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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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)

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.

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.

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.

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.

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.

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.

Under the combined influence of climate change and human activities, vegetation ecosystem has undergone profound changes. It can be seen that there are obvious differences in the evolution patterns and driving mechanisms of vegetation ecosystem in different historical periods. Therefore, it is urgent to identify and reveal the dominant factors and their contribution rates in the vegetation change cycle. Based on the data of climate elements (sunshine hours, precipitation and temperature), human activities (population intensity and GDP intensity) and other natural factors (altitude, slope and aspect), this study explored the spatial and temporal evolution patterns of vegetation NDVI in the Yellow River Basin of China from 1989 to 2019 through a residual method, a trend analysis, and a gravity center model, and quantitatively distinguished the relative actions of climate change and human activities on vegetation evolution based on Geodetector model. The results showed that the spatial distribution of vegetation NDVI in the Yellow River Basin showed a decreasing trend from southeast to northwest. During 1981-2019, the temporal variation of vegetation NDVI showed an overall increasing trend. The gravity centers of average vegetation NDVI during the study period was distributed in Zhenyuan County, Gansu Province, and the center moved northeastwards from 1981 to 2019. During 1981-2000 and 2001-2019, the proportion of vegetation restoration areas promoted by the combined action of climate change and human activities was the largest. During the study period (1981-2019), the dominant factors influencing vegetation NDVI shifted from natural factors to human activities. These results could provide decision support for the protection and restoration of vegetation ecosystem in the Yellow River Basin.

With the acceleration of urbanization, changes in the urban ecological environment and landscape pattern have led to a series of prominent ecological environmental problems. In order to better coordinate the balanced relationship between city and ecological environment, we selected land use change data to evaluate the habitat quality in Hohhot City of China, which is of great practical significance for regional urban and economic development. Thus, the integrated valuation of ecosystem services and tradeoffs (InVEST) and Cellular Automata-Markov (CA-Markov) models were used to analyze, predict, and explore the Spatiotemporal evolution path and characteristics of urban land use, and forecast the typical evolution pattern of land use in 2030. The results showed that the land use types in Hohhot City changed significantly from 2000 to 2020, and the biggest change took place in cultivated land, grassland, shrub, and artificial surface. The decrease of cultivated land area and the increase of artificial surface area were the main impact trend of land use change. The average value of habitat quality had been decreasing continuously from 2000 to 2020, and the values of habitat degradation were 0.2605, 0.2494, and 0.2934 in 2000, 2010, and 2020, respectively, showing a decreasing trend. The decrease of habitat quality was caused by the needs of economic development and urban construction, as well as the impact of land occupation. During this evolution, many cultivated land and urban grassland had been converted into construction land. The simulated land use changes in 2030 are basically the same as those during 2000-2020, and the habitat quality will still be declining. The regional changes are influenced by the urban rapid development and industrial layout. These results can provide decision-making reference for regional urban planning and management as well as habitat quality evaluation.

Whether millennial- to centennial-scale climate variations throughout the Holocene convey universal climate change is still widely debated. In this study, we aimed to obtain a set of high-resolution multi-proxy data (1343 particle size samples, 893 total organic carbon samples, and 711 pollen samples) from an alluvial-lacustrine-aeolian sequence based on an improved age-depth model in the northwestern margin of the East Asian monsoon region to explore the dynamics of climate changes over the past 30 ka. Results revealed that the sequence not only documented the major climate events that corresponded well with those reported from the North Atlantic regions but also revealed many marked and high-frequency oscillations at the millennial- and centennial-scale. Specifically, the late stage of the last glacial lasting from 30.1 to 18.1 cal. ka BP was a dry and cold period. The deglacial (18.1-11.5 cal. ka BP) was a wetting (probably also warming) period, and three cold and dry excursions were found in the wetting trend, i.e., the Oldest Dryas (18.1-15.8 cal. ka BP), the Older Dryas (14.6-13.7 cal. ka BP), and the Younger Dryas (12.5-11.5 cal. ka BP). The Holocene can be divided into three portions: the warmest and wettest early portion from 11.5 to 6.7 cal. ka BP, the dramatically cold and dry middle portion from 6.7 to 3.0 cal. ka BP, and the coldest and driest late portion since 3.0 cal. ka BP. Wavelet analysis results on the total pollen concentration revealed five substantially periodicities: c. 5500, 2200, 900, 380, and 210 a. With the exception of the c. 5500 a quasi-cycle that was causally associated with the Atlantic meridional overturning circulation, the other four quasi-cycles (i.e., c. 2200, 900, 380, and 210 a) were found to be indirectly causally associated with solar activities. This study provides considerable insight into the dynamic mechanism of the Asian climate on a long-time scale and future climatic change.

