The release of essential nutrients from soil minerals for plant growth in calcareous soils, facilitated by organic extractants, is critical in semi-arid areas, particularly for elements affected by high soil pH. This study aims to investigate the release of calcium (Ca), magnesium (Mg), and phosphorus (P) through the application of wood vinegar extract in surface calcareous soils in Borojerd City, Lorestan Province, Iran. The experiment was conducted using a completely randomized design with three replications. The treatments included soils from three different land uses: vineyard, wheat field, and rangeland, each treated with 1.00% wood vinegar solution. Cumulative measurements of the specified elements were recorded over 10 consecutive 0.5 h intervals. The release data were analyzed using four various kinetic models (Elovich equation, parabolic diffusion law, power function equation, and zero-order kinetics). The highest concentrations recorded were for Ca (39,500.00 mg/kg), Mg (5880.00 mg/kg), and P (5.00 mg/kg) in grape cultivation. The findings revealed a significant difference in Ca release between grape cultivation and rangeland (P<0.01), while the Mg release showed a significant difference between both grape cultivation and rangeland and wheat cultivation (P<0.01). Additionally, the cumulative release of P showed significant differences between grape cultivation and both wheat and rangeland (P<0.01). The results indicated that the zero-order kinetics provided the best fit for the data (R²=0.99). The maximum initial release amount was observed in grape cultivation when applying the zero-order kinetics, while the highest release rate was achieved using the parabolic diffusion law across three applications. Wood vinegar had the capacity to degrade various clay minerals, including vermiculite, smectite, palygorskite, and, to some extent, illite, resulting in the release of associated elements. Consequently, it can be concluded that wood vinegar can be effectively utilized in grape cultivation as an agent for reducing soil acidity, thereby enhancing the availability of soil nutrients and decreasing reliance on chemical fertilizers.

Assessing and managing ecological risks in ecologically fragile areas remain challenging at present. To get to know the ecological risk situation in Turpan City, China, this study constructed an ecological risk evaluation system to obtain the ecological risk level (ERL) and ecological risk index (ERI) based on the multi-objective linear programming-patch generation land use simulation (MOP-PLUS) model, analyzed the changes in land use and ecological risk in Turpan City from 2000 to 2020, and predicted the land use and ecological risk in 2030 under four different scenarios (business as usual (BAU), rapid economic development (RED), ecological protection priority (EPP), and eco-economic equilibrium, (EEB)). The results showed that the conversion of land use from 2000 to 2030 was mainly between unused land and the other land use types. The ERL of unused land was the highest among all the land use types. The ecological risk increased sharply from 2000 to 2010 and then decreased from 2010 to 2020. According to the value of ERI, we divided the ecological risk into seven levels by natural breakpoint method; the higher the level, the higher the ecological risk. For the four scenarios in 2030, under the EPP scenario, the area at VII level was zero, while the area at VII level reached the largest under the RED scenario. Comparing with 2020, the areas at I and II levels increased under the BAU, EPP, and EEB scenarios, while decreased under the RED scenario. The spatial distributions of ecological risk of BAU and EEB scenarios were similar, but the areas at I and II levels were larger and the areas at V and VI levels were smaller under the EEB scenario than under the BAU scenario. Therefore, the EEB scenario was the optimal development route for Turpan City. In addition, the results of spatial autocorrelation showed that the large area of unused land was the main reason affecting the spatial pattern of ecological risk under different scenarios. According to Geodetector, the dominant driving factors of ecological risk were gross domestic product rating (GDPR), soil type, population, temperature, and distance from riverbed (DFRD). The interaction between driving factor pairs amplified their influence on ecological risk. This research would help explore the low ecological risk development path for urban construction in the future.

Salt-tolerant bacteria associated with halophytes enhance plant resistance and adaptation to environmental stress. The purpose of this study was to investigate the diversity and plant-beneficial traits of bacteria associated with three halophytes in an arid land, Northwest China. The bacterial strains were isolated from the roots, shoots, rhizosphere, and bulk soil of three halophytes, i.e., Salicornia europaea L., Kalidium foliatum (Pall.) Moq., and Suaeda aralocaspica (Bunge) Freitag & Schütze, collected from the saline soils near to the Wujiaqu City, Xinjiang, Northwest China. A total of 567 strains were isolated and identified from these three halophytes belonging to 4 phyla, 6 classes, 25 orders, 36 families, and 66 genera, including 147 potential novel species. A total of 213 strains exhibited one or more plant growth- promoting properties, while 20 strains demonstrated multiple in vitro plant growth-promoting activities, including phosphate solubilization, nitrogen fixation, siderophore production, and production of hydrolytic enzymes such as protease and cellulase. Our findings showed that halophytes in the arid land harbor diverse bacteria with the potential to enhance plant growth and adaptability under challenging environmental conditions.

Water is essential for agricultural production; however, climate change has exacerbated drought and water stress in arid and semi-arid areas such as Iran. Despite these challenges, irrigation water efficiency remains low, and current water management schemes are inadequate. Consequently, Iranian crops suffer from low water productivity, highlighting the urgent need for enhanced productivity and improved water management strategies. In this study, we investigated irrigation management conditions in the Hamidiyeh farm, Khuzestan Province, Iran and used the calibrated AquaCrop and WinSRFR (a surface irrigation simulation model) models to reflect these conditions. Subsequently, we examined different management scenarios using each model and evaluated the results from the second year. The findings demonstrated that combining simulation of the AquaCrop and WinSRFR models was highly effective and could be employed for irrigation management in the field. The AquaCrop model accurately simulated wheat yield in the first year, being 2.6 t/hm², which closely aligned with the measured yield of 3.0 t/hm². Additionally, using the WinSRFR model to adjust the length of existing borders from 200 to 180 m resulted in a 45.0% increase in efficiency during the second year. To enhance water use efficiency in the field, we recommended adopting borders with a length of 180 m, a width of 10 m, and a flow rate of 15 to 18 L/s. The AquaCrop and WinSRFR models accurately predicted border irrigation conditions, achieving the highest water use efficiency at a flow rate of 18 L/s. Combining these models increased farmers' average water consumption efficiency from 0.30 to 0.99 kg/m³ in the second year. Therefore, the results obtained from the AquaCrop and WinSRFR models are within a reasonable range and consistent with international recommendations. This adjustment is projected to improve the water use efficiency in the field by approximately 45.0% when utilizing the border irrigation method. Therefore, integrating these two models can provide comprehensive management solutions for regional farmers.

Root system architecture has often been overlooked in plant research despite its critical role in plant adaptation to environmental conditions. This study focused on the root system architecture of the desert shrub Reaumuria soongorica in the Alxa steppe desert, Northwest China. Plant samples were collected during May-September 2019. Using excavation methods, in situ measurements, and root scanning techniques, we analyzed the root distribution, topology, and branching patterns of R. soongorica across an age sequence of 7-51 a. Additionally, we investigated the allometric relationships of root collar diameter with total coarse root length, biomass, and topological parameters. The results showed that the roots of R. soongorica were predominantly concentrated in shallow soil layers (10-50 cm), with lateral root branching and biomass allocation increasing with shrub age. The root topology exhibited a herringbone-like structure, with average topological and modified topological indices of 0.89 and 0.96, respectively, both of which adjusted with shrub age. The root system displayed a self-similar branching pattern, maintaining a constant cross-sectional area ratio of 1.13 before and after branching, deviating from the area-preserving rule. These adaptive traits allow R. soongorica to efficiently expand its nutrient acquisition zone, minimize internal competition, and optimize resource uptake from the upper soil layers. Furthermore, significant linear relationships were observed between log₁₀-transformed root collar diameter and log₁₀-transformed total coarse root length, biomass, and topological parameters. These findings advance non-destructive approaches for studying root characteristics and contribute to the development of root-related models. Besides, this study provides new insights into the adaptive strategies of R. soongorica under extreme drought conditions, offering valuable guidance for species selection and cultivation in desert restoration efforts.

Intense evaporation in areas with loess-like sulfate saline soils has resulted in significant ecological challenges that include water shortages and soil salinization. Investigating evaporation rate in loess-like sulfate saline soils under varying salt contents carries crucial implications for understanding regional water loss processes, predicting soil salinization advancement, and formulating effective ecological management strategies. Therefore, this study sampled the loess-like sulfate saline soil that is widely distributed in western China as experimental materials and investigated the impact of different initial salt contents (0.00%, 0.50%, 1.50%, 3.00%, and 5.00%) on the evaporation rate, water content, and temperature of soil. The results showed that the evaporation rate decreased with increasing initial salt content. After a salt accumulation layer formed on the soil surface, the water content of the surface soil fluctuated. An increase in the initial salt content resulted in a corresponding increase in the surface temperature. Considering the evaporation characteristics of loess-like sulfate saline soil and the impact of an anomalous increase in surface soil water content on soil surface resistance, this study proposed a modified evaporation model on the basis of Fujimaki's evaporation model of saline soil by introducing a correction coefficient β to modify the soil surface resistance. A comparison of the calculated evaporation rates before and after the modification with the measured evaporation rates revealed a significant improvement in the calculation accuracy of the modified model, indicating that the modified model is capable of more accurately simulating the evaporation rate of sulfate saline soil with different initial salt contents. This paper proposes an effective method for calculating the evaporation rate of loess-like sulfate saline soils, providing a theoretical basis for evaporation research in saline soil.

