The damaging pest Agrilus viduus Kerremans was recorded for the first time in Ili Prefecture, Xinjiang. This pest has entered the core area of wild fruit forest, where it has damaged wild apples and wild apricots. Through field surveys, fixed-point observations, and laboratory rearing, the distribution range, life history, damage characteristics, and host plants of this pest in the wild fruit forest area were preliminarily studied. This pest is distributed in Xinyuan County, Gongliu County, Huocheng County, and Tekes County and has entered the wild fruit forests of Xinyuan County, Gongliu County, and Huocheng County. In terms of its reproduction, this pest exhibits one generation per year, starts to be active in the first half of May and begins to emerge in early July, with the peak emergence period in late July. Adult insects start to lay eggs in mid-July, and the emergence process ends in early August. In early November, the second-and third-instar larvae begin to overwinter. The damage mainly takes the form of larvae boring into the phloem, cambium, and xylem of host plants. When substantial infestation occurs, death of the host can occur. This pest can damage wild apricots, wild apples, and some other economically important fruit trees in the wild fruit forest. The oviposition characteristics of this pest are rather special. Eggs are laid in clusters on the bark surface and then covered with secretions to form egg cases. The distribution of this species’ egg cases is highly correlated with the height of apricot trees, with them mainly being found at heights of 120-240 cm; the distribution of the egg cases is also related to the basal diameter, being found mainly on branches with diameters of 2-3 cm. A literature review and field investigation revealed that this insect is a pest that has been newly introduced into the wild fruit forest of Xinjiang, posing a significant threat and requiring the attention of local authorities. There is an urgent need for physical control, biological control, and chemical control methods to be applied to eradicate it in accordance with its biological characteristics.

As the scarcity of global water intensifies, accurate assessments of water resource carrying capacity (WRCC) have become essential for sustainably managing regional water resources and combating the adverse effects of climate change. However, the water resources-ecology-society system is highly complex, involving multidimensional interactions anddynamic internal changes that cannot be fully captured by a single evaluation method. This paper reviews the application status and research progress of coupled-model methods for WRCC evaluation. A systematic comparative analysis reveals the strengths and limitations of the major evaluation methods—systems analysis, comprehensive evaluation, and machine learning—in WRCC evaluation. Particular attention is devoted to the challenges of these methods in arid regions. The dynamic feedback mechanisms, nonlinear modeling capabilities, data-driven characteristics, and applicabilities of different methods are analyzed through a horizontal comparison study. The review also analyzes the suitabilities and limitations of each method in arid regions and explores the feasibility of coupled models, providing new insights for resolving WRCC issues in these areas. Multimodel integration and data-driven optimization will enhance the generalizability and applicability of models in future, facilitating the transition of water resource management from static evaluation to dynamic simulation and precise prediction. These developments will offer scientific support for sustainable water resource utilization in arid regions and worldwide.

The ongoing decline in biodiversity adversely effects ecosystem services. Investigating spatiotemporal changes in land use and habitat quality in the Three River Source Region is crucial for ecological protection and restoration. This study, based on the PLUS model and the InVEST model’s habitat quality module, conducts multi-scenario simulations to predict land use changes and estimate habitat quality. The results are as follows: (1) During the historical period, 9663.53 km² of grassland converted to unused land, represented the largest proportion of total land conversion, whereas unused land converted to grassland only covered 3659.27 km², the grassland degraded into unused land to a relatively serious extent in the Three River Source Region. (2) Multi-scenario predictions for 2030 reveal that the biodiversity conservation scenario performs best, followed by the grassland protection scenario, then the water resources protection scenario, and finally the natural development scenario. (3) Among conversion types, the contribution rate of converting unused land to grassland in enhancing habitat quality is highest at 0.7167, followed by that of converting unused land to water bodies, at 0.2603. Implementing biodiversity protection strategies, resolving the grass-livestock conflict, and enhancing management of unused land, while reducing grassland-to-unused land conversion will help mitigate the decline in habitat quality.

Salinization in the irrigation areas of watersheds in downstream arid regions exacerbates soil degradation, crop yield reduction, and river water salinization, severely limiting agricultural production and harming ecological stability. It arises in a manner influenced by the depth of groundwater and poor irrigation and drainage management. Scientifically formulating measures to regulate soil water-salt is key to addressing these issues. In this study, field experiments were conducted in a typical farmland area of the riparian zone by the downstream part of Aksu River. Based on dynamic observations and field survey data, an unsaturated model was established using the HYDRUS-1D software to simulate soil water and salt transport patterns during the cotton growing season, determine appropriate regulatory strategies, and explore the relationship between the stable groundwater evaporation depth and riparian soil structure. The results revealed that the identification and validation accuracy of the soil moisture content and total dissolved solids were 0.862 and 0.752 with root mean square errors of 0.033 and 0.008, respectively, indicating that the model was highly reliable. Irrigation infiltration accounted for 85% of the total soil water recharge, introducing 127.164 mg·cm^-2 of salt, while soil water discharge to groundwater accounted for 59.67% of the total discharge, removing 267.78 mg·cm^-2 of salt. The water balance error was 9.2% and the desalination rate was 33.89%. Considering the demand for water for crops and soil salinity dynamics, setting the irrigation water depth to 70 cm while maintaining the groundwater depth at approximately 220 cm can effectively reduce the soil salinity in the root zone. In sandy loam structures, the position of the loam layer has little effect on the critical evaporation depth of groundwater (150 cm), but significantly influences the stable evaporation depth and actual evaporation. If the loam layer is closer to the surface, the stable evaporation depth becomes shallower and the actual evaporation decreases. The findings provide a reference for preventing salinization and managing water resources in arid regions.

Incorporating agricultural irrigation water into the global trade chain and determining its sustainability is vital for ensuring water and food security. However, the issue of sustainability in the virtual water of crop trade has received limited attention, due to the conflict between economic benefits and water resource utilization. Thus, based on the crop production and trade matrix data from the Food and Agriculture Organization, this study conducted physical trade flow and spatial correlation analyses as well as multiscale geographically weighted regression to systematically analyze the spatiotemporal distribution, the spatial correlation characteristics, and the driving factors of net exported virtual water sustainability in global crop trade from 2000 to 2019. Based on the findings, the sustainable and unsustainable net exported virtual water volumes in global crop trade (especially cotton) exhibited a fluctuating upward trend (approximately 0.20 Gm³ per year) over the past two decades. However, due to agricultural technological advancements, the proportion of unsustainable virtual water in the total virtual water trade volume decreased from 42.31% to 41.40%. Although the spatial analysis revealed considerable spatial clustering of unsustainable net exported virtual water volumes between 2000 and 2009, as shown by global and local Moran’s I statistics, this clustering trend weakened and became more dispersed over the past decade. Moreover, the increase in net exported virtual water was mainly driven by changes in cultivated land area, with agricultural value-added having a significant negative impact on virtual water in trade. Overall, these results highlight the importance of implementing stringent food security policies in order to facilitate the sustainable development of the global virtual water trade in crops and to further reduce the proportion of unsustainable water use.

Based on the 2022 daily precipitation data from weather stations in the eastern Tibetan Plateau, this study evaluated the accuracy of three datasets from the China Meteorological Administration: the Multi-source Precipitation Analysis System (CMPAS), Land Data Assimilation System (CLDAS), and Global Atmospheric Reanalysis (CRA)—via error indices and grading methods. The results indicate: (1) CMPAS exhibits the lowest error and highest correlation, making it the most reliable for annual precipitation analysis. (2) CMPAS monthly data align closely with observations, while CRA overestimates and CLDAS underestimates precipitation in most months. (3) During two large-scale precipitation events, CLDAS best captures accumulated rainfall, while CMPAS more accurately reflects precipitation centers, intensities, timing, and location. Overall, CMPAS is the most effective dataset for analyzing precipitation in the region, supporting improved monitoring of sparse areas and laying a solid foundation for climate operations and disaster prevention.

