Biogeographical studies of migration and mobility in archaeology and bioarchaeology rely on accurately characterizing local 87Sr/86Sr ranges, either through baseline studies or by statistically parsing archaeological results at a given site. However, when baseline materials are difficult to obtain or suspected to deviate from prehistoric isotopic catchments, archaeological data may provide an accurate characterization of local ranges. Through a spatial meta-analysis of 87Sr/86Sr values from archaeological human, faunal, and artifact samples (n = 1658) from 45 publications, this study aims to quantify and compare variation in bioavailable strontium and create the first predictive isotope model (or isoscape) for 87Sr/86Sr values in the prehistoric Andes. Descriptive statistics, including the coefficient of variation, are compared between sites from different temporal categories, and between coastal, yungas, and highland sites. Regional differences in the 87Sr/86Sr values of male and female biological sex categories are compared for human enamel and bone samples, and between sequentially-forming enamel and bone samples. The study finds that the archaeological dataset trimmed of outliers provides a reliable model of local ranges. However, we caution that when migration and trade networks being investigated are within homogeneous isoscape regions, or between contiguous neighbors, multiple isotopic signatures should be incorporated into provenience estimations.
ASJC Scopus subject areas
FingerprintDive into the research topics of 'An archaeological strontium isoscape for the prehistoric andes: Understanding population mobility through a geostatistical meta-analysis of archaeological 87Sr/86Sr values from humans, animals, and artifacts'. Together they form a unique fingerprint.
Data for: An Archaeological Strontium Isoscape for the Prehistoric Andes: Understanding Population Mobility Through a Geostatistical Meta-Analysis of Archaeological 87Sr/86Sr Values from Humans, Animals, and Artifacts
Scaffidi, B. K. (Contributor) & Knudson, K. (Contributor), Mendeley Data, Apr 26 2021