Leaf traits can directly reflect the adaptation strategies of plants to the environment. However, there is limited knowledge on the adaptation strategies of heteromorphic leaves of male and female Populus euphratica Oliv. in response to individual developmental stages (i.e., diameter class) and canopy height changes. In this study, morphological and physiological properties of heteromorphic leaves of male and female P. euphratica were investigated. Results showed that both male and female P. euphratica exhibited increased leaf area (LA), leaf dry weight (LDW), leaf thickness (LT), net photosynthetic rate (P_n), transpiration rate (T_r), stomatal conductance (g_s), proline (Pro), and malondialdehyde (MDA) concentration, decreased leaf shape index (LI) and specific leaf area (SLA) with increasing diameter and canopy height. Leaf water potential (LWP) increased with increasing diameter, LWP decreased significantly with increasing canopy height in both sexes, and carbon isotope fraction (δ¹³C) increased significantly with canopy height in both sexes, all of which showed obvious resistance characteristics. However, males showed greater LA, LT, P_n, T_r, and Pro than females at the same canopy height, and males showed significantly higher LA, SLA, LT, P_n, T_r, g_s, and MDA, but lower LWP and δ¹³C than females at the same canopy height, suggesting that male P. euphratica have stronger photosynthetic and osmoregulatory abilities, and are sensitive to water deficiency. Moreover, difference between male and female P. euphratica is closely related to the increase in individual diameter class and canopy height. In summary, male plants showed higher stress tolerance than female plants, and differences in P_n, g_s, T_r, Pro, MDA, δ¹³C, and LWP between females and males were related to changes in leaf morphology, diameter class, and canopy height. The results of this study provide a theory for the differences in growth adaptation strategies during individual development of P. euphratica.

Green development of agriculture is important for achieving coordinated and high-quality regional development for China. Using provincial data from 1990 to 2020, this work explored the dynamics of agricultural green development efficiency of 31 provinces in China, its spatiotemporal characteristics, and its driving factors using a super-efficiency slacks-based measure (Super-SBM), the Malmquist productivity index (MPI), spatial autocorrelation, and a geographic detector. Results showed that the overall agricultural green development efficiency showed a U-shaped trend, suggesting a low level of efficiency. Although a gradient difference was visible among eastern, central, and western regions, the efficiency gap narrowed each year. Technological progress and efficiency both promoted agricultural green development efficiency, especially technological progress. Agricultural green development efficiency had significant spatial aggregation characteristics, but Moran's I result showed a downward trend from 2015 to 2020, indicating a risk of spatial dispersion in the later stage. The provinces with high agricultural green development efficiency were mainly concentrated in the eastern region, while those with low efficiency were concentrated in the central and western regions. Agricultural green development efficiency was influenced by various factors, which showed differences according to time and region. The impact of the labor force's education level and technological progress increased during the study period, and significantly facilitated agricultural green development efficiency in the eastern region, while the central and western regions were still affected by the scale level and environmental regulation, reflecting the advantages of the eastern region in terms of economy and technology. In the future, strengthening agricultural scientific and technological innovation and deepening interprovincial cooperation can help further improve the level of green agricultural development. In addition, local governments should formulate more precise local agricultural support policies based on macro-level policies and local conditions.

