A lacustrine surface-sediment pollen dataset covering the Tibetan Plateau and its potential in past vegetation and climate reconstructions

Abstract. A dataset of pollen extracted from the surface-sediments of lakes with broad spatial coverage is essential for pollen-based reconstructions of past vegetation and climate. We collected 90 new lake surface-sediment pollen samples from the Tibetan Plateau (TP), covering major vegetation types, including alpine forest, alpine meadow, alpine steppe, and alpine desert. By integrating these new data with previously published lacustrine pollen datasets, we established a comprehensive modern pollen dataset comprising 476 samples across the TP, covering the full range of climatic gradients across the TP, with Net Primary Production (NPP) from 0.16 to 6617.36 kg C m−2, mean annual precipitation (Pann) from 97 to 788 mm, mean annual temperature (Tann) −9.09 to 6.93 °C, mean temperature of the coldest month (Mtco) −23.48 to −2.65 °C, and mean temperature of the warmest month (Mtwa) 1.77 to 19.26 °C. Numerical analyses based on the comprehensive modern pollen dataset (n=476) revealed that Pann is the primary climatic determinant for pollen distribution, while NPP is a valuable variable reflecting vegetation conditions. To detect the quantitative relationship between pollen and NPP / Pann, both Weighted-Averaging Partial Least Squares (WA-PLS) and Random Forest algrithom (RF) were employed. The performance of both models suggests that this modern pollen dataset has good predictive power in estimating past NPP and Pann, but RF has a slight advantage with this dataset. This comprehensive modern pollen dataset provides a reliable basis for reconstructing past vegetation and climate changes on the central TP. However, caution is required when applying it to pollen spectra from marginal regions of the TP or to records covering the Last Glacial period, where analogue quality is relatively poor. The dataset, including site locations, pollen percentages, NPP, and climate data for 90 lakes, is available at the National Tibetan Plateau Data Center (TPDC; Tian et al., 2025; https://doi.org/10.11888/Paleoenv.tpdc.302470).