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We present a calibration-set based on modern pollen and satellite-based Advanced Very High Resolution Radiometer (AVHRR) observations of woody cover (including needleleaved, broadleaved and total tree cover) in eastern continental Asia, which shows good performance under cross-validation with the modern analogue technique (all the coefficients of determination between observed and predicted values are greater than 0.65). The calibration-set is used to reconstruct woody cover from a taxonomically harmonized and temporally standardized fossil pollen dataset (including 274 cores) with 500-year resolution over the last 22 kyr. The spatial range of forest has not noticeably changed in eastern continental Asia during the last 22 kyr, although woody cover has, especially at the margin of the eastern Tibetan Plateau and in the forest-steppe transition area of north-central China. Vegetation was sparse during the LGM in the present forested regions, but woody cover increased markedly at the beginning of the Bølling/Allerød period (B/A; ca. 14.5 ka bp ) and again at the beginning of the Holocene (ca. 11.5 ka bp ), and is related to the enhanced strength of the East Asian Summer Monsoon. Forest flourished in the mid-Holocene (ca. 8 ka bp ) possibly due to favourable climatic conditions. In contrast, cover was stable in southern China (high cover) and arid central Asia (very low cover) throughout the investigated period. Forest cover increased in the north-eastern part of China during the Holocene. Comparisons of these regional pollen-based results with simulated forest cover from runs of a global climate model (for 9, 6 and 0 ka bp (ECHAM5/JSBACH ∼1.125° spatial resolution)) reveal many similarities in temporal change. The Holocene woody cover history of eastern continental Asia is different from that of other regions, likely controlled by different climatic variables, i.e. moisture in eastern continental Asia; temperature in northern Eurasia and North America. [ABSTRACT FROM AUTHOR]

A modern pollen dataset from China and Mongolia (18–52°N, 74–132°E) is investigated for its potential use in climate reconstructions. The dataset includes 2559 samples, 229 terrestrial pollen taxa and four climatic variables — mean annual precipitation (P ann ): 35–2091 mm, mean annual temperature (T ann ): –12.1–25.8 °C, mean temperature in the coldest month (Mt co ): –33.8–21.7 °C, and mean temperature in the warmest month (Mt wa ): 0.3–29.8 °C. Modern pollen–climate relationships are assessed using canonical correspondence analysis (CCA), Huisman–Olff–Fresco (HOF) models, the modern analogue technique (MAT), and weighted averaging partial least squares (WA-PLS). Results indicate that P ann is the most important climatic determinant of pollen distribution and the most promising climate variable for reconstructions, as assessed by the coefficient of determination between observed and predicted environmental values (r 2 ) and root mean square error of prediction (RMSEP). Mt co and Mt wa may be reconstructed too, but with caution. Samples from different depositional environments influence the performance of cross-validation differently, with samples from lake sediment-surfaces and moss polsters having the best fit with the lowest RMSEP. The better model performances of MAT are most probably caused by spatial autocorrelation. Accordingly, the WA-PLS models of this dataset are deemed most suitable for reconstructing past climate quantitatively because of their more reliable predictive power. [ABSTRACT FROM AUTHOR]