Surface soil cracking in alpine meadows signifies the transition of degradation from quantitative accumulation to qualitative deterioration. Quantitative research remains insufficient regarding changes in the mechanical properties of degraded meadow soils and the mechanical thresholds for cracking initiation. This study explored the relationships between surface cracking and the physical properties, tensile strength, and matrix suction of root-soil composites in alpine meadow sites with different stages of degradation (undegraded (UD), lightly degraded (LD), moderately degraded (MD), and heavily degraded (HD)) under different water gradients (high water content (HWC), medium water content (MWC), and low water content (LWC)) corresponding to different drying durations at a constant temperature of 40.0°C. The Huangcheng Mongolian Township in Menyuan Hui Autonomous County, Qinghai Province, China was chosen as the study area. The results indicated that as the degradation degree of alpine meadow intensified, both water content of root-soil composite and the fine grain content of soil decreased. In contrast, the root-soil mass ratio and root area ratio initially increased and then decreased with progressive degradation. Under a consistent water content, the tensile strength of root-soil composite followed a pattern of MD>HD>LD>UD. The peak displacement of tensile strength also decreased as the degradation degree of alpine meadow increased. Both the tensile strength and matrix suction of root-soil composite increased as root-soil water content decreased. A root-soil water content of 30.00%-40.00% was found to be the critical threshold for soil cracking in alpine meadows. Within this range, the matrix suction of root-soil composite ranged from 50.00 to 100.00 kPa, resulting in the formation of linear cracks in the surface soil. As the root-soil water content continued to decrease, liner cracks evolved into branch-like and polygonal patterns. The findings of this study provide essential data for improving the mechanical understanding of grassland cracking and its development process.

Precipitation is scarce in semi-arid areas, which results in serious drought. Occurrence of flash drought is quite often in these areas, and flash drought may also cause significant disasters. However, monitoring flash drought is still weak and remains a challenge. This study aims to identify, evaluate, and monitor flash drought events that occurred from 1961 to 2020 in reservoirs of the Ceará State, Brazil. The Christian's method, standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), and evaporative demand drought index (EDDI) were used to assess the severity and persistence of flash drought. Moreover, analyses conducted in 2001, 2008, 2011, 2012, 2016, and 2020 revealed the complexity and interaction of flash drought with environmental and meteorological factors. The results indicated that in dry years such as 2001, 2012, and 2016, drought indices pointed to the intensification of drought conditions, with impacts on major reservoirs in the area, such as Banabuiú, Castanhão, and Orós. Low precipitation, associated with high evaporative demand, intensified water stress, reducing water availability for the population and local ecosystems. In wet years such as 2008, 2011, and 2020, SPEI and EDDI indicated higher moisture levels and drought relief, favoring the recovery of reservoirs. It was also observed that most flash drought episodes evolved into conventional droughts, highlighting their persistence and potential long-term impact. Moreover, the months of May and November presented a higher frequency of flash drought during the wet and dry periods, respectively, negatively impacting most of the studied reservoirs. These findings underscore the need for effective drought monitoring and mitigation strategies to reduce its impacts on agriculture and water resources in the semi-arid area. Early detection and analysis of flash drought are important for improving water resource management and for continuous adaptation to changing drought conditions.

The western alpine region is an important freshwater supply and water conservation area for China and its surrounding areas. As ecological civilization construction progresses, the ecohydrology of the western alpine region in China, which is a crucial ecological barrier, has undergone significant changes. In this study, we collected 1077 sampling points and presented a comprehensive overview of research results pertaining to the hydrochemistry of river water, meltwater, groundwater, and precipitation in the western alpine region of China using piper diagram, end-member diagram, and hydrological process indication. Water resources in the western alpine region of China were found to be weakly alkaline and have low total dissolved solids (TDS). The mean pH values for river water, meltwater, groundwater, and precipitation are 7.92, 7.58, 7.72, and 7.32, respectively. The mean TDS values for river water, meltwater, groundwater, and precipitation are 280.99, 72.48, 544.41, and 67.68 mg/L. The hydrochemical characteristics of the water resources in this region exhibit significant spatial and temporal variability. These characteristics include higher ion concentrations during the freezing period and higher ion concentrations in inland river basins, such as the Shule River Basin and Tarim River Basin. The principal hydrochemical type of river water and meltwater is HCO₃^-•SO₄^2--Ca²⁺, whereas the principal cations in groundwater are Mg²⁺ and Ca²⁺, and the principal anions are HCO₃^- and SO₄^2-. In terms of precipitation, the principal hydrochemical type is SO₄^2--Ca²⁺. The chemical ions in river water and groundwater are primarily influenced by rock weathering and evaporation-crystallization, whereas the chemical ions in meltwater are mainly affected by rock weathering and atmospheric precipitation, and the chemical ions in precipitation are derived primarily from terrestrial sources. The main forms of water input in the western alpine region of China are precipitation and meltwater, and mutual recharge occurs between river water and groundwater. Hydrochemical characteristics can reflect the impact of human activities on water resources. By synthesizing the regional hydrochemical studies, our findings provide insights for water resources management and ecological security construction in the western alpine region in China.

Agriophyllum squarrosum (L.) Moq., commonly known as sandrice, is an annual medicinal plant prevalent in the dunes across China's deserts. A garden trial revealed that flavonoid content varies among sandrice ecotypes due to long-term local adaptation to water variability. To investigate how sandrice responds to drought stress through the molecular metabolic regulation of flavonoids, we employed transcriptomic and metabolomic analyses during a 9-d ambient drought stress, examining three ecotypes along a precipitation gradient. The three ecotypes located in Dengkou (DK) County, Dulan (DL) County, and Aerxiang (AEX) village of northern China, which had 137, 263, and 485 mm precipitation, respectively. Soil moisture content was 4.04% after drought stress, causing seedlings of the three sandrice ecotypes to display collapsed structures, yellowing leaves, wilting, and curling. Among these, DL exhibited superior drought tolerance, in which plant height increase (PHI) and leaf area (LA) were significantly higher than those of DK and AEX. Flavonoid-targeted metabolomics identified that rutin, isoquercitrin, and astragalin constituted over 95.00% of the 15 flavonoid metabolites detected. A total of 12 differentially accumulated flavonoids (DAFs) were found, with rutin being the most abundant (1231.57-2859.34 ng/100 mg fresh weight (FW)), showing a gradual increase along the precipitation gradient. Transcriptomic analysis revealed 14 common differentially expressed genes (DEGs) associated with flavonoid synthesis among the three ecotypes. Integrative analysis of DEGs and DAFs indicated that sandrice adapts to drought stress by activating different flavonoid synthesis pathways. In DK, the dihydrokaempferol-dihydroquercetin pathway, regulated by flavonoid 3'-monooxygenase (CYP75B1), likely enhances drought adaptation. In AEX, transcriptional repression by O-methylatransferase (OMT) shifts the metabolic flux from the quercetin-isorhamnetin pathway to the quercetin-isoquercetin-rutin pathway in response to drought. DL, the most drought- tolerant ecotype, appears to activate the naringenin-apigenin-luteolin route and employs a unique flavonoid accumulation pattern in response to drought stress. Our data reveal that flavonoid synthesis in sandrice is fine-tuned among ecotypes to cope with drought, offering valuable germplasm resources and evaluation methods for sandrice acclimation and providing insights into drought response in non-model plants.

