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

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.