The precipitation concentration index (PCI) is a measure of precipitation during the year. Based on the monthly precipitation data of 15 meteorological stations in the Yarlung Zangbo River Basin (YZRB) from 1981 to 2024, the spatiotemporal variation characteristics of PCI, the amount of seasonal precipitation, its frequency and intensity over the last 44 years, and the reasons for a change in PCI were analyzed using a linear equation, Person coefficient, and five mutation tests, including the Mann-Kendall and Cramer tests. The results indicated that (1) The PCI increased from east to west in YZRB, whereas annual precipitation, precipitation frequency, and precipitation intensity decreased from east to west. (2) Over the past 44 years, the PCI decreased at a rate of -0.26 per decade, indicating a trend toward more evenly distributed monthly precipitation throughout the year. Precipitation exhibited an increasing trend from January to July and October (the fastest increase in July), and it decreased in other months (the most in September). Monthly precipitation accounted for the proportion of annual precipitation (MPAP), which increased in February and April-July (the largest in May). MPAP was decreased in other months (the largest decrease in September). (3) The increase of precipitation in spring, summer, and winter was primarily due to the increase in precipitation intensity, whereas the decrease of precipitation frequency played a major role in the decreased amount of precipitation during autumn. Furthermore, the increase in annual precipitation intensity resulted from the significant increase of the Tibetan Plateau-1 index and the western Pacific warm pool intensity index. The decrease in the PCI was related to a decrease in the seasonal difference under the background of warming. (4) The PCI was lower only in the 2000s, but was higher in the other three decades, although there was a sudden change in the early 1990s. The abrupt changes in annual precipitation, frequency, and intensity occurred during the first 10 years of the 2000s and the middle and late 1990s.

The arid region of Northwest China is an area of notable vegetation vulnerability, where vegetation cover plays a crucial role in sustaining unique terrestrial ecosystems. This study utilized Landsat data and the pixel dichotomy model to analyze spatiotemporal variation patterns of Fractional Vegetation Cover (FVC) in the arid region of Northwest China from 1990-2022. Integrating land use data, the research employed Sen’s slope estimation, the Mann-Kendall test, and correlation analysis to investigate FVC characteristics across different vegetation types and their responses to climatic factors. The results indicate that: (1) FVC exhibited a fluctuating upward trend, with an annual increase rate of 0.98×10^-4; spatial heterogeneity was significant, with areas predominantly characterized by very low vegetation coverage, while river basin regions displayed higher FVC values. (2) Land use transformation has driven the evolution of FVC patterns, with increases in forestland and cultivated land contributing to the expansion of areas with very high FVC coverage (increasing by 3.0% and 18.8%, respectively); grassland remains the dominant cover across all levels, with an average proportion exceeding 47.7%. (3) Average precipitation during the vegetation growing season ranks as follows: shrubland>forestland>grassland>cropland, whereas temperature trends are reversed; evapotranspiration follows the order: forestland>cropland>grassland>shrubland; the average annual humid area proportion is 61.03% in shrubland regions, compared to less than 5% in cropland regions. FVC shows negative correlations with precipitation (52.0%), temperature (60.2%), evapotranspiration, and aridity index (63%). Vegetation demonstrates significant sensitivity to climate change. The findings provide an important basis for ecological management and restoration in the arid regions of Northwest China.

Accurate crop yield prediction is crucial for governments to understand production levels, plan agricultural activities, and ensure national food security. Meteorological factors critically influence crop yields, and yield prediction methods and technology systems based on these factors serve as important references. Meteorological yield prediction predominantly employs statistical methods because of their simplicity, ease of implementation, and high accuracy, making them the most widely used techniques in China. This study reviews the application of the most commonly used statistical methods in meteorological yield prediction in China—including the key meteorological factor, climate suitability, and historical meteorological impact index methods. Through extensive data collection and investigation, a detailed overview is provided regarding the crop types and regions where each statistical method has been applied, the quantities and time scales of selected meteorological factors, various calculation approaches for meteorological indicators, and the modeling techniques adopted. The paper elaborates on the effectiveness of each statistical method across different regions and crops, evaluates the performance of integrated statistical models, and compares the forecast accuracy of different approaches. In doing so, several issues in the statistical prediction of meteorological yields are identified. For example, the key meteorological factor method offers advantages such as easy model parameter acquisition and operational applicability; however, it primarily considers the effects of light, temperature, and water, potentially overlooking other meteorological factors and disasters. The climate suitability method comprehensively accounts for the light, temperature, and water resources required for crop growth but mainly focuses on average states with lower temporal resolution, making it difficult to capture the impact of short-term disastrous weather. The historical meteorological impact index method objectively and quantitatively predicts the influence of meteorological conditions on crop yields; however, it is challenging to identify truly similar years. These issues contribute to unstable forecast results. To overcome these limitations, future efforts can focus on integrating data from multiple sources (such as satellite remote sensing, wireless sensor networks, Internet of Things, etc.), introducing advanced data analysis technologies and new statistical methods (such as machine learning and deep learning algorithms), and combining these with crop growth models to establish an integrated technology system based on agriculture, meteorology, remote sensing, and artificial intelligence. This will facilitate the development of mixed forecasting models suitable for various spatiotemporal scales, which are efficient and highly accurate. By conducting applicability analyses for different regions and crops, the precision, accuracy, and comprehensiveness of agricultural meteorological services will be enhanced.

Using MODIS snow product data, this study investigates the spatiotemporal variation characteristics of the snowmelt period over the Mongolian Plateau during the 2003-2022 hydrological years. The movement of the snowmelt line toward higher latitudes and its response to air temperature are tracked and analyzed at 15-day intervals. The results show that: (1) The proportion of snow-covered area to the total area of the Mongolian Plateau during the 2003-2022 hydrological years ranged from 55.59% to 87.61%, with the smallest snow cover in 2018 and the largest in 2009. Additionally, over the past 20 years, the snowmelt start time on the Mongolian Plateau exhibited a significant advancing trend at a rate of 0.18 days per decade (P<0.05), while the stable snow-cover area showed a delaying trend. (2) Spatially, snowmelt occurred significantly later in northern regions of the Mongolian Plateau compared to southern regions. Stable snow-cover areas were primarily concentrated in the western Mongolia and northeastern Inner Mongolia, where snowmelt times were generally later. Approximately 64.9% of these areas showed an advancing trend in snowmelt, while regions with delaying trends were mainly distributed in the northwestern part of the study area. (3) Observational analysis at half-monthly scales from January during the winter season revealed that the movement of the snowmelt line demonstrated successive synchronicity with the -5 ℃ and 0 ℃ isotherms. Correlation coefficients between snowmelt line positions and temperature, except for the year 2018 (with the least snow cover), generally fell within the higher range of 0.72 to 0.98, indicating that temperature is a key factor influencing the position of the snowmelt line.

In arid areas, farmlands are few, water-holding capacity is poor, seepage is considerable, and crop yield is low. Understanding soil moisture movement in sandy loam farmland is crucial for conserving water resources and enhancing crop yields. This study focused on the sandy loam maize farmland in the middle reaches of the Heihe River, and three experimental plots—flat film irrigation, ridge mulching irrigation, and drip irrigation under film irrigation—were set up. The HYDRUS-2D model was used to simulate the soil moisture migration process of the maize farmland under different irrigation modes. The results revealed that: (1) The simulated values of the HYDRUS-2D model agreed strongly with the measured data, with R² reaching more than 0.864 and RMSE remaining below 0.006 cm³·cm^-3, which verified the feasibility and reliability of the model in the dynamic simulation of soil moisture in sandy loam farmland. (2) Compared with the flat land mulching irrigation mode, the ridge mulching irrigation mode could increase the soil volume water content of the crops’ root zone by about 20% and reduce the seepage loss by 13.3% when the irrigation water volume was reduced by 2099 m³·hm^-2. Compared with the flat land mulching irrigation mode, the drip irrigation mode under film irrigation could reduce the irrigation water consumption by 50% and the leakage by 50.7%. (3) The drip irrigation mode under film displayed “frequent irrigation and small amount” so that the water could be more directly and efficiently replenished in the crops’ root zone, which significantly improved the soil volume water content in the root zone of maize and further reduced the seepage. The sandy loam farmland in the middle reaches of the Heihe River should be irrigated by drip irrigation under film to save water and increase yield. (4) The HYDRUS-2D model’s parameter system can also provide a reference for the dynamic simulation of irrigation water in the same type of sandy loam farmland in northern China.

