Geographic Patterns of Craniofacial Variation in Pre-Hispanic Populations from the Southern Cone of South America

• Published in: Human biology Vol. 83; no. 4; pp. 491 - 507
• Main Authors: Fabra, Mariana, Demarchi, Darío A.
• Format: Journal Article
• Language: English
• Published: United States Wayne State University Press 01-08-2011
• Subjects: Argentina; Asian Continental Ancestry Group; Biological anthropology; Biological variation; Centrales; Cephalometry; CRANIOMETRICS; Craniometry; ENVIRONMENT; European Continental Ancestry Group; Genetic aspects; Genetic diversity; Genetic Drift; Genetic Variation - genetics; Geography; History, Ancient; Humans; Indians, South American - history; Indians, South American - statistics & numerical data; Morphology; Morphology (Biology); Museums; Natural history; Paleontology - history; Paleontology - statistics & numerical data; Phylogeography - history; Phylogeography - statistics & numerical data; Physiological aspects; Population; Prehistoric peoples; Regression Analysis; s; Sample surveys; SIERRAS CENTRALES; Skull; Skull - anatomy & histology; SOUTH AMERICA; Spatial analysis; SPATIAL AUTOCORRELATION; SPATIAL REGRESSION; Variables; Argentina; South America
• ISSN: 0018-7143; 1534-6617; 1534-6617
• DOI: 10.3378/027.083.0404

In this study we analyzed the relationships and patterns of spatial variation from morphological cranial variability of 17 population samples representing the ancient inhabitants of the central territory of Argentina (archaeologically known as “Sierras Centrales”) and other pre-Hispanic populations from different ecological and geographic regions of the Southern Cone of South America (Argentina and Uruguay), based on the analysis of 10 craniofacial measurements. Results obtained from D2 distances can be interpreted as evidence of a similar biological history for the populations that inhabited the Sierras Centrales and the population of Santiago del Estero. Matrix correlation analysis demonstrated that craniometric variation is significantly influenced by geography, suggesting that populations that lived at lower geographical distance share more biological similarity. Global spatial autocorrelation analysis suggests a clinal pattern for the biological variation, although Moran's I estimates calculated for each variable demonstrate that only nasal height and breadth show this spatial pattern of variation. Results from spatial regression techniques show a significant effect of altitude modeling nasal shape, in agreement with previous studies suggesting that nasal morphology is strongly influenced by environment variables.