A knowledge of the tree-ring stable nitrogen isotope ratio (δ¹⁵N) can deepen our understanding of forest ecosystem dynamics by indicating the long-term availability, cycling and sources of nitrogen (N). However, the radial mobility of N blurs the interannual variations in the long-term N records. Previous studies of the chemical extraction of tree rings before analysis had produced inconsistent results and it is still unclear whether it is necessary to pre-treat wood samples from specific tree species to remove soluble N compounds before determining the δ¹⁵N values. We compared the effects of pre-treatment with organic solvents and hot ultrapure water on the N concentration and δ¹⁵N of tree rings from endemic Qinghai spruce (Picea crassifolia) growing in the interior of the central Qilian Mountains, China, during the last 60 a. We assessed the effects of different preparation protocols on the removal of the labile N compounds and investigated the need to pre-treat wood samples before determining the δ¹⁵N values of tree rings. Increasing trends of the tree-ring N concentration were consistently observed in both the extracted and unextracted wood samples. The total N removed by extraction with organic solvents was about 17.60%, with a significantly higher amount in the sapwood section (P<0.01). The δ¹⁵N values of tree rings decreased consistently from 1960 to 2019 in both the extracted and unextracted wood samples. Extraction with organic solvents increased the δ¹⁵N values markedly by about 5.2‰ and reduced the variations in the δ¹⁵N series. However, extraction with hot ultrapure water had little effect, with only a slight decrease in the δ¹⁵N values of about 0.5‰. Our results showed that the radial pattern in the inter-ring movement of N in Qinghai spruce was not minimized by extraction with either organic solvents or hot ultrapure water. It is unnecessary to conduct hot ultrapure water extraction for the wood samples from Qinghai spruce because of its negligible effect on the removal of the labile N. The δ¹⁵N variation trend of tree rings in the unextracted wood samples was not influenced by the heartwood-sapwood transition zone. We suggest that the δ¹⁵N values of the unextracted wood samples of the climate-sensitive Qinghai spruce could be used to explore the ecophysiological dynamics while focusing on the long-term variations.

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.

Glaciers are highly sensitive to climate change and are undergoing significant changes in mid-latitudes. In this study, we analyzed the spatiotemporal changes of typical glaciers and their responses to climate change in the period of 1990-2015 in 4 different mountainous sub-regions in Xinjiang Uygur Autonomous Region of Northwest China: the Bogda Peak and Karlik Mountain sub-regions in the Tianshan Mountains; the Yinsugaiti Glacier sub-region in the Karakorum Mountains; and the Youyi Peak sub-region in the Altay Mountains. The standardized snow cover index (NDSI) and correlation analysis were used to reveal the glacier area changes in the 4 sub-regions from 1990 to 2015. Glacial areas in the Bogda Peak, Karlik Mountain, Yinsugaiti Glacier, and Youyi Peak sub-regions in the period of 1990-2015 decreased by 57.7, 369.1, 369.1, and 170.4 km², respectively. Analysis of glacier area center of gravity showed that quadrant changes of glacier areas in the 4 sub-regions moved towards the origin. Glacier area on the south aspect of the Karlik Mountain sub-region was larger than that on the north aspect, while glacier areas on the north aspect of the other 3 sub-regions were larger than those on the south aspect. Increased precipitation in the Karlik Mountain sub-region inhibited the retreat of glaciers to a certain extent. However, glacier area changes in the Bogda Peak and Youyi Peak sub-regions were not sensitive to the increased precipitation. On a seasonal time scale, glacier area changes in the Bogda Peak, Karlik Mountain, Yinsugaiti Glacier, and Youyi Peak sub-regions were mainly caused by accumulated temperature in the wet season; on an annual time scale, the correlation coefficient between glacier area and annual average temperature was -0.72 and passed the significance test at P<0.05 level in the Karlik Mountain sub-region. The findings of this study can provide a scientific basis for water resources management in the arid and semi-arid regions of Northwest China in the context of global warming.

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.

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.

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.