Vegetation plays a major role in soil protection against erosion effects, and studies have also highlighted its importance in retaining sediments from roadside slopes. Yet, hydro-sedimentological studies under natural precipitation conditions are still scarce in semi-arid areas due to difficulties in monitoring the few and very concentrated precipitation events. Quantifying sediment connectivity and yield at watershed scale, often highly impacted by the erosion of unpaved roads, is necessary for management plans. This study aims to evaluate the efficiency of native vegetation on roadside slope segments in Caatinga biome in retaining sediments and conserving the soil in a semi-arid area of Brazil. Surface runoff, sediment concentration, and yield measurements were measured from 34 natural precipitation events in four years on two slopes with and without vegetation. The runoff coefficients of the plot with no vegetation varied from 3.0% to 58.0%, while in the vegetated plot, they showed variation from 1.0% to 21.0%. The annual specific sediment yield ranged from 4.6 to 138.7 kg/(hm²•a) for the vegetated plot and from 34.9 to 608.5 kg/(hm²•a) for the unvegetated one. These results indicate a 4 to 12 times higher soil loss on the unvegetated slope in relation to the vegetated one and demonstrate that natural Caatinga vegetation acts as an effective barrier against surface-transported sediments. Moreover, natural Caatinga vegetation present on the slope plays an important role in breaking connectivity between sediment flows from unpaved roads and the watershed drainage system. These findings indicate that investments in unpaved road and roadside slope restoration, not only enhance road infrastructure but also promote environmental gains by reducing the impact of erosion.

Diversity of soil microorganisms in different habitats of arid and semi-arid areas plays an important role in the soil texture and nutrient, promoting the growth of vegetation in those areas. To clarify the response of soil bacterial community diversity to the changes of environmental factors in different habitats, this study collected soil samples under the canopies of Tamarix ramosissima Ledeb. in oasis, transition zone, and desert habitats in the upper reaches of the Tarim River, Northwest China. High-throughput sequencing technology and PICRUSt2 software were used to explore the composition and function of soil bacterial communities in different habitats of T. ramosissima. The results showed that: (1) soil environmental factors under the canopy of T. ramosissima in the three habitats differed significantly, with soil moisture and nutrient conditions being better in the oasis; (2) Proteobacteria, Bacteroidetes, Firmicutes, Actinobacteria, and Gemmatimonadetes were the major bacterial communities in the three habitats; (3) soil bacterial community composition under the canopy of T. ramosissima varied greatly, and the richness was significantly different among the three habitats; (4) redundancy analysis indicated that soil water content and available phosphorous were the most important environmental factors influencing the composition of soil bacterial community; and (5) 6 primary functions and 21 secondary functions were obtained by PICRUSt2 function prediction, with metabolism being the most dominant function. This study revealed the response of soil bacterial community composition to habitat changes and their driving factors in the upper reaches of the Tarim River, which could improve the understanding of ecological sensitivity of soil microorganisms in arid and semi-arid areas, and provide a theoretical foundation for improving soil quality and ecological protection.

Grassland is a key component of the ecosystem in the Qinghai Lake Basin, China. Understanding the effects of climate change and human activities on grassland productivity significantly improves ecological conservation and promotes sustainable vegetation growth in this area. Based on the net primary productivity (NPP) products of MOD17A3HGF (a moderate-resolution imaging spectroradiometer (MODIS) product that provides annual NPP at 500 m resolution) and meteorological data, we analyzed the spatial and temporal evolution of grassland NPP and its interaction with climate factors in the Qinghai Lake Basin from 2001 to 2022 via partial correlation and trend analysis methods. We also used the deflecting trend residual method and scenario analysis method to quantitatively assess the relative contributions of climatic factors and human activities to grassland NPP. The results revealed that: (1) during the past 22 a, grassland NPP increased considerably, with a gradient change from the northwest to the southeast of the study area; (2) sunshine duration, precipitation, and temperature positively influenced grassland NPP, with sunshine duration exerting a stronger effect on grassland NPP than precipitation and temperature; and (3) 98.47% of the grassland in the study area was restored, with an average contribution of 65.00% from human activities and 35.00% from climatic alterations. Compared with climate change, human-induced factors had a greater effect on grassland NPP in this area. The results of the study not only provide important scientific support for ecological restoration and sustainable development of the basin but also offer new ideas for research on similar ecologically fragile areas.

Ecological security patterns are paramount to the advancement of an ecological civilization in China, aiming to enhance the stability and service functions of ecosystems to achieve sustainable regional development. However, current regional ecological protection efforts have not been effectively integrated into the regional development planning of ecological security pattern. This study systematically assessed the effectiveness of ecological protection projects in Yanchi County, Ningxia Hui Autonomous Region, China, through the evaluation of landscape ecological quality. Based on the evaluation results of landscape ecological quality, this study used morphological pattern analysis (MSPA), minimum cumulative resistance (MCR) model, and gravity model together to construct the ecological security pattern of Yanchi County. The findings revealed that from 1990 to 2020, with the implementation of ecological protection projects started from 2000, the landscape stability of Yanchi County first decreased and then increased, and the intensity of landscape disturbance first intensified but then decreased, indicating an improvement in the landscape ecological quality and a significant enhancement of the ecological environment in Yanchi County. The ecological security pattern of Yanchi County consisted of 10 ecological sources, 10 ecological source points, 23 ecological corridors, and 27 ecological nodes. The ecological security pattern of Yanchi County exhibited distinct spatial variations, with stronger ecological security observed in the southern part than in northern part of the county. The ecological sources were denser in the southern part than in the northern part of the county, and accordingly, the length of ecological corridors was shorter and denser in the southern than that in the northern part of the county. Based on the spatial distribution of landscape ecological quality and the characteristics of ecological security pattern of Yanchi County in 2020, we suggested Yanchi County to build four zones to optimize the ecological security pattern construction: the Haba Lake ecological conservation zone, the urban ecological planning zone, the ecological environment restoration zone, and the ecological security improvement zone. This study can provide essential guidance for the construction of ecological security pattern in farming-pastoral areas both in China and worldwide.

Recent years have witnessed increasingly frequent extreme precipitation events, especially in desert steppes in the semi-arid and arid transition zone. Focusing on a desert steppe in western-central Inner Mongolia Autonomous Region, China, this study aimed to determine the principle time-varying pattern of extreme precipitation and its dominant climate forcings during the period 1988-2017. Based on the generalized additive models for location, scale, and shape (GAMLSS) modeling framework, we developed the best time-dependent models for the extreme precipitation series at nine stations, as well as the optimized non-stationary models with large-scale climate indices (including the North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), Southern Oscillation (SO), Pacific Decadal Oscillation (PDO), Arctic Oscillation (AO), and North Pacific Oscillation (NPO)) as covariates. The results indicated that extreme precipitation remained stationary at more than half of the stations (Hailisu, Wuyuan, Dengkou, Hanggin Rear Banner, Urad Front Banner, and Yikewusu), while linear and non-linear time-varying patterns were quantitatively identified at the other stations (Urad Middle Banner, Linhe, and Wuhai). These non-stationary behaviors of extreme precipitation were mainly reflected in the mean value of extreme precipitation. The optimized non-stationary models performed best, indicating the significant influences of large-scale climate indices on extreme precipitation. In particular, the NAO, NPO, SO, and AMO remained as covariates and significantly influenced the variations in the extreme precipitation regime. Our findings have important reference significance for gaining an in-depth understanding of the driving mechanism of the non-stationary behavior of extreme precipitation and enable advanced predictions of rainstorm risks.

Challenges in land use and land cover (LULC) include rapid urbanization encroaching on agricultural land, leading to fragmentation and loss of natural habitats. However, the effects of urbanization on LULC of different crop types are less concerned. The study assessed the impacts of LULC changes on agriculture and drought vulnerability in the Aguascalientes region, Mexico, from 1994 to 2024, and predicted the LULC in 2034 using remote sensing data, with the goals of sustainable land management and climate resilience strategies. Despite increasing urbanization and drought, the integration of satellite imagery and machine learning models in LULC analysis has been underutilized in this region. Using Landsat imagery, we assessed crop attributes through indices such as normalized difference vegetation index (NDVI), normalized difference water index (NDWI), normalized difference moisture index (NDMI), and vegetation condition index (VCI), alongside watershed delineation and spectral features. The random forest model was applied to classify LULC, providing insights into both historical and future trends. Results indicated a significant decline in vegetation cover (109.13 km²) from 1994 to 2024, accompanied by an increase in built-up land (75.11 km²) and bare land (67.13 km²). Projections suggested a further decline in vegetation cover (41.51 km²) and continued urban land expansion by 2034. The study found that paddy crops exhibited the highest values, while common bean and maize performed poorly. Drought analysis revealed that mildly dry areas in 2004 became severely dry in 2024, highlighting the increasing vulnerability of agriculture to climate change. The study concludes that sustainable land management, improved water resource practices, and advanced monitoring techniques are essential to mitigate the adverse effects of LULC changes on agricultural productivity and drought resilience in the area. These findings contribute to the understanding of how remote sensing can be effectively used for long-term agricultural planning and environmental sustainability.