With rapid socioeconomic development, competition between human activities and the natural environment has intensified significantly, making the balance between socioeconomic development and environmental protection critical. This study constructs a coupling coordination model for a water resources-socioeconomic-ecological environment system to assess the coordination status of the Inner Mongolia section in the Yellow River Basin from 1998 to 2022. Additionally, an improved LSTM model is employed to predict the development trends over the next five years under four integrated regulation scenarios. The results indicate that: (1) The evaluation indices of the water resources, socioeconomic, and ecological environment subsystems across cities in the Yellow River Basin are 0.47-0.57, 0.47-0.87, and 0.42-0.58, respectively, reflecting moderate overall coordination level in the water resources and ecological environment subsystems, whereas the socioeconomic subsystem exhibits relatively higher values but still has room for improvement. (2) The coupling coordination degree of the system in each city shows a gradual upward trend (0.67-0.80), with an overall increase of 19%. (3) Future scenario predictions reveal that joint regulation of water resources and socioeconomic factors leads to the most significant improvements in Alxa, Bayannur, and Ulanqab, whereas joint regulation of socioeconomic and ecological environment factors yields the greatest improvements in Wuhai. Meanwhile, joint regulation of water resources and the ecological environment proves most effective in Baotou, Hohhot, and Ordos.

The success of sand fixation projects in deserts is dependent on soil hydrothermal conditions, which are essential for the healthy growth of sand fixation plants. Vertical pipe surface drip irrigation is a new water-saving and temperature-control conservation technology focused on combating soil drought and surface heat stress on seedlings. However, the mechanisms regulating hydrothermal distribution and migration status remain unclear, and its widespread application in sand-fixing areas lacks a theoretical formulation. Thus, this study constructed a mathematical model of soil water-heat migration for vertical tube surface drip irrigation using HYDRUS-2D software. The study investigated the effects of key irrigation parameters (drip head flow rate and irrigation water temperature) and vertical tube parameters (tube diameter and burial depth) on soil water-heat distribution and migration. The accuracy of the constructed model was confirmed through indoor experiments. Consequently, a single-factor analysis was conducted involving nine simulation scenarios to study the impacts of four influencing factors—drip head flow rate (1, 2, and 3 L·h^-1), irrigation water temperatures (10, 20, and 30 ℃), riser diameter (9.6, 11.6, and 13.2 cm), and riser depth (15, 20, and 25 cm) to obtain the distributions and migration patterns of the soil hydrothermal properties. The results showed the following. (1) Soil hydrothermal changes during irrigation occurred through water-heat coupling influenced by irrigation water temperature. Dynamic changes were most pronounced in the early stage of irrigation, particularly in the inner surface layer of the tube. Over time, these changes stabilized. Water infiltration from the bottom holes of the tube into the surrounding soil increased the soil moisture rapidly before stabilizing. Further, the soil temperature was affected by the irrigation water temperature, exhibiting slight increases or decreases. (2) The diameter of the vertical tube had a minimal effect on the soil hydrothermal changes during drip irrigation. However, the burial depth had a significant influence on the soil moisture but minimal impact on the thermal environment. Outside the tube, the soil moisture distribution around the tube formed a distinct pattern, with the bottom of the tube functioning as a dividing line. Above this line, the soil moisture content at the same point decreased as the burial depth increased, while below this line, the soil moisture content increased with greater burial depth. (3) The drip head flow was a critical factor in determining the soil moisture status although its impact on the soil temperature distribution was limited. The larger the drip head flow, the higher the soil moisture content at the same points outside the pipe. (4) The influence of the irrigation water temperature on the soil moisture distribution was relatively weak; however, it directly influenced the soil temperature. Higher irrigation water temperatures resulted in increased soil temperature at the same points inside and outside the pipe. (5) When adjustments to the vertical tube’s diameter and burial depth were not feasible, soil hydrothermal conditions in the root zone could be effectively regulated by adjusting the drip head flow rate and irrigation water temperature. Thus, this study offers a scientific basis for the design, operation, and management of a vertical pipe surface drip irrigation project for sand fixation plants.

To examine the mineralization characteristics and their effect on soil organic carbon components in sandy loamy soils following the application of organic fertilizers in conjunction with trace elements, indoor culture experiments and field trials were conducted. We assessed the decomposition rate and residue ratio as well as the influence of varying amounts of organic fertilizer on soil organic carbon, active organic carbon, particulate organic carbon, organo-mineral-bound organic carbon, and microbial carbon content, as well as the level of amino sugars, N-galactosamine, and galactomannan. Compared with the application of organic fertilizers alone, the addition of trace elements to the indoor culture significantly decreased the amount of mineralized organic carbon in the sandy loam soils. In field trials, this addition further increased active organic carbon (1.79%-1.99%), low-active organic carbon (2.20%-4.91%), organo-mineral-bound organic carbon (3.89%-7.95%), and microbial carbon (1.71%-8.10%) content, while also enhancing the level of amino sugars (3.46%-6.32%), N-galactosamine (1.21%-13.32%), galactomannan (2.41%-6.14%), and microbial residual carbon (2.70%-4.99%). However, the increase was less pronounced for high-active organic carbon (0.71%-1.48%) and particulate organic carbon (4.91%-5.86%) content. The addition of micro and trace elements to organic fertilizers may, to some extent, mitigate the mineralization process of organic fertilizers in sandy soils, thereby enhancing the level of labile organic carbon, recalcitrant organic carbon, organic carbon bound with minerals, and microbial biomass carbon in the soil, ultimately promoting the turnover and retention of organic carbon in the soil.

Ammopiptanthus nanus is an endangered evergreen shrub that is endemic to the desert area of Central Asia. It exhibits strong cold and drought resistance, serves as a model species for examining the mechanisms of plant adaptation to extreme environments, and is a focus of conservation research in desert biodiversity. In this study, black and green Ammopiptanthus nanus seeds were used to study the germination and viability of newly harvested seeds and their storage by three methods. The results indicated that the germination rate of the newly harvested seeds increased with an increase in temperature, and the viability of the newly harvested seeds reached 100%. There was a significant difference in the germination of seeds with the two colors under dry-cold and -hot storage conditions, with green seeds showing significantly higher germination rates compared with black seeds (P<0.05). However, there was no significant difference in germination under wet-cold storage conditions. Wet-cold storage promoted seed germination, whereas dry-cold and -hot storage resulted in inhibition. The three storage methods had little effect on the viability of either color seed, and viability after storage was >95%. Temperature and humidity are important ecological factors that influence seed germination and viability in Ammopiptanthus nanus. The difference in seed germination represents a strategy for adapting to harsh habitats, which is conducive to increasing its survival and reproduction ability. Wet-cold storage increases the seed germination rate and maintains viability, thus providing valuable technical guidance for the conservation of germplasm resources and nursery breeding.

This study explored the nutrient requirements of Lycium barbarum in Ningxia using a 4-year-old “Ningqi No. 7.” Four treatments (150 mg·L^-1, 210 mg·L^-1, 270 mg·L^-1, and 350 mg·L^-1) were set up using nitrogen concentration as the control index based on an experimental device for nutrient recycling in soilless cultivation. The growth, yield, and quality indexes of L. barbarum were monitored, and nutrient absorption during growth was examined. The results showed that the absorption of large and medium elements (N>K>Ca>Mg>P) as well as trace elements (Fe>B>Mn>Zn>Cu). Maximum N and K absorption was 1.578 g·d^-1 and 0.954 g·d^-1 at the spring shoot growth stage, 0.029 g·d^-1, 9.321 mg·d^-1, and 3.935 mg·d^-1 at the first flowering stage, and 0.254 g·d^-1, 0.764 g·d^-1, 1.113 mg·d^-1, 0.498 mg·d^-1, and 0.184 mg·d^-1 at the summer fruit stage. N, P, and K uptake had correlation coefficients of 0.95, 0.98, and 0.84 with yield, respectively, and none significant for the trace elements. The TOPSIS entropy weight analysis identified the T4 treatment (350 mg·d^-1) as optimal. Producing 1000 kg of dried wolfberry fruit required the absorption of 269.92 kg of N, 5.96 kg of P, 133.93 kg of K, 135.73 kg of Ca, 48.81 kg of Mg, 534.04 g of Mn, 1729.08 g of Fe, 96.79 g of Zn, 41.08 g of Cu, and 737.49 g of B, with nutrient utilization ratios of N:P:K:Ca:Mg=10:0.22:4.96:5.03:1.81 (major elements) and Fe:Mn:Zn:Cu:B=10:3.09:0.56:0.24:4.27 (trace elements).