During aeolian processes, the two most critical factors related to dust emissions are soil particle and aggregate saltation, which greatly affect the vertical profiles of near-surface dust concentrations. In this study, we measured PM10 concentrations at four different heights (0.10, 0.50, 1.00 and 2.00 m) with and without continuous and simultaneous aeolian saltation processes on a Gobi surface in northwestern China from 31 March to 10 April, 2017. We found that the vertical concentration profiles of suspended PM10 matched the log-law model well when there was no aeolian saltation. For the erosion process with saltation, we divided the vertical concentration profiles of PM10 into the saltation-affected layer and the airflow-transport layer according to two different dust sources (i.e., locally emitted PM10 and upwind transported PM10). The transition height between the saltation-affected layer and the airflow-transport layer was not fixed and varied with saltation intensity. From this new perspective, we calculated the airflow-transport layer and the dust emission rate at different times during a wind erosion event occurred on 5 April 2017. We found that dust emissions during wind erosion are primarily controlled by saltation intensity, contributing little to PM10 concentrations above the ground surface compared to PM10 concentrations transported from upwind directions. As erosion progresses, the surface supply of erodible grains is the most crucial factor for saltation intensity. When there was a sufficient amount of erodible grains, there was a significant correlation among the friction velocity, saltation intensity and dust emission rate. However, when supply is limited by factors such as surface renewal or an increase in soil moisture, the friction velocity will not necessarily correlate with the other two factors. Therefore, for the Gobi surface, compared to limiting dust emissions from upwind directions, restricting the transport of suspended dust in its path is by far a more efficient and realistic option for small areas that are often exposed to dust storms. This study provides some theoretical basis for correctly estimating PM10 concentrations in the Gobi areas.

Wind controls the formation and development of sand dunes. Therefore, understanding the wind regimes is necessary in sand dune research. In this study, we combined the wind data from 2017 to 2019 at four meteorological stations (Cherigele and Wuertabulage stations in the lake basins, and Yikeri and Sumujilin stations on the top of sand dunes) in the hinterland of the Badain Jaran Desert in China, with high resolution Google Earth images to analyze the correlation between the wind energy environments and dune morphology. The results of data analysis indicated that both the wind direction and sand drift intensity exhibited notable spatial and temporal variations. The highest level of wind activity was observed in spring. Northwesterly and northeasterly winds were the dominant in the Badain Jaran Desert. At the Cherigele, Wuertabulage, and Yikeri stations, the drift potential (DP) was below 200.00 vector units (VU). The wind energy environments in most areas could be classified as low-energy environments. The resultant drift direction differed at different stations and in different seasons, but the overall direction was mainly the southeast. The resultant drift potential (RDP)/DP ratio was greater than 0.30 in most parts of the study area, suggesting that the wind regimes mainly exhibited unimodal or bimodal characteristics. Differences between the thermodynamic properties and the unique landscape settings of lakes and sand dunes could alter the local circulation and intensify the complexity of the wind regimes. The wind regimes were weaker in the lake basins than on the top of sand dunes. Transverse dunes were the most dominant types of sand dunes in the study area, and the wind regimes at most stations were consistent with sand dune types. Wind was thus the main dynamic factor affecting the formation of sand dunes in the Badain Jaran Desert BJD. The results of this study are important for understanding the relationship between the wind regimes and aeolian landforms of the dune field in the deserts.

Caragana korshinskii Kom. and Tamarix ramosissima Ledeb. are pioneer shrubs for water and soil conservation, and for windbreak and sand fixation in arid and semi-arid areas. Understanding the water use characteristics of different pioneer shrubs at different ages is of great importance for their survival when extreme rainfall occurs. In recent years, the stable isotope tracing technique has been used in exploring the water use strategies of plants. However, the widespread δ²H offsets of stem water from its potential sources result in conflicting interpretations of water utilization of plants in arid and semi-arid areas. In this study, we used three sets of hydrogen and oxygen stable isotope data (δ²H and δ¹⁸O, corrected δ²H_{_c1} based on SW-excess and δ¹⁸O, and corrected δ²H_{_c2} based on -8.1‰ and δ¹⁸O) as inputs for the MixSIAR model to explore the water use characteristics of C. korshinskii and T. ramosissima at different ages and in response to rainfall. The results showed that δ²H_{_c1} and δ¹⁸O have the best performance, and the contribution rate of deep soil water was underestimated because of δ²H offset. During the dry periods, C. korshinskii and T. ramosissima at different ages both obtained mostly water from deeper soil layers. After rainfall, the proportions of surface (0-10 cm) and shallow (10-40 cm) soil water for C. korshinskii and T. ramosissima at different ages both increased. Nevertheless, there were different response mechanisms of these two plants for rainfall. In addition, C. korshinskii absorbed various potential water sources, while T. ramosissima only used deep water. These flexible water use characteristics of C. korshinskii and T. ramosissima might facilitate the coexistence of plants once extreme rainfall occurs. Thus, reasonable allocation of different plants may be a good vegetation restoration program in western Chinese Loess Plateau.

