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.

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.

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.

Objective, accurate, and timely evaluation of the spatiotemporal changes and driving forces of ecological environment quality is of great significance for the formulation of ecological protection plans and policies. Taking Alxa Left Banner as an example, this study constructs a Remote Sensing-based Ecological Index (RSEI) for arid regions based on the Google Earth Engine (GEE) platform and analyzes the spatiotemporal changes and driving forces of RSEI over the past 30 years (1991-2021). The study shows that: (1) Over the past 30 years, the RSEI of Alxa Left Banner has shown a fluctuating upward trend, with the maximum RSEI in 2012 (0.360) and the minimum in 2007 (0.264). (2) Over the past 30 years, the area of ecological improvement (RSEI>0.2, 3.15%) in Alxa Left Banner is larger than the area of degradation (RSEI<-0.2, 2.48%), with the largest area showing no change (-0.2<RSEI<0.2, 94.37%). Regions with poorer RSEI are mainly distributed in bare land areas, while the RSEI of forest, grassland, farmland, and impervious surface areas has gradually improved. (3) From 1991 to 2021, the Global Moran’s I index ranged between 0.600 and 0.650, indicating a high degree of clustering. (4) According to the results of the linear mixed-effects model, human activities account for 89% of the changes in RSEI, while climate change accounts for 11%. In summary, over the past 30 years, the overall ecological environment quality in the Alxa Desert area has gradually improved, with significant improvements in the northern edge of the Tengger Desert, primarily due to human activities, especially the aerial seeding afforestation projects.

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.

Leaves and roots respond to drought stress through morphological, physiological, and biomass accumulation changes. Alhagi sparsifolia is the dominant plant in the desert-oasis transition zone of Cele. We analyzed the characteristics of growth and physiological changes in leaves and roots of 1-year-old A. sparsifolia seedlings through a pot experiment. Results revealed the adaptive strategy of A. sparsifolia to drought stress. We simulated three water conditions (CK is well-watered: 70%-75% field capacity (FC); W₁ is mild stress: 50%-55% FC; W₂ is severe stress: 25%-30% FC). The results show the following: (1) Drought significantly inhibited the growth of the aboveground and underground tissues of A. sparsifolia. The main manifestations are: leaf area, root length, root surface area, root tissue density, and soluble sugar content of leaves and roots decreased significantly under stress (P < 0.05). The leaf tissue density, leaf dry matter content, specific root length, proline and malondialdehyde contents of leaf and root increased. (2) In the early growth stage, the aboveground biomass of A. sparsifolia under all treatments was relatively high (root-shoot ratios under CK, W₁, and W₂ were 0.43 ± 0.14, 0.59 ± 0.1, and 0.83 ± 0.83), while in the late growth stage, the below-ground biomass under all treatments was relatively high. The root-shoot ratio was the highest under severe stress (3.12 ± 0.32). The results indicate that A. sparsifolia enhanced the investment of resources underground in the late growth stage, and the resource allocation characteristic is more obvious under severe drought stress. (3) Pearson-correlation analysis showed that there was a significant tradeoff between core traits related to leaf morphology and root physiology in A. sparsifolia (P < 0.05). Meanwhile, the leaf and root had synergistic changes in physiological metabolism. The results preliminary indicate the adaptive characteristics and A. sparsifolia seedlings under drought exhibit high dry matter storage, defense capacity, and low water consumption. A. sparsifolia can coordinate the resource allocation relationship between leaves and roots. At the same time, with drought stress time increased, the adaptive strategy of slow investment and conservative growth of A. sparsifolia was gradually formed. The results provide a reference for the restoration and management of desert vegetation in this region.

