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China is the largest wheat-producing country in the world. Wheat is one of the two major staple cereals consumed in the country and about 60% of Chinese population eats the grain daily. To safeguard the production of this important crop, about 85% of wheat areas in the country are under irrigation or high rainfall conditions. However, wheat production in the future will be challenged by the increasing occurrence and magnitude of adverse and extreme weather events. In this paper, we present an analysis that combines outputs from a wide range of General Circulation Models (GCMs) with observational data to produce more detailed projections of local climate suitable for assessing the impact of increasing heat stress events on wheat yield. We run the assessment at 36 representative sites in China using the crop growth model CSM-CropSim Wheat of DSSAT 4.5. The simulations based on historical data show that this model is suitable for quantifying yield damages caused by heat stress. In comparison with the observations of baseline 1996-2005, our simulations for the future indicate that by 2100 the projected increases in heat stress would lead to an ensemble-mean yield reduction of −7.1% (with a probability of 80%) and −17.5% (with a probability of 96%) for winter wheat and spring wheat, respectively, under the irrigated condition. Although such losses can be fully compensated by CO fertilization effect as parameterized in DSSAT 4.5, a great caution is needed in interpreting this fertilization effect because existing crop dynamic models are unable to incorporate the effect of CO acclimation (the growth-enhancing effect decreases over time) and other offsetting forces. [ABSTRACT FROM AUTHOR]

Warming of the climate system is unequivocal, and the change of climate variables will eventually have a great impact on vegetation cover and agricultural practices, especially in the arid area Xinjiang in China, whose agriculture and ecosystems are heavily vulnerable to climate change. In this paper, normalized difference vegetation index (NDVI) was used to study the vegetation growth and its response to climate change in Xinjiang. Firstly, two NDVI datasets (Global Inventory Modeling and Mapping Studies (GIMMS) and Moderate Resolution Imaging Spectroradiometer (MODIS)) were merged through a pixel-wise regression analysis to obtain a long time series of NDVI data, and then, relationships between yearly NDVI and yearly climate variables, and monthly NDVI and monthly climate variables were extensively investigated for grassland and cropland in northern and southern Xinjiang, respectively. Results show the following: (1) there was an increasing trend in NDVI for both grassland and cropland in both northern and southern Xinjiang over the past decades and trends were significant except that for grassland in northern Xinjiang; (2) precipitation and evaporation were more important than temperature for grassland in northern Xinjiang, while precipitation and temperature were more important than evaporation for grassland in southern Xinjiang and cropland in both northern and southern Xinjiang; (3) NDVI was highly correlated with accumulated monthly precipitation instead of monthly precipitation, and there was a lagged effect of precipitation, temperature, and evaporation on NDVI change. However, lagged effects were only significant in specific months. The results could be helpful to agricultural practices; e.g., based on lagged effect of precipitation, irrigation in July is very important for crop growth. [ABSTRACT FROM AUTHOR]

Understanding the seasonal behaviour of a subtropical forest and its inter-annual variation is crucial to understanding and monitoring its ecosystem function in the context of global warming. Based on the Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index dataset, a wavelet transform method was used to investigate the inter-annual variations of vegetation phenology in a subtropical mountain and hill region in Fujian, China, during 2001-2010. The results show a distinct inter-annual variation of vegetation phenology related to climate variability even if most areas presented non-significant trends. The start dates significantly advanced and end dates delayed in 2003 and 2008, due to anomalously warm conditions. There was generally a gradient of increasing start dates, and earlier end dates of vegetation growing season, due to colder temperatures at higher altitudes. However, the altitudinal phenology relationship also depends on its corresponding rainfall conditions. Earlier start dates were observed at higher altitudes during rainfall deficit years such as 2008, which coincides with relatively abundant rainfall at higher altitudes. This paper reveals that vegetation phenology was coupled with altitudinal gradient, with distinct responses at different combinations of alternate temperature and precipitation conditions variability. [ABSTRACT FROM AUTHOR]