Exploring the quantitative pre assessment of the climate impact of vegetation greenness changes in the Qaidam Basin can help promote the integrated protection and systematic management of mountains, waters, forests, fields, lakes, grasses, sands, and gases. This article is based on MODIS NDVI data, meteorological data, and climate change prediction datasets. It monitors the changes in vegetation greenness with NDVI ≤ 0.3 in the Qaidam Basin from 2000 to 2023, analyzes the climate driving factors of vegetation with different greenness, and predicts the future trends of vegetation changes with different greenness. The results showed that in the past 24 years, vegetation types Ⅰ, Ⅱ, and Ⅲ in the Qaidam Basin accounted for 49.33%, 19.81%, and 30.86% of low green vegetation, respectively. Among them, the vegetation areas of S_sum, S_Ⅰ, and S_Ⅱ decreased significantly (P<0.001), while the vegetation area of S_Ⅲ increased significantly, indicating a clear improvement in vegetation quality; The cumulative effect of water and heat conditions on precipitation of low green vegetation for 2-3 years and temperature for 5 years is significantly (P<0.01) greater than that of the current year, indicating that a warm and humid climate promotes the healthy development of grasslands; Under the three emission scenarios of RCP2.6, RCP4.5, and RCP8.5 in the future, the overall trend of low green vegetation in the Qaidam Basin is decreasing, and future climate conditions are favorable for vegetation restoration and expansion. The research results can provide scientific basis for the development of ecological environment protection and desertification control measures in the Qaidam Basin.

Water resources form the foundation for maintaining ecosystem balance and ensuring human life and economic development. Simulating hydrological processes in arid and semi-arid ecosystems promotes the effective utilization of local water resources. This paper analyzed the applicability of two models—the Distributed Hydrology Soil Vegetation Model (DHSVM) and the Soil and Water Assessment Tool (SWAT)—in different types of watersheds in semi-arid regions by performing: Sensitivity analysis and parameter calibration. simulation of monthly runoff for the upper reaches of the Xar Moron River and the Laoha River during the growing seasons of 2011-2012 and 2017-2019. The upper reaches of the Xar Moron River are dominated by grasslands, while those of the Laoha River are dominated by forestland and farmland. The results show that DHSVM exhibits 7 primary sensitive parameters in the Xar Moron River and 6 in the Laoha River, whereas SWAT identifies 11 and 12 sensitive parameters, respectively. Following parameter calibration, in the upper reaches of the Xar Moron River the Nash-Sutcliffe efficiency coefficient for DHSVM is 0.70 during calibration and 0.11 during validation, while for SWAT it is 0.43 and 0.04, respectively. In the upper reaches of the Laoha River, the Nash-Sutcliffe efficiency coefficients for DHSVM are 0.56 and 0.70 during the two periods, compared with 0.86 and 0.54 for SWAT. The findings indicate that both models are applicable for simulating hydrological processes in the study area, with DHSVM more accurately simulating overall runoff and SWAT more accurately simulating peak monthly runoff.

To more accurately obtain precipitation distributions in remote areas, this study combined the high-resolution advantages of radar and the wide-coverage detection of satellites. By integrating radar and satellite-derived precipitation, we generated high-precision quantitative precipitation estimation products. Using the strong convective events in Xinjiang on August 12 and 13, 2023, as an example, we used radar reflectivity for precipitation inversion based on cloud classification and Z-R relationships. We fed the Himawari 9 satellite brightness temperature and IMERG precipitation into a BP neural network model to establish the relationship between the average brightness temperature and the average rainfall intensity. Subsequently, we used the instantaneous brightness temperature of the Himawari 9 satellite to invert the momentary precipitation through the BP neural network model. We also proposed two precipitation data fusion schemes: Scheme I uses a uniform correction value to integrate radar and satellite precipitation, whereas Scheme Ⅱ further considers the precipitation intensity levels for comparison. Finally, we obtained high-precision precipitation inversion products for Xinjiang. The results showed that: (1) Cloud classification based on brightness temperature can finely estimate precipitation within the radar range, and brightness temperature differences can reduce the impact of non-precipitating clouds to some extent. (2) The root mean square error (RMSE) of the satellite precipitation inversion was 1.793 mm·h^-1, with a coefficient of determination (R²) of 0.572, indicating reasonable model accuracy. The binary classification score indicated that the model can accurately invert precipitation in over 70% of the areas. (3) The fusion of precipitation by the two schemes slightly improved the accuracy of short-duration light rain distributions. Scheme Ⅱ outperformed Scheme I for short-duration moderate rain but showed a slight decline for short-duration heavy rain compared with Scheme I, indicating that the asynchrony between satellite observation and near-surface precipitation had some impact. (4) Under a 95% confidence interval, the P-values for the RMSE and R² differences between the two schemes and satellite inversion were all less than 0.005, while the P-value for Scheme Ⅱ compared with Scheme I was greater than 0.05. Both fusion schemes significantly improved the accuracy of the satellite precipitation; however, the improvement of Scheme Ⅱ, which considers the precipitation intensity levels, over Scheme I was minimal.

Against the backdrop of a gradual decline in global atmospheric nitrogen deposition, the legacy effects of long-term nitrogen addition on alpine grassland ecosystems remain unclear. This study investigated such legacy effects on plant communities in alpine grasslands through a 16-year controlled experiment conducted in the Bayinbuluke alpine grassland of the central Tianshan Mountains. The results revealed that: (1) Four years after the end of fertilization and regarding the functional traits of the dominant species, high nitrogen treatment (N15) significantly increased the plant height (+20%), leaf area (+16%), and specific leaf area (+5%) of Leymus tianschanicus but reduced the plant height (-23%) and specific leaf area (-1.5%) of Festuca kryloviana. Moreover, the legacy effects on F. kryloviana gradually weakened over the recovery time. (2) At the community level, long-term nitrogen addition exhibited positive legacy effects on rhizomatous grasses but adverse legacy effects on brunch grasses, significantly enhancing the cover and aboveground net primary productivity of the community. However, these legacy effects exhibited a diminishing trend over time. Under the N15 treatment, the increase in community cover declined from 32% to 18%, while the ANPP decreased from 64% to 44%. (3) Regarding soil chemical properties, adding nitrogen had significant positive legacy effects on the total soil nitrogen content but no significant legacy effects on the total soil phosphorus or organic carbon content. The negative legacy effect on soil pH gradually weakened, with the inhibitory effect under N15 treatment decreasing from -3.4% in 2023 to -1.4% in 2024. Soil total phosphorus and organic carbon content exhibited low correlations with vegetation characteristics, and the four soil factors collectively explained only a small proportion of the vegetation variation. This study demonstrates that, against the background of reduced or ceased atmospheric nitrogen deposition, historical nitrogen deposition continues to exert persistent legacy effects on grassland ecosystems, with some of these effects gradually diminishing over the recovery time.

Nitrous oxide (N₂O) a remarkable greenhouse gas in the atmosphere, exerts a pronounced effect on global climate warming. Changes in land use types critically affects N₂O emissions, particularly in ecologically fragile semiarid regions with more complex underlying mechanisms. However, there is still a lack of systematic research on how complex and diverse land use types affect soil N₂O emissions in semiarid regions of China and the key driving factors involved. To address this, this study focused on four typical land use types in the semiarid Loess Plateau of central Gansu Province: Picea asperata forest, Medicago sativa grassland, abandoned land, and wheat field. Soil N₂O fluxes were monitored using the static chamber-gas chromatography method, combined with soil physicochemical property data, to elucidate the key drivers regulating soil N₂O emissions under different land use types. Compared to the abandoned land, the Picea asperata forest and Medicago sativa grassland had significantly increased soil water content, while wheat fields exhibited elevated ammonium nitrogen (NH₄⁺-N) and nitrate nitrogen (NO₃^--N) concentrations. Compared to the abandoned land, the Medicago sativa grassland and wheat fields exhibited markedly enhanced nitrate reductase and nitrite reductase activities, which decreased with an increase in soil depth across all treatments. Soil N₂O fluxes under different land use types exhibited an initial increase followed by a decline during the vegetation growth stages. The total soil N₂O emissions decreased by 34.2% and 23.3% in the Picea asperata forest and Medicago sativa grassland, respectively, and increased by 32.47% in the wheat fields, compared to the abandoned land. Random forest analysis identified soil temperature as the most influential factor affecting the soil N₂O flux. Overall, compared to the abandoned land and wheat fields, the artificial forest and grassland systems in the study area demonstrated superior emission reduction effects. Therefore, future vegetation restoration and ecological rehabilitation efforts should prioritize optimizing the proportional allocation of “forest-grass-cropland” land use types and appropriately increasing the coverage of artificial forests and grasslands to achieve the dual objectives of ecological benefits and emission mitigation.