Based on the data from 19 sounding stations in 2022-2023, this study investigates the temporal and spatial variations of the temperature inversions in the lower, middle, and upper troposphere in northwest China. The results indicated the following: (1) In terms of monthly variations, inversions across all three tropospheric levels exhibit similar patterns, peaking in December and January-February of the following year and reaching a minimum from June to August. (2) In terms of spatial distribution, among the low-level inversions, low-level inversions were most frequent in northern Xinjiang, at 40%-60%; the greatest thickness of low-level inversions was observed in northern Shanxi, exceeding 90 m; the intensity of low-level inversions was stronger in most areas of Xinjiang, ranging from 2 ℃ and 3 ℃. For mid-level inversions, their frequency was highest in Qinghai and decrease outward from this region. High-level inversions were most pronounced in northern Xinjiang, with their frequency decreasing outward from this region. (3) The occurrence of low-level inversions in northwest China is influenced by surface radiation and topography, the occurrence of mid-level inversions is associated with warm advection and subsidence movement, and the occurrence of high-level inversions may be related to the top of the temperate troposphere and ozone. (4) In the summer of northwest China, influenced by solar radiation and surface cooling. below the 0 ℃ isotherm height, the intensity of inversions is stronger; above the 0 ℃ isotherm height, the inversions have weaker intensity.

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.

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.

In this study, we investigated the physiological responses of Pinus sylvestris var. mongolica seedlings to drought stress and subsequent rehydration. A pot experiment was conducted using 2-year-old seedlings subjected to five water treatments, including control (80%), light drought (40%), moderate drought (20%), severe drought (10%), and extremely severe drought (5%). We measured leaf water content, photosynthesis, chlorophyll fluorescence, leaf osmoregulatory substances, and antioxidant enzyme activity during drought and after rehydration. The results showed the following: (1) The physiological state of the seedlings was minimally affected by the light drought. The activities of superoxide dismutase and peroxidase peaked under moderate and severe drought stress, increasing by 25.26% and 38.8%, respectively. Conversely, the net photosynthetic rate, transpiration rate, and photochemical quenching coefficient under extremely severe drought stress decreased by 94.76%, 87.19%, and 72.35%, respectively, while the leaf malondialdehyde content was the highest in this condition. (2) The chlorophyll fluorescence and leaf proline content of the seedlings were restored to control levels after rehydration. However, the average photosynthetic indices of rehydrated leaves only returned to 28.51% after extremely severe drought stress. Additionally, leaf water use efficiency, soluble sugar content, and antioxidant enzyme activity were significantly higher than the control after rehydration (P<0.05). In conclusion, extremely severe drought stress primarily reduces photosynthetic ability and disrupts the cell membrane stability of Pinus sylvestris var. mongolica seedlings. Conversely, rehydration after moderate drought improves water utilization and the scavenging ability of reactive oxygen species, thereby improving drought resistance. This improved information provides theoretical insights for the efficient cultivation, management, and evaluation of drought resistance in the Pinus sylvestris var. mongolica plantation.

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.

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.

In this study, google earth engine (GEE) was used to extract the normalized difference vegetation index (NDVI) and Albedo parameters. The NDVI-Albedo space was constructed to monitor aeolian desertification in Ongniud Banner from 1991 to 2015, and the influence of key driving factors and mechanism of aeolian desertification in Ongniud Banner were analyzed using geographical detectors combined with natural and anthropogenic factors. The following key results were obtained: (1) Aeolian desertification in Ongniud Banner first experienced the development of evolution process, which then was reversed. During the development period from 1991 to 2000, the total area of aeolian desertified land increased by 2130.29 km², with extremely severe changes in both aeolian and non-aeolian desertified land, which had dynamic attitudes of 9.5 and -4.8, respectively. From 2000 to 2015, the total desertified land area of aeolian decreased by 3364.61 km², and the extreme severe aeolian and non-aeolian desertification land were the main changes, with dynamic attitudes of -4.2 and 8.3, respectively; (2) The extreme areas of aeolian desertification in the Ongniud Banner were mainly distributed in the central east and the north of Xiliaohe Plain, while the aeolian desertification in most areas of Jibeiliaoxi Mountain in southwest region is relatively light. From the perspective of transfer, the development area of various types of aeolian desertification land was 5333.75 km², while the reversed area from 1991 to 2000 was 1157.29 km². Notably, the non-aeolian desertified to moderate aeolian desertified land area was the largest covering 1000.24 km². From 2000 to 2015, the development area of all types of aeolian desertified land was only 424.65 km², while the reversed area was 7041.80 km². The area of moderate desertified land covering 1449.74 km² was reverted to non-desertified land; (3) From 1991 to 2000, both natural and anthropogenic factors drove the aeolian desertification process in the study area, with terrain and sand source as the main reasons for the formation of spatial distribution pattern of aeolian desertified land in Ongniud Banner. The warm and dry climate conditions, as well as intensified human activities led to the development of aeolian desertification in Ongniud Banner. From 2000 to 2015, aeolian desertification reversal was driven by the implementation of a series of anti-desertification policies and the improvement of natural conditions.

