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Lifespan of fine roots plays important roles in regulating carbon (C) cycling in terrestrial ecosystems. Determination of root lifespan and elucidation of its regulatory mechanism in different plant communities are essential for accurate prediction of C cycling from ecosystem to regional scales. Temperate steppes in Inner Mongolia grasslands have three major types, i.e., Stipa krylovii, Stipa grandis and Stipa breviflora grasslands. There have been no studies to compare the root dynamics among the three types of grasslands. In the present study, we determined root lifespan of the three grasslands using the rhizotron. We found that root lifespan differed substantially among the three types of grasslands within the temperate steppes of Inner Mongolia, such that root lifespan of Stipa breviflora > Stipa grandis > Stipa krylovii grasslands. Root lifespan across the three types of grasslands in the Inner Mongolian temperate steppes displayed a similar temporal pattern, i.e. lifespan of the roots produced in spring and autumn was shortest and longest, respectively, whereas lifespan of summer-produced roots was between that of roots produced in spring and autumn. The spatial and temporal differences in root lifespan across the three types of grasslands were mainly determined by contents of soluble sugars in roots of the dominant species. The differences in root lifespan across the major types of grasslands and different seasons highlight the necessity to take into account these differences in the prediction of C cycling within grassland ecosystem by the simulating model. [ABSTRACT FROM AUTHOR]

Enhanced deposition of atmospheric nitrogen (N) resulting from anthropogenic activities has negative impacts on plant diversity in grassland ecosystems globally. Several mechanisms have been proposed to explain the species loss. Ion toxicity due to N deposition-induced soil acidification has been suggested to be responsible for species loss in acidic grasslands, while few studies have evaluated the role of soilmediated homeostasis of ions in species loss under elevated N deposition in alkaline grasslands. To determine whether soil-mediated processes are involved in changes in species composition by N deposition, the effects of 9 yrN addition on soil properties, aboveground biomass (AGB) and species composition were investigated in an Inner Mongolia steppe. Low to moderate N addition rate (2, 4, 8 g N m-2 yr-1) significantly enhanced AGB of grasses, while high N addition rate (> 16 g N m-2 yr-1) reduced AGB of forbs, leading to an overall increase in AGB of the community under low to moderate N addition rates. Forb richness was significantly reduced by N addition at rates greater than 8 gNm-2 yr-1, while no effect of N addition on grass richness was observed, resulting in decline in total species richness. N addition depleted base cations (Ca2+, Mg2+ and K+) in soils, reduced soil pH and mobilized Mn2+, Fe3+ and Cu2+ ions in soils. Soil inorganic-N concentration was negatively correlated with forb richness, explaining 27.2% variation of forb richness. The concentrations of base cations (Ca2+ and Mg2+) and metal ions (Mn2+ and Cu2+) showed positively and negatively linear correlation with forb richness, accounting for 25.9 and 41.4% variation of forb richness, respectively. These results reveal that disruption of metal ion homeostasis in soils by N addition, particularly enhanced release of soil Mn2+ and Cu2+ may be associated with reduction in forb richness in temperate steppe of Inner Mongolia. [ABSTRACT FROM AUTHOR]

As important green energy, wind power and photovoltaic power have great development prospects. The suitability evaluation of wind and solar power plants is a popular research field, which is related to the sustainable and healthy development of wind and solar power generation. In this paper, based on multiple dimensions such as land types, climatic conditions, topographic features and policy environment, we selected 10 indicators and combined (analytical hierarchy process) AHP method to build a suitability assessment model for evaluating the suitability of solar and wind power in Inner Mongolia, China. The findings revealed that, Inner Mongolia has a great potential to generate wind and solar electricity, for wind power, the category of 'excellent' regions covers 83855 km2 and represents 7.10% of the total surface area; for solar power, 7.66% (nearly 90420 km2) are classified as 'excellent'. The suitability of both solar and wind energy in the western region is considered to have the most suitable development region, parts of Alxa League and Bayannur City have great potential for combined wind and solar power generation. The research results could provide important technical and data support for capacity evaluation and power station location decision. [ABSTRACT FROM AUTHOR]

