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

Area of Science:

• Forensic Anthropology
• Biological Anthropology
• Human Osteology

Background:

• Current forensic anthropology in South Africa relies heavily on metric approaches for population affinity estimation.
• Non-metric, macromorphoscopic methods for population affinity are under-researched in South African populations.

Purpose of the Study:

• To explore 17 cranial macromorphoscopic traits for improved population affinity estimation among South African populations (Black, White, Coloured).
• To develop a methodology compliant with best practices for forensic casework.

Main Methods:

• Analysis of 17 cranial macromorphoscopic traits in a South African sample.
• Statistical tests (Kruskal-Wallis, Dunn's) to identify significant population differences.
• Random forest modeling to assess classification accuracy and reliability.

Main Results:

• Significant population differences were found for 13 of the 17 traits.
• A classification model using all traits achieved 79% accuracy in estimating population affinity.
• Inferior nasal margin, nasal bone contour, and nasal aperture shape were key discriminators.

Conclusions:

• Macromorphoscopic traits are validated for population affinity estimation in South African skeletal remains.
• This data can enhance forensic casework and skeletal analyses in South Africa.
• The non-metric approach offers a valuable complement to existing craniometric methods.