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.

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 effects of water, salt, and nitrogen (N) regulation on changes in the soil water, transport of salt nutrients, and growth indices and yield of cotton (Gossypium hirsutum) were analyzed under drip irrigation covered by film. A two-year three-factor full-combination field experiment was conducted to study the effects of three levels of irrigation (W1: 2700 m³·hm^-2, W2: 3600 m³·hm^-2, and W3: 4500 m³·hm^-2), salinity (S1: 3 dS·m^-1, S2: 6 dS·m^-1, and S3: 9 dS·m^-1), and N (F1: 105 kg·hm^-2, F2: 210 kg·hm^-2, and F3: 315 kg·hm^-2). The effects of different combinations of water-salt-nitrogen on soil moisture, salinity, N distribution, plant growth, and yield were investigated. The results showed the following: the soil moisture was mainly located in the 30-40 cm soil layer, and the water content of different soil depths essentially first increased and then decreased. The average water content of the 0-40 cm soil layer in the bud and boll stages of S3F3W1 and S2F3W1 increased by 1.3%-21.8% compared with that of S1F3W1, and the average water content of the combination of S1F3 increased by 1.39%-13.83% compared with those of S1F2 and S1F1 under the same amount of irrigation. The soil salinity tended to decrease and then increase during the fertile period. The S1 treatment increased and then decreased the soil salinity as N application increased, and the soil salinity in S2 and S3 decreased as the N application increased. The N content was significantly higher with the F3 treatment than F1 or F2. In the W2 and W3 treatments, N slowly accumulated in the 40-60 cm soil layer, and the N content was significantly higher with the S1 treatment than S2 or S3. The soil moisture, salinity, and N content interacted; under appropriate soil moisture and N conditions, lower soil salinity enabled the plants to utilize nutrients more efficiently, which facilitated their growth, and thus enhanced yield. To obtain high economic benefit, the recommended rate of irrigation for low and medium saline soils is 3600 m³·hm^-2 and the rate of N is 210 kg·hm^-2. For highly saline soils, the recommended rate of irrigation is 4500 m³·hm^-2 and the rate of N is 315 kg·hm^-2. This study provides a theoretical basis to explore the mechanism of water and salt nutrient transport and the efficient use of water and fertilizer in cotton farmland ecosystems under multiyear drip irrigation under a membrane in arid areas.

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.

