An application of hierarchical Bayesian modeling to better constrain the chronologies of Upper Paleolithic archaeological cultures in France between ca. 32, 000–21, 000 calibrated years before present. (15th September 2019) - Banks, William E.; Bertran, Pascal; Ducasse, Sylvain; Klaric, Laurent; Lanos, Philippe; Renard, Caroline; Mesa, Miriam
Abstract: Investigations of chronology play a key role in the majority of archaeological research endeavors and are particularly pertinent to examinations of culture-environment relationships, especially during periods characterized by rapid and marked climatic variability and environmental reorganization. Rigorous evaluations of available data and robust methods are required if one wishes to reconstruct reliable chronologies, and this is especially the case when examining periods that are associated with a relatively few radiometric measurements. Such is the case for the Upper Paleolithic archaeological record documented in present-day France from 32, 000 to 21, 000 calibrated years BP. We take into account critically examined radiocarbon measurements from contextually secure archaeological contexts and employ a recently-developed method of Hierarchical Bayesian Modeling to reconstruct the chronology of archaeological cultures from the Middle Gravettian to the Badegoulian. The calculated chronological intervals for each typo-technologically defined culture phase are compared to the Greenland ice core climatic record and a terrestrial paleoenvironmental record from Bergsee Lake (Southern Germany)—itself expressed in calendar years calculated with the same calibration curve employed in our age model—thereby permitting each archaeological culture to be correlated accurately with documented paleoclimatic variability. Highlights: Robust chronologies are needed to correlate past cultures with climate variability. A recently-developed method of Hierarchical Bayesian Modeling is employed. Temporal intervals for archaeological cultures are determined with this method. Arguments are presented as to why this new Bayesian method is preferable.