Globally, many lakes are drying up, leaving exposed lakebeds where wind erosion releases dust and sand rich in salt and harmful heavy metals into the atmosphere. Therefore, understanding the characteristics and spatial distribution of playa surface crusts is important to recognize the manifestation of salt dust storms. The objective of this study was to explore the playa surface crust types as well as their spatial distribution and evolution of Qehan Lake in Inner Mongolia Autonomous Region, China to understand the salt dust release potential of different types of playa surface crusts. Various crust characteristics were investigated by field sampling in Qehan Lake, and playa surface crusts were further divided into five types: vegetated areas, salt crusts, clay flats, curly crusts, and margins. It should be noted that curly crusts were distributed in clay flats and covered only a small area in Qehan Lake. The spatial distribution characteristics of playa surface crust types were obtained by supervised classification of remote sensing images, and the salt dust release potential of crusts was explored by the wind tunnel experiments. The field investigation of Qehan Lake revealed that playa surface crust types had a circum-lake band distribution from the inside to the outside of this lake, which were successively vegetated areas, clay flats, salt crusts, and margins. The spatial distribution patterns of playa surface crust types were mainly controlled by the hydrodynamics of the playa, soil texture, and groundwater. There was a significant negative correlation between crust thickness and electrical conductivity. The results of the wind tunnel experiments showed that the initial threshold of friction wind velocity for the salt dust release was higher in clay flats (0.7-0.8 m/s) than in salt crusts (0.5-0.6 m/s). Moreover, the particle leap impact processes occurring under natural conditions may reduce this threshold value. Salinity was the main factor controlling the difference in the initial threshold of friction wind velocity for the salt dust release of clay flats and salt crusts. This study provides a scientific reference for understanding how salt dust is released from a lakebed, which may be used for ecological restoration of dry salt lakes.

Many arid areas have very severe climates with extremely high summer temperatures, strong solar radiation, and a lack of drinking water during the driest season. Therefore, antelopes living in arid areas are forced to solve two main problems: avoiding overheating and maintaining water balance. Generally, there are physiological, morphological, and behavioral mechanisms for antelope adaptations to arid environments. Among the mechanisms, behavioral adjustments have a minimal cost and are activated first, while physiological mechanisms are the most energetically costly and involve adaptations to high temperatures when other mechanisms are insufficient. In previous publications, some examples of the antelope behavioral adaptations have been described only rarely, while in this review, we try to clarify all available information on the adaptations of antelopes living in arid areas to their native environments, paying particular attention to behavioral adjustments. Behavioral mechanisms, especially daily activity, diet and microclimate selection, and migrations, are so important and commonly used by antelopes in natural conditions, in which physiological mechanisms are usually not involved. Antelopes adjust their behaviors according to environmental changes so successfully that purely physiological mechanisms are discovered under laboratory conditions; for example, adaptive heterothermia or selective brain cooling phenomenon is difficult to observe in their natural habitats. This review provides a better understanding of the main behavioral mechanisms of antelope adaptations to arid environments and allows for the identification of the key factors for successful conservation of antelopes in their natural habitats.

Shrub species are used in restoration projects on dryland for their facilitation effects, which include environmental improvements and protection from herbivore feeding. Facilitation effects on forage grasses are potentially important in improving grazing capacity on rangelands. However, the morphology-dependent performance of benefactor plants in facilitating forage species growth and supplementation under moderate grazing intensity remains unclear. Here, our main purpose was to measure facilitation performance in terms of the survival of a native forage grass, Agropyron cristatum (L.) Gaertn. (Gramineae)., in accordance with the growth conditions of a sand-fixing benefactor shrub, Caragana microphylla Lam., in the Hulun Buir Grassland, northern China. Six study sites with patches of A. cristatum and C. microphylla were established at the foot of fixed sand dunes. At each site, five quadrats were set in places where C. microphylla coverage was 100% and A. cristatum grew among the shrubs (shrub quadrats), and another five were set where A. cristatum grew alone without C. microphylla (grass quadrats). We measured the morphological traits of C. microphylla and A. cristatum in all 60 quadrats, along with the soil water content and soil temperature. The data were compared between the shrub and grass quadrats by generalized linear mixed-effect models to assess the shrub's facilitation effects. We also used such models to elucidate the relationship between the average height of C. microphylla and the morphological traits of A. cristatum in the shrub quadrats. The maximum height, average grazed height, and the number of seed heads of A. cristatum were greater in the shrub quadrats than in the grass quadrats. The soil surface temperature was lower in the shrub quadrats. The maximum height and seed head number of A. cristatum were positively associated with the average height of C. microphylla. These results suggest that the grazing impact and heat stress were smaller in shrub quadrats than in grass quadrats, and that the degree of this protective effect depended on the shrub height. The shrub canopy seemed to reduce the increase in soil temperature and keep the grass vigorous. Livestock likely avoided grazing grasses in the C. microphylla patches because of the shrub's spiny leaves; only the upper parts of the grass stems (including the seed heads) protruding from the shrub canopy were grazed. The sand-fixing shrub thus moderates the grazing impact and soil temperature, and contributes to vegetation restoration and grazing system sustainability.

The ecological quality of inland areas is an important aspect of the United Nations Sustainable Development Goals (UN SDGs). The ecological environment of Northwest China is vulnerable to changes in climate and land use/land cover, and the changes in ecological quality in this arid region over the last two decades are not well understood. This makes it more difficult to advance the UN SDGs and develop appropriate measures at the regional level. In this study, we used the Moderate Resolution Imaging Spectroradiometer (MODIS) products to generate remote sensing ecological index (RSEI) on the Google Earth Engine (GEE) platform to examine the relationship between ecological quality and environment in Xinjiang during the last two decades (from 2000 to 2020). We analyzed a 21-year time series of the trends and spatial characteristics of ecological quality. We further assessed the importance of different environmental factors affecting ecological quality through the random forest algorithm using data from statistical yearbooks and land use products. Our results show that the RSEI constructed using the GEE platform can accurately reflect the ecological quality information in Xinjiang because the contribution of the first principal component was higher than 90.00%. The ecological quality in Xinjiang has increased significantly over the last two decades, with the northern part of this region having a better ecological quality than the southern part. The areas with slightly improved ecological quality accounted for 31.26% of the total land area of Xinjiang, whereas only 3.55% of the land area was classified as having a slightly worsen (3.16%) or worsen (0.39%) ecological quality. The vast majority of the deterioration in ecological quality mainly occurred in the barren areas Temperature, precipitation, closed shrublands, grasslands and savannas were the top five environmental factors affecting the changes in RSEI. Environmental factors were allocated different weights for different RSEI categories. In general, the recovery of ecological quality in Xinjiang has been controlled by climate and land use/land cover during the last two decades and policy-driven ecological restoration is therefore crucial. Rapid monitoring of inland ecological quality using the GEE platform is projected to aid in the advancement of the comprehensive assessment of the UN SDGs.

Exploring the current runoff characteristics after the large-scale implementation of the Grain for Green (GFG) project and investigating its sensitivities to potential drivers are crucial for water resource prediction and management. Based on the measured runoff data of 62 hydrological stations in the Weihe River Basin (WRB) from 2006 to 2018, we analyzed the temporal and spatial runoff characteristics in this study. Correlation analysis was used to investigate the relationships between different runoff indicators and climate-related factors. Additionally, an improved Budyko framework was applied to assess the sensitivities of annual runoff to precipitation, potential evaporation, and other factors. The results showed that the daily runoff flow duration curves (FDCs) of all selected hydrological stations fall in three narrow ranges, with the corresponding mean annual runoff spanning approximately 1.50 orders of magnitude, indicating that the runoff of different hydrological stations in the WRB varied greatly. The trend analysis of runoff under different exceedance frequencies showed that the runoff from the south bank of the Weihe River was more affluent and stable than that from the north bank. The runoff was unevenly distributed throughout the year, mainly in the flood season, accounting for more than 50.00% of the annual runoff. However, the trend of annual runoff change was not obvious in most areas. Correlation analysis showed that rare-frequency runoff events were more susceptible to climate factors. In this study, daily runoff under 10%-20% exceeding frequencies, consecutive maximum daily runoff, and low-runoff variability rate had strong correlations with precipitation, aridity index, and average runoff depth on rainy days. In comparison, daily runoff under 50%-99% exceeding frequencies, consecutive minimum daily runoff, and high-runoff variability rate had weak correlations with all selected impact factors. The sensitivity analysis results suggested that the sensitivity of annual runoff to precipitation was always higher than that to potential evaporation. The runoff about 87.10% of the selected hydrological stations were most sensitive to precipitation changes, and 12.90% were most sensitive to other factors. The spatial pattern of the sensitivity analysis indicated that in relatively humid southern areas, runoff was more sensitive to potential evaporation and other factors, and less sensitive to precipitation.