Based on data from 152 meteorological stations in Northwest China and 16 climate models of CMIP6, the CMIP6 model data were bias-corrected using the RoMBC method. The Standardized Precipitation Evapotranspiration Index (SPEI) was then constructed to analyze the spatial and temporal distribution and variation of drought in Northwest China under the historical and future scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). The results are as follows: (1) Under the historical scenario, the northwest area experienced a notable increase in both the temperature and precipitation. The temperature and precipitation have been rising at a rate of 0.15-0.74 ℃ and 2.71-14.83 mm per decade, respectively, and the same is expected for future scenarios. (2) From 1975 to 2014, the annual and seasonal SPEI in Northwest China decreased overall. The maximum decline rate in spring was 0.19 per decade. Droughts in most areas were increasingly intense throughout the year, particularly in spring and winter. In terms of drought frequency in Northwest China, mild and moderate droughts appeared more than severe and extreme droughts, and this type of natural disaster was more frequent in the east of the country than in the west. (3) From 2020 to 2100, Northwest China is likely to suffer from droughts, but there are no distinct drought characteristics identified in the research under the SSP1-2.6 scenario. The northwest region is expected to experience an increase in the number of droughts, trends in drought, and drought frequency under the other three scenarios. The most severe drought conditions were observed under the SSP5-8.5 scenario. This study provides insights into the spatial and temporal development of drought in Northwest China using meteorological and model data. The findings can serve as a basis for drought risk assessment, scientific water resources management, and agricultural production in the region.

Studying the degree and mechanism of landscape pattern’s influence on inland river water quality is of great significance for the water environment protection of inland river basins in arid areas. This study was based on the Liyuan River in Linze County. We studied landscape pattern data and measured water quality, using redundancy and correlation analyses to investigate the relationship between landscape patterns and water quality in different buffer zones. The water bodies in the study area generally met the Class II water quality standard, except for the average value of the chemical oxygen demand (COD_Cr) concentration, which fell into Class III. Additionally, the average dissolved oxygen (DO), total phosphorus (TP), permanganate index (COD_Mn), and ammonia nitrogen (NH₃-N) concentration values met the Class II water quality standard. The buffer zone’s landscape composition was dominated by arable land, and construction land was the second largest type. Analyzing the landscape index revealed that the strength of human activities was not evenly distributed in the buffer zone, and the degree of human interference was the greatest in the 100 m buffer zone. The human interference degree in the 100 m buffer zone was the greatest. The proportion of cultivated land was significantly and positively correlated with DO, TP, electrical conductivity (EC), dissolved solids (TDS), and salinity, while constructed land was significantly and positively correlated with TP and NH₃-N. The largest patch index (LPI) and contagion index (CONTAG) were positively correlated with the water quality indicators, whereas patch density (PD), edge density (ED), landscape shape index (LSI), and Shannon’s diversity index (SHDI) were negatively correlated. Redundancy analysis indicated that the explanatory rate of the changes in the water quality indicators by the composition of the landscape and landscape indices was the highest in the 300 m buffer zone. The analysis indicated that the explanatory rate of landscape composition and index on water quality index changes were the highest in the 300 m buffer zone, and the 300 m buffer zone was determined to be the optimal buffer scale for landscape pattern’s influence on the water quality index. Therefore, optimizing the landscape structure within the 300 m buffer zone to enhance the retention and adsorption capacity of pollutants can improve the water quality of the Liyuan River.

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.

Nuomuhong region is an important Wolfberry cultivation base in Qinghai Province, China. Accurate and rapid extraction of the primary vegetation types is of critical significance for the sustainable development of agriculture in this region. However, the arid nature of the Nuomuhong area, characterized by sparse vegetation cover and significant soil background effects, presents challenges for vegetation extraction using only a limited number of remote sensing sources or partial features. Therefore, integrating multiple remote sensing data sources, exploring significant features for vegetation classification, and experimenting with different classification and optimization methods are paramount for enhancing the accuracy and reliability of vegetation classification in arid regions. Based on the Google Earth Engine (GEE) platform, this study used Sentinel-1 Synthetic Aperture Radar and Sentinel-2 optical data to explore the importance of red edge, texture, and radar features in extracting vegetation types in arid regions. Additionally, it verifies the feasibility of using the GINI index (GINI) to determine the optimal feature combination. The main geospatial types in Nomu Hong, Qinghai, China, in 2021 were extracted by combining them with the support vector machine algorithm. The classification results were processed using decision fusion methods. The results showed that: (1) Sentinel-2 red edge index, texture data, and Sentinel-1 radar band were beneficial for the extraction of vegetation-related information, with an overall classification accuracy and Kappa coefficient of 95.51% and 0.9406, respectively. (2) Based on the importance obtained by the GINI index, the features involved in the classification were reduced from 29 to 17, and the significance was radar polarization features > spectral features > texture features. (3) Using a simple noniterative clustering algorithm and neighborhood filtering voting decision fusion method not only achieved the optimal overall accuracy and Kappa coefficient but also had an excellent suppression effect on isolated noise. Using the GEE remote sensing cloud platform, multisource remote sensing data, and machine learning algorithms, this study can accurately, quickly, and efficiently extract large-scale arid region geospatial information, which can have great application potential.