The mineral dust emitted from Central Asia has a significant influence on the global climate system. However, the history and mechanisms of aeolian activity in Central Asia remain unclear, due to the lack of well-dated records of aeolian activity and the intense wind erosion in some of the dust source areas (e.g., deserts). Here, we present the records of aeolian activity from a sedimentary sequence in the southern Gurbantunggut Desert of China using grain size analysis and optically stimulated luminescence (OSL) dating, based on field sampling in 2019. Specifically, we used eight OSL dates to construct chronological frameworks and applied the end-member (EM) analysis for the grain size data to extract the information of aeolian activity in the southern Gurbantunggut Desert during the last 900 a. The results show that the grain size dataset can be subdivided into three EMs (EM1, EM2, and EM3). The primary modal sizes of these EMs (EM1, EM2, and EM3) are 126.00, 178.00, and 283.00 μm, respectively. EM1 represents a mixture of the suspension components and saltation dust, while EM2 and EM3 show saltation dust transported over a shorter distance via strengthened near-surface winds, which can be used to trace aeolian activity. Combined with the OSL chronology, our results demonstrate that during the last 900 a, more intensive and frequent aeolian activity occurred during 450-100 a BP (Before Present) (i.e., the Little Ice Age (LIA)), which was reflected by a higher proportion of the coarse-grained components (EM2+EM3). Aeolian activity decreased during 900-450 a BP (i.e., the Medieval Warm Period (MWP)) and 100 a BP-present (i.e., the Current Warm Period (CWP)). Intensified aeolian activity was associated with the strengthening of the Siberian High and cooling events at high northern latitudes. We propose that the Siberian High, under the influence of temperature changes at high northern latitudes, controlled the frequency and intensity of aeolian activity in Central Asia. Cooling at high northern latitudes would have significantly enhanced the Siberian High, causing its position to shift southward. Subsequently, the incursion of cold air masses from high northern latitudes resulted in stronger wind regimes and increased dust emissions from the southern Gurbantunggut Desert. It is possible that aeolian activity may be weakened in Central Asia under future global warming scenarios, but the impact of human activities on this region must also be considered.

Soil erosion is one of the most serious environmental issues constraining the sustainable development of human society and economies. Soil compound erosion is the result of the alternation or interaction between two or more erosion forces. In recent years, fluctuations and extreme changes in climatic factors (air temperature, precipitation, wind speed, etc.) have led to an increase in the intensity and extent of compound erosion, which is increasingly considered in soil erosion research. First, depending on the involvement of gravity, compound erosion process can be divided into compound erosion with and without gravity. We systematically summarized the research on the mechanisms and processes of alternating or interacting soil erosion forces (wind, water, and freeze-thaw) considering different combinations, combed the characteristics of compound erosion in three typical regions, namely, high-elevation areas, high-latitude areas, and dry and wet transition regions, and reviewed soil compound erosion research methods, such as station observations, simulation experiments, prediction models, and artificial neural networks. The soil erosion model of wind, water, and freeze-thaw interaction is the most significant method for quantifying and predicting compound erosion. Furthermore, it is proposed that there are several issues such as unclear internal mechanisms, lack of comprehensive prediction models, and insufficient scale conversion methods in soil compound erosion research. It is also suggested that future soil compound erosion mechanism research should prioritize the coupling of compound erosion forces and climate change.

