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Temporal and spatial stability of the vegetation climate relationship is a basic ecological assumption for pollen-based quantitative inferences of past climate change and for predicting future vegetation. We explore this assumption for the Holocene in eastern continental Asia (China, Mongolia). Boosted regression trees (BRT) between fossil pollen taxa percentages (Abies, Artemisia, Betula, Chenopodiaceae, Cyperaceae, Ephedra, Picea, Pinus, Poaceae and Quercus) and climate model outputs of mean annual precipitation (P-ann) and mean temperature of the warmest month (Mt(wa)) for 9 and 6 ka (ka = thousand years before present) were set up and results compared to those obtained from relating modern pollen to modern climate. Overall, our results reveal only slight temporal differences in the pollen climate relationships. Our analyses suggest that the importance of P-ann compared with Mt(wa) for taxa distribution is higher today than it was at 6 ka and 9 ka. In particular, the relevance of P-ann for Picea and Pinus increases and has become the main determinant. This change in the climate tree pollen relationship parallels a widespread tree pollen decrease in north-central China and the eastern Tibetan Plateau. We assume that this is at least partly related to vegetation climate disequilibrium originating from human impact. Increased atmospheric CO2 concentration may have permitted the expansion of moisture-loving herb taxa (Cyperaceae and Poaceae) during the late Holocene into arid/semi-arid areas. We furthermore find that the pollen climate relationship between north-central China and the eastern Tibetan Plateau is generally similar, but that regional differences are larger than temporal differences. In summary, vegetation climate relationships in China are generally stable in space and time, and pollen-based climate reconstructions can be applied to the Holocene. Regional differences imply the calibration-set should be restricted spatially.
The concept of a Global Monsoon (GM) has been proposed based on modern precipitation observations, but its application over a wide range of temporal scales is still under debate. Here, we present a synthesis of 268 continental paleo-moisture records collected from monsoonal systems in the Eastern Hemisphere, including the East Asian Monsoon (EAsM), the Indian Monsoon (IM), the East African Monsoon (EAfM), and the Australian Monsoon (AuM) covering the last 18,000 years. The overall pattern of late Glacial to Holocene moisture change is consistent with those inferred from ice cores and marine records. With respect to the last 10,000 years (10 ka), i.e. a period that has high spatial coverage, a Fuzzy c-Means clustering analysis of the moisture index records together with "Xie-Beni" index reveals four clusters of our data set. The paleoclimatic meaning of each cluster is interpreted considering the temporal evolution and spatial distribution patterns. The major trend in the tropical AuM, EAfM, and IM regions is a gradual decrease in moisture conditions since the early Holocene. Moisture changes in the EAsM regions show maximum index values between 8 and 6 ka. However, records located in nearby subtropical areas, i.e. in regions not influenced by the intertropical convergence zone, show an opposite trend compared to the tropical monsoon regions (AuM, EAfM and IM), i.e. a gradual increase. Analyses of modern meteorological data reveal the same spatial patterns as in the paleoclimate records such that, in times of overall monsoon strengthening, lower precipitation rates are observed in the nearby subtropical areas. We explain this pattern as the effect of a strong monsoon circulation suppressing air uplift in nearby subtropical areas, and hence hindering precipitation. By analogy to the modern system, this would mean that during the early Holocene strong monsoon period, the intensified ascending airflows within the monsoon domains led to relatively weaker ascending or even descending airflows in the adjacent subtropical regions, resulting in a precipitation deficit compared to the late Holocene. Our conceptual model therefore integrates regionally contrasting moisture changes into the Global Monsoon hypothesis. (C) 2017 Elsevier Ltd. All rights reserved.