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In this paper, field spectroradiometer and aboveground biomass (AGB) data were acquired at the harvest stage at two sites in semiarid grasslands in Inner Mongolia, China. Four forms of commonly used vegetation indices (VIs) using all possible combinations of narrow-band first derivative (FDR) and raw reflectance (RR) were calculated, and the best FDR-VIs and RR-VIs were chosen by a linear regression analysis against AGB. The stepwise multiple linear regression (SMLR) models using the optimal FDR-VIs, RR-VIs, and both FDR-VIs and RR-VIs as input variables were developed for estimating the AGB. Results demonstrated that the estimation performance using the best FDR-VIs were comparable with the best RR-VIs, while the accuracy has been further improved by combining the best FDR-VIs and RR-VIs (maximum decrease in RMSE of 44% and minimum RMAE of 4.7%). The approach was found to be an important step for more accurate and effective grassland AGB estimation. [ABSTRACT FROM AUTHOR]

Biomass is an important indicator for monitoring vegetation degradation and productivity. This study tests the applicability of Hyperspectral Remote-Sensing in situ measurements for high-precision estimation aboveground biomass (AGB) on regional scales of Khorchin grassland in Inner Mongolia, China. In order to improve prediction accuracy of AGB which is frequently used as an indicator of aboveground net primary productivity (ANPP), this paper combined ground measurement with remote sensing inversion to build the spectral model. The ground normalized difference vegetation index (SOC_NDVI) calculated from ground spectral of grassland vegetation which was measured by a portable visible/NIR hyperspectral spectrometer (SOC 710). Meanwhile, the remote normalized difference vegetation index (TM_NDVI) calculated from remote spectral of grassland vegetation which was measured by Thematic Mapper (TM) from Landsat 8 which launched by National Aeronautics and Space Administration (NASA). According to regression analysis for the relationship between AGB and SOC_NDVI, SOC_NDVI and TM_NDVI, the evaluation model for aboveground biomass was developed (AGB = 12.523×e3.370×(0.462×TM_NDVI+0.413), standard error = 24.74 g m-2, R2 = 0.636, p < 0.001). The model accuracy verification results show that the correlation between the measured value and the predicted value of biomass was better with low model standard error. The model could make up for the lack of timeliness and comprehensiveness of conventional ground biomass survey, and provide technical support for high-precision large-area productivity estimation and ecological degradation diagnosis of regional scale grassland. [ABSTRACT FROM AUTHOR]

Since the typical destructive methods for measuring aboveground biomass (AGB) have many limitations, a variety of non-destructive techniques have been developed. In this paper, the potential of ground-based hyperspectral remote-sensed data for non-destructive assessment of semi-arid pasture AGB at the peak productive period was investigated. The reflectance spectrometric and AGB data were sampled at the end of the growing season (almost peak biomass) over two locations at pastures in the southern Horqin sandy land, eastern Inner Mongolia, China. All combinations (two-band and three-band) of narrow bands in the forms of simple ratio vegetation index (SRVI), normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI) and enhanced vegetation index (EVI) were used in a linear regression analysis against AGB. The predictive performance of the stepwise multiple linear regression (SMLR) using 4 best VIs as input variables was compared with the performance of multivariate partial least squares regression (PLSR) using all reflectance bands as input variables to estimate AGB. It was observed that the relationship between AGB and single band spectral reflectance was low, while the estimation performance of the best VIs based on all available wavebands was improved considerably. In addition, the best VIs based on all available wavebands had considerably better fitting performance than those based on traditionally used wavebands for estimating AGB. In comparison to PLSR using the full individual reflectance as input variables, SMLR using the best VIs as input variables performed much better, with the maximum decrease in RMSECV of 37% and the relative mean absolute errors always below 12.5%. The study demonstrated the high potential to estimate pasture AGB, which is a proxy for pasture forage yield, at the peak productive period using a hyperspectral technique. [ABSTRACT FROM AUTHOR]