In the current situation of frequent forest fires, the study of forest burned area mapping is important. However, there is still room for improvement in the accuracy of existing forest burning area mapping methods. Therefore, in this paper, an unsupervised method based on fire index enhancement and GRNN (General Regression Neural Network) is proposed for automated forest burned area mapping from single-date post-fire remote sensing imagery. The proposed method first uses adaptive spatial context information to enhance the generated fire index to improve its ability to indicate the burned areas. Then the uncertainty analysis is performed on the enhanced fire index to extract reliable burned samples and non-burned samples for subsequent classifier training. Finally, the improved GRNN model considering the spatial correlation of pixels is used as a classifier to binarize the enhanced fire index to generate the final burned area map. Based on two commonly used fire indexes, NBR (Normalized Burn Ratio) and BAI (Burned Area Index), this paper conducts burned area mapping experiments on a post-fire image of a forest area in Inner Mongolia, China to test the effectiveness of the proposed method, and two commonly used threshold methods (Otsu and Kmeans clustering) are also used to conduct burned area mapping based on threshold segmentation of fire index for comparison experiments. The experimental results prove the effectiveness and superiority of the proposed method. The proposed method is unsupervised and automated, so it has high application value and potential under the current situation of frequent forest fires. [ABSTRACT FROM AUTHOR]

Optimum management of irrigated crops in regions with shallow saline groundwater requires a careful balance between application of irrigation water and upward movement of salinity from the groundwater. Few field-validated surrogate models are available to aid in the management of irrigation water under shallow groundwater conditions. The objective of this research is to develop a model that can aid in the management using a minimum of input data that are field validated. In this paper a 2-year field experiment was carried out in the Hetao irrigation district in Inner Mongolia, China, and a physically based integrated surrogate model for arid irrigated areas with shallow groundwater was developed and validated with the collected field data. The integrated model that links crop growth with available water and salinity in the vadose zone is called Evaluation of the Performance of Irrigated Crops and Soils (EPICS). EPICS recognizes that field capacity is reached when the matric potential is equal to the height above the groundwater table and thus not by a limiting hydraulic conductivity. In the field experiment, soil moisture contents and soil salt conductivity at five depths in the top 100 cm, groundwater depth, crop height, and leaf area index were measured in 2017 and 2018. The field results were used for calibration and validation of EPICS. Simulated and observed data fitted generally well during both calibration and validation. The EPICS model that can predict crop growth, soil water, groundwater depth, and soil salinity can aid in optimizing water management in irrigation districts with shallow aquifers. [ABSTRACT FROM AUTHOR]

On August 10, 2016, China launched its first C-band full polarimetric radar satellite, named Gaofen-3 (GF-3), for urban and agriculture monitoring, landslide detection, ocean applications, etc. According to the design specification, GF-3 is expected to work at -35 dB crosstalk and 0.5 dB channel imbalance, with less than 10 degree error. The absolute radiometric bias is expected to be less than 1.5 dB in a single scene and 2.0 dB when operating for a long time. To complete the calibration and evaluation, the Institute of Electronics, Chinese Academy Sciences (IECAS) built a test site at Inner Mongolia, and deployed active reflectors (ARs) and trihedral corner reflectors (CRs) to solve and evaluate the hardware distortion. To the best of the authors' knowledge, the product accuracy of GF-3 has not been comprehensively evaluated in any open publication. The remote sensing community urgently requires a detailed report about the product accuracy and stability, before any subsequent application. From June to August of 2017, IECAS begun its second round ground campaign and deployed 10 CRs to evaluate product distortions. In this paper, we exploit Inner Mongolia CRs to investigate polarimetric and radiometric accuracy of QPSI I Stripmap. Although some CRs found fall into AR side lobe, the rest CRs enable us to preliminarily evaluate the accuracy of some special imaging beams. In the experimental part, the image of July 6, 2017 was checked by 5 trihedral CRs and the integration estimation method demonstrated the crosstalk varying from -42.65 to -32.74 dB, and the channel imbalance varying from -0.21 to 0.47 with phase error from -2.4 to 0.2 degree. Comparing with the theoretical radar cross-section of 1.235 m trihedral CR, i.e. 35 dB, the radiometric error varies about 0.20±0.29 dB in HH channel and 0.40±0.20 dB in VV channel. [ABSTRACT FROM AUTHOR]