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.

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.

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.

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.

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.

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.

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.

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)

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.

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.

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.

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.

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.

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.

Rapid industrialization and urbanization have led to the most serious habitat degradation in China, especially in the loess hilly area of the Yellow River Basin, where the ecological environment is relatively fragile. The contradiction between economic development and ecological environment protection has aroused widespread concern. In this study, we used the habitat quality of Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST-HQ) model at different scales to evaluate the dynamic evolution characteristics of habitat quality in Lanzhou City, Gansu Province of China. The spatiotemporal variations of habitat quality were analyzed by spatial autocorrelation. A Geographical Detector (Geodetector) model was used to explore the driving factors that influencing the spatial differentiation of habitat quality, including natural factors, socio-economic factors, and ecological protection factors. The results showed that the habitat quality index of Lanzhou City decreased from 0.4638 to 0.4548 during 2000-2018. The areas with reduced the habitat quality index were mainly located in the Yellow River Basin and Qinwangchuan Basin, where are the main urban areas and the new economic development areas, respectively. The spatial distribution of habitat quality presented a trend of high in the surrounding areas and low in the middle, and showed a significant positive spatial autocorrelation. With the increase of study scale, the spatial distribution of habitat quality changed from concentrated to dispersed. The spatial differentiation of habitat quality in the study area was the result of multiple factors. Among them, topographic relief and slope were the key factors. The synergistic enhancement among these driving factors intensified the spatial differentiation of habitat quality. The findings of this study can provide a scientific basis for land resources utilization and ecosystem restoration in the arid and semi-arid land.

Litter decomposition is an important component of the nutrient recycling process and is highly sensitive to climate change. However, the impacts of warming and increased precipitation on litter decomposition have not been well studied, especially in the alpine grassland of Tianshan Mountains. We conducted a manipulative warming and increased precipitation experiment combined with different grassland types to examine the impact of litter quality and climate change on the litter decomposition rate based on three dominant species (Astragalus mongholicus, Potentilla anserina, and Festuca ovina) in Tianshan Mountains from 2019 to 2021. The results of this study indicated there were significant differences in litter quality, specific leaf area, and leaf dry matter content. In addition, litter quality exerted significant effects on litter decomposition, and the litter decomposition rate varied in different grassland types. Increased precipitation significantly accelerated the litter decomposition of P. anserina; however, it had no significant effect on the litter decomposition of A. mongholicus and F. ovina. However, warming consistently decreased the litter decomposition rate, with the strongest impact on the litter decomposition of F. ovina. There was a significant interaction between increased precipitation and litter type, but there was no significant interaction between warming and litter type. These results indicated that warming and increased precipitation significantly influenced litter decomposition; however, the strength was dependent on litter quality. In addition, soil water content played a crucial role in regulating litter decomposition in different grassland types. Moreover, we found that the litter decomposition rate exhibited a hump-shaped or linear response to the increase of soil water content. Our study emphasizes that ongoing climate change significantly altered litter decomposition in the alpine grassland, which is of great significance for understanding the nutrient supply and turnover of litter.

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.

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.

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.

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.

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.

There is a lack of research on soil microplastics in arid oases considering the rapid economic development of northwestern China. Here, we studied the occurrence and sources of microplastics in soil, as well as the relationships between microplastics and adsorbed heavy metals in the Ebinur Lake Basin, a typical arid oasis in China. Results showed that (1) the average microplastic content in all soil samples was 36.15 (±3.27) mg/kg. The contents of microplastics at different sampling sites ranged from 3.89 (±1.64) to 89.25 (±2.98) mg/kg. Overall, the proportions of various microplastic shapes decreased in the following order: film (54.25%)>fiber (18.56%)>particle (15.07%)>fragment (8.66%)>foam (3.46%); (2) among all microplastic particles, white particles accounted for the largest proportion (52.93%), followed by green (24.15%), black (12.17%), transparent (7.16%), and yellow particles (3.59%). The proportions of microplastic particle size ranges across all soil samples decreased in the following order: 1000-2000 µm (40.88%)>500-1000 µm (26.75%)>2000-5000 µm (12.30%)>100-500 µm (12.92%)>0-100 µm (7.15%). FTIR (Fourier transform infrared) analyses showed that polyethylene terephthalate (PET), polypropylene (PP), polycarbonate (PC), polyethylene (PE), and polystyrene (PS) occurred in the studied soil; (3) random forest predictions showed that industrial and agricultural production activities and the discharge of domestic plastic waste were related to soil microplastic pollution, in which agricultural plastic film was the most important factor in soil pollution in the study area; and (4) seven heavy metals extracted from microplastics in the soil samples showed significant positive correlations with soil pH, EC, total salt, N, P, and K contents (P<0.01), indicating that these soil factors could significantly affect the contents of heavy metals carried by soil microplastics. This research demonstrated that the contents of soil microplastics are lower than other areas of the world, and they mainly come from industrial and agricultural activities of the Ebinur Lake Basin.