As the fundamental terrain of deserts, sand ridges play a crucial role in shaping the surface water and thermal environment at different slope positions, which profoundly influences how biological soil crusts develop and their spatial distribution patterns. Lichen crusts are widely distributed on the desert surface. However, issues such as how lichen crusts at different slope positions affect the soil phosphorous cycle and what factors play key roles in influencing this remain unclear. Against this background, this study was conducted in Gurbantunggut Desert, involving a systematic analysis of the changes in phosphorus fractions and related enzyme activities in the lichen crust and 0-5 cm soil layer beneath the crust at different slope positions. The results showed that stable phosphorus in the soil (HCl-Pi, HHCl-Po, HHCl-Pi, and Residual-P) accounted for over 75% of the total phosphorus (TP) content, followed by medium labile phosphorus (NaOH-Pi and NaOH-Po) and labile phosphorus (Resin-P, NaHCO₃-Pi, and NaHCO₃-Po). The slope position had a significant impact on stable phosphorus, and the soil layer had a significant impact on medium labile phosphorus (P<0.05). The data on the contents of stable phosphorus, TP, organic phosphorus (Po), and inorganic phosphorus (Pi) all revealed that, in the crust layer, the values at the bottom of the slope were significantly higher than those on the east and west slopes, while in the 0-5 cm soil layer, the values on the west slope were significantly lower than those at the bottom of the slope and on the east slope (P<0.05). However, the content of NaOH-Pi was significantly higher on the east and west slopes than at the bottom of the slope in the crust layer, and it was significantly higher on the west slope than on the east slope and at the bottom of the slope in the 0-5 cm soil layer. In terms of soil enzymes, the east slope exhibited the lowest activity of alkaline phosphatase activity (ALP) and β-glucosidase activity (GC) in the crust layer, but the highest in the 0-5 cm soil layer. Random forest model analysis showed that the changes in moisture and temperature brought about by the slope position were the most important factors affecting the levels of labile phosphorus and stable phosphorus in the crust soil, respectively. This provides scientific support that enriches the theoretical framework of soil phosphorous cycling in desert ecosystems.

Assessing climate comfort in the Shaanxi-Gansu-Ningxia region is essential for the development of red tourism and the promotion of ecological sustainability. Using daily meteorological data from 1953 to 2020, including average temperature, wind speed, and relative humidity, this study applies a comprehensive climate comfort evaluation model integrated with GIS-based spatial interpolation and zoning methods to systematically analyze the spatiotemporal distribution of climate comfort in the region. The results show that, temporally, the climate is generally comfortable from May to September, while discomfort prevails from December to February. Spatially, northern Shaanxi exhibits relatively favorable climatic conditions, whereas the southwestern Xihaigu region is less suitable in terms of climate comfort. Under the influence of global warming, the annual average number of comfortable days has increased, whereas the number of uncomfortable days has significantly decreased since 2000. Comprehensive zoning results indicate that southwestern and central high-altitude areas experience lower comfort levels, while other regions remain relatively favorable. Further analysis reveals that for each unit change in the climate comfort index, the red tourism visitor flow index changes by 0.593%. Notably, Yan’an, due to its rich red tourism resources and favorable climate, has a significantly higher attractiveness index than other regions. Future red tourism planning should be dynamically optimized to address climate change and evolving tourist preferences. This study offers a scientific basis for regional tourism development and the sustainable advancement of red tourism. A scientific reference for regional tourism development and the sustainable advancement of red tourism activities.

Land resources are the most fundamental production factors for human survival and development. Investigating the driving factors of land use change and simulating future land use scenarios are of great significance for regional sustainable development. Taking the Gansu section in the Yellow River Basin as the research area, this paper, based on multi-source data, employs methods such as the land use transfer matrix, GeoDetector, and the Mixed-cell Cellular Automata (MCCA) model to reveal the evolution characteristics of land use and conduct multi-scenario simulations for 2035. The results are as follows: (1) From 2000-2020, the land use/cover in the research area mainly comprised cultivated land, forest land, and grassland. The extent of forest and grassland cover was relatively high, and the area of cultivated land decreased significantly. Moreover, the conversion between cultivated land and grassland was the most obvious. (2) The dominant factors influencing land use change of the Gansu section in the Yellow River Basin include elevation, temperature, precipitation, distance from rural settlements, and population density. The q-values of the interaction effects of all driving factors have increased. (3) The MCCA model exhibits high simulation accuracy, with an overall accuracy of 0.903. In 2035, the simulation results vary among scenarios. Under the natural evolution scenario, cultivated land and unused land contract, while other land types expand. Under the cultivated land protection scenario, the current stock of cultivated land is maintained, but the area of grassland decreases significantly. In the ecological priority scenario, the areas of forest land and grassland increase significantly. The economic development scenario is manifested in a more aggressive development paradigm, under which construction land experiences a remarkable expansion. The research results provide references for land management and high-quality development of the Gansu section in the Yellow River Basin.

Stoichiometric homeostasis of carbon (C), nitrogen (N), and phosphorus (P) in the plant-soil-microbial continuum is crucial for the maintenance of nutrient cycling stability in fragile ecosystems. To address the challenges of imbalanced C:N:P stoichiometry in eolian sandy soils and the uncertain effects of organic amendments in the Horqin Sandy Land, this study conducted a field experiment to compare the impacts of biochar and straw additions on the stoichiometric characteristics of C, N, and P within an oat cultivation system. The experimental design included a control group (CK), biochar amendment treatments (low B1: 3%, medium B2: 5%, and high B3: 10% by mass), and straw amendment treatments (low S1: 3%, medium S2: 5%, and high S3: 10% by mass). Grounded in ecological stoichiometry and homeostasis theory, this study systematically analyzed the C:N:P response characteristics of oat plants, soil, and microbial communities. The results showed that (1) Biochar amendments (B2 and B3) significantly enhanced the C-N-P cycling efficiency of the oat system and demonstrated superior regulation over elemental allocation compared with straw addition. While biochar had negligible effects on C, N, and P content in oat shoots, it considerably increased these nutrients in the roots. Under the B3 treatment, root C, N, and P content increased by 45.2%, 65.2%, and 71.4%, respectively, relative to the control (CK), outperforming straw S3 by 28.7%, 60.2%, and 14.5%. Soil C, N, and P pools exhibited even greater responses: biochar B3 elevated soil C (240.2% vs. CK; 118.4% vs. S3), N (157.8% vs. CK; 81.4% vs. S3), and P (81.2% vs. CK; 17.5% vs. S3) contents. Microbial biomass followed a similar trend, with C, N, and P increasing by 95.3%, 88.7%, and 134.7% over CK, and by 61.2%, 21.7%, and 43.5% over S3, respectively. Additionally, biochar significantly reduced the C:N and C:P ratios in the shoots, roots, and microbial biomass while increasing these ratios in the soil. This bidirectional regulatory effect was not observed with straw treatment. (2) The homeostasis of oat roots under biochar and straw addition exhibited weaker stability and higher sensitivity to exogenous nutrient inputs compared with stems, leaves, and microorganisms. (3) The C, N, and P concentrations in the plants and microbial biomass of different organs of jasmine followed the order of C>N>P, and the C:N, C:P, and N:P ratios followed the order of N:P>C:P>C:N. Collectively, biochar amendments significantly enhanced the C sequestration capacity and elemental stoichiometric stability of the plant-soil-microbial continuum by improving the oat’s N and P assimilation efficiency. The high-dose biochar (B3 treatment) demonstrated the most pronounced effects. This study establishes a mechanistic foundation for sustainable management of sandy agroecosystems and provides practical guidelines for using biochar as a carbon-negative soil amendment in arid regions.

