Harmonized chronologies of a global late Quaternary pollen dataset (LegacyAge 1.0)

We present a chronology framework named LegacyAge 1.0 containing harmonized chronologies for 2831 pollen records (downloaded from the Neotoma Paleoecology Database and the supplementary Asian datasets) together with their age control points and metadata in machine-readable data formats. All chronologies use the Bayesian framework implemented in Bacon version 2.5.3. Optimal parameter settings of priors (accumulation.shape, memory.strength, memory.mean, accumulation.rate, and thickness) were identified based on information in the original publication or iteratively after preliminary model inspection. The most common control points for the chronologies are radiocarbon dates (86.1 %), calibrated by the latest calibration curves (IntCal20 and SHCal20 for the terrestrial radiocarbon dates in the Northern Hemisphere and Southern Hemisphere and Marine20 for marine materials). The original publications were consulted when dealing with outliers and inconsistencies. Several major challenges when setting up the chronologies included the waterline issue (18.8% of records), reservoir effect (4.9 %), and sediment deposition discontinuity (4.4 %). Finally, we numerically compare the LegacyAge 1.0 chronologies to those published in the original publications and show that the reliability of the chronologies of 95.4% of records could be improved according to our assessment. Our chronology framework and revised chronologies provide the opportunity to make use of the ages and age uncertainties in synthesis studies of, for example, pollen-based vegetation and climate change. The LegacyAge 1.0 dataset, including metadata, datings, harmonized chronologies, and R code used, is openaccess and available at PANGAEA (https://doi.org/10.1594/PANGAEA.933132; Li et al., 2021) and Zenodo (https://doi.org/10.5281/zenodo.5815192; Li et al., 2022), respectively.

Automated summary

This article presents a chronology framework called LegacyAge 1.0, which includes harmonized chronologies for 2831 pollen records along with their age control points and metadata. The chronologies were created using a Bayesian framework and optimal parameter settings. Calibrated radiocarbon dates were used as the most common control points, and outliers and inconsistencies were addressed by consulting the original publications. The LegacyAge 1.0 chronologies were numerically compared to the original publications, resulting in improved reliability for 95.4% of the records. This chronology framework and revised chronologies offer opportunities for synthesis studies on pollen-based vegetation and climate change.