Three-North Shelterbelt Forest (TSF) program, is one of six key forestry programs and has a 73-year construction period, from 1978 to 2050. Quantitative analysis of the carbon sequestration of shrubs in this region is important for understanding the overall function of carbon sequestration of the forest and other terrestrial ecosystems in China. This study investigated the distribution area of shrubland in the TSF region based on remote sensing images in 1978 and 2008, and calculated the carbon density of shrubland in combination with the field investigation and previous data from published papers. The carbon sequestration quantity and rate from 1978 to 2008 was analyzed for four sub-regions and different types of shrubs in the TSF region. The results revealed that: 1) The area of shrubland in the study area and its four sub-regions increased during the past thirty years. The area of shrubland for the whole region in 2008 was 1.2 × 10 ha, 72.8% larger than that in 1978. The Inner Mongolia-Xinjiang Sub-region was the largest shrubland distribution area, while the highest coverage rate was found in the North China Sub-region. 2) In decreasing order of their carbon sequestration, the four types of shrubs considered in this study were Hippophae rhamnoides, Caragana spp., Haloxylon ammodendron and Vitex negundo var. heterophylla. The carbon sequestration of H. rhamnoides, with a maximum mean carbon density of 16.5 Mg C/ha, was significantly higher than that of the other three species. 3) The total carbon sequestration of shrubland in the study region was 4.5 × 10 Mg C with a mean annual carbon sequestration of 1.5 × 10 Mg C. The carbon density in the four sub-regions decreased in the following order: the Loess Plateau Sub-region, the North China Sub-region, the Northeast China Sub-region and the Inner Mongolia-Xinjiang Sub-region. The paucity of studies and data availability on the large-scale carbon sequestration of shrub species suggests this study provides a baseline reference for future research in this area. [ABSTRACT FROM AUTHOR]

Aims: The anthropogenic nitrogen (N) input has considerable consequences on soil microbial biomass, which is critical for biogeochemical cycling. As prevalent grassland management, mowing may reduce soil N storage, enhance plant biodiversity and soil microbial carbon (C) availability, all of which are important regulators of soil microbial biomass. However, convincing data is still scarce about how mowing affects soil microbial biomass under N enrichment. Methods: The interactive effects of N addition (0 – 50 g N m−2 yr−1) and mowing (unmown vs. mown) on soil microbial biomass C (MBC) were measured by manipulating 6 years' N addition experiment in Inner Mongolia grassland of China. Results: Mowing increased soil inorganic N concentration, available Cu2+ concentration, plant aboveground net primary production (ANPP), species richness, Shannon-Wiener biodiversity and ratio of fungal to bacterial biomass, and decreased soil available Mn2+ concentration under N enrichment. Mowing also significantly reduced the dominance of Leymus chinensis. While mowing did not affect the soil MBC compared with that in only N added plots. The soil MBC was positively regulated by plant species richness and biodiversity, while was negatively regulated by ANPP, soil inorganic N, available Cu2+ and Mn2+ concentration in mown plots. Conclusions: The results highlight that mowing cannot mitigate the negative effects of N enrichment on soil MBC. The soil, plant and microbial properties play important roles in regulating the response of soil MBC to mowing in N-enriched soil. This work improves the mechanistic understanding of the linkages between plant community and soil microbial C cycling. [ABSTRACT FROM AUTHOR]

