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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Located in the convergence zone of the Qinghai-Xizang Plateau Ecological Barrier and the Northern Sand Control Belt, the Babusha region acts as a frontline defense against the southward encroachment of the Tengger Desert. Assessing changes in the ecological environment quality in the Babusha region holds significant value for evaluating the effectiveness of regional desertification control and advancing the Three-North Shelterbelt Development Program. This study used data from the Google Earth Engine platform to investigate land use pattern changes in the Babusha region from 1986 to 2021. A comprehensive assessment of the spatiotemporal changes in the regional ecological environment quality was conducted using the normalized difference vegetation index (NDVI), desertification index (DI), and remote sensing ecological index (RSEI). The results were as follows: (1) Over time, the desert area in the Babusha region has continued to decrease, the grassland area has progressively increased, and the vegetation coverage has improved. From 1986 to 2021, NDVI and RSEI showed a fluctuating upward trend, with NDVI increasing from 0.14 to 0.31 (>50% increase) and RSEI increasing from 0.22 to 0.24 (9.39% increase). In contrast, DI exhibited a fluctuating downward trend, decreasing from 0.79 to 0.57 with a cumulative reduction of 27.85%. (2) Areas with high NDVI and RSEI values were concentrated in the southern and northwestern parts of the study region, dominated by woodland and cultivated land, whereas areas with low NDVI and RSEI values were distributed in the northern region characterized by extremely low vegetation coverage and desert. (3) The trend analysis primarily revealed a nonsignificant or significant increase in NDVI and RSEI values and a nonsignificant decrease in DI values. Specifically, 12.12% and 61.10% of the study area exhibited a nonsignificant and significant increase in NDVI, respectively, whereas 5.06% and 38.63% of the study area showed a nonsignificant and significant increase in RSEI, respectively. The ecological improvement areas were concentrated in the northwestern and southeastern regions with higher human activity levels. From 1986 to 2021, the Babusha region demonstrated marked vegetation restoration, sustained improvement in the ecological environment, and significantly effective desertification control, facilitating the establishment of a replicable Babusha model.

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.

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.

Using hourly precipitation data collected from automatic weather stations (AWS) in eastern Gansu Province during the summer months from 2010 to 2021, a total of 50 regional heavy rain showers were identified. An analysis was then conducted to examine the spatiotemporal distribution and intensity of such events in eastern Gansu Province. The obtained results can be summarized as follows: (1) The intensity of the heavy rain showers primarily ranged between 20 and 30 mm·h^-1, which accounted for more than 60% of such events. Intensities exceeding 40 mm·h^-1 represented less than 10% of such events. Notably, short bouts of intense precipitation with intensities exceeding 50 mm·h^-1 occurred in 74% of the heavy rain showers in the studied region. (2) In the studied region, heavy rain showers mainly occur from mid-June to late August, peaking in the period from late July to mid-August. While such events occur throughout the year, the interannual variability in their occurrence is significant and closely associated with the position of the Western Pacific subtropical high, the transport of abnormally warm water vapor from the South China Sea or East China Sea, and significant baroclinic features resulting from the interaction of weather systems at mid- and low latitudes. (3) The area typically affected by heavy rain showers in eastern Gansu Province accounts for only 3.17% of its total area. However, there are notable regional variations in the spatial distribution of these events, with areas struck by high-intensity rainfall being primarily located in the Taizishan region, the western section of the Qinling Mountain, Liupan Mountain, and Ziwu Mountain. Additionally, areas affected by rainfall of extreme intensity, exceeding 40 mm·h^-1, are concentrated in these high-incidence centers. (4) There is a clear pattern in the distribution of stations recording heavy rain showers under different circulation patterns. Stations associated with the eastward-moving plateau trough type are dispersed and most abundant. Meanwhile, stations related to the subtropical high’s southwestern airflow type record the lowest median number of such events. Finally, stations experiencing shear between two high-pressure systems are concentrated, while those associated with the northwest airflow type are the least numerous. There was no significant difference in the distribution of the events with heavy rainfall intensity among these circulation types. However, rainfall intensities between 30 and 50 mm·h^-1 are more likely to occur in the two high-shear types.