Check dams are widely used on the Loess Plateau in China to control soil and water losses, develop agricultural land, and improve watershed ecology. Detailed information on the number and spatial distribution of check dams is critical for quantitatively evaluating hydrological and ecological effects and planning the construction of new dams. Thus, this study developed a check dam detection framework for broad areas from high-resolution remote sensing images using an ensemble approach of deep learning and geospatial analysis. First, we made a sample dataset of check dams using GaoFen-2 (GF-2) and Google Earth images. Next, we evaluated five popular deep-learning-based object detectors, including Faster R-CNN, You Only Look Once (version 3) (YOLOv3), Cascade R-CNN, YOLOX, and VarifocalNet (VFNet), to identify the best one for check dam detection. Finally, we analyzed the location characteristics of the check dams and used geographical constraints to optimize the detection results. Precision, recall, average precision at intersection over union (IoU) threshold of 0.50 (AP₅₀), IoU threshold of 0.75 (AP₇₅), and average value for 10 IoU thresholds ranging from 0.50-0.95 with a 0.05 step (AP_50-95), and inference time were used to evaluate model performance. All the five deep learning networks could identify check dams quickly and accurately, with AP_50-95, AP₅₀, and AP₇₅ values higher than 60.0%, 90.0%, and 70.0%, respectively, except for YOLOv3. The VFNet had the best performance, followed by YOLOX. The proposed framework was tested in the Yanhe River Basin and yielded promising results, with a recall rate of 87.0% for 521 check dams. Furthermore, the geographic analysis deleted about 50% of the false detection boxes, increasing the identification accuracy of check dams from 78.6% to 87.6%. Simultaneously, this framework recognized 568 recently constructed check dams and small check dams not recorded in the known check dam survey datasets. The extraction results will support efficient watershed management and guide future studies on soil erosion in the Loess Plateau.

Soil water content is a key controlling factor for vegetation restoration in sand dunes. The deep seepage and lateral migration of water in dunes affect the recharge process of deep soil water and groundwater in sand dune ecosystems. To determine the influence of vegetation on the hydrological regulation function of sand dunes, we examined the deep seepage and lateral migration of dune water with different vegetation coverages during the growing season in the Horqin Sandy Land, China. The results showed that the deep seepage and lateral migration of water decreased with the increase in vegetation coverage on the dunes. The accumulated deep seepage water of mobile dunes (vegetation coverage<5%) and dunes with vegetation coverage of 18.03%, 27.12%, and 50.65% accounted for 56.53%, 51.82%, 18.98%, and 0.26%, respectively, of the rainfall in the same period. The accumulated lateral migration of water in these dunes accounted for 12.39%, 6.33%, 2.23%, and 7.61% of the rainfall in the same period. The direction and position of the dune slope affected the soil water deep seepage and lateral migration process. The amounts of deep seepage and lateral migration of water on the windward slope were lower than those on the leeward slope. The amounts of deep seepage and lateral migration of water showed a decreasing trend from the bottom to the middle and to the top of the dune slope. According to the above results, during the construction of sand-control projects in sandy regions, we suggest that a certain area of mobile dunes (>13.75%) should be retained as a water resource reservoir to maintain the water balance of artificial fixed dune ecosystems. These findings provide reliable evidence for the accurate assessment of water resources within the sand dune ecosystem and guide the construction of desertification control projects.

Litter and root activities may alter the temperature sensitivity (Q₁₀) of soil respiration. However, existing studies have not provided a comprehensive understanding of the effects of litter and root carbon inputs on the Q₁₀ of soil respiration in different seasons. In this study, we used the trench method under in situ conditions to measure the total soil respiration (R_total), litter-removed soil respiration (R_no-litter), root-removed soil respiration (R_no-root), and the decomposition of soil organic matter (i.e., both litter and root removal; R_SOM) in different seasons of pioneer (Populus davidiana Dode) and climax (Quercus liaotungensis Mary) forests on the Loess Plateau, China. Soil temperature, soil moisture, litter biomass, fine root biomass, litter carbon, and root carbon were analyzed to obtain the drive mechanism of the Q₁₀ of soil respiration in the two forests. The results showed that the Q₁₀ of soil respiration exhibited seasonality, and the Q₁₀ of soil respiration was higher in summer. The litter enhanced the Q₁₀ of soil respiration considerably more than the root did. Soil temperature, soil moisture, fine root biomass, and litter carbon were the main factors used to predict the Q₁₀ of different soil respiration components. These findings indicated that factors affecting the Q₁₀ of soil respiration highly depended on soil temperature and soil moisture as well as related litter and root traits in the two forests, which can improve our understanding of soil carbon-climate feedback in global warming. The results of this study can provide reference for exploring soil respiration under temperate forest restoration.

Wind erosion is a key global environmental problem and has many adverse effects. The Mu Us Sandy Land of northern China is characterized by an arid climate, where vegetation patches and bare sand patches are usually distributed mosaically, and aeolian activities occur frequently. Vegetation plays a significant role in controlling wind erosion. Artemisia ordosica is the most dominant native plant species in the Mu Us Sandy Land. It is urgent to study the wind-proof and sand-fixing effects of Artemisia ordosica in the Mu Us Sandy Land. This study analyzed the wind-proof and sand-fixing effects of Artemisia ordosica based on the field data of wind regimes, aeolian sediment transport, and surface change of Artemisia ordosica plots with four coverages (denoted as site A, site B, site C, and site D) in the Mu Us Sandy Land during the period from 1 June 2018 to 29 June 2019. The coverages of Artemisia ordosica at site A, site B, site C, and site D were 2%, 16%, 29%, and 69%, respectively. The annual average wind speeds at 2.0 m height above the ground for site A, site B, site C, and site D were 3.47, 2.77, 2.21, and 1.97 m/s, respectively. The annual drift potentials were 193.80, 69.72, 15.05, and 6.73 VU at site A, site B, site C, and site D, respectively. The total horizontal aeolian sediment fluxes during the period from 2-3 June 2018 to 6 June 2019 at site A, site B, site C, and site D were 4633.61, 896.80, 10.54, and 6.14 kg/m, respectively. Site A had the largest surface changes, and the surface changes at site B were significantly weaker than those at site A, whereas the surface changes at site C and site D were minimal. The results indicated that Artemisia ordosica significantly reduced the wind speed, drift potential, aeolian sediment transport, and surface changes. The higher the coverage of Artemisia ordosica is, the more obvious the effects of wind-proof and sand-fixing. Wind erosion would be effectively controlled in the Mu Us Sandy Land if the coverage of Artemisia ordosica is greater than 29%. These results provide a scientific basis for evaluating the ecosystem service function of Artemisia ordosica and the vegetation protection and construction projects in the Mu Us Sandy Land.

Drought has pronounced and immediate impacts on agricultural production, especially in semi-arid and arid rainfed agricultural regions. Quantification of drought and its impact on crop yield is essential to agricultural water resource management and food security. We investigated drought and its impact on winter wheat (Triticum aestivum L.) yield in the Chinese Loess Plateau from 2001 to 2015. Specifically, we performed a varimax rotated principal component analysis on drought severity index (DSI) separately for four winter wheat growth periods: pre-sowing growth period (PG), early growth period (EG), middle growth period (MG), and late growth period (LG), resulting in three major subregional DSI dynamics for each growth period. The county-level projections of these major dynamics were then used to evaluate the growth period-specific impacts of DSI on winter wheat yields by using multiple linear regression analysis. Our results showed that the growth period-specific subregions had different major DSI dynamics. During PG, the northwestern area exhibited a rapid wetting trend, while small areas in the south showed a slight drying trend. The remaining subregions fluctuated between dryness and wetness. During EG, the northeastern and western areas exhibited a mild wetting trend. The remaining subregions did not display clear wetting or drying trends. During MG, the eastern and southwestern areas showed slight drying and wetting trends, respectively. The subregions scattered in the north and south had a significant wetting trend. During LG, large areas in the east and west exhibited wetting trends, whereas small parts in south-central area had a slight drying trend. Most counties in the north showed significant and slight wetting trends during PG, EG, and LG, whereas a few southwestern counties exhibited significant drying trends during PG and MG. Our analysis identified close and positive relationships between yields and DSI during LG, and revealed that almost all of the counties were vulnerable to drought. Similar but less strong relationships existed for MG, in which northeastern and eastern counties were more drought-vulnerable than other counties. In contrast, a few drought-sensitive counties were mainly located in the southwestern and eastern areas during PG, and in the northeastern corner of the study region during EG. Overall, our study dissociated growth period-specific and spatial location-specific impacts of drought on winter wheat yield, and might contribute to a better understanding of monitoring and early warning of yield loss.