Rapid population growth is increasing pressure on the world water resources. Agriculture will require crops to be grown with less water. This is especially the case for the closed Yellow River basin, necessitating a better understanding of the fate of irrigation water in the soil. In this paper, we report on a field experiment and develop a physically based model for the shallow groundwater in the Hetao irrigation district in Inner Mongolia, in the arid middle reaches of the Yellow River. Unlike other approaches, this model recognizes that field capacity is reached when the matric potential is equal to the height above the groundwater table and not by a limiting soil conductivity. The field experiment was carried out in 2016 and 2017. Daily moisture contents at five depths in the top 90 cm and groundwater table depths were measured in two fields with a corn crop. The data collected were used for model calibration and validation. The calibration and validation results show that the model-simulated soil moisture and groundwater depth fitted well. The model can be used in areas with shallow groundwater to optimize irrigation water use and minimize tailwater losses. [ABSTRACT FROM AUTHOR]

Land use change is an important theme of the research on the impact of human interaction on global change. In this paper, two phases of land use data were interpretated from remote sensing images of 1978 and 2018, and the spatial-temporal characteristics of land use change in China's Inner Mongolia Region from 1978 to 2018 were analyzed. The results indicated that grasslands and arable land are mainly distributed in the central and eastern region of Inner Mongolia, forest land are mainly distributed in the eastern region, and unused land is mainly distributed in the western region. From 1978 to 2018, the area of arable land in Inner Mongolia decreased by 9,000 km2, forest land increased by 900 km2, and the area of grassland decreased by 1,400 km2. Urban and rural, industrial mines, and residential land continued to increase with an area of 7,800 km2; and unused land increased by an area of 11,500 km2. It was indicated that after 40 years of development, land use in urban and rural areas, industrial mines, and residential areas caused by human activities in the Inner Mongolia Region has increased significantly. At the same time, the policy of returning farmland to forests to protect the environment has achieved significant results. [ABSTRACT FROM AUTHOR]

Water availability is one of the most important environmental controls on vegetation phenology, especially in semi-arid regions. It is often represented in terms of soil moisture in small-scale studies, whereas it tends to be represented by precipitation in large-scale (e.g., regional) studies. Clearly, soil moisture is the more appropriate indicator for root water uptake and vegetation growth/phenology. Its potential advantage and applicability needs to be demonstrated at regional scales. The paper presents a data-based regional study of the effectiveness of novel water and temperature-based indices to predict spring vegetation green-up dates based on the Normalized Difference Vegetation Index (NDVI) observations in the grasslands of Inner Mongolia, China. The macro-scale hydrological model, VIC (Variable Infiltration Capacity), is employed to generate a soil moisture database across the region. In addition to a standard index based on temperature, two potential hydrology-based indices for prediction of spring onset dates are defined, based on the simulated soil moisture data as well as on observed precipitation data. Results indicate that the correspondence between the NDVI-derived green-up onset date and the soil-moisture-derived potential onset date exhibits a significantly better correlation as a function of increasing aridity compared to that based on precipitation. In this way the soil-moisture-based index is demonstrated to be superior to the precipitation-based index in terms of capturing grassland spring phenology. The results also showed that both of the hydrological (water-based) indices were superior to the thermal (temperature-based) index in determining the patterns of grass green-up in the Inner Mongolia region, indicating water availability to be the dominant control on average. The understanding about the relative controls on grassland phenology and the effectiveness of alternative indices to capture these controls are important for future studies of vegetation phenology change under climate change. [ABSTRACT FROM AUTHOR]