Litter decomposition has an important role in the carbon and nutrient cycling of terrestrial ecosystems. Climatic conditions are the main factors involved in litter decomposition. Currently, few studies have examined litter decomposition in alpine grassland ecosystems. To determine the effects of meteorological factors on the litter decomposition and nutrient release processes under a climate change background, the Stipa purpurea endophytic fungal symbiont was used along with the litter decomposition bag method to analyze the decomposition characteristics with endophytic fungi (E+) and without endophytic fungi (E-). The effect of meteorological factors on the decomposition rate of Stipa purpurea was analyzed. The results indicated that the decomposition rate of E+ was higher compared with that of E-, whereas the decomposition cycle was shorter. With the extension of time, the total nitrogen content of Stipa purpurea showed an increasing trend, lignin content gradually changed from significantly higher in E+ to no significant difference between the two, and the cellulose content gradually changed from significantly lower in E+ compared with E- (P<0.05). Regardless of endophytic fungi, the litter weight and mass loss rate of Stipa purpurea were correlated with the mean monthly temperature and the mean ground temperature (P<0.05). Precipitation was positively correlated with the litter decomposition rate of Stipa purpurea, and the total nitrogen content of the litter was positively correlated with temperature and precipitation (P<0.05). The lignin and cellulose content were negatively correlated with temperature and precipitation. The duration of sunshine had a positive effect on the decomposition of litter, and the lignin, cellulose, and litter weight content were strongly correlated with sunshine duration. Overall, endophytic fungi accelerate the decomposition of Stipa purpurea litter. For E+ and E-, the effect of meteorological factors on the decomposition of Stipa purpurea litter was consistent.

This study examines cotton growth affected by soil temperature under the condition of phosphate fertilizer drip application. It also explores the role and mechanism of soil temperature regulation of cotton root growth on improving the utilization rate of cotton phosphate fertilizer. Using potted tests, three soil temperature gradients were examined: low temperature (LT: 11-18 ℃), medium temperature (MT: 22-26 ℃), and high temperature (HT: 30-34 ℃). Single factor testing with water bath temperature control was utilized. The effects of various soil temperatures on the growth traits, biomass, root distribution, effective soil phosphorus distribution, and phosphate utilization efficiency in cotton were assessed. As soil temperature increased, cotton plant height, stem thickness, leaf number and biomass all showed parabolic changes that peaked in the medium temperature (22-26 ℃) group. Additionally, root length in the 0 to 5 cm soil layer increased with soil temperature, most notably with high temperature treatment, followed by low temperature and medium temperature treatments increasing by 5.2%-126.9% and 4.9%-62.3%, respectively. Below the 5 cm soil layer, root length decreased with increasing temperature, with the medium temperature treatment having the longest root length, 81.68%-98.43%, which was 170.17%-218.35% longer than the low temperature and high temperature treatment, respectively. The effective P content of each treatment increased with lower temperatures, with the medium and high temperature treatment content being 13.7% and 20.5% lower than the low temperature treatment, respectively. Phosphorus absorption and phosphate utilization were maximized in the medium temperature cotton, followed by the low temperature cotton. With the lowest high temperature, the total phosphorus absorption in the medium temperature cotton increased relatively by 49.69% and 89.36% compared with low temperature and high temperature treatments, respectively. Furthermore, the phosphate utilization rate was twice and 50% higher than the high and low temperature treatments, respectively. These findings indicate that based on the effects of soil temperature on cotton growth, root and soil effective phosphorus distribution, phosphorus absorption, and phosphate utilization, the most suitable soil temperature for cotton growth is 22-26 ℃.