Qilian Mountains in Northwest China is a significant ecological security barrier due to its distinctive geographic setting, which has significant biological resource and gene pool. In order to assess the soil quality and ecosystem health in this area, we identified the structural characteristics and functional groups of soil microbial communities. This study focused on Amidongsuo, a typical watershed of the Qilian Mountains, and researched the vertical distribution and dominant populations of soil microorganisms in different habitats, and the relationship between soil microorganisms and environmental factors. Soil microorganisms from three grassland plots, five shrubland plots, and five forest plots in Amidongsuo were studied using high-throughput sequencing. The Venn diagram showed that the types of bacteria were fewer than those of fungi in Amidongsuo. Soil bacteria Acidobacteriota, Proteobacteria, and Methylomirabilota as well as fungi Basidiomycota, Ascomycota, and Mortierellomycota played dominant roles in Amidongsuo, according to the LEfSe (linear discriminant analysis (LDA) effect size) and community structure analyses. According to the ANOSIM (analysis of similarities) result, for both bacteria and fungi, R values of grassland and shrubland were small (R²=0.045 and R²=0.256, respectively), indicating little difference between these two ecosystems. RDA (redundancy analysis) showed a closer relationship between soil nutrients and fungi, and a gradually decreasing correlation between soil nutrients and microorganisms with increasing soil depth. Bacteria were mainly affected by pH, nitrogen (N), and potassium (K), while fungi were mainly affected by K. Overall, fungi had more effect on soil quality than bacteria. Therefore, adjustment of soil K content might improve the soil environment of Amidongsuo in the Qilian Mountains.

Manipulated precipitation patterns can profoundly influence the metabolism of soil microorganisms. However, the responses of soil organic carbon (SOC) and nutrient turnover to microbial metabolic limitation under changing precipitation conditions remain unclear in semi-arid ecosystems. This study measured the potential activities of enzymes associated with carbon (C: β-1,4-glucosidase (BG) and β-D-cellobiosidase (CBH)), nitrogen (N: β-1,4-N-acetylglucosaminidase (NAG) and L-leucine aminopeptidase (LAP)) and phosphorus (P: alkaline phosphatase (AP)) acquisition, to quantify soil microbial metabolic limitations using enzymatic stoichiometry, and then identify the implications for soil microbial metabolic limitations and carbon use efficiency (CUE) under decreased precipitation by 50% (DP) and increased precipitation by 50% (IP) in a temperate grassland. The results showed that soil C and P were the major elements limiting soil microbial metabolism in temperate grasslands. There was a strong positive dependence between microbial C and P limitations under manipulated precipitation. Microbial metabolism limitation was promoted by DP treatment but reversed by IP treatment. Moreover, CUE was inhibited by DP treatment but promoted by IP treatment. Soil microbial metabolism limitation was mainly regulated by soil moisture and soil C, N, and P stoichiometry, followed by available nutrients (i.e., NO- 3, NH+ 4, and dissolved organic C) and microbial biomass (i.e., MBC and MBN). Overall, these findings highlight the potential role of changing precipitation in regulating ecosystem C turnover by limiting microbial metabolism and CUE in temperate grassland ecosystems.

The preceding and succeeding precipitation (PSP) often act together with extreme precipitation (EP), in turn, causing floods, which is an objective component that is often overlooked with regard to summer flood hazards in the arid region of Northwest China. In this study, event-based extreme precipitation (EEP) was defined as continuous precipitation that includes at least one day of EP. We analyzed the spatiotemporal variation characteristics of four EEP types (front EEP, late EEP, balanced EEP, and single day EEP) across the Loess Plateau (LP) based on data acquired from 87 meteorological stations from 1960 to 2019. Precipitation on the LP basically maintained a spatial pattern of "low in the northwest region and high in the southeast region", and EP over the last 10 a increased significantly. The cumulative precipitation percentage of single day EEP was 34% and was dominant for 60 a, while the cumulative precipitation percentage of front, late, and balanced EEP types associated with PSP accounted for 66%, which confirms to the connotation of EEP. The cumulative frequencies of front and late EEP types were 23% and 21%, respectively, while the cumulative frequency of balanced EEP had the lowest value at only 13%. Moreover, global warming could lead to more single day EEP across the LP, and continuous EEP could increase in the northwestern region and decrease in the eastern region in the future. The concept of process-oriented EP could facilitate further exploration of disaster-causing processes associated with different types of EP, and provide a theoretical basis for deriving precipitation disaster chains and construction of disaster cluster characteristics.