Numerous ecological factors influence a plant's ability to live and grow, in which dryness is a substantial constraint on plant growth in arid and semi-arid areas. In response to a specific environmental stress, plants can use the most effective bacteria to support and facilitate their growth and development. Today, plant growth promoting rhizobacteria (PGPR) is widely used to reduce drought stress on plant growth. In this study, the effects of drought on Festuca ovina L. germination, growth, and nutrient absorption were investigated using PGPR in a factorial test with a completely random design under four water regimes. Soil water content was kept at 100% FC (field capacity), 70% FC (FC), 50% FC, and 30% FC. The treatments were inoculated with Azotobacter vinelandii, Pantoea agglomerans+Pseudomonas putida, and a mixture of bio-fertilizers. Results showed that the effects of drought stress were significantly reduced (P<0.05) when A. vinelandii and P. agglomerans+P. putida were used separately, however, the combined treatment of bio-fertilizers had a greater influence on seed germination than the single application. P. agglomerans+P. putida under 30% FC condition resulted in higher increases in stem, root length, and plant dry biomass. The highest uptake of nutrients was observed for the combined treatment of bio-fertilizers under 30% FC condition. Therefore, the use of A. vinelandii and P. agglomerans+P. putida, applied separately or combined, increased tolerance to drought stress in F. ovina by increased germination indices, dry weight, stem length, and root length. Because of the beneficial effects of PGPR on the growth characteristics of plants under drought conditions and the reduction of negative effects of drought stress, inoculating F. ovina seeds with Azotobacter and Pseudomonas is recommended to improve their growth and development characteristics under drought conditions. PGPR, as an affordable and environmentally friendly method, can improve the production of forage in water-stress rangelands.

In the current scenario, Lake Urmia, one of the vastest hyper saline lakes on the Earth, has been affected by serious environmental degradation. Using different satellite images and observational data, this study investigated the changes in the lake for the period 1970-2020 based on the effects of climate change and several human-induced processes on Lake Urmia, such as population growth, excessive dam construction, low irrigation water use efficiency, poor water resources management, increased sediment flow into the lake, and lack of political and legal frameworks. The results indicated that between 1970 and 1997, the process of change in Lake Urmia was slow; however; the shrinkage was faster between 1998 and 2018, with about 30.00% of the lake area disappearing. As per the findings, anthropogenic factors had a much greater impact on Lake Urmia than climate change and prolonged drought; the mismanagement of water consumption in the agricultural sector and surface and underground water withdrawals in the basin have resulted in a sharp decrease in the lake's surface. These challenges have serious implications for water resources management in Lake Urmia Basin. Therefore, we provided a comprehensive overview of anthropogenic factors on the changes in Lake Urmia along with existing opportunities for better water resources management in Lake Urmia Basin. This study serves as a guideline framework for climate scientists and hydrologists in order to assess the effects of different factors on lake water resources and for decision-makers to formulate strategies and plans according to the management task.

The greatest failure rate of reforestation programs is basically related to water deficit, especially at the seedling stage. Therefore, the main objective of this work is to investigate the responses of three accessions of carob trees (Ceratonia siliqua L.) with 2-year-old from different climate regions to drought generated by four water treatments: Tc (250 mm), T1 (180 mm), T2 (100 mm), and T3 (50 mm). The first accession (A1) comes from the protected national park of Ichkeul in northern Tunisia. This zone belongs to the bioclimatic sub-humid stage. The second accession (A2) comes from Melloulech, located in the center-east of Tunisia, belonging to the bioclimatic semi-arid stage. The third accession (A3) comes from the mountain of Matmata, located in the south of Tunisia, belonging to the bioclimatic hyper-arid stage. The experiment was undertaken in a greenhouse. Gaz exchange indices (net photosynthesis (A), stomatal conductance (g_s), transpiration rate (E), and internal CO₂ concentration (C_i)) were determined. Predawn (Ψ_pd) and midday (Ψ_md) leaf water potentials, relative soil water content (SWC), and morphological parameters (plant height (H), number of leaves (NL), number of leaflets (Nl), and number of branches (NB)) were estimated. The results showed that significant differences (P<0.001) were found between physiological and morphological parameters of each accession. The highest growth potential was recorded for Tc treatment in both accessions A1 and A2. Significant decreases in g_s, E, C_i, and SWC were recorded with the increases in water stress applied from treatment T1 to T3. Positive and significant correlations were found between SWC and Ψ_pd for all studied accessions. Ψ_pd and Ψ_md decreased as water stress increased, ranging from -0.96 to -1.50 MPa at sunrise and from -1.94 to -2.83 MPa at midday, respectively, under control and T3 treatments. C. siliqua accessions responded to drought through exhibiting significant changes in their physiological and morphological behavior. Both accessions A1 and A2 showed greater drought tolerance than accession A3. These seedlings exhibit different adaptive mechanisms such as stress avoidance, which are aimed at reducing transpiration, limiting leaf growth, and increasing root growth to exploit more soil water. Therefore, C. siliqua can be recommended for the ecological restoration in Mediterranean ecosystems.

Dew is an essential water resource for the survival and reproduction of organisms in arid and semi-arid regions. Yet estimating the dew amount and quantifying its long-term variation are challenging. In this study, we elucidate the dew amount and its long-term variation in the Kunes River Valley, Northwest China, based on the measured daily dew amount and reconstructed values (using meteorological data from 1980 to 2021), respectively. Four key results were found: (1) the daily mean dew amount was 0.05 mm during the observation period (4 July-12 August and 13 September-7 October of 2021). In 35 d of the observation period (i.e., 73% of the observation period), the daily dew amount exceeded the threshold (>0.03 mm/d) for microorganisms; (2) air temperature, relative humidity, and wind speed had significant impacts on the daily dew amount based on the relationships between the measured dew amount and meteorological variables; (3) for estimating the daily dew amount, random forest (RF) model outperformed multiple linear regression (MLR) model given its larger R² and lower MAE and RMSE; and (4) the dew amount during June-October and in each month did not vary significantly from 1980 to the beginning of the 21^st century. It then significantly decreased for about a decade, after it increased slightly from 2013 to 2021. For the whole meteorological period of 1980-2021, the dew amount decreased significantly during June-October and in July and September, and there was no significant variation in June, August, and October. Variation in the dew amount in the Kunes River Valley was mainly driven by relative humidity. This study illustrates that RF model can be used to reconstruct long-term variation in the dew amount, which provides valuable information for us to better understand the dew amount and its relationship with climate change.

Pendjari Biosphere Reserve (PBR), a primary component of the W-Arly-Pendjari transboundary biosphere reserve, represents the largest intact wild ecosystem and pristine biodiversity spot in West Africa. This savannah ecosystem has long been affected by fire, which is the main ecological driver for the annual rhythm of life in the reserve. Understanding the fire distribution patterns will help to improve its management plan in the region. This study explores the fire regime in the PRB during 2001-2021 in terms of burned area, seasonality, fire frequency, and mean fire return interval (MFRI) by analysing moderate resolution imaging spectroradiometer (MODIS) burned area product. Results indicated that the fire season in the PBR extends from October to May with a peak in early dry season (November-December). The last two fire seasons (2019-2020 and 2020-2021) recorded the highest areas burned in the PBR out of the twenty fire seasons studied. During the twenty years period, 8.2% of the reserve burned every 10-11 months and 11.5% burned annually. The largest part of the reserve burned every one to two years (63.1%), while 8.3% burned every two to four years, 5.8% burned every four to ten years, and 1.9% burned every ten to twenty years. Only 1.3% of the entire area did not fire during the whole study period. Fire returned to a particular site every 1.39 a and the annual percentage of area burned in the PBR was 71.9%. The MFRI (MFRI<2.00 a) was low in grasslands, shrub savannah, tree savannah, woodland savannah, and rock vegetation. Fire regime must be maintained to preserve the integrity of the PBR. In this context, we suggest applying early fire in tree and woodland savannahs to lower grass height, and late dry season fires every two to three years in shrub savannah to limit the expansion of shrubs and bushes. We propose a laissez-faire system in areas in woodland savannah where the fire frequency is sufficient to allow tree growth. Our findings highlight the utility of remote sensing in defining the geographical and temporal patterns of fire in the PBR and could help to manage this important fire prone area.