Arid regions function as important global sources and sinks for microplastics (MPs), with their unique climatic conditions and human activity patterns giving rise to specific MP pollution characteristics. This article systematically reviews recent advances in understanding MP sources, pollution patterns, migration, and ecological risks within arid environments. Regarding pollution characteristics, soil MP abundance exhibits significant spatial heterogeneity, with fibrous microplastics accounting for 64%-92% of the total. Polyethylene, polypropylene, and nylon are identified as the main polymer components, primarily originating from agricultural film residues. In terms of migration mechanisms, wind erosion and sandstorm events dominate local-to-regional-scale transport. Due to their high aspect ratio and low density, fibrous microplastics are particularly prone to cross-border atmospheric migration, further prolonged by the coupling effect of electric and wind fields on their atmospheric residence time. Ecologically, MPs exert multi-dimensional impacts on ecosystems by altering soil physicochemical properties (e.g., pore structure and water retention capacity), interfering with microbial metabolism, and inducing oxidative stress in plants. Future research efforts should focus on integrating multiscale models, investigating the combined effects of microplastics and other pollutants, and establishing a standardized monitoring system.

This study uses ground meteorological observation data from 11 national meteorological stations and 192 regional stations in the Tuha Area, spanning from 1974 to 2024, to analyze the spatiotemporal variations of sand-dust weather and its correlation with meteorological factors. The results reveal the following: (1) Floating dust is the most frequently occurring sand-dust weather event in the area, followed by blowing sand; sandstorms occur least frequently. The peak period for sand-dust weather is in spring. Blowing sand and sandstorms are more common in summer and the least in winter, whereas floating dust is more frequent in autumn than in summer. (2) The distribution of sand-dust weather days shows a pattern of higher occurrence in the west compared to the east, and more prevalence in basins than in mountainous areas. High-incidence areas for floating dust include Tuokexun and Gaochang District of Turpan City. Blowing sand and sandstorms are mainly concentrated around the Tuokexun-East Kan’er Station and Naomaohu Station, whereas mountainous regions such as Barkol and Yiwu in Hami City experience very few sand-dust weather events. In addition, significant differences exist in wind direction and speed associated with sand-dust weather across different regions. (3) Over the past 50 years, the total number of sand-dust weather days has shown an overall decreasing trend, with floating dust decreasing at the fastest rate of 7.1 days per decade. The 1970s recorded the highest sand-dust weather, whereas 2013 recorded the lowest. In the past decade, the total number of days with sand-dust, floating dust, and blowing sand has significantly increased. Abrupt changes in the annual counts of sand-dust, floating dust, and blowing sand occurred in 1991, 1995, and 1991, respectively, whereas the trend for sandstorm days did not exhibit a clear abrupt change. (4) The number of sand-dust days shows a significant positive correlation with both the number of strong wind days and average wind speed, a significant negative correlation with average temperature, and no clear correlation with precipitation or sunshine duration.

The Three-North Shelterbelt Forest Program (TNSFP), a major ecological engineering initiative in China, faces growing challenges from shifting precipitation patterns. This study utilizes daily precipitation data from 323 meteorological stations across the TNSFP region. The percentile threshold method was used to define extreme precipitation thresholds, calculate relevant indices, and analyze their spatiotemporal evolution. The results Show that (1) Distinct south-north gradient in annual precipitation, with amounts decreasing from the southeast to the northwest. The spatiotemporal distribution of extreme precipitation is closely linked to topography. (2) Southeastern areas exhibit higher extreme precipitation totals, though these show a declining trend. In contrast, the number of extreme precipitation days and their contribution rate have significantly increased in the northwest. (3) Cluster analysis highlights that the intensification of extreme precipitation is concentrated in specific regions, the southern foothills of the Greater Hinggan Mountains, the Qilian Mountains, and the Tianshan-Altai Mountains. In these areas, extreme precipitation accounts for one-third to one-half of annual rainfall. The likely drivers of this intensification include Arctic warming, westerly belt fluctuations, and topographic uplift: demonstrating the complex interactions between large-scale climate patterns and regional geographic features that shape observed trends. These findings have significant implications for the ongoing management and resilience of the TNSFP. Understanding the spatiotemporal characteristics of extreme precipitation is essential for developing effective strategies. This research provides valuable insights for anticipating future climate impacts and formulating disaster prevention and mitigation measures.