Nitrogen deposition and water tables are important factors to control soil microbial community structure. However, the specific effects and mechanisms of nitrogen deposition and water tables coupling on bacterial diversity, abundance, and community structure in arid alpine wetlands remain unclear. The nitrogen deposition (0, 10, and 20 kg N/(hm²•a)) experiments were conducted in the Bayinbulak alpine wetland with different water tables (perennial flooding, seasonal waterlogging, and perennial drying). The 16S rRNA (ribosomal ribonucleic acid) gene sequencing technology was employed to analyze the changes in bacterial community diversity, network structure, and function in the soil. Results indicated that bacterial diversity was the highest under seasonal waterlogging condition. However, nitrogen deposition only affected the bacterial Chao1 and beta diversity indices under seasonal waterlogging condition. The abundance of bacterial communities under different water tables showed significant differences at the phylum and genus levels. The dominant phylum, Proteobacteria, was sensitive to soil moisture and its abundance decreased with decreasing water tables. Although nitrogen deposition led to changes in bacterial abundance, such changes were small compared with the effects of water tables. Nitrogen deposition with 10 kg N/(hm²•a) decreased bacterial edge number, average path length, and robustness. However, perennial flooding and drying conditions could simply resist environmental changes caused by 20 kg N/(hm²•a) nitrogen deposition and their network structure remain unchanged. The sulfur cycle function was dominant under perennial flooding condition, and carbon and nitrogen cycle functions were dominant under seasonal waterlogging and perennial drying conditions. Nitrogen application increased the potential function of part of nitrogen cycle and decreased the potential function of sulfur cycle in bacterial community. In summary, composition of bacterial community in the arid alpine wetland was determined by water tables, and diversity of bacterial community was inhibited by a lower water table. Effect of nitrogen deposition on bacterial community structure and function depended on water tables.

Critical zone (CZ) plays a vital role in sustaining biodiversity and humanity. However, flux quantification within CZ, particularly in terms of subsurface hydrological partitioning, remains a significant challenge. This study focused on quantifying subsurface hydrological partitioning, specifically in an alpine mountainous area, and highlighted the important role of lateral flow during this process. Precipitation was usually classified as two parts into the soil: increased soil water content (SWC) and lateral flow out of the soil pit. It was found that 65%-88% precipitation contributed to lateral flow. The second common partitioning class showed an increase in SWC caused by both precipitation and lateral flow into the soil pit. In this case, lateral flow contributed to the SWC increase ranging from 43% to 74%, which was notably larger than the SWC increase caused by precipitation. On alpine meadows, lateral flow from the soil pit occurred when the shallow soil was wetter than the field capacity. This result highlighted the need for three-dimensional simulation between soil layers in Earth system models (ESMs). During evapotranspiration process, significant differences were observed in the classification of subsurface hydrological partitioning among different vegetation types. Due to tangled and aggregated fine roots in the surface soil on alpine meadows, the majority of subsurface responses involved lateral flow, which provided 98%-100% of evapotranspiration (ET). On grassland, there was a high probability (0.87), which ET was entirely provided by lateral flow. The main reason for underestimating transpiration through soil water dynamics in previous research was the neglect of lateral root water uptake. Furthermore, there was a probability of 0.12, which ET was entirely provided by SWC decrease on grassland. In this case, there was a high probability (0.98) that soil water responses only occurred at layer 2 (10-20 cm), because grass roots mainly distributed in this soil layer, and grasses often used their deep roots for water uptake during ET. To improve the estimation of soil water dynamics and ET, we established a random forest (RF) model to simulate lateral flow and then corrected the community land model (CLM). RF model demonstrated good performance and led to significant improvements in CLM simulation. These findings enhance our understanding of subsurface hydrological partitioning and emphasize the importance of considering lateral flow in ESMs and hydrological research.

Evapotranspiration is the most important expenditure item in the water balance of terrestrial ecosystems, and accurate evapotranspiration modeling is of great significance for hydrological, ecological, agricultural, and water resource management. Artificial forests are an important means of vegetation restoration in the western Loess Plateau, and accurate estimates of their evapotranspiration are essential to the management and development of water use strategies for artificial forests. This study estimated the soil moisture and evapotranspiration based on the HYDRUS-1D model for the artificial Platycladus orientalis (L.) Franco forest in western mountains of Loess Plateau, China from 20 April to 31 October, 2023. Moreover, the influence factors were identified by combining the correlation coefficient method and the principal component analysis (PCA) method. The results showed that HYDRUS-1D model had strong applicability in portraying hydrological processes in this area and revealed soil water surplus from 20 April to 31 October, 2023. The soil water accumulation was 49.64 mm; the potential evapotranspiration (ET_p) was 809.67 mm, which was divided into potential evaporation (E_p; 95.07 mm) and potential transpiration (T_p; 714.60 mm); and the actual evapotranspiration (ET_a) was 580.27 mm, which was divided into actual evaporation (E_a; 68.27 mm) and actual transpiration (T_a; 512.00 mm). From April to October 2023, the ET_p, E_p, T_p, ET_a, E_a, and T_a first increased and then decreased on both monthly and daily scales, exhibiting a single-peak type trend. The average ratio of T_a/ET_a was 0.88, signifying that evapotranspiration mainly stemmed from transpiration in this area. The ratio of ET_a/ET_p was 0.72, indicating that this artificial forest suffered from obvious drought stress. The ET_p was significantly positively correlated with ET_a, and the R² values on the monthly and daily scales were 0.9696 and 0.9635 (P<0.05), respectively. Furthermore, ET_a was significantly positively correlated with temperature, solar radiation, and wind speed, and negatively correlated with relative humidity and precipitation (P<0.05); and temperature exhibited the highest correlation with ET_a. Thus, ET_p and temperature were the decisive contributors to ET_a in this area. The findings provide an effective method for simulating regional evapotranspiration and theoretical reference for water management of artificial forests, and deepen understanding of effects of each influence factors on ET_a in arid areas.

Against the backdrop of global warming, climate extremes and drought events have become more severe, especially in arid and semi-arid areas. This study forecasted the characteristics of climate extremes in the Xilin River Basin (a semi-arid inland river basin) of China for the period of 2021-2100 by employing a multi-model ensemble approach based on three climate Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) from the latest Coupled Model Intercomparison Project Phase 6 (CMIP6). Furthermore, a linear regression, a wavelet analysis, and the correlation analysis were conducted to explore the response of climate extremes to the Standardized Precipitation Evapotranspiration Index (SPEI) and Streamflow Drought Index (SDI), as well as their respective trends during the historical period from 1970 to 2020 and during the future period from 2021 to 2070. The results indicated that extreme high temperatures and extreme precipitation will further intensify under the higher forcing scenarios (SSP5-8.5>SSP2-4.5>SSP1-2.6) in the future. The SPEI trends under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios were estimated as -0.003/a, -0.004/a, and -0.008/a, respectively, indicating a drier future climate. During the historical period (1970-2020), the SPEI and SDI trends were -0.003/a and -0.016/a, respectively, with significant cycles of 15 and 22 a, and abrupt changes occurring in 1995 and 1996, respectively. The next abrupt change in the SPEI was projected to occur in the 2040s. The SPEI had a significant positive correlation with both summer days (SU) and heavy precipitation days (R10mm), while the SDI was only significantly positively correlated with R10mm. Additionally, the SPEI and SDI exhibited a strong and consistent positive correlation at a cycle of 4-6 a, indicating a robust interdependence between the two indices. These findings have important implications for policy makers, enabling them to improve water resource management of inland river basins in arid and semi-arid areas under future climate uncertainty.

Cotton, as one of important economic crops, is widely planted in the saline-alkaline soil of southern Xinjiang, China. Moreover, in order to control the saline-alkaline content for seed germination and seedlings survive of cotton, farmers always adopt salt leaching during winter and spring seasons. However, excessive amount of salt leaching might result in the waste of water resources and unsuitable irrigation seasons might further increase soil salinization. In this study, a field experiment was conducted in the saline-alkaline soil in 2020 and 2021 to determine the effects of leaching amount and period on water-salinity dynamics and cotton yield. Five leaching amounts (0.0 (W0), 75.0 (W1), 150.0 (W2), 225.0 (W3), and 300.0 (W4) mm) and three leaching periods (seedling stage (P1), seedling and squaring stages (P2), and seedling, squaring, flowering, and boll setting stages (P3)) were used. In addition, a control treatment (CK) with a leaching amount of 300.0 mm in spring was performed. The soil water-salt dynamics, cotton growth, seed cotton yield, water productivity (WP), and irrigation water productivity (WPI) were analyzed. Results showed that leaching significantly decreased soil electrical conductivity (EC), and W3P2 treatment reduced EC by 11.79% in the 0-100 cm soil depth compared with CK. Plant height, stem diameter, leaf area index, and yield under W3 and W4 treatments were greater than those under W1 and W2 treatments. Compared with W3P1 and W3P3 treatments, seed cotton yield under W3P2 treatment significantly enhanced and reached 6621 kg/hm² in 2020 and 5340 kg/hm² in 2021. Meanwhile, WP and WPI under W3P2 treatment were significantly higher than those under other leaching treatments. In conclusion, the treatment of 225.0 mm leaching amount and seedling and squaring stages-based leaching period was beneficial for the salt control, efficient water utilization, and yield improvement of cotton in southern Xinjiang, China.