Climate change caused by past, current, and future greenhouse gas emissions has become a major concern for scientists in the field in many countries and regions of the world. This study modelled future precipitation change by downscaling a set of large-scale climate predictor variables (predictors) from the second generation Canadian Earth System Model (CanESM2) under two Representative Concentration Pathway (RCP) emission scenarios (RCP4.5 and RCP8.5) in the semi-arid Borana lowland, southern Ethiopia. The Statistical DownScaling Model (SDSM) 4.2.9 was employed to downscale and project future precipitation change in the middle (2036-2065; 2050s) and far (2066-2095; 2080s) future at the local scale. Historical precipitation observations from eight meteorological stations stretching from 1981 to 1995 and 1996 to 2005 were used for the model calibration and validation, respectively, and the time period of 1981-2018 was considered and used as the baseline period to analyze future precipitation change. The results revealed that the surface-specific humidity and the geopotential height at 500 hPa were the preferred large-scale predictors. Compared to the middle future (2050s), precipitation showed a much greater increase in the far future (2080s) under both RCP4.5 and RCP8.5 scenarios at all meteorological stations (except Teletele and Dillo stations). At Teltele station, the projected annual precipitation will decrease by 26.53% (2050s) and 39.45% (2080s) under RCP4.5 scenario, and 34.99% (2050s) and 60.62% (2080s) under RCP8.5 scenario. Seasonally, the main rainy period would shift from spring (March to May) to autumn (September to November) at Dehas, Dire, Moyale, and Teltele stations, but for Arero and Yabelo stations, spring would consistently receive more precipitation than autumn. It can be concluded that future precipitation in the semi-arid Borana lowland is predicted to differ under the two climate scenarios (RCP4.5 and RCP8.5), showing an increasing trend at most meteorological stations. This information could be helpful for policymakers to design adaptation plans in water resources management, and we suggest that the government should give more attention to improve early warning systems in drought-prone areas by providing dependable climate forecast information as early as possible.

Restoration of mining soils is important to the vegetation and environment. This study aimed to explore the variations in soil nutrient contents, microbial abundance, and biomass under different gradients of substrate amendments in mining soils to select effective measures. Soil samples were collected from the Bayan Obo mining region in Inner Mongolia Autonomous Region, China. Contents of soil organic matter (SOM), available nitrogen (AN), available phosphorus (AP), available potassium (AK), microbial biomass carbon/microbial biomass nitrogen (MBC/MBN) ratio, biomass, and bacteria, fungi, and actinomycetes abundance were assessed in Agropyron cristatum L. Gaertn., Elymus dahuricus Turcz., and Medicago sativa L. soils with artificial zeolite (AZ) and microbial fertilizer (MF) applied at T0 (0 g/kg), T1 (5 g/kg), T2 (10 g/kg), and T3 (20 g/kg). Redundancy analysis (RDA) and technique for order preference by similarity to ideal solution (TOPSIS) were used to identify the main factors controlling the variation of biomass. Results showed that chemical indices and microbial content of restored soils were far greater than those of control. The application of AZ significantly increases SOM, AN, and AP by 20.27%, 23.61%, and 40.43%, respectively. AZ significantly increased bacteria, fungi, and actinomycetes abundance by 0.63, 3.12, and 1.93 times of control, respectively. RDA indicated that AN, MBC/MBN ratio, and SOM were dominant predictors for biomass across samples with AZ application, explaining 87.6% of the biomass variance. SOM, MBC/MBN ratio, and AK were dominant predictors with MF application, explaining 82.9% of the biomass variance. TOPSIS indicated that T2 was the best dosage and the three plant species could all be used to repair mining soils. AZ and MF application at T2 concentration in the mining soils with M. sativa was found to be the most appropriate measure.

The dead fuel moisture content (DFMC) is the key driver leading to fire occurrence. Accurately estimating the DFMC could help identify locations facing fire risks, prioritise areas for fire monitoring, and facilitate timely deployment of fire-suppression resources. In this study, the DFMC and environmental variables, including air temperature, relative humidity, wind speed, solar radiation, rainfall, atmospheric pressure, soil temperature, and soil humidity, were simultaneously measured in a grassland of Ergun City, Inner Mongolia Autonomous Region of China in 2021. We chose three regression models, i.e., random forest (RF) model, extreme gradient boosting (XGB) model, and boosted regression tree (BRT) model, to model the seasonal DFMC according to the data collected. To ensure accuracy, we added time-lag variables of 3 d to the models. The results showed that the RF model had the best fitting effect with an R² value of 0.847 and a prediction accuracy with a mean absolute error score of 4.764% among the three models. The accuracies of the models in spring and autumn were higher than those in the other two seasons. In addition, different seasons had different key influencing factors, and the degree of influence of these factors on the DFMC changed with time lags. Moreover, time-lag variables within 44 h clearly improved the fitting effect and prediction accuracy, indicating that environmental conditions within approximately 48 h greatly influence the DFMC. This study highlights the importance of considering 48 h time-lagged variables when predicting the DFMC of grassland fuels and mapping grassland fire risks based on the DFMC to help locate high-priority areas for grassland fire monitoring and prevention.

Stipagrostis ciliata (Desf.) De Winter is a pastoral C₄ grass grown in arid regions. This research work focused on assessing the growth of S. ciliata accessions derived from two different climate regions (a wet arid region in the Bou Hedma National Park in the central and southern part of Tunisia (coded as WA), and a dry arid region from the Matmata Mountain in the south of Tunisia (coded as DA)) under water stress conditions. Specifically, the study aimed to investigate the phenological and physiological responses of potted S. ciliata seedlings under different water treatments: T₁ (200 mm/a), T₂ (150 mm/a), T₃ (100 mm/a) and T₄ (50 mm/a). Growth phenology, net photosynthesis (P_n), stomatal conductance (g_s), midday leaf water potential (Ψ_md), predawn leaf water potential (Ψ_pd), soil water content (SWC) and soil water potential (Ψ_s) were observed during the water stress cycle (from December 2016 to November 2017). The obtained results showed that the highest growth potential of the two accessions (WA and DA) was recorded under treatment T₁. The two accessions responded differently and significantly to water stress. Photosynthetic parameters, such as P_n and g_s, decreased sharply under treatments T₂, T₃ and T₄ compared to treatment T₁. The higher water stress increased the R/S ratio (the ratio of root dry biomass to shoot dry biomass), with values of 1.29 and 2.74 under treatment T₄ for accessions WA and DA, respectively. Principal component analysis (PCA) was applied, and the separation of S. ciliata accessions on the first two axes of PCA (PC1 and PC2) suggested that accession DA was detected in the negative extremity of PC1 and PC2 under treatments T₁ and T₂. This accession was characterized by a high number of spikes. For treatments T₃ and T₄, both accessions were detected in the negative extremity of PC1 and PC2. They were characterized by a high root dry biomass. Therefore, S. ciliata accessions responded to water stress by displaying significant changes in their behaviours. Accession WA from the Bou Hedma National Park (wet arid region) showed higher drought tolerance than accession DA from the Matmata Mountain (dry arid region). S. ciliata exhibits a significant adaptation capacity for water limitation and may be an important species for ecosystem restoration.

Climate change impacts on grasslands that cover a quarter of the global land area, have become unprecedented during the 21^st century. One of the important ecological realms, arid grasslands of northern China, which occupy more than 70% of the region's land area. However, the impact of climate change on vegetation growth in these arid grasslands is not consistent and lacks corresponding quantitative research. In this study, NDVI (normalized difference vegetation index) and climate factors including temperature, precipitation, solar radiation, soil moisture, and meteorological drought were analyzed to explore the determinants of changes in grassland greenness in Inner Mongolia Autonomous Region (northern China) during 1982-2016. The results showed that grasslands in Inner Mongolia witnessed an obvious trend of seasonal greening during the study period. Two prominent climatic factors, precipitation and soil moisture accounted for approximately 33% and 27% of grassland NDVI trends in the region based on multiple linear regression and boosted regression tree methods. This finding highlights the impact of water constraints to vegetation growth in Inner Mongolia's grasslands. The dominant role of precipitation in regulating grassland NDVI trends in Inner Mongolia significantly weakened from 1982 to 1996, and the role of soil moisture strengthened after 1996. Our findings emphasize the enhanced importance of soil moisture in driving vegetation growth in arid grasslands of Inner Mongolia, which should be thoroughly investigated in the future.