The reconstruction of paleovegetation and paleoclimate requires an understanding of the relationships between surface pollen assemblages and modern vegetation and climate. Here, we analyzed the characteristics of surface pollen assemblages across different vegetation zones in the Tianshan Mountains. Using surface pollen analysis and vegetation sample surveys at 75 sites on the northern slopes of the Tianshan Mountains, we determined the correlation between the percentage of dominant pollen types and the corresponding vegetation cover. Redundancy analysis was used to investigate the relationships between surface pollen assemblages and environmental factors. Our results show that the Tianshan Mountains contain several distinct ecological regions, which can be divided into five main vegetation zones from low to high altitudes: mountain desert zone (Hutubi County (HTB): 500-1300 m; Qitai County (QT): 1000-1600 m), mountain steppe zone (HTB: 1400-1600 m; QT: 1650-1800 m), mountain forest zone (HTB: 1650-2525 m; QT: 1850-2450 m), subalpine meadow zone (HTB: 2550-2600 m; QT: 2500-2600 m), and alpine mat vegetation zone (HTB: 2625-2700 m; QT: 2625-2750 m). The surface pollen assemblages of different vegetation zones can accurately reflect the characteristics of the mountainous vegetation patterns on the northern slopes of the Tianshan Mountains when excluding the widespread occurrence of Chenopodiaceae, Artemisia, and Picea pollen. Both average annual precipitation (P_ann) and annual average temperature (T_ann) affect the distribution of surface pollen assemblages. Moreover, P_ann is the primary environmental factor affecting surface pollen assemblages in this region. A significant correlation exists between the pollen percentage and vegetation cover of Picea, Chenopodiaceae, Artemisia, and Asteraceae. Moreover, Picea, Chenopodiaceae, and Artemisia pollen are over-represented compared with their corresponding vegetation cover. The Asteraceae pollen percentage roughly reflects the distribution of a species within the local vegetation. These results have important implications for enhancing our understanding of the relationship between surface pollen assemblages and modern vegetation and climate.

Malus sieversii (wild apple tree), only distributed in the Tianshan Mountains in Central Asia, is a tertiary relic species and an ancestral species of cultivated apples. However, existing natural populations of wild apple trees have been declining. To date, spatiotemporal variations in the growth status of declining wild apple trees and influencing factors in the narrow valley areas in the Tianshan Mountains remain unclear. In this study, field investigation and sampling were carried out in three years (2016-2018) at four elevations (1300, 1400, 1500, and 1600 m) in the Qiaolakesai Valley (a typical longitudinal narrow valley in the Yili River Valley) of the western Tianshan Mountains in Xinyuan County, Xinjiang Uygur Autonomous Region, China. Projective coverage, dead branch percentage, and 18 twig traits (these 20 parameters were collectively referred to as plant traits) were determined to comprehensively reflect the growth status of declining wild apple trees. The values of dead branch percentage ranged from 36% to 59%, with a mean of 40%. Year generally showed higher impact on plant traits than elevation. In 2017 and 2018, projective coverage, leaf size, leaf nitrogen concentration, and nitrogen to phosphorous ratio were markedly higher than those in 2016. However, dead branch percentage and leaf and stem phosphorous concentrations showed the opposite trend. Most of the topological parameters of plant trait networks differed in the three years, but the strength of trait-trait association increased year by year. The mean difference between day and night temperatures (MDT), annual accumulative precipitation, soil electrical conductivity, and soil pH had the greatest impact on the plant trait matrix. The growth status of declining wild apple trees was directly and positively affected by MDT and leaf size. In conclusion, the growth of declining wild apple trees distributed in the narrow valley areas was more sensitive to interannual environmental changes than elevation changes. The results are of great significance for further revealing the decline mechanism of wild apple trees in the Tianshan Mountains.