Water-soluble organic carbon (WSOC) in the cryosphere can significantly influence the global carbon cycle and radiation budget. However, WSOC in the snowpack has received little scientific attention to date. This study reports the fluorescence characteristics, absorption properties, and radiative effects of WSOC based on 34 snow samples collected from sites in northeastern China. A significant degree of regional WSOC variability is found, with concentrations ranging from 0.5±0.2 to 5.7±3.7µ g g -1 (average concentration: 3.6±3.2µ g g -1). The three principal fluorescent components of WSOC are identified as (1) the high-oxygenated humic-like substances (HULIS-1) of terrestrial origin, (2) the low-oxygenated humic-like substances (HULIS-2) of mixed origin, and (3) the protein-like substances (PRLIS) derived from autochthonous microbial activity. In southeastern Inner Mongolia (SEIM), a region dominated by desert and exposed soils, the WSOC exhibits the highest humification index (HIX) but the lowest fluorescence (FI) and biological (BIX) indices; the fluorescence signal is mainly attributed to HULIS-1 and thus implicates soil as the primary source. By contrast, the HIX (FI and BIX) value is the lowest (highest), and the percentage of PRLIS is the highest in the remote area of northeastern Inner Mongolia (NEIM), suggesting a primarily biological source. For south and north of northeastern China (SNC and NNC), both of which are characterized by intensive agriculture and industrial activity, the fluorescence signal is dominated by HULIS-2, and the HIX, FI, and BIX values are all moderate, indicating the mixed origins for WSOC (anthropogenic activity, microbial activity, and soil). We also observe that, throughout northeastern China, the light absorption of WSOC is dominated by HULIS-1, followed by HULIS-2 and PRLIS. The contribution of WSOC to albedo reduction (average concentration: 3.6 µ g g -1) in the ultraviolet–visible (UV–Vis) band is approximately half that of black carbon (BC average concentration: 0.6 µ g g -1). Radiative forcing is 3.8 (0.8) W m -2 in old (fresh) snow, equating to 19 % (17 %) of the radiative forcing of BC. These results indicate that WSOC has a profound impact on snow albedo and the solar radiation balance. [ABSTRACT FROM AUTHOR]

Daily global surface solar irradiance (SSI) is of great importance parameter in the surface energy balance, climate modelling, and solar energy utilization. However, it is still challenging to extend the estimated instantaneous solar radiation to the daily global SSI from either geostationary satellites or polar-orbiting satellites. In this study, a method for estimating the daily global SSI is proposed based on the Himawari-8 hourly SSI products using pixel-by-pixel Gaussian fitting to simulate the diurnal SSI variation. Compared with ground-based observations, the daily global SSI estimated by Gaussian fitting have higher accuracy under various weather conditions than by the simple accumulation or quadratic polynomials, and the coefficient of determination (R2) between the estimated and observed values exceeds 0.86. The verification results also show different estimation accuracies under different weather conditions. The root-mean-square errors (RMSEs) under clear-sky and all-sky conditions are 2.36 MJ/m2 and 3.06 MJ/m2, respectively. In addition, experimental results show that the daily global SSI in China has high spatial heterogeneity. For higherelevation areas with low cloud cover, such as the Qinghai-Tibet Plateau, Inner Mongolia, and Northwest China, the daily global SSI is higher than other areas. In contrast, the values of daily global SSI is relatively low in the eastern regions of Southwest and Northeast China. [ABSTRACT FROM AUTHOR]

