The impact of data reduction on classical and Bayesian 210Pb dating models

Abstract

Accurate dating of sediment layers is vital for deciphering Earth’s environmental history. This study addresses the precision and accuracy of lead-210 (²¹⁰Pb) dating models, a critical tool in sedimentary research for understanding environmental changes. Traditional Constant Rate of Supply (CRS) methods, while widely used, often struggle with accuracy, particularly in complex sedimentation scenarios. We contrast the CRS model with Plum, an advanced Bayesian approach, using simulated ²¹⁰Pb profiles derived from varied sedimentation processes. Our analysis reveals that even under ideal CRS conditions, the model’s precision does not significantly improve with additional data. In the contrary, Plum consistently outperforms CRS in both accuracy and precision, even with limited data inputs. As data volume increases, Plum’s performance improves markedly, unlike CRS. The Bayesian framework effectively addresses the complexities overlooked by CRS, demonstrating its superiority in refining sediment chronologies. This paper highlights the importance of incorporating statistical advancements in sediment dating techniques. By applying refined Bayesian methods like Plum, researchers can achieve more reliable sediment chronologies, essential for robust environmental studies and unravelling complex climate histories. Our findings suggest that embracing statistical innovations in geochronology can substantially enhance our understanding of Earth’s environmental changes.