Accurate identification for ecological restoration is essential for promoting sustainable ecological development. Longnan City, as a crucial water source conservation area and ecological security barrier in the upper reaches of the Yangtze River, plays a critical role in maintaining the regional ecological balance. This study used the InVEST model to evaluate ecosystem services and combined the morphological spatial pattern analysis (MSPA) method with circuit theory to construct the ecological security pattern of Longnan City, then analyze its evolution. The results showed: (1) From 2000 to 2022, the number of ecological source areas increased, primarily distributed in the Kang County, Hui County, and Cheng County. The spatial distribution exhibited a pattern of higher density in the south and lower in the north. (2) The average resistance value first decreased then increased, while the length of ecological corridors initially increased and later decreased, during the study period with a net reduction of approximately 508.94 km. Spatially, the corridors shifted from central to southeastern regions. (3) Ecological bottleneck areas, primarily dominated by forests, croplands, and grasslands, were concentrated in low-resistance zones. Their total area decreased annually, with a net reduction of about 144.84 km² over the study period. Ecological obstacles also decreased in both number and area, mainly clustered in Wudu County, Li County, and Tanchang District. Thus, the research results provide a scientific foundation for the formulation of ecological restoration plans and promotion of high-quality regional economic development in Longnan City. The findings provide scientific support for formulating ecological restoration plans and promoting high-quality economic development in Longnan City.

Pixel-based classification struggles with the accurate identification of glacier changes in areas with similar spectral characteristics, particularly in debris-covered areas where spectral features closely resemble the surrounding mountains and rocks, thereby resulting in low extraction accuracy. This study investigates the Yinsugaiti and Yalong Glaciers using Google Earth Engine to integrate spectral indices, microwave texture features, and topographic data. An object-based (OB) machine learning algorithm is applied for automated glacier extraction and compared to pixel-based (PB) classification methods. The results show the following. (1) The OB classification approach, integrating multi-feature fusion, significantly improved the glacier extraction accuracy. The OB_RF classifier achieved an overall accuracy of 98.1%, a Kappa coefficient of 0.97, and an F1-score of 98.67%, outperforming the OB_CART and OB_GTB classifiers. When compared to PB_RF, the overall accuracy, Kappa coefficient, and F1-score increased by 1.7%, 0.024, and 5.57%, respectively. (2) Between 2001-2022, the Yinsugaiti and Yalong Glaciers retreated at average annual rates of 0.08% and 0.13%, respectively. (3) Supraglacial debris was primarily distributed below 5000 and 4800 m on the Yinsugaiti and Yalong Glacier, respectively. Over the same period, debris-covered areas on both glaciers expanded upward.

This study examines the surface deformation characteristics and deformation rate prediction of large-scale landslides in the upper regions of the Yellow River between the Longyang and Jishi Gorge riverbanks. The study area was the Xijitan giant landslide within the Guide region of the upper Yellow River. The Small Baseline Subset Interferometric Synthetic Aperture Rader（SBAS-InSAR）technology was employed to monitor the surface deformation of the Xijitan giant landslide and analyze, its deformation rates and variation characteristics for the period 2019-2022. The results show that the following. (1) The maximum surface deformation rate of the landslide body was -96 mm·a^-1, with a maximum cumulative deformation of 464.71 mm. Distinct deformation zones were observed along the front and rear edges of the landslide body, with surface deformation rates ranging across -96-16 mm·a^-1. (2) The cumulative deformation of characteristic points on a landslide body, determined using SBAS-InSAR technology, exhibited a maximum cumulative deformation of -140.50 mm. (3) The long short-term memory (LSTM) neural network model was used to predict the cumulative deformation of these points, and the results were compared with those obtained using Support Vector Machine（SVM） and Back Propagation（BP） neural network models. The LSTM model demonstrated high prediction accuracy, with an absolute error within 5 mm and a goodness-of-fit (R²) greater than 0.8. This confirmed the effectiveness of the LSTM model in predicting the cumulative surface deformation of landslides. Thus, the findings of this study provide data support and practical guidance for the enhanced monitoring of giant landslide deformation in the upper Yellow River region and the early detection of potential landslides.

The periodic outburst floods from the Kyagar Glacier-dammed Lake pose a severe threat to downstream areas. In the context of global warming, research on monitoring and early warning for the Kyagar Glacier-dammed Lake is particularly important. Therefore, this study aimed to determine the alert area for the Kyagar Glacier-dammed Lake outburst floods. The area changes and sudden drainage events of the lake were first analyzed using multi-source optical remote sensing data from 1990-2023. Then, the critical minimum drainage volume of the lake was calculated using an area-volume empirical formula and historical flood data. At the same time, the rationality of the alert area was verified through the relationship between the drainage volume and the net flood peak discharge established in this study. The results showed that the lake experienced 20 sudden drainage events over the past 34 years, 17 of which led to glacial lake outburst floods. The periods 1996-2009 and 2015-2019 were unstable, with repeated lake filling and draining. The alert area for the outburst floods of the Kyagar Glacier-dammed Lake is 1.046 km², and the alert net flood peak discharge resulting from the sudden drainage is 418 m³·s^-1. Although the lake area shows a decreasing trend, the risk of flood disasters triggered by the Kyagar Glacier-dammed Lake outburst floods does not necessarily decrease. The lake outburst flood, when superimposed on high basic runoff, can still threaten downstream areas. When the lake area approaches its alert area, it is necessary to monitor its changes closely and implement early warning measures in combination with the basic runoff at the hydrological station. The proposed alert lake area and its determination method may provide scientific support for early warning monitoring of the outburst flood of the Kyagar Glacier-dammed Lake and offer guidance for early warning of flood disasters in the Yarkand River Basin.

There are high levels of boron in surface water and groundwater in the oasis area of Qiemo County, Xinjiang, which seriously affects the health of residents. To clarify the chemical characteristics of the oasis water and the main source of the boron, 24 groundwater samples from each of 20 locations were collected in 2023. They were then analyzed using a Piper three-line plot, Gibbs diagram, and correlation analysis, along with evaluations of hydrogen-oxygen isotopes. An APCS-MLR (absolute principal component-multiple linear regression) model of the chemical characteristics of surface water and groundwater and the source of the boron was also constructed, as well as quantitative evaluation of the contribution of different factors to water boron levels and other hydrochemical components. The results showed that the surface water and groundwater in the oasis area of Qiemo County are weakly alkaline, the mean pH is 8.22, the groundwater is mainly brackish water, and the anode ions are mainly S O_4^{2-}and Na⁺. There are many types of hydrochemistry, with surface water and groundwater mainly containing SO₄·Cl-Na·Mg. The mean level of boron in the surface water in the study area was 2.34 mg·L^-1, with an exceeding rate of 100%; meanwhile, the corresponding value in the groundwater was 1.73 mg·L^-1, with an exceeding rate of 70%. APCS-MLR receptor model analysis revealed that the hydrochemical components and boron sources were mainly soluble filter-enrichment factors (F1: 58.21%), native geological factors (F2: 15.42%), human activity factors (F3: 11.18%), and unknown sources. These findings clarify the cause of the excessive boron in the area, and show that the geological environment has a great influence on the accumulation of boron in water.

The sandy lands of northeastern China, located near the edge of the East Asian monsoon zone, are highly sensitive to climate change, making them ideal for investigating the evolutionary history of regional aeolian processes. This study presents optically stimulated luminescence dating of aeolian sediments from two representative profiles situated near the edge of the Horqin Sandy Land (KE) and the Otindag Sandy Land (HS). By integrating sedimentary facies data from the two profiles with additional regional paleoenvironmental records, we reconstructed the regional aeolian evolution history and examined the factors influencing sand and paleosol formation. The results revealed that: (1) The KE profile indicated the development of dark black sandy paleosols between about 9.8 and 3.0 ka, likely reflecting weak aeolian activity. In contrast, thick light gray sandy paleosols formed from around 0.2 ka, indicating intensified aeolian activity and continuous reworking of surface sediments, preventing older deposit formation. (2) In the HS profile, gray-yellow aeolian sand layers were deposited around 13.4 ka, 1.2-0.5 ka, and since 0.5 ka, indicating episodes of strong aeolian activity. Dark black sandy paleosols formed between about 11.6 and 1.9 ka, corresponding to a period of weaker aeolian activity. (3) Since about 13.4 ka, the region has undergone three stages of climatic and aeolian evolution: (i) a warming period from 13.4 ka to the early Holocene, associated with relatively strong aeolian activity; (ii) a warm and humid midHolocene, marked by reduced aeolian activity; and (iii) a late Holocene period of fluctuating cooling, during which aeolian activity increased again. (4) Variations in the timing of dark black sandy paleosol development between the KE and HS profiles, compared with records from the central parts of these sandy lands, suggest that regional topography and paleoclimatic differences may significantly influence aeolian sediment development.