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.

This study used the Lhasa River Basin, which is a typical plateau basin to clarify the spatiotemporal characteristics of land use change and its impact on a plateau basin habitat quality. The google earth engine (GEE) platform and random forest classification algorithm were used to interpret the land use information of the Lhasa River Basin from 1990 to 2020, and to analyze the spatiotemporal dynamic changes of land use in the past 30 years. The InVEST model was integrated to evaluate the habitat quality of the basin, and to explore the characteristics of its habitat quality changes. The results showed that the efficiency and accuracy of land use classification improved by selecting the vegetation growing season, supplementing and replacing missing data with images obtained in the previous and following years, and generating annual composite cloud free images for land use classification in the alpine and high-altitude areas. An optimal RF classification model combining the spectral, textural, and topographical features of Landsat images was established to classify land use information in the plateau basin. The observed OA, Kappa coefficient, and the F1-score were 88.16%, 0.84, and 0.70, respectively. Since the 1990, the features of the land use change in the Lhasa River Basin have been characterized by “five increases and three decreases,” with an increase being observed in the areas under grassland, construction, forest land, wetland, and water, while the areas under cultivated land, glaciers, and permanent snow or unused land having a decrease. Among them, the growth rate of construction land had the largest increase of 288.35%, while the largest decrease was detected in cultivated land with 50.18%, which could mainly be attributed to overpopulation in the urban areas. Most significant decrease occurred in the unused land area, and the changed area was mainly converted with grassland. During the study period, high quality habitats were mainly distributed in the downstream areas, southwest, and the main source areas of the basin, included the grassland, water, glaciers, permanent snow, and wetland. Poor qualities of habitats were observed in the Lhasa municipal district, Dazi District, Linzhou County, Qushui County, and Mozhugongka County, as well as in the unutilized land in the middle and upper reaches of the basin. The overall habitat quality of the watershed showed an alternating transition pattern of initial decrease, then increase, followed by a decrease, and a slowed down transition, while the habitat quality index increased from 0.53 to 0.57. Population growth and rapid urbanization accelerated the expansion of urban areas and the reduction of arable land, while climate change and ecological engineering played a positive role in improving the quality of habitat in Lhasa River Basin. This study provides a scientific basis and reference for formulating ecological restoration strategies, sustainable land use, and habitat quality improvement in a plateau area.

