Soil-surface pollen assemblages and quantitative relationships with vegetation and climate from the Inner Mongolian Plateau and adjacent mountain areas of northern China

Abstract

We statistically analyzed 396 soil-surface pollen samples from the Inner Mongolian Plateau and its adjacent mountain areas of northern China to gain insights into pollen–vegetation–climate. The results of indicator species analysis, canonical correspondence analysis (CCA) and boosted regression tree (BRT) analysis suggest that: 1) soil-surface pollen assemblages can differentiate between desert, steppe, meadow steppe, cool broadleaved forest, cool conifer forest, and temperate forest, but fail to differentiate between steppe and forest steppe; shrub and temperate forest; and temperate broadleaved forest, temperate mixed conifer-broadleaved forest, and eurythermic conifer forest; 2) pollen taxa, with low percentages but frequent occurrences, strongly indicate presence in the vegetation; 3) mean annual precipitation (MAP) is the most dominant variable influencing soil-surface pollen assemblages and the most promising climate variable for quantitative reconstructions. Weighted averaging partial least squares regression (WA-PLS), modern analogue technique (MAT), and boosted regression trees (BRT) were used to construct a series of pollen-climate calibration sets. WA-PLS and MAT outperform BRT under leave-one-out cross-validation. WA-PLS models are less susceptible to spatial auto-correlation than MAT models, making WA-PLS models generally the best choice. Our soil-surface pollen data will contribute to modern pollen data in eastern Asia.