AI Article Synopsis

  • The cranium is crucial for studying population differences and ancestry, but postcranial alternatives are needed when the cranium is unavailable.
  • This study analyzed 39 measurements from 11 postcranial bones of 360 South Africans to identify ancestry differences among black, white, and coloured individuals, ensuring equal representation of sex and ancestry.
  • Results showed significant differences between groups, with multivariate models achieving high classification accuracy (up to 87%), demonstrating that postcranial analysis can effectively distinguish between modern South African populations.

Article Abstract

The cranium is widely recognized as the most important skeletal element to use when evaluating population differences and estimating ancestry. However, the cranium is not always intact or available for analysis, which emphasizes the need for postcranial alternatives. The purpose of this study was to quantify postcraniometric differences among South Africans that can be used to estimate ancestry. Thirty-nine standard measurements from 11 postcranial bones were collected from 360 modern black, white and coloured South Africans; the sex and ancestry distribution were equal. Group differences were explored with analysis of variance (ANOVA) and Tukey's honestly significant difference (HSD) test. Linear and flexible discriminant analysis (LDA and FDA, respectively) were conducted with bone models as well as numerous multivariate subsets to identify the model and method that yielded the highest correct classifications. Leave-one-out (LDA) and k-fold (k=10; FDA) cross-validation with equal priors were used for all models. ANOVA and Tukey's HSD results reveal statistically significant differences between at least two of the three groups for the majority of the variables, with varying degrees of group overlap. Bone models, which consisted of all measurements per bone, resulted in low accuracies that ranged from 46% to 63% (LDA) and 41% to 66% (FDA). In contrast, the multivariate subsets, which consisted of different variable combinations from all elements, achieved accuracies as high as 85% (LDA) and 87% (FDA). Thus, when using a multivariate approach, the postcranial skeleton can distinguish among three modern South African groups with high accuracy.

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Source
http://dx.doi.org/10.1016/j.forsciint.2015.10.015DOI Listing

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