Exploring cranial macromorphoscopic variation and classification accuracy in a South African sample

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Authors

Liebenberg, Leandi
L'Abbe, Ericka Noelle
Stull, Kyra Elizabeth

Journal Title

Journal ISSN

Volume Title

Publisher

Springer

Abstract

To date South African forensic anthropologists are only able to successfully apply a metric approach to estimate population affinity when constructing a biological profile from skeletal remains. While a non-metric, or macromorphoscopic approach exists, limited research has been conducted to explore its use in a South African population. This study aimed to explore 17 cranial macromorphoscopic traits to develop improved methodology for the estimation of population affinity among black, white and coloured South Africans and for the method to be compliant with standards of best practice. The trait frequency distributions revealed substantial group variation and overlap, and not a single trait can be considered characteristic of any one population group. Kruskal-Wallis and Dunn’s tests demonstrated significant population differences for 13 of the 17 traits. Random forest modelling was used to develop classification models to assess the reliability and accuracy of the traits in identifying population affinity. Overall, the model including all traits obtained a classification accuracy of 79% when assessing population affinity, which is comparable to current craniometric methods. The variable importance indicates that all the traits contributed some information to the model, with the inferior nasal margin, nasal bone contour, and nasal aperture shape ranked the most useful for classification. Thus, this study validates the use of macromorphoscopic traits in a South African sample, and the population-specific data from this study can potentially be incorporated into forensic casework and skeletal analyses in South Africa to improve population affinity estimates.

Description

DATA AVAILABILITY : The dataset generated/analysed during the current study are available from the corresponding author on reasonable request.

Keywords

Forensic anthropology, Population affinity, Ancestry, Random forest (RF), Variable importance, SDG-03: Good health and well-being

Sustainable Development Goals

SDG-03:Good heatlh and well-being

Citation

Liebenberg, L., L’Abbé, E.N. & Stull, K.E. Exploring cranial macromorphoscopic variation and classification accuracy in a South African sample. International Journal of Legal Medicine 138, 2081–2092 (2024). https://doi.org/10.1007/s00414-024-03230-2.