Exploring Mutual and Exclusive Biological Information in Cranial Metric and Morphological Variables

Abstract

Evidence suggests that both craniometric and cranial morphoscopic (MMS) traits elucidate information about cranial
phenotypic variation and are appropriate proxies of genetic variation. Yet, the types of variation underlying the expression of craniometric and MMS traits are unknown. Recent data sets of matched skeletal metric and MMS data enable a holistic exploration into the cranial phenotype. Subsequently, the current study strived to provide a better understanding of cranial data used to measure human variation in biological anthropology. Two contemporary U.S. samples were pooled to increase sample size and diversity. Following down-sampling for balanced representation of reported biological males and females, the final sample comprised 310 individuals. Twenty-five interlandmark distances and 11 MMS traits were used in numerous analyses: polychoric correlation, mutual information, mixed factor analysis, and factor analysis of mixed data. No demographic information besides reported biological sex was retained in the analyses. The results consistently indicate that having information about one data type does not provide certainty of another data type, even when the variables are analogous (i.e., nasal breadth and nasal aperture width). Findings reassert that skeletal variables should be analyzed jointly rather than independently to best capture the cranial phenotype. The results also highlight the differential influence of biological variables, such as sexual dimorphism, on the two types of cranial data. As data availability increases and additional matched data-type comparisons can be conducted, we will continue to gain a better understanding of the complexities surrounding skeletal phenotypic variation, evolutionary theory, and population affinity