The Tianshan Mountains of Central Asia, highly sensitive to climate change, has been comprehensively assessed for its ecosystem vulnerability across multiple aspects. However, studies on the region's main river systems and hydropower resources remain limited. Thus, examining the impact of climate change on the runoff and gross hydropower potential (GHP) of this region is essential for promoting sustainable development and effective management of water and hydropower resources. This study focused on the Kaidu River Basin that is situated above the Dashankou Hydropower Station on the southern slope of the Tianshan Mountains, China. By utilizing an ensemble of bias-corrected global climate models (GCMs) from Coupled Model Intercomparison Project Phase 6 (CMIP6) and the Variable Infiltration Capacity (VIC) model coupled with a glacier module (VIC-Glacier), we examined the variations in future runoff and GHP during 2017-2070 under four shared socio-economic pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) compared to the baseline period (1985-2016). The findings indicated that precipitation and temperature in the Kaidu River Basin exhibit a general upward trend under the four SSP scenarios, with the fastest rate of increase in precipitation under the SSP2-4.5 scenario and the most significant changes in mean, maximum, and minimum temperatures under the SSP5-8.5 scenario, compared to the baseline period (1980-2016). Future runoff in the basin is projected to decrease, with rates of decline under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios being 3.09, 3.42, 7.04, and 7.20 m³/s per decade, respectively. The trends in GHP are consistent with runoff, with rates of decline in GHP under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios at 507.74, 563.33, 1158.44, and 1184.52 MW/10a, respectively. Compared to the baseline period (1985-2016), the rates of change in GHP under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios are -20.66%, -20.93%, -18.91%, and -17.49%, respectively. The Kaidu River Basin will face significant challenges in water and hydropower resources in the future, underscoring the need to adjust water resource management and hydropower planning within the basin.

The Loess Plateau (LP), one of the most ecologically fragile regions in China, is affected by severe soil erosion and environmental degradation. Despite large-scale ecological restoration efforts made by Chinese government in recent years, the region continues to face significant ecological challenges due to the combined impact of climate change and human activities. In this context, we developed a kernal Remote Sensing Ecological Index (kRSEI) using Moderate Resolution Imaging Spectroradiometer (MODIS) products on the Google Earth Engine (GEE) platform to analyze the spatiotemporal patterns and trends in ecological environmental quality (EEQ) across the LP from 2000 to 2022 and project future trajectories. Then, we applied partial correlation analysis and multivariate regression residual analysis to further quantify the relative contributions of climate change and human activities to EEQ. During the study period, the kRSEI values exhibited significant spatial heterogeneity, with a stepwise degradation pattern in the southeast to northwest across the LP. The maximum (0.51) and minimum (0.46) values of the kRSEI were observed in 2007 and 2021, respectively. Trend analyses revealed a decline in EEQ across the LP. Hurst exponent analysis predicted a trend of weak anti-persistent development in most of the plateau areas in the future. A positive correlation was identified between kRSEI and precipitation, particularly in the central and western regions; although, improvements were limited by a precipitation threshold of 837.66 mm/a. A moderate increase in temperature was shown to potentially benefit the ecological environment within a certain range; however, temperature of -1.00°C-7.95°C often had a negative impact on the ecosystem. Climate change and human activities jointly influenced 65.78% of LP area on EEQ, primarily having a negative impact. In terms of contribution, human activities played a dominant role in driving changes in EEQ across the plateau. These findings provide crucial insights for accurately assessing the ecological state of the LP and suggest the design of future restoration strategies.

Film-stalk spaced dual mulching is a new type of cultivation measure that is increasingly highlighted in semi-arid areas in China. Despite its potential, there is limited understanding of how different mulching materials affect both soil quality and crop yield in these areas. To address this gap, we conducted a two-year (2020-2021) field experiment in central China to explore the yield-enhancing mechanisms and assess the impact of various mulching materials on soil and corn yield. The experiment comprised six treatments, i.e., plastic film-whole stalk spaced mulching in fall (PSF), plastic film-whole stalk spaced mulching in spring (PSS), black and silver plastic film-whole stalk spaced mulching in spring (BPSS), biodegradable film-whole stalk spaced mulching in spring (BSS), liquid film-whole stalk spaced mulching in spring (LSS), and non-mulching cultivation (CK). Results revealed that BPSS demonstrated the most significant yield increase, surpassing CK by a notable 10.0% and other mulching treatments by 2.4%-5.9%. The efficacy of BPSS lied in its provision of favorable hydrothermal conditions for corn cultivation, particularly during hot season. Its cooling effect facilitated the establishment of optimal temperature conditions relative to transparent mulching, leading to higher root growth indices (e.g., length and surface area), as well as higher leaf photosynthetic rate and dry matter accumulation per plant. Additionally, BPSS maintained higher average soil moisture content within 0-100 cm depth compared with biodegradable mulching and liquid mulching. As a result, BPSS increased activities of urease, catalase, and alkaline phosphatase, as well as the diversity and abundance of soil bacteria and fungi in the rhizosphere zone of corn, facilitating nutrient accessibility by the plant. These findings suggest that selecting appropriate mulching materials is crucial for optimizing corn production in drought-prone areas, highlighting the potential of BPSS cultivation.

The Tarim River Basin (TRB) is a vast area with plenty of light and heat and is an important base for grain and cotton production in Northwest China. In the context of climate change, however, the increased frequency of extreme weather and climate events is having numerous negative impacts on the region's agricultural production. To better understand how unfavorable climatic conditions affect crop production, we explored the relationship of extreme weather and climate events with crop yields and phenology. In this research, ten indicators of extreme weather and climate events (consecutive dry days (CDD), min Tmax (TXn), max Tmin (TNx), tropical nights (TR), warm days (Tx90p), warm nights (Tn90p), summer days (SU), frost days (FD), very wet days (R95p), and windy days (WD)) were selected to analyze the impact of spatial and temporal variations on the yields of major crops (wheat, maize, and cotton) in the TRB from 1990 to 2020. The three key findings of this research were as follows: extreme temperatures in southwestern TRB showed an increasing trend, with higher extreme temperatures at night, while the occurrence of extreme weather and climate events in northeastern TRB was relatively low. The number of FD was on the rise, while WD also increased in recent years. Crop yields were higher in the northeast compared with the southwest, and wheat, maize, and cotton yields generally showed an increasing trend despite an earlier decline. The correlation of extreme weather and climate events on crop yields can be categorized as extreme nighttime temperature indices (TNx, Tn90p, TR, and FD), extreme daytime temperature indices (TXn, Tx90p, and SU), extreme precipitation indices (CDD and R95p), and extreme wind (WD). By using Random Forest (RF) approach to determine the effects of different extreme weather and climate events on the yields of different crops, we found that the importance of extreme precipitation indices (CDD and R95p) to crop yield decreased significantly over time. As well, we found that the importance of the extreme nighttime temperature (TR and TNx) for the yields of the three crops increased during 2005-2020 compared with 1990-2005. The impact of extreme temperature events on wheat, maize, and cotton yields in the TRB is becoming increasingly significant, and this finding can inform policy decisions and agronomic innovations to better cope with current and future climate warming.

Coal mining predisposes soils to heavy metal (HM) accumulation, which adversely affects the ecological environment and human health, particularly in extremely arid and vulnerable areas. In this study, soil samples were gathered from the Black Mountain Open Pit Coal Mine in Turpan City, Northwest China to determine the health risk of heavy metals (HMs). Results showed that positive matrix factorization model divided the sources of soil HMs into four categories, i.e., natural and animal husbandry (43.46%), industrial transportation (22.87%), fossil fuel combustion (10.64%), and atmospheric deposition and domestic pollution (23.03%). All kinds of pollution evaluation indices showed that Cd (cadmium) and Pb (plumbum) pollution was evident. The Monte Carlo simulated health risk assessment results showed that 4.00% non-carcinogenic risk and 12.00% carcinogenic risk were posed to children, and the positive matrix factorization-based health risk assessment showed that fossil fuel combustion had the highest contribution to the health risks to adults and children, while industrial transportation was the lowest. In this study, the risks of HMs in the soil of mining area were analyzed using source analysis, which not only provides reliable data support for the prevention and control of HM pollution in the soil of this arid mining area, but also provides a theoretical basis for subsequent regional research.