Water supply services sustain the survival and development of human society and are key to promoting the construction of China’s ecological civilization and the high-quality development of river basins. As a significant component of ecosystem services, it is central to ensuring the stability of watershed ecosystems and promoting the construction of ecological civilization in arid and semi-arid regions. This study focuses on the Ili River Valley in Xinjiang, analyzing the equilibrium characteristics of water supply and demand from 2005 to 2020. Using statistical yearbook and remote-sensing data, we apply models of water supply services, the water resources security index (FSI), and supply-demand matching analysis. The results indicate: (1) The FSI of the Ili River Valley fluctuates from “rising to falling,” and the supply-demand balance exhibits a three-stage evolution from “general deficit to general surplus to deficit persistence.” The spatial difference is significant: five counties and cities continue to deficit (i.e., Yining City, Yining County, Huocheng County, Qapqal Xibe Autonomous County, and Xinyuan County), while three counties and one city (i.e., Nilek County, Tekes County, Zhaosu County, and the city of Horgos [2020]) maintain the surplus that appeared in 2010 during the surplus inflection point. (2) The match between water supply and demand presents three dominant types: “low supply-high demand,” “low supply-low demand,” and “high supply-low demand.” The spatial distribution of supply-demand matching types is differentiated by gradients in the east, middle, and west. Counties and cities with the same matching types display spatial agglomeration and industrial convergence. They are significantly driven by the regional economic structure, which manifests in the following ways: the livestock areas with superior ecological fundamentals maintain a high supply capacity, while the arable land-intensive agricultural areas continue to face high demand pressure. To support regional sustainable development, this study analyzes county-level water supply-demand matching in the Ili River Valley, considering socioeconomic and natural geographic factors. Based on the analysis, ecological management zones—conservation, control, and improvement—are defined to promote integrated development, ecosystem sustainability, and efficient water resource use.

Plant-based sand-fixing agents are ecofriendly materials that effectively stabilize sand without polluting the soil, and their decomposition products promote plant growth. This study investigated the physical characteristics of consolidated layers formed by plant-based sand-fixing agents and their effects on soil water movement in sandy farmland using water infiltration and evaporation simulation experiments with three plant-based sand-fixing agents (Artemisia desertorum, flax, and black locust) and six application rates (0.5 g·m^-2, 1.0 g·m^-2, 2.0 g·m^-2, 3.0 g·m^-2, 4.0 g·m^-2, and 5.0 g·m^-2). Wind-sand soil sprayed with the same amount of pure water served as the control (CK). The results showed the following: (1) The soil physical properties were altered. The compressive strength of the consolidated layer was in the order of black locust >flax >Artemisia desertorum>CK. The average compressive strength of the consolidated layer treated with the three agents increased by 109.38%, 95.06%, and 58.46% compared with CK, respectively. The compressive strength of the same agent increased with concentration. Soil bulk density increased with higher application rates, with a maximum increase of 3.76% compared with CK. Meanwhile, the total porosity and saturated and minimum water-holding capacity decreased by up to 44.55%, 47.65%, and 53.62%, respectively, compared with CK. (2) The water infiltration rate was effectively reduced. The infiltration times were as follows: flax (29.53 min)≈black locust (29.52 min) >Artemisia desertorum (29.03 min) >CK (26.08 min). As the application rate increased, the infiltration time showed a U-shaped trend for black locust and flax agents, whereas Artemisia desertorum increased gradually. (3) The soil water evaporation rates were significantly reduced. For all three agents, the application rates of 2.0-4.0 g·m^-2 demonstrated the most pronounced effects. (4) Application rates of 2.0-4.0 g·m^-2 improved water retention and prevented excessively slow water infiltration. This study provides theoretical support for the exploration of new sand-fixing agents and their application in the prevention of wind erosion in sandy farmland soils.

The Loess Plateau (LP) in China is highly sensitive to climate change, making it an ideal region for understanding temperature dynamics under global warming. This study analyzed the spatio-temporal variations of integrated temperature indicators for ≥0 ℃ and ≥10 ℃—including the first date (FD), ending data (ED), duration (DD), and active integrated temperature (AIT)—using daily average temperature data from 55 meteorological stations on the LP spanning 1960 to 2019. Methods such as linear fitting, mutation tests, and dominance analysis were employed. The results indicate that, from 1960 to 2019, the indicators for both thresholds changed synchronously, with an advancing FD, a delayed ED, a prolonged DD, and an increasing AIT (P<0.01). Notably, most interdecadal shifts occurred in the 1990s, with abrupt changes concentrated from the late 1990s to the early 2000s. The spatial distribution of mean values for both thresholds was similar, showing that FD advanced, ED delayed, DD prolonged, and AIT increased from northwest to southeast. However, the spatial trends differed: the magnitude of the ED delay followed an east-west pattern with alternating phases, while the increase in AIT was higher in the east and lower in the west. For the ≥0 ℃ threshold, changes in FD, ED, and DD were influenced jointly by latitude and altitude, whereas changes in the other indicators were mainly driven by altitude, with contribution rates between 65.59% and 72.17%. The contribution of FD changes to DD changes was 65.1% for ≥0 ℃ and 68.4% for ≥10 ℃, each exhibiting opposite spatial distribution patterns. Compared with 1960-1989, most indicators—except DD and AIT for ≥0 ℃ and FD for ≥10 ℃—showed significant shifts (in terms of earlier or delayed timing, extended duration, or increased magnitude) during 1990-2019, with more pronounced changes at the ≥0 ℃ threshold. Furthermore, the contribution of FD change to DD change decreased by 2.3% for ≥0 ℃ but increased by 15.2% for ≥10 ℃. Spatially, the variation in contribution rates exhibited a “higher-lower-higher” pattern along the south-to-west axis and a contrast with higher values in the southeast and lower in the northwest. Overall, the integrated temperature indicators for both thresholds on the LP show significant responses to climate warming, with distinct regional and temporal characteristics.

The magnetic susceptibility of soils is crucial for paleoenvironmental and paleoclimatic studies. However, debate persists regarding whether soil magnetic susceptibility can serve for paleoprecipitation reconstruction or reflects changes in prevenance in arid regions. To address this issue, new magnetic measurements were conducted on modern soil samples across the Tengger Desert, on the edge of the East Asian summer monsoon region. The weak correlation between the soil magnetic susceptibility, frequency-dependent susceptibility, and modern mean annual precipitation (R²=0.01 and 0.02) suggests that precipitation is not the primary factor driving variations in the surface soil magnetic susceptibility in the Tengger Desert. Conversely, distinct magnetic differences among arid regions indicate that soil magnetic susceptibility can differentiate between origin areas. These findings underscore the need for careful interpretation of soil magnetic susceptibility when conducting climate and environmental research in arid regions.

This study examines Robinia pseudoacacia plantations of different stand ages (18, 22, 26, 30, 33, and 40 years) in the Caijiachuan watershed of Jixian County, located in the Loess Plateau region of western Shanxi. Using the Hedley phosphorous fractionation method, we investigated the distribution patterns of soil phosphorous fractions (H₂O-P, NaHCO₃-P, NaOH-P, D.HCl-P, C.HCl-P, and Residual-P) in the 0-100 cm soil layer across different stand ages. This study clarifies how soil phosphorous fractions change with stand age and explores the influence of soil physicochemical properties on these changes. The results showed that the average total phosphorous content at 0-100 cm soil depth followed this trend: 30 a (590.44 mg·kg^-1)>26 a (571.68 mg·kg^-1)>22 a (527.05 mg·kg^-1)>18 a (517.83 mg·kg^-1)>33 a (490.71 mg·kg^-1)>40 a (464.49 mg·kg^-1). The distribution of phosphorous fractions in the soil followed the order: stable phosphorous>residual phosphorous>moderately active phosphorous>active phosphorous. Each phosphorous fraction initially increased and then decreased with stand age, peaking in the 30-year-old plantation. Additionally, as the soil depth increased, both total phosphorous and phosphorous fractions decreased. Redundancy analysis revealed that soil total nitrogen content and soil pH were the primary factors influencing the phosphorous fraction variations. These findings suggest that in the early stages of afforestation, soil phosphorous fractions gradually accumulate in R. pseudoacacia plantations, peaking at middle stand ages. However, as the stand age increases, phosphorous limitation becomes more pronounced, leading to a gradual decline in phosphorous fractions after maturing. Therefore, from the perspective of phosphorous limitation, appropriate phosphorous fertilization at around 30 years of age can effectively mitigate phosphorous deficiency in mature R. pseudoacacia plantations in the Loess Plateau region of western Shanxi Province.