Agriculture faces risks due to increasing stress from climate change, particularly in semi-arid regions. Lack of understanding of crop water requirement (CWR) and irrigation water requirement (IWR) in a changing climate may result in crop failure and socioeconomic problems that can become detrimental to agriculture-based economies in emerging nations worldwide. Previous research in CWR and IWR has largely focused on large river basins and scenarios from the Coupled Model Intercomparison Project Phase 3 (CMIP3) and Coupled Model Intercomparison Project Phase 5 (CMIP5) to account for the impacts of climate change on crops. Smaller basins, however, are more susceptible to regional climate change, with more significant impacts on crops. This study estimates CWRs and IWRs for five crops (sugarcane, wheat, cotton, sorghum, and soybean) in the Pravara River Basin (area of 6537 km²) of India using outputs from the most recent Coupled Model Intercomparison Project Phase 6 (CMIP6) General Circulation Models (GCMs) under Shared Socio-economic Pathway (SSP)245 and SSP585 scenarios. An increase in mean annual rainfall is projected under both scenarios in the 2050s and 2080s using ten selected CMIP6 GCMs. CWRs for all crops may decline in almost all of the CMIP6 GCMs in the 2050s and 2080s (with the exceptions of ACCESS-CM-2 and ACCESS-ESM-1.5) under SSP245 and SSP585 scenarios. The availability of increasing soil moisture in the root zone due to increasing rainfall and a decrease in the projected maximum temperature may be responsible for this decline in CWR. Similarly, except for soybean and cotton, the projected IWRs for all other three crops under SSP245 and SSP585 scenarios show a decrease or a small increase in the 2050s and 2080s in most CMIP6 GCMs. These findings are important for agricultural researchers and water resource managers to implement long-term crop planning techniques and to reduce the negative impacts of climate change and associated rainfall variability to avert crop failure and agricultural losses.

The Mongolian Plateau in East Asia is one of the largest contingent arid and semi-arid areas of the world. Under the impacts of climate change and human activities, desertification is becoming increasingly severe on the Mongolian Plateau. Understanding the vegetation dynamics in this region can better characterize its ecological changes. In this study, based on Moderate Resolution Imaging Spectroradiometer (MODIS) images, we calculated the kernel normalized difference vegetation index (kNDVI) on the Mongolian Plateau from 2000 to 2023, and analyzed the changes in kNDVI using the Theil-Sen median trend analysis and Mann-Kendall significance test. We further investigated the impact of climate change on kNDVI change using partial correlation analysis and composite correlation analysis, and quantified the effects of climate change and human activities on kNDVI change by residual analysis. The results showed that kNDVI on the Mongolian Plateau was increasing overall, and the vegetation recovery area in the southern region was significantly larger than that in the northern region. About 50.99% of the plateau showed dominant climate-driven effects of temperature, precipitation, and wind speed on kNDVI change. Residual analysis showed that climate change and human activities together contributed to 94.79% of the areas with vegetation improvement. Appropriate human activities promoted the recovery of local vegetation, and climate change inhibited vegetation growth in the northern part of the Mongolian Plateau. This study provides scientific data for understanding the regional ecological environment status and future changes and developing effective ecological protection measures on the Mongolian Plateau.

Desertification research in arid and semi-arid regions has always been actively pursued. In China, the problem of desertification in Xinjiang has also received extensive attention. Due to its unique geography, many scholars have conducted corresponding research on the desertification status of Xinjiang. In this paper, we comprehensively reviewed desertification in Xinjiang, and compared the underlying mechanisms of desertification and the status of desertification conditions after the implementation of ecological control projects. On a larger scale, desertification in Xinjiang can be divided into soil salinization inside oases and sandy desertification on the edges of oases. Human activities are considered the main cause of desertification, but natural factors also contribute to varying degrees. Research on the mechanisms of desertification has effectively curbed the development of desertification, but unreasonable use of land resources accelerates the risk of desertification. For desertification control, there are several key points. First, desertification monitoring and the early warning of desertification expansion should be strengthened. Second, monitoring and reversing soil salinization also play an important role in the interruption of desertification process. It is very effective to control soil salinization through biological and chemical methods. Third, the management of water resources is also essential, because unreasonable utilization of water resources is one of the main reasons for the expansion of desertification in Xinjiang. Due to the unreasonable utilization of water resources, the lower reaches of the Tarim River are cut off, which leads to a series of vicious cycles, such as the deterioration of ecological environment on both sides of the river and the worsening of desertification. However, in recent years, various desertification control projects implemented in Xinjiang according to the conditions of different regions have achieved remarkable results. For future studies, research on the stability of desert-oasis transition zone is also significantly essential, because such investigations can help to assess the risk of degradation and control desertification on a relatively large scale.

Extreme precipitation events are one of the most dangerous hydrometeorological disasters, often resulting in significant human and socio-economic losses worldwide. It is therefore important to use current global climate models to project future changes in precipitation extremes. The present study aims to assess the future changes in precipitation extremes over South Asia from the Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models (GCMs). The results were derived using the modified Mann-Kendall test, Sen's slope estimator, student's t-test, and probability density function approach. Eight extreme precipitation indices were assessed, including wet days (RR1mm), heavy precipitation days (RR10mm), very heavy precipitation days (RR20mm), severe precipitation days (RR50mm), consecutive wet days (CWD), consecutive dry days (CDD), maximum 5-day precipitation amount (RX5day), and simple daily intensity index (SDII). The future changes were estimated in two time periods for the 21^st century (i.e., near future (NF; 2021-2060) and far future (FF; 2061-2100)) under two Shared Socioeconomic Pathway (SSP) scenarios (SSP2-4.5 and SSP5-8.5). The results suggest increases in the frequency and intensity of extreme precipitation indices under the SSP5-8.5 scenario towards the end of the 21^st century (2061-2100). Moreover, from the results of multimodel ensemble means (MMEMs), extreme precipitation indices of RR1mm, RR10mm, RR20mm, CWD, and SDII demonstrate remarkable increases in the FF period under the SSP5-8.5 scenario. The spatial distribution of extreme precipitation indices shows intensification over the eastern part of South Asia compared to the western part. The probability density function of extreme precipitation indices suggests a frequent (intense) occurrence of precipitation extremes in the FF period under the SSP5-8.5 scenario, with values up to 35.00 d for RR1mm and 25.00-35.00 d for CWD. The potential impacts of heavy precipitation can pose serious challenges to the study area regarding flooding, soil erosion, water resource management, food security, and agriculture development.

Grassland degradation is influenced by climate change and human activities, and has become a major obstacle for the development of arid and semi-arid areas, posing a series of environmental and socio-economic problems. An in-depth understanding of the inner relations among grassland vegetation dynamics, climate change, and human activities is therefore greatly significant for understanding the variation in regional environmental conditions and predicting future developmental trends. Based on MODIS (moderate resolution imaging spectroradiometer) NDVI (normalized difference vegetation index) data from 2000 to 2020, our objective is to investigate the spatiotemporal changes of NDVI in the Xilin Gol grassland, Inner Mongolia Autonomous Region, China. Combined with 12 natural factors and human activity factors in the same period, the dominant driving factors and their interactions were identified by using the geographic detector model, and multiple scenarios were also simulated to forecast the possible paths of future NDVI changes in this area. The results showed that: (1) in the past 21 a, vegetation cover in the Xilin Gol grassland exhibited an overall increasing trend, and the vegetation restoration (84.53%) area surpassed vegetation degradation area (7.43%); (2) precipitation, wind velocity, and livestock number were the dominant factors affecting NDVI (the explanatory power of these factors exceeded 0.4). The interaction between average annual wind velocity and average annual precipitation, and between average annual precipitation and livestock number greatly affected NDVI changes (the explanatory power of these factors exceeded 0.7). Moreover, the impact of climate change on NDVI was more significant than human activities; and (3) scenario analysis indicated that NDVI in the Xinlin Gol grassland increased under the scenarios of reduced wind velocity, increased precipitation, and ecological protection. In contrast, vegetation coverage restoration in this area was significantly reduced under the scenarios of unfavorable climate conditions and excessive human activities. This study provides a scientific basis for future vegetation restoration and management, ecological environmental construction, and sustainable natural resource utilization in this area.

Understanding the dynamics of surface water area and their drivers is crucial for human survival and ecosystem stability in inland arid and semi-arid areas. This study took Gansu Province, China, a typical area with complex terrain and variable climate, as the research subject. Based on Google Earth Engine, we used Landsat data and the Open-surface Water Detection Method with Enhanced Impurity Control method to monitor the spatiotemporal dynamics of surface water area in Gansu Province from 1985 to 2022, and quantitatively analyzed the main causes of regional differences in surface water area. The findings revealed that surface water area in Gansu Province expanded by 406.88 km² from 1985 to 2022. Seasonal surface water area exhibited significant fluctuations, while permanent surface water area showed a steady increase. Notably, terrestrial water storage exhibited a trend of first decreasing and then increasing, correlated with the dynamics of surface water area. Climate change and human activities jointly affected surface hydrological processes, with the impact of climate change being slightly higher than that of human activities. Spatially, climate change affected the 'source' of surface water to a greater extent, while human activities tended to affect the 'destination' of surface water. Challenges of surface water resources faced by inland arid and semi-arid areas like Gansu Province are multifaceted. Therefore, we summarized the surface hydrology patterns typical in inland arid and semi-arid areas and tailored surface water 'supply-demand' balance strategies. The study not only sheds light on the dynamics of surface water area in Gansu Province, but also offers valuable insights for ecological protection and surface water resource management in inland arid and semi-arid areas facing water scarcity.