Water clarity serves as a sensitive tool for understanding the spatial pattern and historical trend in lakes' trophic status. Despite the wide availability of remotely sensed data, this metric has not been fully explored for long-term environmental monitoring. To this end, we utilized Landsat top-of-atmosphere reflectance products within Google Earth Engine in the period 1984–2018 to retrieve the average Secchi disk depth (SDD) for each lake in each year. Three SDD datasets were used for model calibration and validation from different field campaigns mainly conducted during 2004–2018. The red / blue band ratio algorithm was applied to map SDD for lakes (>0.01 km 2) based on the first SDD dataset, where R2=0.79 and relative RMSE (rRMSE) =61.9 %. The other two datasets were used to validate the temporal transferability of the SDD estimation model, which confirmed the stable performance of the model. The spatiotemporal dynamics of SDD were analyzed at the five lake regions and individual lake scales, and the average, changing trend, lake number and area, and spatial distribution of lake SDDs across China were presented. In 2018, we found the number of lakes with SDD <2 m accounted for the largest proportion (80.93 %) of the total lakes, but the total areas of lakes with SDD of <0.5 and >4 m were the largest, both accounting for about 24.00 % of the total lakes. During 1984–2018, lakes in the Tibetan–Qinghai Plateau region (TQR) had the clearest water with an average value of 3.32±0.38 m, while that in the northeastern region (NLR) exhibited the lowest SDD (mean 0.60±0.09 m). Among the 10 814 lakes with SDD results for more than 10 years, 55.42 % and 3.49 % of lakes experienced significant increasing and decreasing trends, respectively. At the five lake regions, except for the Inner Mongolia–Xinjiang region (MXR), more than half of the total lakes in every other region exhibited significant increasing trends. In the eastern region (ELR), NLR and Yungui Plateau region (YGR), almost more than 50 % of the lakes that displayed increase or decrease in SDD were mainly distributed in the area range of 0.01–1 km 2 , whereas those in the TQR and MXR were primarily concentrated in large lakes (>10 km 2). Spatially, lakes located in the plateau regions generally exhibited higher SDD than those situated in the flat plain regions. The dataset is freely available at the National Tibetan Plateau Data Center (10.11888/Hydro.tpdc.271571, Tao et al., 2021). [ABSTRACT FROM AUTHOR]

Gradual riparian wetland drying is increasingly sensitive to global warming and contributes to climate change. Riparian wetlands play a significant role in regulating carbon and nitrogen cycles. In this study, we analyzed the emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) from riparian wetlands in the Xilin River basin to understand the role of these ecosystems in greenhouse gas (GHG) emissions. Moreover, the impact of the catchment hydrology and soil property variations on GHG emissions over time and space was evaluated. Our results demonstrate that riparian wetlands emit larger amounts of CO2 (335–2790 mgm-2h-1 in the wet season and 72–387 mgm-2h-1 in the dry season) than CH4 and N2O to the atmosphere due to high plant and soil respiration. The results also reveal clear seasonal variations and spatial patterns along the transects in the longitudinal direction. N2O emissions showed a spatiotemporal pattern similar to that of CO2 emissions. Near-stream sites were the only sources of CH4 emissions, while the other sites served as sinks for these emissions. Soil moisture content and soil temperature were the essential factors controlling GHG emissions, and abundant aboveground biomass promoted the CO2 , CH4 , and N2O emissions. Moreover, compared to different types of grasslands, riparian wetlands were the potential hotspots of GHG emissions in the Inner Mongolian region. Degradation of downstream wetlands has reduced the soil carbon pool by approximately 60 %, decreased CO2 emissions by approximately 35 %, and converted the wetland from a CH4 and N2O source to a sink. Our study showed that anthropogenic activities have extensively changed the hydrological characteristics of the riparian wetlands and might accelerate carbon loss, which could further affect GHG emissions. [ABSTRACT FROM AUTHOR]