The quantification of grassland above-ground biomass (AGB) and grazing intensity (GI) and their distribution in space is of great significance to grassland management and eco-conservation. Remote-sensing technology is widely applied, but it is difficult to measure accurately when monitoring GI. In this study, the neural network, random forest and statistical function models of the relationship between Landsat NDVI and AGB were constructed by field survey and literature data collection in Inner Mongolia grassland, China. By comparing the accuracy among the three models, we constructed a remote-sensing retrieving model of grass AGB. We also estimated the grassland AGB during the peak growing season (August) for Inner Mongolia. Frequency histograms were then made to identify AGB thresholds under four GI levels (light or ungrazed, moderate grazing, overgrazing and extreme grazing) for each of three grassland types (meadow steppe, typical steppe and desert steppe). This study shows that the random forest model simulates grass AGB more accurately than other models. The spatial distribution of AGB in Inner Mongolia grasslands showed a tendency of decreasing from southeast to northwest, with an increasing trend in the last 10 years. The four GI levels in 2021 accounted for 18%, 25%, 36% and 21% of the grasslands in Inner Mongolia, respectively, and over the last 10 years the GI first improved and then deteriorated. This study provides a guideline to remote monitoring for grassland AGB and GI, and supplies scientific support for sustainable management and grassland restoration of large-scale grasslands. [ABSTRACT FROM AUTHOR]

Grassland is the primary land use in China, which has experienced extensive degradation in recent decades due to overexploitation. Here, we conducted field experiments to quantify the degraded grassland's recovery rate in Northeast Inner Mongolia in response to restoration measures, including fallow + enclosure (FE) and mowing + enclosure (ME) in comparison to livestock grazing (LG), since 2005. Plant community properties were surveyed and aboveground biomass (AGB) sampled in summer 2013. Our results showed that the regional dominant species Leymus chinensis retained its dominance under FE, whereas a range of forb species gained dominance under LG. Vegetative cover was maximal under FE and minimal under LG. The least amount of vegetation development and AGB were observed under LG. However, plant diversity showed an opposite pattern, with maximal diversity under LG and minimal under FE. Statistical analysis revealed that AGB was negatively associated with plant diversity for all treatments except ME. For ME, a positive AGB-diversity relationship was characterized, suggesting that mowing intensity was a controlling factor for the AGB-diversity relationship. Overall, these results demonstrated that enclosure plus mowing represented an effective conservation measure that provided fair support to forage production and a progressive pathway to a more resilient grassland system. [ABSTRACT FROM AUTHOR]

Vegetation green aboveground biomass is an important parameter of terrestrial ecosystem process-based models, and is closely related to photosynthetic activity. In this paper, the hyperspectral predictors for estimating green aboveground biomass were evaluated based on field spectral and corresponding biophysical parameter measurements during the growing seasons of 2009 and 2010 in the desert steppe of Inner Mongolia. Results showed that the performance of red-edge reflectance curve area (between normalized reflectance curve and wavelength in 680–780 nm region) was better than that of traditional vegetation indices (VIs) and red-edge position (REP). The model based on red-edge reflectance curve area produced a lower standard error of prediction (26.4 g m−2) compared with the optimal narrow-band ratio vegetation index (RVI) (37.4 g m−2), normalized difference vegetation index (NDVI) (33.5 g m−2), soil-adjusted vegetation index (SAVI) (37.5 g m−2) and modified soil-adjusted vegetation index (MSAVI) (38.6 g m−2). Statistical analyses performed on the slopes and intercepts of the fitted lines between actual and predicted values demonstrated that no statistical differences (P > 0.05) were found in regards to slope = 1 and intercept = 0 for red-edge reflectance curve area and optimal SAVI and MSAVI, whereas the slope and intercept based on optimal RVI were different (P < 0.05) from 1 to 0 respectively, and the slope based on optimal NDVI was different (P < 0.05) from 1. In conclusion, the red-edge reflectance curve area method is a practical and suitable technique for complementing the existing methods on estimation of green aboveground biomass in arid and semi-arid areas. [Copyright &y& Elsevier]