Eco-environmental quality is a measure of the suitability of the ecological environment for human survival and socioeconomic development. Understanding the spatial-temporal distribution and variation trend of eco-environmental quality is essential for environmental protection and ecological balance. The remote sensing ecological index (RSEI) can quickly and objectively quantify eco-environmental quality and has been extensively utilized in regional ecological environment assessment. In this paper, Moderate Resolution Imaging Spectroradiometer (MODIS) images during the growing period (July-September) from 2000 to 2020 were obtained from the Google Earth Engine (GEE) platform to calculate the RSEI in the three northern regions of China (the Three-North region). The Theil-Sen median trend method combined with the Mann-Kendall test was used to analyze the spatial-temporal variation trend of eco-environmental quality, and the Hurst exponent and the Theil-Sen median trend were superimposed to predict the future evolution trend of eco-environmental quality. In addition, ten variables from two categories of natural and anthropogenic factors were analyzed to determine the drivers of the spatial differentiation of eco-environmental quality by the geographical detector. The results showed that from 2000 to 2020, the RSEI in the Three-North region exhibited obvious regional characteristics: the RSEI values in Northwest China were generally between 0.2 and 0.4; the RSEI values in North China gradually increased from north to south, ranging from 0.2 to 0.8; and the RSEI values in Northeast China were mostly above 0.6. The average RSEI value in the Three-North region increased at an average growth rate of 0.0016/a, showing the spatial distribution characteristics of overall improvement and local degradation in eco-environmental quality, of which the areas with improved, basically stable and degraded eco-environmental quality accounted for 65.39%, 26.82% and 7.79% of the total study area, respectively. The Hurst exponent of the RSEI ranged from 0.20 to 0.76 and the future trend of eco-environmental quality was generally consistent with the trend over the past 21 years. However, the areas exhibiting an improvement trend in eco-environmental quality mainly had weak persistence, and there was a possibility of degradation in eco-environmental quality without strengthening ecological protection. Average relative humidity, accumulated precipitation and land use type were the dominant factors driving the spatial distribution of eco-environmental quality in the Three-North region, and two-factor interaction also had a greater influence on eco-environmental quality than single factors. The explanatory power of meteorological factors on the spatial distribution of eco-environmental quality was stronger than that of topographic factors. The effect of anthropogenic factors (such as population density and land use type) on eco-environmental quality gradually increased over time. This study can serve as a reference to protect the ecological environment in arid and semi-arid regions.

Lakes play important roles in sustaining the ecosystem and economic development in Inner Mongolia Autonomous Region of China, but the spatial patterns and driving mechanisms of water quality in lakes so far remain unclear. This study aimed to identify the spatial changes in water quality and the driving factors of seven lakes (Juyanhai Lake, Ulansuhai Lake, Hongjiannao Lake, Daihai Lake, Chagannaoer Lake, Hulun Lake, and Wulannuoer Lake) across the longitudinal axis (from the west to the east) of Inner Mongolia. Large-scale research was conducted using the comprehensive trophic level index (TLI (Σ)), multivariate statistics, and spatial analysis methods. The results showed that most lakes in Inner Mongolia were weakly alkaline. Total dissolved solids and salinity of lake water showed obvious zonation characteristics. Nitrogen and phosphorus were identified as the main pollutants in lakes, with high average concentrations of total nitrogen and total phosphorus being of 4.05 and 0.21 mg/L, respectively. The values of TLI (Σ) ranged from 49.14 to 71.77, indicating varying degrees of lake eutrophication, and phosphorus was the main driver of lake eutrophication. The lakes of Inner Mongolia could be categorized into lakes to the west of Daihai Lake and lakes to the east of Daihai Lake in terms of salinity and TLI (Σ). The salinity levels of lakes to the west of Daihai Lake exceeded those of lakes to the east of Daihai Lake, whereas the opposite trend was observed for lake trophic level. The intensity and mode of anthropogenic activities were the driving factors of the spatial patterns of lake water quality. It is recommended to control the impact of anthropogenic activities on the water quality of lakes in Inner Mongolia to improve lake ecological environment. These findings provide a more thorough understanding of the driving mechanism of the spatial patterns of water quality in lakes of Inner Mongolia, which can be used to develop strategies for lake ecosystem protection and water resources management in this region.

Land use/land cover (LULC) change and climate change are two major factors affecting the provision of ecosystem services which are closely related to human well-being. However, a clear understanding of the relationships between these two factors and ecosystem services in Central Asia is still lacking. This study aimed to comprehensively assess ecosystem services in Central Asia and analyze how they are impacted by changes in LULC and climate. The spatiotemporal patterns of three ecosystem services during the period of 2000-2015, namely the net primary productivity (NPP), water yield, and soil retention, were quantified and mapped by the Carnegie-Ames-Stanford Approach (CASA) model, Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, and Revised Universal Soil Loss Equation (RUSLE). Scenarios were used to determine the relative importance and combined effect of LULC change and climate change on ecosystem services. Then, the relationships between climate factors (precipitation and temperature) and ecosystem services, as well as between LULC change and ecosystem services, were further discussed. The results showed that the high values of ecosystem services appeared in the southeast of Central Asia. Among the six biomes (alpine forest region (AFR), alpine meadow region (AMR), typical steppe region (TSR), desert steppe region (DSR), desert region (DR), and lake region (LR)), the values of ecosystem services followed the order of AFR>AMR>TSR>DSR> DR>LR. In addition, the values of ecosystem services fluctuated during the period of 2000-2015, with the most significant decreases observed in the southeast mountainous area and northwest of Central Asia. LULC change had a greater impact on the NPP, while climate change had a stronger influence on the water yield and soil retention. The combined LULC change and climate change exhibited a significant synergistic effect on ecosystem services in most of Central Asia. Moreover, ecosystem services were more strongly and positively correlated with precipitation than with temperature. The greening of desert areas and forest land expansion could improve ecosystem services, but unreasonable development of cropland and urbanization have had an adverse impact on ecosystem services. According to the results, ecological stability in Central Asia can be achieved through the natural vegetation protection, reasonable urbanization, and ecological agriculture development.

Soil organic carbon (SOC) and its stable isotope composition reflect key information about the carbon cycle in ecosystems. Studies of carbon fractions in oasis continuous cotton-cropped fields can elucidate the SOC stability mechanism under the action of the human-land relationship during the oasification of arid land, which is critical for understanding the carbon dynamics of terrestrial ecosystems in arid lands under global climate change. In this study, we investigated the Alar Reclamation Area on the northern edge of the Tarim Basin, Xinjiang Uygur Autonomous Region of China, in 2020. In original desert and oasis farmlands with different reclamation years, including 6, 10, 18, and 30 a, and different soil depths (0-20, 20-40, 40-60 cm), we analyzed the variations in SOC, very liable carbon (C_VL), liable carbon (C_L), less liable carbon (C_LL), and non-liable carbon (C_NL) using the method of spatial series. The differences in the stable carbon isotope ratio (δ¹³C) and beta (β) values reflecting the organic carbon decomposition rate were also determined during oasification. Through redundancy analysis, we derived and discussed the relationships among SOC, carbon fractions, δ¹³C, and other soil physicochemical properties, such as the soil water content (SWC), bulk density (BD), pH, total salt (TS), total nitrogen (TN), available phosphorus (AP), and available potassium (AK). The results showed that there were significant differences in SOC and carbon fractions of oasis farmlands with different reclamation years, and the highest SOC was observed at the oasis farmland with 30-a reclamation year. C_VL, C_L, C_LL, and C_NL showed significant changes among oasis farmlands with different reclamation years, and C_VL had the largest variation range (0.40-4.92 g/kg) and accounted for the largest proportion in the organic carbon pool. The proportion of C_NL in the organic carbon pool of the topsoil (0-20 cm) gradually increased. δ¹³C varied from -25.61‰ to -22.58‰, with the topsoil showing the most positive value at the oasis farmland with 10-a reclamation year; while the β value was the lowest at the oasis farmland with 6-a reclamation year and then increased significantly. Based on the redundancy analysis results, the soil physicochemical properties, such as TN, AP, AK, and pH, were significantly correlated with C_L, and TN and AP were positively correlated with C_VL. However, δ¹³C was not significantly influenced by soil physicochemical properties. Our analysis advances the understanding of SOC dynamics during oasification, revealing the risk of soil carbon loss and its contribution to terrestrial carbon accumulation in arid lands, which could be useful for the sustainable development of regional carbon resources and ecological protection in arid ecosystem.

