Dental Analysis of Classic Period Population Variability in the Maya Area

Dental analysis of Classic period population variability in the Maya area

Scherer, Andrew Kenneth Chair: Wright December 2004

In this dissertation I examine population history and structure in the Maya area during the Classic period (A.D. 250-900). Within the Maya area, archaeologists have identified regional variation in material culture between archaeological zones. These cultural differences may correspond to biological differences between Classic Maya populations. I test the hypothesis that Classic Maya population structure followed an isolation by distance model. I collected dental nonmetric and metric traits on 977 skeletons, from 18 Classic period sites, representing seven different archaeological zones. I corrected the data for intraobserver error. For the dental nonmetric data, I developed a Maya-specific trait dichotomization scheme and controlled for sex bias. I tested the dental metric data for normality and age affects. I imputed missing dental metric data for some traits and the remaining set of traits was Q-mode transformed to control for allometric factors. I analyzed the dental nonmetric and metric datasets with both univariate and multivariate tests. I found, with a log likelihood ratio, that 50% of the nonmetric traits exhibited statistically significant differences between Maya sites. I performed a Mean Measure of Divergence analysis of the dental nonmetric dataset and found that majority of the resulting pairwise distance values were significant. Using cluster analysis and multidimensional scaling, I found that the dental nonmetric data do not support an isolation by distance organization of Classic Maya population structure. In the ANOVA and MANOVA tests, I did not find major statistically significant differences in dental metrics between Maya sites. Using principal components analysis, a Mahalanobis Distance test, and R matrix analysis, I found a generally similar patterning of the dental metric data. The dental metric data to not support an isolation by distance model for Classic Maya population structure. However, the geographically outlying sites from Kaminaljuyu and the Pacific Coast repeatedly plotted as biological outliers. R matrix analysis indicates that gene flow, not genetic drift, dominated Classic Maya population structure. Based on the results of the dental nonmetric and metric analyses, I reject the hypothesis that isolation by distance is a valid model for Classic Maya population structure. From the multivariate analyses of the dental nonmetric and metric data, a few notable observations are made. The major sites of Tikal and Calakmul both demonstrate substantial intrasite biological heterogeneity, with some affinity to other sites but with little to one another. Piedras Negras demonstrates some evidence for genetic isolation from the other lowland Maya sites. In the Pasión Zone, Seibal and Altar de Sacrificios demonstrate some affinity to one another, though Dos Pilas is an outlier. The R matrix analysis found evidence of Classic period immigration into Seibal from outside the network of sites tested. The Belize Zone exhibited substantial heterogeneity among its sites, with the site of Colha showing some affinity to the Central Zone. Copan, despite being a geographic outlier, demonstrates genetic affinity with the rest of the Maya area. Kaminaljuyu and the Pacific Coast were both found to be outliers. These results indicate that dental nonmetric and metric data are a useful tool for investigating ancient biological variability in the Maya area and contribute to our expanding understanding of population history in that region.sites, with the site of Colha showing some affinity to the Central Zone. Copan, despite being a geographic outlier, demonstrates genetic affinity with the rest of the Maya area. Kaminaljuyu and the Pacific Coast were both found to be outliers. These results indicate that dental nonmetric and metric data are a useful tool for investigating ancient biological variability in the Maya area and contribute to our expanding understanding of population history in that region.