Invasive plants have significantly impacted the function and biodiversity of the global ecosystem. In the context of global climate change, the effective control of invasive plants is important for maintaining the stability of grassland ecosystems. The spectral differences between invasive plants and native dominant species during phenological stages provide an opportunity for remote sensing technology to monitor their spatiotemporal distribution. Previous studies have primarily focused on single-phase monitoring and the classification of plants, with relatively fewer studies on multitemporal continuous monitoring, particularly during early phenological stages. In this study, we focused on Pedicularis kansuensis, an invasive species of the Bayinbuluk grassland of Xinjiang, using UAV-based multispectral data and machine learning algorithms to extract spatial distribution data for P. kansuensis during key phenological stages in 2023 (emergence, initial flowering, peak flowering, and senescence stages) and the peak flowering stage in 2024. We examined the feasibility of extracting P. kansuensis at each phenological stage and analyzed changes in inter-annual spatial distribution. The results indicated that (1) The random forest algorithm slightly outperformed the support vector machine, with model accuracy varying with the growth stages of P. kansuensis; specifically, peak flowering stage (late July to late August) > initial flowering stage (late June to early July) > emergence stage (mid-June) > senescence stage (mid-September). Throughout the growth season, spatial distribution during the early growth stages (emergence and initial flowering) exhibited a high spatial overlap with the peak flowering stage, and the key features were consistent with those of the peak flowering stage. This suggests that the random forest algorithm can effectively map the distribution of P. kansuensis during the emergence stage, which provides important technical support for the early-stage monitoring of invasive plants; (2) The spatial distribution of P. kansuensis exhibited significant inter-annual variation, with less than 15% spatial overlap between the two years; (3) During the growth season, the most important feature for distinguishing P. kansuensis (excluding the senescence stage), from other co-occurring species was the normalized difference index, calculated from the 555 nm and 720 nm bands, followed by the green band. Because P. kansuensis had entered the senescence stage, there was a noticeable change in feature importance, with significant differences in various background environments. These results demonstrate the feasibility of using UAV-based multispectral remote sensing technology for monitoring the early phenological stages of P. kansuensis and offer technical support for early warning and control measures.

Exploring the transition situation of land use in ecologically significant but underdeveloped areas is crucial for promoting urban-rural integration and achieving regional sustainable development. Using the land use data from five time points in Gansu Province from 2000 to 2020, this study analyzed the quantitative distribution, spatial patterns, and mutual transfer of land use types. The Future Land Use Simulation model was used to simulate the land use transformation under four scenarios of inertia development, urban-rural integration, planning constraints, and ecological restoration in 2035. The study found that: (1) The main land use types in Gansu Province are cultivated land, grassland, and unused land, exhibiting significant regional heterogeneity in spatial distribution. The comprehensive land use dynamics initially increased, then decreased, before increasing again. (2) Under the influence of the continuous promotion of the Western Development Strategy and the policy of returning farmland to forest and grassland, the land use transition in the Gansu Province is mainly manifested in the transfer of cultivated land to grassland and woodland, and the transfer of construction land to cultivated land and grassland. (3) Under the two scenarios of urban-rural integration and planning constraints, the results of land use simulation are reasonable, considering cultivated land protection and regional ecological environment restoration, which can meet the needs of future development. This study provides a valuable reference for land governance and spatial planning in Gansu Province.

Evapotranspiration, as a crucial component of the water cycle, is vital for regulating water resources and protecting the environment, especially in arid regions where it plays a significant role in water consumption and redistribution. This study focused on Aksu River Basin and used MOD16 evapotranspiration product data from 2001 to 2022 to systematically analyze the patterns of spatial and temporal variation of actual evapotranspiration (AET ) and potential evapotranspiration (PET ), along with an exploration of the factors influencing them. The findings provide a scientific basis for managing regional water resources and protecting the environment. The results indicate the following: (1) The MOD16 product data are consistent with ET₀ data (R²=0.8133), and the product accuracy meets the requirements for studying the spatial and temporal distribution of evapotranspiration in Aksu River Basin. (2) The multi-year average AET and PET are 168.36 mm and 1569.03 mm, respectively. AET shows an overall increasing trend, while PET exhibits a decreasing one. There are significant differences in the spatial distribution of AET and PET, with the opposite trends being exhibited. (3) Over the last 22 years, AET in Aksu River Basin has significantly increased, mainly in cultivated land, forestland, and oases, while PET has decreased overall but increased near the edges of oases and along river channels. AET is less stable than PET, and the Hurst indices of both indicate that the trends may change in future, with 56% of the area showing anti-persistence for AET and 89% for PET. (4) Changes in AET and PET are intrinsically linked to changes in climatic factors, with wind speed and relative humidity being the main factors influencing regional variations in these two variables. This study provides an important scientific reference for managing and using water resources in arid regions.

This study investigated the community structure and function of generalized and specialized fungal species (GFS and SFS, respectively) in the soil and roots of Pinus sylvestris var. mongolica forests and their relationship with soil physicochemical properties, aiming to identify key microbial mechanisms affecting ecosystem functioning in P. sylvestris var. mongolica forests. Using high-throughput sequencing technology, we analyzed the differences in the community structure and functional groups of GFS and SFS in the soil and roots of natural forests and plantations (24 a, 35 a, 44 a) of P. sylvestris var. mongolica in the Hulunbuir Desert. The results were as follows: (1) The soil and root-associated GFS retained 169 operational taxonomic units (OTUs) in total, the soil SFS retained 603 OTUs, and the root-associated SFS retained 216 OTUs, including Tricholoma and Suillus in soil GFS; and Tricholoma, Suillus, and Cadophora in root-associated GFS; Penicillium in soil SFS; and Acephala in root-associated SFS. (2) The relative abundance of symbiotic nutritive fungi accounted for 28.49%-47.21% of soil GFS, and the dominant ecological functional group was ectomycorrhizal fungi, which showed a trend of increasing and then decreasing with forest age. Saprophytic nutritive fungi accounted for 17.01%-40.01% of soil SFS. The relative abundance of saprophytic nutritive fungi in plantation forests was lower than that in natural forests, and it showed a tendency of increasing and decreasing followed by increasing with forest age. Symbiotic trophic fungi accounted for 43.25%-54.45% of the root-associated GFS; the dominant ecological functional group was ectomycorrhizal fungi, which showed an increasing trend with increasing forest age, and the relative abundance of ectomycorrhizal fungi in natural forests was higher than that in plantation forests. (3) The soil organic matter and available phosphorus content of natural P. sylvestris var. mongolica forests were significantly higher than those of plantation forests (P<0.05). In plantation forests, with increasing forest age, the soil organic matter (SOM), total phosphorus (TP), available nitrogen (AN), and available phosphorus in the soil increased significantly (P<0.05), whereas the soil pH decreased but not significantly (P>0.05). GFS was mainly dominated by SOM, soil NH₄⁺-N, and TP (P< 0.05). Furthermore, the community variability of root-associated SFS was regulated by total nitrogen (P<0.05), whereas soil SFS was significantly affected by only TP, AN, and NO₃^--N (P<0.05). The drivers of fungal community structure showed significant ecological niche differentiation. This study contributes to a deeper understanding of the ecological functions of fungi in the soil and roots of P. sylvestris var. mongolica forests, providing a basis for the sustainable management and protection of P. sylvestris var. mongolica forests in the Hulunbuir Desert.