The desert in northern China is one of important sources of loess and one significant source of material for sandstorms in Asia. The sand/dust that is transported from desert when sandstorms occur can destroy the growth of crops, cause serious losses and great harm to the economic construction and life safety, and cause natural environment pollution. Hence, it is very important to deepen the research into heavy metals in surface deposits at vulnerable ecological region of arid land of northern China to guide local industrial and agricultural development and improve environmental protection. In this research, 10 heavy metal elements (Cr, Mn, Fe, Co, Ni, Cu, Zn, Cd, Pb, and Th) were tested and analyzed in 33 soil sample sites collected from the hinterland of the Tengger Desert, northern China. The results showed that the average abundance of Th exceeded its background soil value of China by more than 5.2 times, which suggests that the Tengger Desert is polluted by Th. In addition, based on principal component analysis, spatial differentiation, and correlation analysis, we identified the source of element with a coefficient of variation in abundance of greater than 0.5 or exceeding the background soil value of China. Principal component analysis and correlation analysis showed that the sources of heavy metals of Cr, Mn, Fe, Co, Ni, Cu, and Cd were similar, while those of Th and Zn were different. Moreover, based on the contents and spatial distribution characteristics of those heavy metal elements, we found that the formation of heavy metal elements enrichment areas is caused by industrial pollution, development of irrigated agricultural, geological, and geomorphic conditions, and the sedimentary environment in the study area. Our result can provide information on the environmental background values of soils in the hinterland of the Tengger Desert.

Background value of China^a(mg/kg)

In the context of global change, it is essential to promote the rational development and utilization of land resources, improve the quality of regional ecological environment, and promote the harmonious development of human and nature for the regional sustainability. We identified land use/land cover types in northern China from 2001 to 2018 with ENVI images and ArcGIS software. Meteorological data were selected from 292 stations in northern China, the potential evapotranspiration was calculated with the Penman-Monteith formula, and reanalysis humidity and observed humidity data were obtained. The reanalysis minus observation (RMO, i.e., the difference between reanalysis humidity and observed humidity) can effectively characterize the impact of different land use/land cover types (forestland, grassland, cultivated land, construction land, water body and unused land) on surface humidity in northern China in the early 21^st century. The results showed that from 2001 to 2018, the area of forestland expanded (increasing by approximately 1.80×10⁴ km²), while that of unused land reduced (decreasing by approximately 5.15×10⁴ km²), and the regional ecological environment was improved. Consequently, land surface in most areas of northern China tended to be wetter. The contributions of land use/land cover types to surface humidity changes were related to the quality of the regional ecological environment. The contributions of the six land use/land cover types to surface humidity were the highest in northeastern region of northern China, with a better ecological environment, and the lowest in northwestern region, with a fragile ecological environment. Surface humidity was closely related to the variation in regional vegetation coverage; when the regional vegetation coverage with positive (negative) contributions expanded (reduced), the land surface became wetter. The positive contributions of forestland and water body to surface humidity were the greatest. Unused land and construction land were associated with the most serious negative contributions to surface humidity. Affected by the regional distribution pattern of vegetation, surface humidity in different seasons decreased from east to west in northern China. The seasonal variation in surface humidity was closely related to the growth of vegetation: surface humidity was the highest in summer, followed by autumn and spring, and the lowest in winter. According to the results, surface humidity is expected to increase in northeastern region of northern China, decrease in northern region, and likely increase in northwestern region.

Velocity is an important component of glacier dynamics and directly reflects the response of glaciers to climate change. As a result, an accurate determination of seasonal variation in glacier velocity is very important in understanding the annual variation in glacier dynamics. However, few studies of glacier velocity in the High Mountain Asia (HMA) region were done. Along these lines, in this work, based on Sentinel-1 glacier velocity data, the distribution of glacier velocity in the HMA region was plotted and their seasonal variations during 2015-2020 were systematically analysed. The average glacier velocity in the HMA region was 0.053 m/d, and was positively correlated with the glacier area and slope. Glaciers in the Karakoram Mountains had the fastest average flow velocity (0.060 m/d), where the glaciers exhibited the largest average area and average slope. Moreover, glaciers in the Gangdisê Mountains had the slowest velocity (0.022 m/d) and the smallest average glacier area. The glacier flows were the fastest in spring (0.058 m/d), followed by summer (0.050 m/d), autumn (0.041 m/d), and winter (0.040 m/d). In addition, the glacier flows were the maximum in May, being 1.4 times of the annual average velocity. In some areas, such as the Qilian, Altun, Tibetan Interior, Eastern Kunlun, and Western Kunlun mountains, the peak glacier velocities appeared in June and July. The glacier velocity in the HMA region decreased in midsummer and reached the minimum in December when it was 75% of the annual average. These results highlight the role of meltwater in the seasonal variation in glacier flows in late spring and early summer. The seasonal velocity variation of lake-terminating glaciers was similar to that of land-terminating ones, but the former flowed faster. The velocity difference close to the mass balance line between the lake- and land-terminating glaciers was obviously greater in spring than in other seasons. In summer, the difference between the lake- and land-terminating glaciers at a normalized distance of 0.05-0.40 from the terminus was significantly greater than those of other seasons. The velocity difference between the lake- and land-terminating glaciers is closely related to the variable of ice thickness, and also to the frictional force of the terminal base reduced by proglacial lakes. Thus, it can be concluded that in addition to the variation of the glacier thickness and viscosity, the variation of glacier water input also plays a key role in the seasonal variation of glacier velocity.

Competition, spatial pattern, and regeneration are important factors affecting community composition, structure, and dynamics. In this study, we surveyed 300 quadrats from three dunes (i.e., fixed dunes, semifixed dunes, and mobile dunes) in the Gurbantunggut Desert, Northwest China, from late May to early June in 2021. The intraspecific and interspecific competition, spatial pattern, and regeneration of Haloxylon ammodendron and Haloxylon persicum were studied using the Hegyi competition index and point pattern analysis methods. The results showed that the optimal competition distance of the objective tree in the H. ammodendron and H. persicum communities was 6 m. The intraspecific and interspecific competition of H. ammodendron was the greatest in fixed dunes, while the competition intensity of H. persicum in semifixed dunes and mobile dunes was greater than that in fixed dunes. The order of competition intensity of the two populations was seedlings>saplings>adults, and the competition intensity gradually decreased with the increase in plant diameter. The spatial distribution pattern of the three life stages of H. ammodendron and H. persicum was random, and there were no correlations between seedlings and saplings, adults and saplings, and seedlings and adults. The density of regenerated seedlings and saplings of H. ammodendron in the three dunes followed the order of fixed dunes>semifixed dunes>mobile dunes, and that of H. persicum in the three dunes followed the order of mobile dunes>semifixed dunes>fixed dunes. Therefore, when artificially planting H. ammodendron and H. persicum for sand control, the planting interval should be 6 m, and seedlings should be planted next to adults to minimize the competition between plants, which can promote the renewal of H. ammodendron and H. persicum and the stabilization of the ecosystem.

Drought occurs in almost all climate zones and is characterized by prolonged water deficiency due to unbalanced demand and supply of water, persistent insufficient precipitation, lack of moisture, and high evapotranspiration. Drought caused by insufficient precipitation is a temporary and recurring meteorological event. Precipitation in semi-arid regions is different from that in other regions, ranging from 50 to 750 mm. In general, the semi-arid regions in the west and north of Iran received more precipitation than those in the east and south. The Terrestrial Climate (TerraClimate) data, including monthly precipitation, minimum temperature, maximum temperature, potential evapotranspiration, and the Palmer Drought Severity Index (PDSI) developed by the University of Idaho, were used in this study. The PDSI data was directly obtained from the Google Earth Engine platform. The Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) on two different scales were calculated in time series and also both SPI and SPEI were shown in spatial distribution maps. The result showed that normal conditions were a common occurrence in the semi-arid regions of Iran over the majority of years from 2000 to 2020, according to a spatiotemporal study of the SPI at 3-month and 12-month time scales as well as the SPEI at 3-month and 12-month time scales. Moreover, the PDSI detected extreme dry years during 2000-2003 and in 2007, 2014, and 2018. In many semi-arid regions of Iran, the SPI at 3-month time scale is higher than the SPEI at 3-month time scale in 2000, 2008, 2014, 2015, and 2018. In general, this study concluded that the semi-arid regions underwent normal weather conditions from 2000 to 2020. In a way, moderate, severe, and extreme dry occurred with a lesser percentage, gradually decreasing. According to the PDSI, during 2000-2003 and 2007-2014, extreme dry struck practically all hot semi-arid regions of Iran. Several parts of the cold semi-arid regions, on the other hand, only experienced moderate to severe dry from 2000 to 2003, except for the eastern areas and wetter regions. The significance of this study is the determination of the spatiotemporal distribution of meteorological drought in semi-arid regions of Iran using strongly validated data from TerraClimate.