Given that Xinjiang Uygur Autonomous Region of China possesses exceptionally abundant solar radiation resources that can be harnessed to develop clean energy, accurately characterizing their spatiotemporal distribution is crucial. This study investigated the applicability of the Clouds and the Earth's Radiant Energy System (CERES) Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product downward surface shortwave radiation dataset (DSSR_CER) under clear-sky conditions in Xinjiang. By integrating multi-source data and utilizing techniques like multivariate fitting and model simulation, we established a two-layer aerosol model and developed a clear-sky downward surface shortwave radiation (DSSR) retrieval model specific to Xinjiang using the Santa Barbara Discrete Atmospheric Radiative Transfer (SBDART) model. We further explored the spatiotemporal distribution characteristics of DSSR under clear-sky conditions in Xinjiang from 2017 to 2019 based on the localized DSSR retrieval model. Our findings revealed a significant discrepancy in DSSR_CER under clear-sky conditions at the Xiaotang station in Xinjiang. By comparing, screening, and correcting core input parameters while incorporating the two-layer aerosol model, we achieved a more accurate SBDART simulated DSSR (DSSR_SBD) compared to DSSR_CER. The annual mean DSSR exhibited a distinct distribution pattern with high values in mountainous regions such as the Altay Mountains, Kunlun Mountains, and Tianshan Mountains and significantly lower values in adjacent lowland areas, including the Tarim River Basin and Junggar Basin. In the four typical administrative regions in northern Xinjiang, the annual mean DSSR (ranging from 551.60 to 586.09 W/m²) was lower than that in the five typical administrative regions in southern Xinjiang (ranging from 522.10 to 623.62 W/m²). These spatial variations stem from a complex interplay of factors, including latitude, altitude, solar altitude angle, and sunshine duration. The variations in seasonal average DSSR aligned closely with variations in the solar altitude angle, with summer (774.76 W/m²) exhibiting the highest values, followed by spring (684.86 W/m²), autumn (544.76 W/m²), and winter (422.74 W/m²). The monthly average DSSR showed a unimodal distribution, peaking in June (792.94 W/m²) and reaching its lowest level in December (363.06 W/m²). Overall, our study findings enhance the current understanding of the spatiotemporal distribution characteristics of DSSR in Xinjiang and provide certain references for the management of clean energy development in this region.

Salt stress might be an important factor that decreases the emergence of seedlings and reduces plants' growth, causing their endangered status. However, the effects of salt stress on the germination of the Mediterranean species are less concern. Limonium strictissimum (Salzm.) Arrigoni, part of the group related to Limonium articulatum (Loisel.) Kuntze, is a Cyrno-Sardinian endemism, which is included in the International Union for Conservation of Nature (IUCN) Red Lists as Endangered (EN). Fresh seeds of L. strictissimum harvested from the only known population in Sardinia and a population in southeastern Corsica were used with the aims to study the effects of temperature and salinity on the seed germination and to evaluate the ability to recover their germination after exposure to salt stress. In both populations, empty fruits with a lower percentage were observed in Sardinia than in Corsica. The seeds showed a high germination capacity, which was not influenced by temperature and did not even differ between the two populations. Compared with non-saline condition, the presence of salt in the substrate, independently of the concentration tested, inhibited seed germination in both populations, with germination percentages never exceeding 40%. The Sardinian population showed a recovery capacity after exposure to high salt stress, always above 50% regardless of the salt concentration and incubation temperature considered. The seeds previously exposed to 125 mM NaCl at 30°C had the lowest recovery percentage (56%), while the highest recovery percentage (84%) was recorded at 25°C with a concentration of 250 mM NaCl. Differently, the Corsican population recorded a higher recovery percentage (54%) in seeds previously exposed to 500 mM NaCl at 20°C, while for the concentration of 125 mM NaCl, the best recovery percentage (11%) was recorded at 30°C. The ability of L. strictissimum to recover germination after salt exposure can be interpreted as an adaptation to the coastal habitats in which it grows. This study provides new insights into the ecophysiology of L. strictissimum seed germination, which could help preserve and implement effective conservation measures for this endangered species with restricted populations.

As one of the main characteristics of atmospheric pollutants, PM_2.5 severely affects human health and has received widespread attention in recent years. How to predict the variations of PM_2.5 concentrations with high accuracy is an important topic. The PM_2.5 monitoring stations in Xinjiang Uygur Autonomous Region, China, are unevenly distributed, which makes it challenging to conduct comprehensive analyses and predictions. Therefore, this study primarily addresses the limitations mentioned above and the poor generalization ability of PM_2.5 concentration prediction models across different monitoring stations. We chose the northern slope of the Tianshan Mountains as the study area and took the January-December in 2019 as the research period. On the basis of data from 21 PM_2.5 monitoring stations as well as meteorological data (temperature, instantaneous wind speed, and pressure), we developed an improved model, namely GCN-TCN-AR (where GCN is the graph convolution network, TCN is the temporal convolutional network, and AR is the autoregression), for predicting PM_2.5 concentrations on the northern slope of the Tianshan Mountains. The GCN-TCN-AR model is composed of an improved GCN model, a TCN model, and an AR model. The results revealed that the R² values predicted by the GCN-TCN-AR model at the four monitoring stations (Urumqi, Wujiaqu, Shihezi, and Changji) were 0.93, 0.91, 0.93, and 0.92, respectively, and the RMSE (root mean square error) values were 6.85, 7.52, 7.01, and 7.28 μg/m³, respectively. The performance of the GCN-TCN-AR model was also compared with the currently neural network models, including the GCN-TCN, GCN, TCN, Support Vector Regression (SVR), and AR. The GCN-TCN-AR outperformed the other current neural network models, with high prediction accuracy and good stability, making it especially suitable for the predictions of PM_2.5 concentrations. This study revealed the significant spatiotemporal variations of PM_2.5 concentrations. First, the PM_2.5 concentrations exhibited clear seasonal fluctuations, with higher levels typically observed in winter and differences presented between months. Second, the spatial distribution analysis revealed that cities such as Urumqi and Wujiaqu have high PM_2.5 concentrations, with a noticeable geographical clustering of pollutions. Understanding the variations in PM_2.5 concentrations is highly important for the sustainable development of ecological environment in arid areas.

The implementation of long-term shelterbelt programs in the middle reaches of the Yellow River (MRYR), China not only has improved the overall ecological environment, but also has led to the changes of land use pattern, causing carbon storage exchanges. However, the relationship between carbon storage and land use change in the MRYR is not concerned, which results in the uncertainty in the simulation of carbon storage in this area. Land use changes directly affect the carbon storage capacity of ecosystems, and as an indicator reflecting the overall state of land use, land use degree has an important relationship with carbon storage. In this study, land use data and the integrated valuation of ecosystem services and trade-offs (InVEST) model were used to assess the trends in land use degree and carbon storage in the MRYR during 1980-2020. The potential impact index and the standard deviation ellipse (SDE) algorithm were applied to quantify and analyze the characteristics of the impact of land use changes on carbon storage. Subsequently, land use transitions that led to carbon storage variations and their spatial variations were determined. The results showed that: (1) the most significant periods of carbon storage changes and land use transitions were observed during 1990-1995 and 1995-2020, with the most changed areas locating in the east of Fenhe River and in northwestern Henan Province; (2) the positive impact of land use degree on carbon storage may be related to the environmental protection measures implemented along the Yellow River, while the negative impact may be associated with the expansion of construction land in plain areas; and (3) the conversion of other land use types to grassland was the primary factor affecting carbon storage changes during 1980-2020. In future land use planning, attention should be given to the direction of grassland conversion, and focus on reasonably limiting the development of construction land. To enhance carbon storage, it will be crucial to increase the area of high-carbon-density land types, such as forest land and grassland under the condition that the area of permanent farmland does not decrease.

