Radiogenic strontium isotope variability in the Valley of Oaxaca: A predictive isoscape for Mesoamerican...

Radiogenic strontium (87Sr/86Sr) isotope analysis is a well-established method for reconstructing the mobility of human populations in the past and present. Baseline 87Sr/86Sr data are fundamental to the method, as Sr varies across the landscape according to local geology and geoenvironmental factors. The method's application within studies of ancient Mesoamerican paleomobility, however, has concentrated on two key regions-Teotihuacan and the Maya region-despite its potential broader relevance across greater Mesoamerica. This is due in part to a lack of available baseline 87Sr/86Sr data for the region at large. Using the Valley of Oaxaca as a case study, we use Bayesian Additive Regression Trees (BART) to generate a locally calibrated predictive 87Sr/86Sr isoscape model of Mesoamerica in general and the Valley of Oaxaca in particular. We integrate (1) observed 87Sr/86Sr data from modern plant samples (n = 95) from 17 sites across the Valley, (2) a compiled database of continental North and South American 87Sr/86Sr data, (3) geological bedrock maps, and (4) high resolution spatial data on geoenvironmental Sr covariates to iteratively develop and test a high performing predictive model for Mesoamerica, highlighting the importance of regional calibration in developing predictive 87Sr/86Sr isoscapes. Our results indicate that though overlap exists, 87Sr/86Sr can be used to detect migration within the Valley of Oaxaca as well as between the Valley and greater Mesoamerica. We then apply our isoscape to previously published human 87Sr/86Sr data from Monte Albán, Oaxaca to demonstrate how our model's explicit quantification of uncertainty in local 87Sr/86Sr ranges allows for more nuanced interpretation of paleomobility in archaeological samples.