In the semi-arid zone of the Liupan Mountains in Ningxia, soil water content is a key factor affecting the survival and growth of trees, and it is necessary to understand the differences in soil water content on different slope positions of forested slopes and their response to different rainfall amounts. For this purpose, a typical slope covered by Larix principis-rupprechtii plantations was selected in the small watershed of Diediegou in the Liupanshan Mountains. From May to October 2021, meteorological conditions (such as precipitation) and changes in soil water content on this slope were continuously monitored with automatic weather stations and soil moisture meters to analyze the differences in soil water content on the slopes and their response to the depth of individual rainfall events. The total precipitation depth during the monitoring period was 443.7 mm, which was close to the long-term annual average, but with severe drought in summer. The results showed the following: (1) The soil water content varied significantly within the growing season; the overall level first decreased and then increased, being the lowest in August (0.112 m³·m^-3). (2) There were clear differences in soil water content among slope positions, generally in the order upper slope [(0.191 ± 0.044) m³·m^-3] > middle slope [(0.158 ± 0.045) m³·m^-3] > lower slope [(0.146 ± 0.034) m³·m^-3]. This indicated that the main factor influencing the differences in soil water content along slope positions is the amount of evapotranspiration by forest/vegetation, rather than the redistribution of rainwater along the slope by slope runoff in this dry year. (3) To the same rainfall depth, the response of soil water content on the middle slope was the most sensitive, followed by that on the upper slope, and the lower slope was the least sensitive, owing to the integrated effects of soil porosity, water-holding capacity, and understory vegetation. (4) At the study site, rainfall was dominated by small rainfall events below 10 mm, with 7 mm representing the threshold for effective rainfall, above which the rainfall is likely to alleviate the soil dryness and recharge the soil moisture in the soil layer of 0-20 cm. The results of this study can aid understanding of the variation and spatial distribution of soil water content on forest slopes in semi-arid mountainous areas and help determine the water-carrying capacity of forest/vegetation and integrated

This study aimed to spatially and temporally characterize not only land surface temperature (LST) in the complex mountainous terrain of Daqingshan, Inner Mongolia but also the environmental factors affecting it. We used the Weather Research and Forecasting Mode (WRF) used to obtain LST data with high temporal and spatial resolution and analyze the variation of mountain influencing factors. The accuracy of the WRF simulated LST (WRF LST) was verified by the observation values of meteorological stations and MODIS LST values, and the relationship between LST and environmental factors was analyzed by the method of comprehensive impact factor analysis and the method of single impact factor analysis. The comprehensive impact factor analysis is based on regional WRF LST and regional environmental factors. Single impact factor analysis achieves the relationship between WRF LST and single environmental factors by fixing other environmental factors. The results revealed that the correlation coefficients between the simulated and observed values were >0.97 (P<0.001) and the spatial correlation with MODIS LST was 0.73 (P<0.05), indicating that WRF has good practicability in mountainous areas. After comprehensive impact factor analysis, it was found the annual WRF LST had the greatest correlation with elevation (R>0.97), followed by temperature at 2 m and water/air mixing ratio at 2 m (R>0.8), vegetation coverage and slope (R>0.3), and other factors. By single impact factor analysis, LST decrease rate with elevation was 0.83 K·(100m)^-1, 0.79 K·(100m)^-1, 0.80 K·(100m)^-1 and 0.32 K·(100m)^-1 in spring, summer, autumn and winter, and it increased by -0.05 K, 0.17 K, -0.14 K, and 0.02 K for every 10° increase in slope in spring, summer fall winter, respectively. LST also increased for every 10% increase in vegetation cover by 0.31 K, 1.41 K in summer and winter, and was not correlated with fall. The slope direction and average LST for the four seasons were south>southwest>southeast>west>east>northwest>northeast>north. The 2 m water-air mixing ratio increased logarithmically with LST, while the 2 m air temperature increased exponentially with LST. This study demonstrated that the WRF model can be used to simulate the spatial and temporal distribution of LST in mountainous terrain and analyze the LST relationship in complex mountain environments.

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 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.