Understanding the impact of meteorological and topographical factors on snow cover fraction (SCF) is crucial for water resource management in the Qilian Mountains (QLM), China. However, there is still a lack of adequate quantitative analysis of the impact of these factors. This study investigated the spatiotemporal characteristics and trends of SCF in the QLM based on the cloud-removed Moderate Resolution Imaging Spectroradiometer (MODIS) SCF dataset during 2000-2021 and conducted a quantitative analysis of the drivers using a histogram-based gradient boosting regression tree (HGBRT) model. The results indicated that the monthly distribution of SCF exhibited a bimodal pattern. The SCF showed a pattern of higher values in the western regions and lower values in the eastern regions. Overall, the SCF showed a decreasing trend during 2000-2021. The decrease in SCF occurred at higher elevations, while an increase was observed at lower elevations. At the annual scale, the SCF showed a downward trend in the western regions affected by westerly (52.84% of the QLM). However, the opposite trend was observed in the eastern regions affected by monsoon (45.73% of the QLM). The SCF displayed broadly similar spatial patterns in autumn and winter, with a significant decrease in the western regions and a slight increase in the central and eastern regions. The effect of spring SCF on spring surface runoff was more pronounced than that of winter SCF. Furthermore, compared with meteorological factors, a variation of 46.53% in spring surface runoff can be attributed to changes in spring SCF. At the annual scale, temperature and relative humidity were the most important drivers of SCF change. An increase in temperature exceeding 0.04°C/a was observed to result in a decline in SCF, with a maximum decrease of 0.22%/a. An increase in relative humidity of more than 0.02%/a stabilized the rise in SCF (about 0.06%/a). The impacts of slope and aspect were found to be minimal. At the seasonal scale, the primary factors impacting SCF change varied. In spring, precipitation and wind speed emerged as the primary drivers. In autumn, precipitation and temperature were identified as the primary drivers. In winter, relative humidity and precipitation were the most important drivers. In contrast to the other seasons, slope exerted the strongest influence on SCF change in summer. This study facilitates a detailed quantitative description of SCF change in the QLM, enhancing the effectiveness of watershed water resource management and ecological conservation efforts in this region.

Understanding the ecological evolution is of great significance in addressing the impacts of climate change and human activities. However, the ecological evolution and its drivers remain inadequately explored in arid and semi-arid areas. This study took the Helan Mountain, a typical arid and semi-arid area in China, as the study area. By adopting an Enhanced Remote Sensing Ecological Index (ERSEI) that integrates the habitat quality (HQ) index with the Remote Sensing Ecological Index (RSEI), we quantified the ecological environment quality of the Helan Mountain during 2010-2022 and analyzed the driving factors behind the changes. Principal Component Analysis (PCA) was used to validate the composite ERSEI, enabling the extraction of key features and the reduction of redundant information. The results showed that the contributions of first principal component (PC1) for ERSEI and RSEI were 80.23% and 78.72%, respectively, indicating that the ERSEI can provide higher precision and more details than the RSEI in assessing ecological environment quality. Temporally, the ERSEI in the Helan Mountain exhibited an initial decline followed by an increase from 2010 to 2022, with the average value of ERSEI ranging between 0.298 and 0.346. Spatially, the ERSEI showed a trend of being higher in the southwest and lower in the northeast, with high-quality ecological environments mainly concentrated in the western foothills at higher altitudes. The centroid of ERSEI shifted northeastward toward Helan County from 2010 to 2022. Temperature and digital elevation model (DEM) emerged as the primary drivers of ERSEI changes. This study highlights the necessity of using comprehensive monitoring tools to guide policy-making and conservation strategies, ensuring the resilience of fragile ecosystems in the face of ongoing climatic and anthropogenic pressures. The findings offer valuable insights for the sustainable management and conservation in arid and semi-arid ecosystems.

Alluvial fans possess diverse geomorphological features and have a significant impact on soil characteristics and variations in ecological stoichiometry. However, it remains unclear how alluvial fans in arid mountainous areas influence the changes in ecological chemical stoichiometry and, consequently, indirectly affect ecosystem function. Alluvial fan, with its diverse topographical features, exerts a multifaceted influence on soil formation and characteristics. Limited information exists regarding the ecological stoichiometric characteristics of the alluvial fan in arid mountainous areas. This study investigated the soil physical-chemical characteristics, enzyme activities, soil ecological stoichiometries, and its driving factors of four types of micro-topographies (alluvial mesas, high floodplain, groove beach, and striated groove) in the foothills of eastern Helan Mountains, China. Results showed that soil physical and chemical properties in the 0-20 cm soil depth was consistently higher than those in the 20-40 cm soil depth, with no changes in pH, total nitrogen, and total potassium. C:P and N:P ratios in alluvial mesas, high floodplain, and striated groove were significantly higher than those in groove beach. Redundancy analysis showed that soil nutrients played the most significant role in the variation of soil ecological stoichiometry characteristics. Topography influenced soil stoichiometry indirectly, primarily through impacts on enzyme activity and soil nutrient elements. These findings elucidate the intricate interplay between soil ecological stoichiometric characteristics and environmental factors across diverse micro-topographies in alluvial fan, contributing to our understanding of the formation and development of soil in dryland.

Due to irrational human activities and extreme climate, the Qinghai-Xizang Plateau, China, faces a serious threat of desertification. Desertification has a detrimental effect on the ecological environment and socioeconomic development. In this study, the desertification sensitivity index (DSI) model was established by integrating the spatial distance model and environmentally sensitive area index evaluation method, and then the model was used to quantitatively analyze the spatial and temporal characteristics of desertification sensitivity of the Qinghai-Xizang Plateau from 1990 to 2020. The results revealed that: (1) a general increasing tendency from southeast to northwest was identified in the spatial distribution of desertification sensitivity. The low-sensitivity areas were mostly concentrated in the Hengduan and Nyaingqêntanglha mountains and surrounding forest and meadow areas. The high-sensitivity areas were located mainly in the Kunlun and Altun mountains and surrounding decertified areas. The center of gravity of all types of desertification-sensitive areas moved to the northwest, and the desertification sensitivity showed a decreasing trend as a whole; (2) the area of highly sensitive desertification areas decreased by 8.37%, with extreme sensitivity being the largest change among the sensitivity types. The desertification sensitivity transfer was characterized by a greater shift to lower sensitivity levels (24.56%) than to higher levels (2.03%), which demonstrated a declining trend; (3) since 1990, the change in desertification sensitivity has been dominated by the stabilizing type I (29.30%), with the area of continuously increasing desertification sensitivity accounting for only 1.10%, indicating that the management of desertification has achieved positive results in recent years; and (4) natural factors have had a more significant impact on desertification sensitivity on the Xizang Plateau, whereas socioeconomic factors affected only localized areas. The main factors influencing desertification sensitivity were vegetation drought tolerance and aridity index. Studying spatiotemporal variations in desertification sensitivity and its influencing factors can provide a scientific foundation for developing strategies to control desertification on the Qinghai-Xizang Plateau. Dividing different desertification-sensitive areas on the basis of these patterns of change can facilitate the formulation of more targeted management and protection measures, contributing to ecological construction and sustainable economic development in the area.

Research on grassland carrying capacity (GCC) and forage-livestock balance is of great significance for promoting the harmonious development of human and grassland. However, the lack of understanding of GCC and forage-livestock balance in the agro-pastoral transition zone of northern China has limited the grassland sustainable development. Here, the spatial and temporal characteristics of GCC and forage-livestock balance in the grassland of agro-pastoral transition zone of northern China from 2000 to 2022 were analyzed using meteorological data and remote sensing data. Geographical detectors and geographically weighted regression were also used to identify the driving factors and their interactions with GCC changes. Moreover, future GCC trends were predicted using the Coupled Model Intercomparison Project Phase 6 dataset. Results revealed that: (1) GCC showed an overall upward trend from 2000 to 2022 but with significant inter-annual fluctuations. Its spatial distribution decreased gradually from north to south and from east to west. Precipitation, temperature, and cumulative solar radiation were the main drivers of the inter-annual variation of GCC, and the interaction between precipitation and temperature was the main influencing factor of the spatial distribution of GCC; (2) the forage-livestock balance was in an overloaded state in most years, but its index remained basically stable. Spatially, grazing overloading was mainly distributed in northeastern area and the severe overloading was mainly distributed in northwestern area; and (3) future projections indicated a downward trend in potential GCC. Under shared socioeconomic pathway (SSP)2-4.5 scenario, the potential GCC had a ranged of 1.38×10⁷-1.86×10⁷ standard sheep unit (SHU) and a mean of 1.60×10⁷ SHU. Meanwhile, the potential GCC under SSP5-8.5 scenario had a range of 1.18×10⁷-1.69×10⁷ SHU and a mean of 1.49×10⁷ SHU. These results indicated that although GCC of the agro-pastoral transition zone of northern China showed an overall increasing trend from 2000 to 2022, the forage-livestock balance index remained basically stable. The GCC was predicted to show a decreasing trend in the future. The findings provide a scientific basis for the sustainable development of grassland and the optimization of grazing management policies in this area.