For the first time in the North China Plain (NCP) region, we investigated the seasonal variations in submicron particles (NR-PM 1) and their chemical composition at a background mountainous site of Xinglong using an Aerodyne high-resolution time-of-flight aerosol mass spectrometer. The average concentration of NR-PM 1 was highest in autumn (15.1 µgm-3) and lowest in summer (12.4 µgm-3), with a greater abundance of nitrate in spring (34 %), winter (31 %) and autumn (34 %) and elevated organics (40 %) and sulfate (38 %) in summer. PM 1 in Xinglong showed higher acidity in summer and moderate acidity in spring, autumn and winter, with average pH values of 2.7±0.6 , 4.2±0.7 , 3.5±0.5 and 3.7±0.6 , respectively, which is higher than those estimated in the United States and Europe. The size distribution of all PM 1 species showed a consistent accumulation mode peaking at approximately 600–800 nm (dva), indicating a highly aged and internally mixed nature of the background aerosols, which was further supported by the source appointment results using positive matrix factorization and multilinear engine analysis. Significant contributions of aged secondary organic aerosol (SOA) in organic aerosol (OA) were resolved in all seasons (>77 %), especially in summer. The oxidation state and the process of evolution of OAs in the four seasons were further investigated, and an enhanced carbon oxidation state (-0.45 –0.10) and O/C (0.54–0.75) and OM/OC (1.86–2.13) ratios – compared with urban studies – were observed, with the highest oxidation state appearing in summer, likely because of the relatively stronger photochemical processing that dominated the formation processes of both less oxidized OA (LO-OOA) and more oxidized OA (MO-OOA). Aqueous-phase processing also contributed to the SOA formation and prevailed in winter, with the share to MO-OOA being more important than that to LO-OOA. In addition, regional transport also played an important role in the variations in SOA. Especially in summer, continuous increases in SOA concentration as a function of odd oxygen (Ox=O3+NO2) were found to be associated with the increases in wind speed. Furthermore, backward trajectory analysis showed that higher concentrations of submicron particles were associated with air masses transported short distances from the southern regions in all four seasons, while long-range transport from Inner Mongolia (western and northern regions) also contributed to summertime particulate pollution in the background areas of the NCP. Our results illustrate that the background particles in the NCP are influenced significantly by aging processes and regional transport, and the increased contribution of aerosol nitrate highlights how regional reductions in nitrogen oxide emissions are critical for remedying occurrence of nitrate-dominated haze events over the NCP. [ABSTRACT FROM AUTHOR]

Grassland aboveground biomass (AGB) is a critical component of the global carbon cycle and reflects ecosystem productivity. Although it is widely acknowledged that dynamics of grassland biomass is significantly regulated by climate change, in situ evidence at meaningfully large spatiotemporal scales is limited. Here, we combine biomass measurements from six long-term (> 30 years) experiments and data in existing literatures to explore the spatiotemporal changes in AGB in Inner Mongolian temperate grasslands. We show that, on average, annual AGB over the past 4 decades is 2561, 1496 and 835 kg ha -1 , respectively, in meadow steppe, typical steppe and desert steppe in Inner Mongolia. The spatiotemporal changes of AGB are regulated by interactions of climatic attributes, edaphic properties, grassland type and livestock. Using a machine-learning-based approach, we map annual AGB (from 1981 to 2100) across the Inner Mongolian grasslands at the spatial resolution of 1 km. We find that on the regional scale, meadow steppe has the highest annual AGB, followed by typical and desert steppe. Future climate change characterized mainly by warming could lead to a general decrease in grassland AGB. Under climate change, on average, compared with the historical AGB (i.e. average of 1981–2019), the AGB at the end of this century (i.e. average of 2080–2100) would decrease by 14 % under Representative Concentration Pathway (RCP) 4.5 and 28 % under RCP8.5. If the carbon dioxide (CO 2) enrichment effect on AGB is considered, however, the estimated decreases in future AGB can be reversed due to the growing atmospheric CO 2 concentrations under both RCP4.5 and RCP8.5. The projected changes in AGB show large spatial and temporal disparities across different grassland types and RCP scenarios. Our study demonstrates the accuracy of predictions in AGB using a modelling approach driven by several readily obtainable environmental variables and provides new data at a large scale and fine resolution extrapolated from field measurements. [ABSTRACT FROM AUTHOR]