Water use efficiency (WUE) is an important measure of the tradeoff between photosynthetic carbon sequestration and water consumption in ecosystems. Estimation of vegetation’ WUE and analysis of the spatiotemporal distribution of vegetation WUE are crucial for ecosystem preservation as well as the wise use and development of water resources in this area. In this study, we assessed the spatial and temporal characteristics of vegetation WUE and its main influencing factors in Salt Lake County from 2000 to 2019 on the basis of GPP and ET data from MODIS. The results were as follows: (1) Both ET and GPP increased significantly from 2000 to 2019 (P<0.01), and the rates of increase were 7.61 mm·a^-1 and 7.23 g C·m^-2·a^-1, respectively. ET and GPP showed obvious heterogeneity in space. (2) Between 2000 and 2019, the vegetation WUE in Yanchi County fluctuated between 0.80 and 1.11 g C·kg^-1·H₂O, and the multiyear average value was 0.91 g C·kg^-1·H₂O. The rate of increase was 0.0013 g C·kg^-1·H₂O·a^-1, but it was not significant. The vegetation WUE showed high heterogeneity in space, with high values mainly distributed in the northeast and low values in the southwest. (3) From 2000 to 2019, WUE mainly increased and decreased in 54.70% and in 45.30% of the area, respectively, in Yanchi County. In the future, 61.48% of the area in Yanchi County will show the same change trends in WUE as in the past, and 38.52% of the area will show reversed trends in WUE. (4) The WUE of each land use type in different study periods decreased in the following order: forest land > cultivated land > grassland. (5) There was a significant correlation between WUE and GPP in Yanchi County (P<0.05), whereas variations in GPP were mainly driven by changes in ET, NDVI, and precipitation, indicating that GPP is the main reason for the changes in WUE in Yanchi County. The Yanchi County Ecological Restoration Project not only enhances vegetation productivity but also increases regional water consumption, resulting in fluctuations in the WUE of the regional ecosystem. This suggests that vegetation restoration in Yanchi County has intensified regional water depletion while enhancing vegetation productivity, which provides a theoretical basis for future ecological revegetation and codevelopment of water resources in Yanchi County.

Further exploration of trends in climate warming and humidification in Northwest China can deepen our understanding of important scientific issues regarding the responses to global warming of arid and semi-arid regions of the Northern Hemisphere in mid-and high latitudes. Using statistical methods such as linear trend, Kriging interpolation, and non-parametric Mann-Kendall test for temperature and precipitation data from 127 stations in Northwest China from 1961 to 2021, we show the following: (1) In the last 60 years, Northwest China as a whole has undergone significant warming and humidification. The regional warming trend was relatively consistent [0.32 ℃·(10a)^-1], while there was a clear regional imbalance of humidification, with the humidification in the west of Northwest China increasing earlier, more steadily, and more significantly than in the east. (Increases in the west were mainly distributed in Northwest Xinjiang, while those in the east were mainly in the Qinghai region). (2) There were pronounced interdecadal fluctuations of warming and humidification, and paradigm shifts in temperature and precipitation trends of Northwest China occurred in 1993 and 2010, respectively, after which the rates of warming and humidification were 0.08 ℃·(10a)^-1 and 37.60 mm·(10a)^-1 higher than beforehand. Warming and humidification were more prominent after these paradigm shifts, with the eastward expansion of warming and humidification being the main feature. (3) The seasonal imbalance of warming and humidification also showed that the warming was most significant in winter in western Northwest China, followed by that in summer; winter precipitation increased significantly in western Northwest China, while spring and summer precipitation increased significantly in eastern Northwest China. These results can provide a theoretical basis for formulating climate change countermeasures in Northwest China.

Castor fiber birulai is primarily distributed in the Ulungu river basin in China. Therefore, investigating the potential distribution of suitable regions is crucial for the conservation of C. f. birulai. A total of 97 distribution sites of C. f. birulai and 28 environmental factors collected from 2021 to 2022 were used to predict the distribution of suitable habitat regions for this species under different climatic scenarios using the MaxEnt model. Results showed that the distribution of suitable habitats was mainly affected by the distance from major roads (0.1-1 km), distance from water channel (within 100 m), landcover type (river, wetland, and forest), altitude (approximately 1000 m), mean temperature of wettest quarter(22-25 mm), and the standard deviation factor of seasonal temperature change (above 1500). In the 2050s (2041-2060, ssp585 climate scenario) and 2070s (2061-2080, ssp126 climate scenario), the high suitability area was the same or slightly increased compared with the current situation, and the area of suitable habitat, which decreased in the two future climate scenarios, was the same. The results of this study can provide a reference point for the protection and management of C. f. birulai under climate changes.