Characteristics of root pullout resistance determine the capacity to withstand uprooting and the slope protection ability of plants. However, mechanism underlying the uprooting of taproot-type shrub species in the loess area of northeastern Qinghai-Xizang Plateau, China remains unclear. In this study, a common taproot-type shrub, Caragana korshinskii Kom., in northeastern Qinghai-Xizang Plateau was selected as the research material. Mechanism of root-soil interaction of vertical root of C. korshinskii was investigated via a combination of a single-root pullout test and numerical simulation analysis. The results indicated that, when pulling vertically, axial force of the roots decreased with an increase in buried depth, whereas shear stress at root-soil interface initially increased and then decreased as burial depths increased. At the same buried depth, both axial force and shear stress of the roots increased with the increase in pullout force. Shear stress and plastic zone of the soil surrounding the root were symmetrically distributed along the root system. Plastic zone was located close to the surface and was caused primarily by tensile failure. In nonvertical pulling, symmetry of shear stress and plastic zone of the soil surrounding the root was disrupted. We observed larger shear stress and plastic zones on the side facing the direction of root deflection. Plastic zone included both shear and tensile failure. Axial force of the root system near the surface decreased as deflection angle of the pullout force increased. When different rainfall infiltration depths had the same vertical pulling force, root axial force decreased with the increase of rainfall infiltration depth and total root displacement increased. During rainfall infiltration, shear stress and plastic zone of the soil surrounding the root were prone to propagating deeper into the soil. These findings provide a foundation for further investigation of soil reinforcement and slope protection mechanisms of taproot-type shrub species in the loess area of northeastern Qinghai-Xizang Plateau and similar areas.

Climate change and human activities have led to desertification and decreased land productivity, significantly affecting human livelihoods in desert regions. Identifying suitable areas for cultivating economic and native plants based on ecological capacity, biological restoration, and risk management can be valuable tools for combating desertification. In this study, we identified suitable areas for the growth of economic and medicinal Moringa peregrina trees in desert regions of Sistan and Baluchestan Province, southern Iran, using library research and field methods. We also assessed the economic involvement of local communities in areas under different topographic conditions (namely flat area, undulating area, rolling area, moderately sloping area, and steep area) in the study area. Financial indicators such as the net present value (NPV), benefit-cost ratio (BCR), internal rate of return (IRR), and return on investment (ROI) were calculated for areas under various topographic conditions in the study area. The rolling area with results of NPV (6142.75 USD), IRR (103.38), BCR (5.38), and ROI (in the 3^rd year) was the best region for investing and cultivating M. peregrina. The minimum economic level varied from 0.80 hm² in the flat area to 21.60 hm² in the steep area. Also, approximately 5,314,629.51 hm² of desert lands in the study area were deemed suitable for M. peregrina cultivation, benefiting around 1,743,246 households in the study area. Cultivating M. peregrina in southern Iran can positively affect local communities and help preserve land from erosion. Our study will provide theoretical support for planting native species in other degraded desert regions to enhance ecosystem services and the well-being of indigenous populations.

Integrating sprinkler with deficit irrigation system is a new approach to improve crop water productivity and ensure water and food security in arid areas of India. This study undertook a field experiment of sprinkler-irrigated cumin (variety GC-4) with a mini-lysimeter setup at an experimental research farm in Jodhpur, India during 2019-2022. Four irrigation treatments T₁, T₂, T₃, and T₄ were designed at irrigation water/cumulative pan evaporation (IW/CPE) of 1.0, 0.8, 0.6, and 0.4, respectively, with three replications. Daily actual crop evapotranspiration (ET_c) was recorded and weekly soil moisture was monitored over the crop growth period. Quantities of applied water and drainage from mini-lysimeters were also measured at every irrigation event. Yield of cumin was recorded at crop maturity. Furthermore, change in farmer's net income from 1-hm² land was computed based on the cost of applying irrigation water and considering yield variations among the treatments. Results indicated the highest mean seasonal actual ET_c (371.7 mm) and cumin yield (952.47 kg/hm²) under T₁ (with full irrigation). Under T₂, T₃, and T₄, the seasonal actual ET_c decreased by 10.4%, 27.6%, and 41.3%, respectively, while yield declined by 5.0%, 28.4%, and 50.8%, respectively, as compared to the values under T₁. Furthermore, crop water productivity of 0.272 (±0.068) kg/m³ under T₂ was found relatively higher in comparison to other irrigation treatments, indicating that T₂ can achieve improved water productivity of cumin in arid areas at an optimum level of deficit irrigation. The results of cost-economics indicated that positive change in farmer's net income from 1-hm² land was 108.82 USD under T₂, while T₃ and T₄ showed net losses of 5.33 and 209.67 USD, respectively. Moreover, value of yield response factor and ratio of relative yield reductions to relative ET_c deficits were found to be less than 1.00 under T₂ (0.48), and more than 1.00 under T₃ (1.07) and T₄ (1.23). This finding further supports that T₂ shows the optimized level of deficit irrigation that saves 20.0% of water with sacrificing 5.0% yield in the arid areas of India. Findings of this study provide useful strategies to save irrigation water, bring additional area under irrigation, and improve crop water productivity in India and other similar arid areas in the world.

Studying the spatiotemporal variation and driving mechanisms of vegetation net primary productivity (NPP) in the Guanzhong Plain Urban Agglomeration (GPUA) of China is highly important for regional green and low-carbon development. This study used the Theil-Sen trend analysis, Mann-Kendall trend test, coefficient of variation, Hurst index, and machine learning method (eXtreme Gradient Boosting and SHapley Additive exPlanations (XGBoost-SHAP)) to analyze the spatiotemporal variation of NPP in the GPUA from 2001 to 2020 and reveal its response to climate change and human activities. The results found that during 2001-2020, the averageNPP in the GPUA showed a significant upward trend, with an annual growth rate of 10.84 g C/(m²•a). The multi-year average NPP in the GPUA was 484.83 g C/(m²•a), with higher values in the southwestern Qinling Mountains and lower values in the central and northeastern cropland and built-up areas. The average coefficient of variation of NPP in the GPUA was 0.14, indicating a relatively stable state overall, but 72.72% of the study area showed weak anti-persistence, suggesting that NPP in most areas may have declined in the short term. According to XGBoost-SHAP analyses, elevation, land use type and precipitation were identified as the main driving factors of NPP. Appropriate precipitation and higher temperatures promote NPP growth, whereas extreme climates, high population density, and nighttime lighting inhibit NPP. This study has important theoretical and practical significance for achieving regional sustainable development, offers a scientific basis for formulating effective ecological protection and restoration strategies, and promotes green, coordinated, and sustainable development in the GPUA.

Understanding how different vegetation-based restoration practices alter soil chemical and microbial characteristics is crucial, as restoration practices influence phosphorus (P) transformation and fractions and modify P adsorption behavior during the restoration process of degraded land. This study investigated the impacts of vegetation-based restoration practices on soil chemical and microbial parameters, P fractions, and patterns of P adsorption and desorption, and highlighted the combined influence on P availability. To evaluate the impact of vegetation-based restoration practices on P fractions and adsorption behavior in the semi-arid degraded land in India, this study compared three distinct tree-based restoration systems, including Leucaena leucocephala (Lam.) de Wit-based silviculture system (SCS), Acacia nilotica (L.) Willd. ex Delile-based silvopasture system (SPS), and Emblica officinalis Gaertn-based hortipasture system (HPS), with a natural grassland system (NGS) and a degraded fallow system (FS) as control. The soil samples across various soil depths (0-15, 15-30, and 30-45 cm) were collected. The findings demonstrated that SCS, SPS, and HPS significantly improved soil organic carbon (SOC) and nutrient availability. Moreover, SCS and SPS resulted in increased microbial biomass phosphorus (MBP) content and phosphatase enzyme activity. The P fractionation analysis revealed that ferrum-associated phosphorus (Fe-P) was the major P fraction, followed by aluminum-associated phosphorus (Al-P), reflecting the dominance of ferrum (Fe) and aluminum (Al) oxides in the semi-arid degraded land. Compared with FS, vegetation-based restoration practices significantly increased various P fractions across soil depths. Additionally, P adsorption and desorption analysis indicated a lower adsorption capacity in tree-based restoration systems than in FS, with FS soils adsorbing higher P quantities in the adsorption phase but releasing less P during the desorption phase. This study revealed that degraded soils responded positively to ecological restoration in terms of P fraction and desorption behavior, influencing the resupply of P in restoration systems. Consequently, litter rich N-fixing tree-based restoration systems (i.e., SCS and SPS) increased total phosphorus (TP) stock for plants and sustained the potential for long-term P supply in semi-arid ecosystems. With the widespread adoption of restoration practices across degraded landscapes, SCS and SPS would significantly contribute to soil restoration and improve productivity by maintaining the soil P supply in semi-arid ecosystems in India.