Propagule traits vary among biomes along geographical gradients such as longitude, but the mechanisms that underlie these variations remain unclear. This study aims to explore seed mass variation patterns of different biome types along a longitudinal gradient and their underlying variation mechanisms by involving an in-depth analysis on the variation of seed mass, fruit type spectra, growth forms and dispersal mode spectra in Inner Mongolia and northeastern China. Plant community characterization and seed collection were conducted in 26 sites spreading over five vegetation types and covering 622 species belonging to 66 families and 298 genera. We found there are significantly declining trends for mean seed mass, vertebrate-dispersed species richness and fleshy-fruited species richness along a longitudinal gradient from forests to desert grasslands. However, we also found the lowest average seed mass and the smallest proportion of species dispersed by vertebrates occurring at typical grasslands in the five biomes. The variations of average seed mass display high congruence with transition of growth form spectra. The selection for these propagule attributes is driven mainly by climatic factors such as precipitation, temperature, soil moisture and evaporation, as well as by internal biotic factors such as growth forms, canopy coverage and leaf area (Ackerly and Donoghue, 1998). A hypothesis was provided that environmental factors and botanical traits that favor greater water availability lead to emergence (or speciation) of species with large seeds or fleshy fruits with high water content. Due to greater water availability and increasing leaf area, much more photosynthate (photosynthesis production) and allometric growth then ultimately increase the biome average seed mass from west to east. Phylogenetic signal or diversity are not found to be significantly involved in the effect on the patterns. A novel mechanistic framework and mathematical model are provided to expound seed variation among species or biomes. [ABSTRACT FROM AUTHOR]

As a typical arid and semi-arid stony Mountain, the Daqing Mountain District，Severe loss of soil water resources has become the most important limiting factor for afforestation survival rate and forest growth in this area. This paper takes the Pinus tabulaeformis plantation belt of Daqing Mountain in Inner Mongolia as the research object，Focusing on the effectiveness and water retention of soil moisture, Based on the kinetic theory of soil water，The soil moisture characteristics of different densities and forest age under similar site conditions were systematically studied, In order to maximize the use of limited natural precipitation through forest-learning measures, Increase soil water resources and maintain them for a longer period of time so that trees can be fully utilized，It provides an important scientific theoretical basis for improving the survival rate and preservation rate of afforestation, expanding forest resources and restoring forest vegetation under the premise of suitable tree in this area and arid and semi-arid area. Research shows that，The rainfall and was the main factor to affect the soil water content dynamic.The CV of soil moisture decreased as soil depth increased. Through dividing the effective threshold of soil moisture, we calculate the effective value of soil moisture of different stand, only in July and September the soil moisture could reach the range of middle efficiency water,another months the soil moisture were in the range of difficult efficiency water.The plants of different density stands were under soil water stress. The proportion of evapotranspir -ation was 60.19%,and it was the maximal output. By the premise of water equilibrium,computing the soil water bearying capacity of vegetation of Pinus tabulaeformis plantation in Daqing Mountain.It was 3000 stock/ha. [ABSTRACT FROM AUTHOR]

