Since Frank Livingstone proposed the idea that there are no races, only clines, in 1962, little has changed in how anthropologists study and, ultimately, estimate ancestry. How we talk about the study of human variation may have changed—shifting away from “racial” labels and toward those of supposed ancestral origins—but the methods we use to label and analyze groups, however termed, have remained the same. The author suggests a new theoretical approach to ancestry estimation that does not rely on group labels, using the Howells Craniometric Data Set as an example. In the suggested workflow, the data structures itself into natural clusters, referred to as “morphogroups,” without relying on a group label. Each morphogroup is explored for subgroups, and the process is repeated until no further distinctions can be made. At each level an individual is compared to the morphogroup in a descriptive manner, focusing on similarities and differences. Lastly, a multi-iteration classification procedure, using random forest modeling, classifies by morphogroup. In this test, hierarchical clustering identifies the optimal number of natural clusters within the data, and principal components analysis is used to explore morphogroups. (The author provides a markdown file of all code used, at https://rpubs.com/kenyhercz2/717620.) Using this suggested workflow, the author identifies three main morphogroups in the Howells data set, each with different numbers of subclusters ranging from 0 to 8. Morphogroup correct classifications are typically in the mid-90% range, and the accompanying sex estimations, between 93% and 100% correct. The author emphasizes that this is but one of myriad ways ancestry could be estimated. Human variation and identity are not static, and we should help one another rethink and redefine what is possible for our field.

Human identification techniques have been a leading tool to hold perpetrators accountable, give families closure, and approximate faces on skulls. This project is a pilot study to critically examine three disciplines that fall under the human identification umbrella: forensic anthropology, forensic genetics, and forensic art. Current facial research in genetics focuses on data from living individuals, identifying specific single-nucleotide polymorphisms (SNPs) that influence specific regions of the face. This study assesses the translation of these regions to craniometric dimensions (interlandmark distances) of the underlying skull itself. The goal of this project is to provide information regarding the correlation of craniometric measurements and SNPs, as well as to encourage interdisciplinary work within the forensic sciences. We examined a selection of candidate SNPs currently identified in the literature to examine correlations between interlandmark distances and these SNPs within the same individual. A series of 99 craniometric landmarks were collected from 17 documented skulls from the Texas State Donated Skeletal Collection using a three-dimensional Microscribe digitizer. Criteria for inclusion in this study included European American ancestry, presence of intact skulls, and presence of associated donor blood cards collected at the time of body donation. Using these blood cards, DNA from each individual was extracted, amplified, and sequenced through next-generation sequencing for the chosen SNPs. Bioinformatics tests were then applied to observe the presence or absence of the major or minor alleles in specific locations on the genome. After determining the presence or absence of an SNP (minor allele), a set of statistical tests were performed, including Spearman's correlation between the craniometric measurements and the individual's genetic data variables; two-way hierarchical clustering and bootstrap forest modeling between variables that demonstrated significant correlation; a principal components analysis on the craniometric data (interlandmark measurements) and genetic data (SNP presence/absence) to check homogeneity of each data set; and a pairwise Procrustes analysis on the correlation of the two data sets as different groups. The results indicate correlations of varying degrees between the targeted craniofacial regions and the targeted SNPs. Eleven SNPs showed significant correlation (p < 0.05), but the correlations were not as expected and showed some interesting results. By group level there was no significant correlation, but there was correlation at the individual level. While some SNPs affected the soft tissues only, others showed correlations with the skull (hard tissue), a finding not previously reported. Combining craniometric and DNA analyses to leverage genotype-phenotype associations has great potential to expand the discourse of current facial approximation and thereby to provide new investigative tools for human identification in forensic anthropology.

The 1943 Battle of Tarawa resulted in the loss of approximately 1,000 US service members on or around Betio Island, Tarawa Atoll, Republic of Kiribati. Nearly half these casualties were accounted for after the battle. The Defense POW/MIA Accounting Agency (DPAA) has worked to identify the remaining ∼510 unaccounted-for service members and has successfully identified ∼160 service members to date. Demographic data pulled from historical documentation of the US losses indicate a relatively homogeneous population (99% White, 81% 17–23 years of age, and only two individuals with a documented religious preference other than Protestant or Catholic). Using this demographic data as a framework, three case studies are presented to demonstrate how a holistic biosocial approach to building identity could facilitate forensic identifications. The temporal and sociocultural contextualization of analyses enables anthropologists to navigate inconsistencies between 21st-century and historical (1940s) social identity concepts to overcome challenges to identification. The case studies demonstrate how biological evidence, genetic evidence, and material evidence (material culture) differently contribute to the social identity of an individual and can impact identification efforts when analytical conclusions are incongruent with historical documentation. The first case of US Battle of Tarawa casualties examines how morphometric biological affinity assessments are biased by the fluidity of social identity concepts when complex morphological and metric indicators of biological affinity are not represented in historical race categories. The second case demonstrates how biogeographic genetic affinity predictions, through a discussion of the G2a4 haplogroup, need to be examined holistically in the context of other lines of evidence. The third case highlights how material evidence can further define social identity beyond physicality, genetic structure, and race. The challenges of interpreting identity from human remains, as highlighted through these examples, are commonly encountered by anthropologists working in disaster victim identification and other humanitarian contexts. Thus, it is imperative for anthropologists to be self-aware of implicit biases toward the current prevailing definitions of biological and social identity and to consider historical perceptions of identity when working in these contexts.

Skeletal estimation methods to reconstruct the juvenile biological profile are largely limited to those estimating age and, to a lesser extent, sex. While body mass is not generally estimated as part of the biological profile in forensic investigations, this is a logical candidate for inclusion in the forensic biological profile, as it has long been of interest in paleoanthropology and several methods to estimate juvenile body mass currently exist. To explore the performance of body mass estimation for juveniles, the authors tested the accuracy and precision of previously published panel regression formulae using two femoral measurements: the breadth of the distal metaphysis and the cross-sectional polar moment of inertia (J). The test sample consisted of measurements of 94 individuals from birth to 12.5 years of age, taken from postmortem computed tomography scans housed at the Office of the Medical Investigator, New Mexico, USA. Results indicate that body mass estimates are more accurate when estimated from cross-sectional than from metaphyseal measures. Both formulae, however, consistently underestimated weight, and the magnitude of the underestimation increased exponentially with age. This suggests that, contrary to what others have argued, body mass estimation is complicated by population variation in body composition. This study reinforces the importance of documenting and investigating the ontogeny of human variation. The global increase in medical imaging in clinical settings can be leveraged to obtain skeletal data for juveniles from a wide range of ontogenic environments, marking an exciting time for the study of human variation.