The ecological security of the Jinghe River Basin, a crucial component of the ecological barrier in northwest China, is of paramount importance. This study constructed a landscape ecological risk assessment model using land use data and landscape pattern indices to evaluate the dynamic characteristics of landscape ecological risk evolution in the Jinghe River Basin. Key driving factors affecting this risk were identified through geodetector analysis. The results revealed the following: (1) Cultivated land and grassland are the predominant landscape types in the basin, with frequent mutual transfer between the two. In addition, the construction land has shown a continuous expansion trend, increasing by a total of 394.5 km² during the study period. (2) Medium-risk areas account for over 41% of the landscape ecological risk types in the Jinghe River Basin. High- and medium-high-risk areas are primarily located along the Jinghe River network, particularly concentrated in the middle and southeastern flat terrain, together constituting about one-tenth of the basin area. Low-risk areas are predominantly found in the eastern and southwestern parts of the basin, where human interference is minimal. (3) Throughout the study period, more than 80% of the basin’s areas maintained stable risk levels, contributing to a reduction in the overall landscape ecological risk. (4) The main driving factors influencing landscape ecological risk include average annual temperature, GDP density, and elevation. The interaction between average annual temperature, average annual precipitation, and other influencing factors has significant effects on landscape ecological risk.

Soil carbon fractions are key for maintaining ecosystem functions. To reveal the variation characteristics and influencing factors of soil carbon fractions in arid sandy ecosystems, this study examined natural (Zygophyllum xanthoxylon, Krascheninnikovia ceratoides, and Artemisia ordosica) and artificial (Corethrodendron scoparium) sand-fixing vegetations on the southern margin of the Tengger Desert, Northwest China. A comparative analysis was conducted to assess the vertical distribution characteristics of soil inorganic carbon (SIC), soil organic carbon (SOC), labile organic carbon (LOC), slowly cycling organic carbon (SCOC), inert organic carbon (IOC), light fraction organic carbon (LFOC), and heavy fraction organic carbon (HFOC) across the 0-100 cm soil profile. Further, soil physicochemical properties were analyzed to identify key driving factors affecting soil carbon fractions. (1) All soil carbon fractions followed the content order: C. scoparium>K. ceratoides>Z. xanthoxylon>A. ordosica, with the overall abundance ranked as SIC>SOC>HFOC>IOC>SCOC>LOC>LFOC. (2) Carbon fractions exhibited significant vertical differentiation across vegetation types. SIC content increased with soil depth, whereas SOC and its fractions (except A. Ordosica) were epimerized. Moreover, in A. Ordosica, SOC and its fractions of peaked at the 20-40 cm soil layer. All soil carbon fractions showed highly significant positive correlations. (3) Soil pH and bulk density were negatively correlated with carbon fractions, whereas total nitrogen, total phosphorus, slow-release potassium, and available potassium were key factors influencing carbon fractions. In conclusion, soil carbon fractions in these arid sand-fixing vegetation predominantly comprised SIC (75.48%). Artificial C. scoparium vegetation exhibited higher overall soil carbon content than that of natural vegetation. By increasing stable carbon fractions (HFOC, IOC, and SCOC) and improving surface-layer carbon sequestration, artificial sand-fixing vegetation significantly improved the desert soil carbon pool stability and sequestration potential. These findings underscore the critical importance of strengthening surface soil conservation and establishing artificial sand-fixing forests for effective ecological restoration in desert regions.