This paper presents a multi-proxy reconstruction of the climate change in Caotanhu wetland using pollen, phytolith and charcoal records, and the data of loss of ignition (LOl), grain size analysis, and susceptibility. Results reveal that between 4550 and 2500 cal. a BP, a dry climatic condition was not favorable for the accumulation of peat. Since 2500 cal. a BP, the climate became humid and the wetland developed with abundant freshwater aquatic plants, which contributed to peat accumulation. Nevertheless, alternate periods of rain and dry climate occurred during that period. Between 2500 and 1810 cal. a BP (550 BC-140 AD), the climate was more humid than at present. A lot of emerged plants, such as Phragmites, Typha and Sparganium, and freshwater green algae grew in the wetland which was surrounded by desert-steppe vegetation composed mainly of Chenopodiaceae, Artemisia, Compositae and Thalictrum. However, from 1810 to 1160 cal. a BP (140-790 AD), the water level started to decrease and hydrophyte species reduced greatly, but some Phragmites still grew in the wetland and around it was desert vegetation with high proportion of Chenopodiaceae and Artemisia. Then from 1160 to 650 a BP (790-1300 AD), it entered a period of desert-steppe with abundant mesic and xerophytic plants. And a lot of aquatic plants prevailed in the wetland. Here, what is noticeable is that percentages of arboreal pollen, consisting mainly of Betula and Picea, increased greatly and reached a maximal value of 27.2%, in which, Betula percentages rose to 23.2%. Hence, it is reasonable to conclude that Betula grew in the highland of the wetland, or Picea timberline shifted downward resulting in the increase of percentages of Betula and Picea pollen, which were transported into the wetland by flood or wind. But since 650 cal. a BP, desert vegetation prevailed around the wetland again with dominant Chenopodiaceae and Artemisia, and the climate was similar to modern one. Despite some aquatic plants still growing in the wetland at that time, their amounts diminished greatly. [ABSTRACT FROM AUTHOR]

Recent climatic changes have affected terrestrial net primary productivity (NPP). This paper presents an investigation of the impact of climatic changes on Chinese terrestrial vegetation NPP by analyzing 18 years' (1982 to 1999) climatic data and satellite observations of vegetation activity. Results indicate that climatic changes in China have eased some critical climatic constraint on plant growth. (1) From 1982 to 1999, modeled NPP increased by 1.42% · a-1 in water-limited regions of Northwest China, 1.46% · a-1 in temperature-limited regions of Northeast China and Tibet Plateau, and 0.99% · a-1 in radiation-limited regions of South China and East China. (2) NPP increased by 24.2%, i.e. 0.76 petagram of carbon (Pg C) over 18 years in China. Changes in climate (with constant vegetation) directly contributed nearly 11.5% (0.36 Pg C). Changes in vegetation (with constant climate) contributed 12.4% (0.40 Pg C), possibly as a result of climate-vegetation feedbacks, changes in land use, and growth stimulation from other mechanisms. (3) Globally, NPP declined during all three major El Niño events (1982 to 1983, 1987 to 1988, and 1997 to 1998) between 1982 and 2000, but Chinese vegetation productivity responded differently to them because of the monsoon dynamics. In the first three events (1982 to 1983, 1987 to 1988, and 1992), Chinese vegetation NPP declined, while in the later two events (1993, 1997 to 1998) increasing obviously. [ABSTRACT FROM AUTHOR]

This paper applies climate change scenarios in China based on the SRES assumptions with the help of RCMs projections by PRECIS (providing regional climates for impacts studies) system introduced to China from the Hadley Centre for Climate Prediction and Research at a high-resolution (50 km×50 km) over China. This research focuses on B2 scenario of SRES. A biogeochemical model "Atmosphere Vegetation Integrated Model (AVIM2)" was applied to simulating ecosystem status in the 21st century. Then vulnerability of ecosystems was assessed based on a set of index of mainly net primary production (NPP) of vegetation. Results show that climate change would affect ecosystem of China severely and there would be a worse trend with the lapse of time. The regions where having vulnerable ecological background would have heavier impacts while some regions with better ecological background would also receive serious impacts. Extreme climate even would bring about worse impact on the ecosystems. Open shrub and desert steppe would be the two most affected types. When the extreme events happen, vulnerable ecosystem would extend to part of defoliate broad-leaved forest, woody grassland and evergreen conifer forest. Climate change would not always be negative. It could be of some benefit to cold region during the near-term. However, in view of mid-term to long-term negative impact on ecosystem vulnerability would be enormously. [ABSTRACT FROM AUTHOR]

Estimates of forest vegetation carbon storage in China varied due to different methods used in the assessments. In this paper, we estimated the forest vegetation carbon storage from the Fourth Forest Inventory Data (FFID) in China using a modified volume-derived method. Results showed that total carbon storage and mean carbon density of forest vegetation in China were 3.8 Pg C (about 1.1% of the global vegetation carbon stock) and 41.32 Mg/ha, respectively. In addition, based on linear multiple regression equation and factor analysis method, we analyzed contributions of biotic and abiotic factors (including mean forest age, mean annual temperature, annual precipitation, and altitude) to forest carbon storage. Our results indicated that forest vegetation carbon storage was more sensitive to changes of mean annual temperature than other factors, suggesting that global warming would seriously affect the forest carbon storage. [ABSTRACT FROM AUTHOR]