Download Dental analysis of Classic period population variability in the Maya

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.