wear on individual trait frequencies, its impact on morphological affinities can be mitigated by including other variables or when comparisons focus only on large-scale biological differences.