District heating (DH) is rapidly expanding in China, which consumes a significant share of the national energy and aggravates pollution problems. Among the Northern provinces, Inner Mongolia Autonomous Region (IMAR) has a large area of district heating which relies heavily on coal boilers. In order to achieve the clean heating development goal, this paper first presents a detailed investigation and mapping of the clean heating resources at county levels in the IMAR. Combined with the different energy-saving strategies, four pathways for future DH were proposed. Considering the forecasted scenarios of DH for years 2025 and 2035, this study compares the proposed pathways in terms of primary energy consumption and economic benefits. It was observed that by replacing coal boilers with clean heating resources, the clean heating sources pathway could reduce coal consumption by about 41%, with 33% annual cost savings in 2018 compared with the reference pathway. However, when taking building renovation into account, the economically optimal renovation plan lies between the proposed SHRP and FHRP. The conclusions from this study provide valuable suggestions for clean heating developments in the IMAR and other parts of Northern China. • Clean heating resources in Inner Mongolia Autonomous Region are investigated and mapped in details. • 4 district heating pathways combining renovations in heating sources and buildings are proposed. • Heat demand for years 2025 and 2035 are forecasted. • Replacing coal boilers with clean heating resources can reducing both energy consumption and annual cost. • The economically optimal building renovation plan lie between the proposed pathways. [ABSTRACT FROM AUTHOR]

Bioenergy will play an intimate and critical role in energy supply and carbon mitigation in the future. In recent years, "customizing the development of bioenergy to local conditions" and "prioritizing distributed utilization" have been the two key principles that have been released by the Chinese government to promote the national‐ and provincial‐level development of bioenergy. While many recognize the importance of bioenergy in achieving low‐carbon transition, little is known about the high‐resolution distribution of usable biomass feedstock and technical bioenergy potential in China, which brings about uncertainties and additional challenges for creating localized utilization plans. We propose a new assessment framework that integrates crop growth models, a land suitability assessment, and the geographic information systems to address these knowledge gaps. Distributions of 11 types of usable biomass feedstock and three kinds of technical bioenergy potential are mapped out through specific transformation technologies at 1 km resolution. At the national level, the final technical biogas potential is 1.91 EJ. The technical bioethanol potential (0.04–0.96 EJ) from the energy crop can supply 0.13–3.12 times the bioethanol demand for the consumption of E10 gasoline in 2015. The technical heat potential (1.06 EJ) can meet 20% of the demand for heating in all provinces (5.38 EJ). Most of the 2020 bioenergy goals can be achieved, excluding that for bioethanol, which will need to require more cellulosic ethanol from residues. At the provincial level, Henan and Inner Mongolia have the potential to develop clean heating alternatives via the substitution of agroforestry residues for coal. The results can provide a systematic analysis of the distribution of biomass feedstocks and technical bioenergy potential in China. With economic factors taken into consideration in further research, it can also support national and provincial governments in making bioenergy development plans in an effective and timely manner. [ABSTRACT FROM AUTHOR]

Climate change has become a global concern for scientists as it is affecting almost every ecosystem. Larix gmelinii and Betula platyphylla are native and dominant forest species in the Daxing'anling Mountains of Inner Mongolia, playing a major role in carbon sequestration of this region. This study was carried out to assess the effect of climate variables including precipitation and temperature on the biomass of Larix gmelinii and Betula platyphylla forests. For this purpose, we used the climate-sensitive stem biomass allometric model for both species separately to find out accurate stem biomass along with climatic factors from 1950 to 2016. A total of 66 random plots were taken to attain the data from this study area. Larix gmelinii and Betula platyphylla stem biomass have a strong correlation with annual precipitation (R2 = 0.86, R2 = 0.71, R2 = 0.79, and R2 = 0.59) and maximum temperature (R2 = 0.76, R2 = 0.64, R2 = 0.67, and R2 = 0.52). However, annual minimum temperature (R2 = 0.58, R2 = 0.43, R2 = 0.55, and R2 = 0.46) and annual mean temperature (R2 = 0.40, R2 = 0.22, R2 = 0.36, and R2 = 0.19) have a relatively negative impact on tree biomass. Therefore, we suggest that both species have a very strong adaptive nature with climatic variation and hence can survive under drought and high-temperature stress climatic conditions. [ABSTRACT FROM AUTHOR]

