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The wetland ecosystem is particularly vulnerable to hydrological and climate changes. The Great Xing'an Mountain is such a region in China that has a large area of wetlands with rare human disturbance. The predictions of the global circulation model CGCM3 (the third-generation coupled global climate model from the Canadian Centre for Climate Modeling and Analysis) indicated that the temperature in The Great Xing'an Mountain will rise by 2-4°C over the next 100 years. This paper predicts the potential distributions of wetlands in this area under the current and warming climate conditions. This predication was performed by the Random Forests model, with 18 environmental variables, which will reflect the climate and topography conditions. The model has been proven to have a great prediction ability. The wetland distributions are primarily topography-driven in the Great Xing'an Mountains. Mean annual temperature, warmness index, and potential evapotranspiration ratio are the most important climatic factors in wetland distributions. The model predictions for three future climate scenarios show that the wetland area tends to decrease, and higher emission will also cause more drastic shrinkage of wetland distributions. About 30% of the wetland area will disappear by 2050. The area will decrease 62.47, 76.90, and 85.83%, respectively, under CGCM3-B1, CGCM3-A1B, and CGCM3-A2 by 2100. As for spatial allocation, wetlands may begin to disappear from the sides to the center and south to north under a warming climate. Under CGCM3-B1, the loss of wetlands may mainly occur in the south hills with flatter terrain, and some may occur in the north hills and intermontane plains. Under CGCM3-A1B, severe vanish of wetlands is predicted. Under CGCM3-A2, only a small area of wetlands may remain in the north of the high mountains. [ABSTRACT FROM AUTHOR]

In plants, silicon (Si) accumulates in phytoliths, which can contain 0.1-6.0 % occluded organic carbon (phytolith-occluded organic carbon, PhytOC). Globally, phytolith formation has implications for the long-term terrestrial carbon balance, and thus, global climate change. In this study, we analyzed the Si contents of 108 species of plants from Inner Mongolia and Hebei, China, to demonstrate the relationships between plant Si content and various phylogenetic and ecological characteristics, and to estimate PhytOC production in the forests of north China. Variations in Si content were related to the plant's higher-level phylogenetic position, according to the Angiosperm Phylogeny Group III classification. In angiosperms, the commelinoid monocot orders accumulated substantially more Si than did the other monocot orders, and the asteroid dicot orders accumulated more Si than did the other dicot orders. In an ecological context, herbs had the highest Si content (0.47 ± 0.26 % dry weight), followed by trees (0.33 ± 0.13 % dry weight) and shrubs (0.24 ± 0.09 % dry weight). The total PhytOC production rate in the forests of north China corresponded to 0.48 ± 0.20 × 10 t CO year, approximately 44 % of which was contributed by the understory vegetation comprising herbs and shrubs. This finding indicates that the phytolith carbon sequestration potential of the forests may be further enhanced by afforestation/reforestation, preserving the understory vegetation, and maximizing the aboveground net primary productivity of all forest layers, especially herbs that accumulate high Si contents. [ABSTRACT FROM AUTHOR]

Three methods were used to distinguish the characteristics of changes in climate variability and normalized difference vegetation index (NDVI) during the period from 1982 to 2000 in China. Great changes in climate variability and an increased trend in NDVI were observed. The changes in precipitation variability were greater than the changes in temperature variability in each month, which is attributed to changes in the monsoon system in East Asia. The abrupt changes in climate and NDVI were more significant in 1983 than in the other years due to the impacts of El Niño/Southern Oscillation (ENSO). Using these results, the influences of changes in climate variability on vegetation were studied in the whole nation, and eight regions were defined according to the vegetation division map of China. The results show that abrupt climate changes at a small scale cannot cause abrupt NDVI changes directly. At a nationwide level, over a longer time scale the persistence of above/below average temperature determines the changes in NDVI; at a shorter time scale, changes in the magnitude of precipitation influence NDVI significantly. Such regional climate variability affects vegetation in different ways owing to the diversity of vegetation types, climatic conditions and topography of the land. [ABSTRACT FROM AUTHOR]

In order to understand how changes in climate and land cover affect carbon cycles and structure and function of regional grassland ecosystems, we developed a grassland landscape productivity model, proposed an approach that combined both process-based modeling and spatial analysis with field measurements, and provided an example of semiarid region in Inner Mongolia, China, in extremely arid conditions. The modeled monthly mean and total net primary productivity, and monthly and annual mean respiration rates for Leymus chinensis steppes during the growing seasons in 2002 were mostly within the normal varying ranges of measured values, or similar to the field measurements, conducted in the similarly arid conditions. And the modeled total net ecosystem productivity (NEP) for L. chinensis steppes and Stipa grandis steppes were both between the lower and the higher measurements or within modeled multi-annual data by the other model. The modeled total NEP was 1.91 g C/m2/year over the entire study region. It indicated that if human disturbances were not considered, carbon budget over the entire study region during the growing seasons was nearly in balance or weak carbon sink even under extremely arid conditions. However, the modeled NEP spatially greatly varied not only over the entire study region (−48.28–52.09 g C/m2/year), but also among different land cover types. The modeled results also showed that there were obvious seasonal variations in carbon fluxes, mainly caused by leaf area index; and annual precipitation was the major limiting factor for the obvious spatial patterns of carbon fluxes from the east to the west. The modeled results also revealed the influence of extreme drought on carbon fluxes. The study provides an effective approach to derive useful information about carbon fluxes for different land cover types, and thus can instruct regional land-use planning and resource management based on carbon storage conditions. [ABSTRACT FROM AUTHOR]

Quantifying climate-induced changes in vegetation patterns is essential to understanding land–climate interactions and ecosystem changes. In the present study, we estimated various distributional changes of vegetation under different climate-change scenarios in the 21st century. Both hypothetical scenarios and Hedley RCM scenarios show that the transitional vegetation types, such as shrubland and grassland, have higher sensitivity to climatic change compared to vegetation under extreme climatic conditions, such as the evergreen broadleaf forest or desert, barren lands. Mainly, the sensitive areas in China lie in the Tibetan Plateau, Yunnan-Guizhou Plateau, northeastern plain of China and eco-zones between different vegetations. As the temperature increases, mixed forests and deciduous broadleaf forests will shift towards northern China. Grassland, shrubland and wooded grassland will extend to southeastern China. The RCM-project climate changes generally have caused positive vegetation changes; vegetation cover will probably improve 19% relative to baseline, and the forest will expand to 8% relative to baseline, while the desert and bare ground will reduce by about 13%. [ABSTRACT FROM AUTHOR]