Non-metric dental trait variation among Eastern European and Western Siberian forest-steppe Neolithic populations
TL;DRAbstract
The main goal of this study was to find a possible link between Neolithic populations of Eastern European and Western Siberian forest-steppe zones using dental non-metric traits.The second one was to verify the reasons for the similarity, using tooth crown morphology data.The frequencies of thirty traits were observed using ASUDAS in seventeen Neolithic and two Mesolithic burial grounds, belonging to nine archaeological cultures from West Siberian Plain and East European Plain.The frequency of eight key traits was used for comparative statistical analysis.These include the shoveling of upper medial incisors, the distal trigonid crest, and the deflecting wrinkle on the lower first molars, the six-cusped and four-cusped lower first molars, the four-cusped lower second molars, the Carabelli cusp on the upper first molars, and the hypocone on the upper second molars.Trigonometrically transformed trait frequencies were subjected to the principal component analysis and cluster analysis based
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The main goal of this study was to find a possible link between Neolithic populations of Eastern European and Western Siberian forest-steppe zones using dental non-metric traits.The second one was to verify the reasons for the similarity, using tooth crown morphology data.The frequencies of thirty traits were observed using ASUDAS in seventeen Neolithic and two Mesolithic burial grounds, belonging to nine archaeological cultures from West Siberian Plain and East European Plain.The frequency of eight key traits was used for comparative statistical analysis.These include the shoveling of upper medial incisors, the distal trigonid crest, and the deflecting wrinkle on the lower first molars, the six-cusped and four-cusped lower first molars, the four-cusped lower second molars, the Carabelli cusp on the upper first molars, and the hypocone on the upper second molars.Trigonometrically transformed trait frequencies were subjected to the principal component analysis and cluster analysis based
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