Summary: Heavy rainfall events are expected to increase in frequency and severity in the future. However, their effects on natural ecosystems are largely unknown, in particular with different seasonal timing of the events and recurrence over multiple years.We conducted a 4 yr manipulative experiment to explore grassland response to heavy rainfall imposed in either the middle of, or late in, the growing season in Inner Mongolia, China. We measured hierarchical responses at individual, community and ecosystem levels.Surprisingly, above‐ground biomass remained stable in the face of heavy rainfall, regardless of seasonal timing, whereas heavy rainfall late in the growing season had consistent negative impacts on below‐ground and total biomass. However, such negative biomass effects were not significant for heavy rainfall in the middle of the growing season. By contrast, heavy rainfall in the middle of the growing season had greater positive effects on ecosystem CO2 exchanges, mainly reflected in the latter 2 yr of the 4 yr experiment. This two‐stage response of CO2 fluxes was regulated by increased community‐level leaf area and leaf‐level photosynthesis and interannual variability of natural precipitation.Overall, our study demonstrates that ecosystem impacts of heavy rainfall events crucially depend on the seasonal timing and multiannual recurrence. Plant physiological and morphological adjustment appeared to improve the capacity of the ecosystem to respond positively to heavy rainfall. [ABSTRACT FROM AUTHOR]

Under the aim of searching for a more sustainable grazing management system, a mixed management system (grazing and haymaking alternate annually) was proposed and tested against traditional management system (used consistently either for grazing or haymaking) in the semiarid grassland of Inner Mongolia with a field manipulation experiment. The responses of aboveground biomass to the two grazing management systems were examined across different levels of organization (i.e., species, plant functional group, and community) and in five consecutive years from 2005 to 2009. The effects of the two systems on seed production potential of four dominant species ( Leymus chinensis, Stipa grandis, Agropyron cristatum, Cleistogenes squarrosa) were also investigated. Our results demonstrate that, in the traditional system, aboveground biomass production across all the levels of organization was reduced by grazing. In mixed system, however, no significantly negative relationship between the biomass response and stocking rate was detected at all organization levels. Precipitation fluctuation had strong influence on biomass responses, and compared to the traditional system the slope of the biomass-precipitation relationship tends to be higher in the mixed system. This effect might be attributed to the more positive response of L. chinensis and A. cristatum to increase in precipitation. In the traditional system, both the ratio and the density of reproductive tillers of the grazing subplots were significantly reduced compared to the haymaking or ungrazed control plots. In the mixed system, there was no significant difference between the haymaking subplots and the ungrazed control plots, regardless of the grazing pressures imposed on the haymaking subplots in the previous growing season. Our findings suggest that the mixed system mitigates the sheep grazing-induced species shift and it tends to be more responsive to increasing precipitation as compared to the traditional system. Therefore, replacement of the traditional grazing strategy with the mixed system could provide an important contribution to sustainable land-use of the Inner Mongolia grasslands. [ABSTRACT FROM AUTHOR]

Although nitrogen addition and recovery from degradation can both promote production of grassland biomass, these two factors have rarely been investigated in combination. In this study, we established a field experiment with six N-treatment (CK, 10, 20, 30, 40, 50 g N m−2 yr−1) on five fields with different degradation levels in the Inner Mongolian steppe of China from 2011-2013. Our observations showed that while the external nitrogen increased the aboveground biomass in all five grasslands, the magnitude of the effects differed with the severity of degradation. Fields with a higher level of degradation tended to have a higher saturation value (20 g N m−2 yr−1) than those with a lower degradation level ( < 10 g N m−2 yr−1). After three years of experimentation, species richness showed little change across degradation levels. Among the four functional groups of grasses, sedges, forbs and legumes, grasses shared the most similar response patterns with those of the whole community, demonstrating the predominant role that they play in the restoration of grassland under a stimulus of nitrogen addition. [ABSTRACT FROM AUTHOR]