Wet mid-late Holocene in central Asia supported prehistoric intercontinental cultural communication: Clues from pollen data

Past precipitation patterns in arid central Asia can help us to understand better the situation of the Eurasian steppe-road of prehistoric intercontinental culture communication. This requires reliable quantitative pollen-based reconstructions to reveal the spatiotemporal pattern of past precipitation (pollen is the most feasible proxy for quantitative reconstruction and spatial comparison). In this study, modern pollen data (n = 1336) from arid central Asian sites with a mean annual precipitation (P-ann) less than 400 mm were used to explore the influence of P-ann on modern pollen assemblages using canonical correlation analysis (CCA) and to create a pollen-P-ann calibration-set using Weighted-Averaging Partial Least Squares (WA-PLS) and Random Forest (RF). We then reconstructed past P-ann variations for 10 Holocene pollen spectra from north-western China and Mongolia. The reconstructions based on the two approaches were compared with short-term reconstructions and meteorological records (past 55 years) to assess their performance, with statistical significance testing of the reconstructions and assessment of analogue quality. Our results show that RF has a slightly better model performance than WAPLS, and is also a suitable approach for past climate reconstruction using pollen data. Lacustrine pollen spectra reflect the overall pattern of multi-year climate changes rather than interannual climate variations. P-ann reconstructions show that eastern arid central Asia had a relatively dry early Holocene (11.5-8 cal ka BP) and a stable humid mid-late Holocene (after 6 ka), which supported prehistoric intercontinental cultural communication.

Automated summary

Past precipitation patterns in arid central Asia can be better understood through reliable quantitative pollen-based reconstructions. By analyzing modern pollen data from arid central Asian sites, the study created a pollen-P-ann calibration-set and reconstructed past P-ann variations. The results showed that RF is a slightly better model for climate reconstruction using pollen data, reflecting overall multi-year climate changes.