Evaluating Chronological Hypotheses by Simulating Radiocarbon Datasets

Author(s): Ian Jorgeson; Ryan Breslawski; Abigail Fisher

Year: 2019


This is an abstract from the "Novel Statistical Techniques in Archaeology I (QUANTARCH I)" session, at the 84th annual meeting of the Society for American Archaeology.

Evaluating chronological hypotheses using complex radiocarbon datasets is challenging. Sources of variability, including measurement error, interlab variability, uncertainty associated with the radiocarbon calibration curve, the inherent randomness of the physical processes of radiocarbon formation and decay, and potential mismatches between the dated event and the desired event (old wood effects, redeposition, etc.), all can compound in ways that are difficult to predict or account for. To overcome this challenge, we generate expected calendar ages for a given hypothesis, simulate radiocarbon measurements of those expected ages, and then compare the distributions of the simulated datasets with the distributions of observed radiocarbon datasets. These simulated datasets incorporate the known sources of variability in the observed datasets, providing insight into the expected dispersion and structure of a radiocarbon dataset. We demonstrate simulations for three chronologies: (1) a synchronous event, the Laacher See volcanic eruption in Germany approximately 12.9ka; (2) a hypothesized synchronous event at 12.8ka, the Younger Dryas boundary; and (3) an "old wood" effect on Valdez Phase (A.D. 1050 to A.D. 1225) dates in Northern New Mexico. Results demonstrate that simulation is a valuable method to evaluate whether a given radiocarbon dataset was produced by a hypothesized chronology.

Cite this Record

Evaluating Chronological Hypotheses by Simulating Radiocarbon Datasets. Ian Jorgeson, Ryan Breslawski, Abigail Fisher. Presented at The 84th Annual Meeting of the Society for American Archaeology, Albuquerque, NM. 2019 ( tDAR id: 451196)

Record Identifiers

Abstract Id(s): 24031