Altitude affects leaf stoichiometry by regulating temperature and precipitation, and influencing soil properties in mountain ecosystems. Leaf carbon concentration (C), leaf nitrogen concentration (N), leaf phosphorous concentration (P), and their stoichiometric ratios of Leontopodium lentopodioides (Willd.) Beauv., a widespread species in degraded grasslands, were investigated to explore its response and adaptation strategy to environmental changes along four altitude gradients (2500, 3000, 3500, and 3800 m a.s.l.) on the northeastern Qinghai-Tibetan Plateau (QTP), China. The leaf C significantly varied but without any clear trend with increasing altitude. Leaf N showed an increasing trend, and leaf P showed a little change with increasing altitude, with a lower value of leaf P at 3500 m than those at other altitudes. Similarity, leaf C:P and N:P exhibited a little change with increasing altitude, which both had greater values at 3500 m than those at other altitudes. However, leaf C:N exhibited a decreasing trend with increasing altitude. Soil NH+ 4-N, soil pH, soil total phosphorus (STP), mean annual temperature (MAT), and mean annual precipitation (MAP) were identified as the main factors driving the variations in leaf stoichiometry of L. lentopodioides across all altitudes, with NH+ 4-N alone accounting for 50.8% of its total variation. Specifically, leaf C and N were mainly controlled by MAT, soil pH, and NH+ 4-N, while leaf P by MAP and STP. In the study area, it seems that the growth of L. lentopodioides may be mainly limited by STP. The results could help to strengthen our understanding of the plasticity of plant growth to environmental changes and provide new information on global grassland management and restoration.

Roots exert pullout resistance under pullout force, allowing plants to resist uprooting. However, the pullout resistance characteristics of taproot-type shrub species of different ages remain unclear. In this study, in order to improve our knowledge of pullout resistance characteristics of taproot systems of shrub species, we selected the shrub species Caragana korshinskii Kom. in different growth periods as the research plant and conducted in situ root pullout test. The relationships among the maximum pullout resistance, peak root displacement, shrub growth period, and aboveground growth indices (plant height and plant crown breadth) were analyzed, as well as the mechanical process of uprooting. Pullout resistance of 4-15 year-old C. korshinskii ranged from 2.49 (±0.25) to 14.71 (±4.96) kN, and the peak displacement ranged from 11.77 (±8.61) to 26.50 (±16.09) cm. The maximum pullout resistance and the peak displacement of roots increased as a power function (R²=0.9038) and a linear function (R²=0.8242) with increasing age, respectively. The maximum pullout resistance and the peak displacement increased with increasing plant height; however, this relationship was not significant. The maximum pullout resistance increased exponentially (R²=0.5522) as the crown breadth increased. There was no significant relationship between the peak displacement and crown breadth. The pullout resistance and displacement curve were divided into three stages: the initial nonlinear growth, linear growth, and nonlinear stages. Two modes of failure of a single root occurred when the roots were subjected to vertical loading forces: the synchronous breakage mode and the periderm preferential breakage mode. These findings provide a foundation for further investigation of the soil reinforcement and slope protection mechanisms of this shrub species in the loess area of northeastern Qinghai-Tibet Plateau, China.

Monitoring rock desert formation caused by two different origins (ice-snow melting and drying) through remote sensing is crucial to our understanding of the interaction between the underlying surface of different rock desert and land-atmosphere types, as well as the relationship between bare land and soil erosion. A number of achievements have been made in remote sensing monitoring of desert areas, but there is a lack of accurate classification and remote sensing identification of rock desert types based on formation mechanism. In this study, the north and south sides of the eastern Kunlun Mountains in the northern part of the Qinghai-Tibet Plateau of China were taken as the study areas. Landsat operational landscape imager, digital elevation model, and precipitation and temperature grid data were used as data sources. By identifying the bare areas based on the normalized difference vegetation index (NDVI), we used the multi-element fusion method of contours, isotherms, and isohyets to identify the rock desert types in the ice-snow melting and dry areas. The results showed that: (1) the rock desert areas identified by remote sensing based on topographic and meteorological elements were highly accurate, with an overall accuracy of 88.45% and kappa coefficient of 0.77. The multi-element fusion method of contours, isotherms, and isohyets could effectively identify the rock desert types in the ice-snow melting and dry areas; (2) the optimal segmentation range of the ice-snow melting and dry areas was 3600 m contour, -2°C-2°C isotherms, and 100-130 mm isohyets. The areas with elevation less than 3600 m, annual average temperature higher than 2°C, and average annual precipitation less than 100 mm were rock desert in the dry areas. The range of -2°C-2°C isotherms and 100-130 mm isohyets was the transition area between the ice-snow melting and dry areas. The areas with elevation higher than 3600 m, annual average temperature less than -2°C, and average annual precipitation higher than 130 mm were rock desert in the ice-snow melting areas; and (3) the identification accuracy of the bare areas based on the NDVI method was better, specifically, the identification accuracy of plain bare areas was generally better than that of mountain bare areas. The remote sensing identification method considers not only the topographic factors that have great influence on the spatial distribution of the two types of rock desert areas, but also the meteorological factors, which can provide a scientific reference for the effective identification of the two types of rock desert areas.

The construction of artificial shelter forests (ASFs) has resulted in substantial ecological, economic, and societal benefits to the Chinese Loess Plateau (CLP). However, the health and benefits of ASFs are being increasingly threatened by the formation of low-efficiency artificial shelter forests (LEASFs). In this study, LEASFs are systematically analyzed in terms of their status, formation mechanisms, and developmental obstacles. The key restoration techniques and schemes were summarized to improve the quality and efficiency of LEASFs. LEASFs are formed by relatively complex mechanisms, but they arise mainly due to poor habitat conditions, improper tree species selections, mismatch between stands and habitat, extensive forest management measures, and human interferences. The restoration and improvement of LEASFs are hindered by water deficits, mismatch between stands and habitat, single management purpose, and low efficiency. LEASFs are becoming more complex due to their wide range, the challenges associated with their restoration, and insufficient technological measures for their restoration. The key techniques of the quality and efficiency improvement of LEASFs include basic forest tending methods, near-natural restoration, multifunction-oriented improvement, and systematic restoration. An understanding on the formation mechanisms of LEASFs and a scientific approach toward their restoration are urgently needed and critical for the ecological protection and high-quality development of LEASFs on the CLP. Based on these analyses, we recommend strengthening the monitoring and supervision of LEASFs, considering the bearing capacity of regional water resources, implementing multiple restoration techniques, promoting multifunction-oriented ecological development, and exploring new management concepts to achieve the sustainable development of ASFs on the CLP.

Water is a limiting factor in the restoration and construction of desert steppe. Exploring plant water sources is necessary to understand soil-plant interactions and species coexistence; however, water sources of major plant communities within the desert steppe of Ningxia Hui Autonomous Region, China remain poorly understood. In this study, we analyzed the water uptake of plants in four typical communities: Agropyron mongolicum Keng.; Sophora alopecuroids Linn.; Stipa breviflora Griseb., and Achnatherum splendens (Trin.) Nevski communities. Stable isotopes δD and δ¹⁸O in the xylem of plant and soil water at different soil depths were analyzed. An IsoSource model was used to determine the soil depths from which plants obtained water. Results showed that A. mongolicum community obtained water predominantly from 0-20 and 40-80 cm depth, S. alopecuroids community from 0-20 cm depth, S. breviflora community from 0-40 cm depth, and A. splendens community from 0-20 and 80-140 cm depths. S. alopecuroides had a wider range of soil depths for water extraction, i.e., utilizing different water sources depending on habitat, and the plasticity of its water uptake pattern determined its role in different communities. Water source of plants relayed heavily on the distribution of their roots. Competition for soil water exists between different plant life forms in the sierozem habitat (A. mongolicum, S. alopecuroids, and S. breviflora communities), and in the sandy soil habitat (A. splendens community). The use of soil water by A. splendens community is more spatially differentiated, and shrubs and herbs can coexist stably. Under the pattern of extended drought period in the future, sierozem habitat may be more favorable for the formation of a dominant monoculture community type of perennial fibrous plants. In aeolian sandy soil habitat, A. splendens had a strong competitive advantage, and the growth of shallow-rooted plants was easily suppressed.