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.

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.

Coal mining has changed the hydrogeological conditions of river basins, and studying how the relationship among different types of water body has changed under the influence of coal mining is of great significance for understanding the regional hydrological cycle. We analyzed the temporal and spatial distribution of hydrochemical properties and environmental isotopes in the Hailiutu River Basin (HRB), China with a mixed model. The results showed that: (1) human activity (e.g., coal mining and agricultural production) causes considerable changes in the hydrochemical properties of surface water in and around the mining areas, and leads to significant increases in the concentrations of Na⁺ and SO2- 4; (2) precipitation is the main source of water vapour in the HRB. The transformation between surface water and groundwater in the natural watershed is mainly affected by precipitation; and (3) in the mining areas, the average contribution rates of precipitation to the recharge of surface water and groundwater increased by 2.6%-7.9% and 2.7%-9.9%, respectively. Groundwater in the Salawusu Formation constitutes up to 61.3%-72.4% of mine water. Overall, this study is beneficial for quantifying the effects of coal mining on local hydrological cycles. The research results can provide a reference for local water resources management and ecological environment improvement.

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.

Sand fences made of punched steel plate (PSP) have recently been applied to control wind-blown sand in desertified and Gobi areas due to their strong wind resistance and convenient in situ construction. However, few studies have assessed the protective effect of PSP sand fences, especially through field observations. This study analyzes the effects of double-row PSP sand fences on wind and sand resistance using field observations and a computational fluid dynamics (CFD) numerical simulation. The results of field observations showed that the average windproof efficiencies of the first-row and second-row sand fences were 79.8% and 70.8%, respectively. Moreover, the average windproof efficiencies of the numerical simulation behind the first-row and second-row sand fences were 89.8% and 81.1%, respectively. The sand-resistance efficiency of the double-row PSP sand fences was 65.4%. Sand deposition occurred close to the first-row sand fence; however, there was relatively little sand on the leeward side of the second-row sand fence. The length of sand accumulation near PSP sand fences obtained by numerical simulation was basically consistent with that through field observations, indicating that field observations combined with numerical simulation can provide insight into the complex wind-blown sand field over PSP sand fences. This study indicates that the protection efficiency of the double-row PSP sand fences is sufficient for effective control of sand hazards associated with extremely strong wind in the Gobi areas. The output of this work is expected to improve the future application of PSP sand fences.

In arid and semi-arid stream-dominated systems, the temporal variability in groundwater recharge has not been widely addressed. Various questions remain about the sources of groundwater recharge, its patterns, and the appropriate measuring techniques. Hence, the main objective of the present study was to assess the changes that might affect the pattern of groundwater recharge under wetter than normal surface water availability. Therefore, the groundwater depth was monitored near a semi-arid Mediterranean intermittent stream on the piedmont of the High Atlas Mountains in the mountain catchment of the Wadi Rheraya over two hydrological years (2014-2016) with different climate conditions: extreme wet and normal conditions. Groundwater recharge was assessed using the episodic master recession algorithm. During the two years, the pattern of groundwater recharge was dominated by episodic events and by a high seasonality from wet seasons to dry seasons. In the wet year (2014-2015), the highest groundwater recharge was recorded following an extreme flood, which deeply replenished groundwater. Furthermore, an exceptional steady state of the groundwater depth was induced by a steady groundwater recharge rate. For several groundwater recharge events, the assessed recharge had multiple sources, mainly from streamflow at the local scale, but possibly from precipitation, underflow, deep percolation or irrigation return from the upstream part of the catchment. Local recharge by streamflow was likely to be short-lived, and lateral recharge was likely to last longer. Consequently, the episodic master recession algorithm estimated the total groundwater recharge that could encompass various sources. In the future, more studies and multidisciplinary approaches should be carried out to partition these sources and determine their specific contributions. In semi-arid stream-dominated systems, different groundwater recharge patterns induced by extreme hydrological events (e.g., wet events) and various potential sources of groundwater recharge should be considered when assessing and predicting groundwater recharge.

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.