This study compared carbon dioxide (CO2) fluxes over three grassland ecosystems in China, including a temperate semiarid steppe in Inner Mongolia (NMG), an alpine shrub-meadow in Qinghai (HB), and an alpine meadowsteppe in Tibet (DX). Measurements were made in 2004 and 2005 using the eddy covariance technique. Objectives were to document the seasonality of the net ecosystem exchange of CO2 (NEE) and its components, gross ecosystem photosynthesis (GEP), and ecosystem respiration (Reco), and to examine how environmental factors affect the CO2 exchange in these grassland ecosystems. The 2005 growing season (from May to September) was warmer than that of 2004 across the three sites, and precipitation in 2005 was less than that in 2004 at NMG and DX. The magnitude of CO2 fluxes (daily and annual sums) was largest at HB, which also showed the highest temperature sensitivity of Reco among the three sites. A stepwise multiple regression analysis showed that the seasonal variation of GEP, Reco, and NEE of the alpine shrubmeadow was mainly controlled by air temperature, whereas leaf area index can likely explain the seasonal variation in GEP, Reco, and NEE of the temperate steppe. The CO2 fluxes of the alpine meadow-steppe were jointly affected by soil moisture and air temperature. The alpine shrub-meadow acted as a net carbon sink over the two study years, whereas the temperate steppe and alpine meadow-steppe acted as net carbon sources. Both GEP and Reco were reduced by the summer and spring drought in 2005 at NMG and DX, respectively. The accumulated leaf area index during the growing season (LAIsum) played a key role in the interannual and intersite variation of annual GEP and Reco across the study sites and years, whereas soil moisture contributed most significantly to the variation in annual NEE. Because LAIsum was significantly correlated with soil moisture at a depth of 20 cm, we concluded that the available soil moisture other than annual precipitation was the most important factor controlling the variation in the CO2 budgets of different grassland ecosystems in China. [ABSTRACT FROM AUTHOR]

Located in western Inner Mongolia, the Badain Jaran Desert is the second largest desert in China and consists of a regular series of stable megadunes, among which over 70 permanent lakes exist. The unexpected lakes in desert attracted research interests on exploring the hydrological process under this particular landscape; however, a very few literatures exist on the diurnal and spatial variation of the drying front in this area, which is the main issue in the desert hydrological process to characterize the movement of water in soil. In order to understand the drying front in the Badain Jaran Desert, a field campaign was conducted by the observations of soil physical parameters and micrometeorological parameters. With the field data, the performance of a vadose zone soil water balance model, the HYDRUS, was verified and calibrated. Then, the HYDRUS was used to produce the spatial and temporal information of coupled water, water vapour and heat transport in sand to characterize the variation pattern of the drying front before, during and after the rainfall. Finally, the deepest drying front was applied to determine the effective infiltration, which is defined as the amount of soil water captured by the sand beneath the deepest drying front by infiltrating water of an incident rainfall event. [ABSTRACT FROM AUTHOR]

This work explored the spatial variation of C3/C4 distribution in the Inner Mongolia, P. R. China, steppe by geostatistical analysis of carbon isotope data of vegetation and sheep wool. Standing community biomass (n=118) and sheep wool (n=146) were sampled in a ∼0.2 Mio km² area. Samples from ten consecutive years (1998-2007) were obtained. Community biomass samples represented the carbon isotopic composition of standing vegetation on about 1000 m² ("community-scale"), whereas the spatio-temporal scale of wool reflected the isotope composition of the entire area grazed by the herd during a 1-yr period (²5-10 km², "farm-scale"). Pair wise sampling of wool and vegetation revealed a 13C-enrichment of 2.7±0.7%o (95% confidence interval) in wool relative to vegetation, but this shift exhibited no apparent relationships with environmental parameters or stocking rate. The proportion of C4 plants in aboveground biomass (PC4, %) was estimated with a two-member mixing model of 13C discrimination by C3 and C4 vegetation (13Δ3 and 13Δ4 respectively), in accounting for the effects of changing 13C in atmospheric CO2 on sample isotope composition, and of altitude and aridity on 13Δ3 PC4 averaged 19%, but the variation was enormous: full-scale (0% to 100%) at community-scale, and 0% to 85% at farm-scale. The farm-scale variation of PC4 exhibited a clear regional pattern over a range of ∼250 km. Importantly PC4 was significantly higher above the 22°C isotherm of the warmest month, which was obtained from annual high-resolution maps and averaged over the different sampling years. This is consistent with predictions from C3/C4 crossover temperature of quantum yield or light use efficiency in C3 and C4 plants. Still, temperature gradients accounted for only 10% of the farm-scale variation of PC4, indicating that additional factors control PC4 on this scale. [ABSTRACT FROM AUTHOR]