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 study of vegetation dynamics and its influencing factors can reveal the response mechanism between vegetation cover dynamics and climate change and has important significance for regional vegetation restoration and ecological sustainability. Based on MODIS multitemporal remote sensing satellite data, this study investigated the quarterly changes in vegetation cover in the arid and semi-arid regions of Northwest China from 2000-2020 using variation coefficient, Theil-Sen median trend analysis, Mann-Kendall significance test, correlation analysis, and Hurst index. The study found that: (1) The spatial variability of the Normalized Difference Vegetation Index (NDVI) was high in winters, and the high fluctuation areas were mainly in the grasslands and unused land areas in the Daxinganling region of Xinjiang and Inner Mongolia. (2) NDVI fluctuates more with the seasons and is most obvious in forests and cultivated areas. (3) NDVI is mainly improving, with the largest improvement in springs (84.63%), the smallest in winters (72.52%), and the most significant improvement in the woodland areas. (4) Surface temperature and precipitation influenced NDVI in all seasons (Significance = 0.05), with precipitation changes significantly affecting NDVI trends in summers and weakly during winters and surface temperature changes significantly affecting NDVI trends in springs and weakly in autumns. (5) The future NDVI also mainly shows an improving trend, with an area of 70.89%; notably, the degraded areas are sporadically distributed in the Tarim and Junggar Basins of Xinjiang. This study’s results provide theoretical references for ecological restoration and management in the arid and semi-arid regions of Northwest China and the response to local climate warming and humidification.

This study aims to provide reference for quantifying the selection model of plant water sources. MixSIAR model and IsoSource model are commonly used to quantify plant water sources by combining hydrogen and oxygen stable isotope technology. However, different models yield varying quantitative results. Hence, choosing the best model is important to reduce the uncertainty of results. In this work, the hydrogen and oxygen stable isotope compositions of stem xylem water and each potential water source of two shrubs were measured from July to September in 2019 and 2021. The dominant tree species Cotoneaster melanocarpus and Berberis heteropoda in the premontane shrub zone of the northern slope of Tianshan Mountain were selected as subjects. MixSIAR and IsoSource models were used to quantify plant water sources, and their results were compared and evaluated according to the root mean square error (RMSE) and parameter R. Results showed (1) differences in the quantification results of the two models for the main potential water sources of plants. These differences were related to the calculation principles of the two models. (2) Under the premise that the two models quantify the same main potential water sources of plants, the IsoSource model quantifies larger values than the MixSIAR model. (3) The results of RMSE and parameter R showed that the error of IsoSource model in quantifying plant water sources was smaller than that of MixSIAR model possibly due to the large difference between C. melanocarpus and B. heteropoda In summary, the MixSIAR model may be more accurate in quantifying the similarity of plant water sources than the IsoSource model.

To address the imbalance between the supply and demand of water resources and compensate for the shortage of freshwater resources, the use of brackish and saline water for irrigation has become crucial. Simultaneously, the effects of different sodium adsorption ratios (SAR) on cotton growth and yield can vary under the same degree of mineralization in irrigation water. Therefore, to further explore the effects of irrigation water mineralization and SAR on cotton, we established three mineralization treatments at 3 g·L^-1(T3), 5 g·L^-1(T5), and 7 g·L^-1(T7). Additionally, we designed three SAR treatments at 10 (mmol·L)^1/2(S10), 15 (mmol·L)^1/2(S15), and 20 (mmol·L)^1/2(S20). Local freshwater irrigation served as a control (CK). In total, 10 treatments were conducted in this experiment to examine the combined effects of irrigation water mineralization and SAR costress on soil salinity, cotton growth, plant ion accumulation, yield, and water use efficiency. The results indicated that soil salinity increased with higher irrigation water mineralization or SAR, initially rising before decreasing with increasing soil depth. Plant Na⁺ content increased with increasing irrigation water mineralization or SAR, with the interaction effect between these factors being highly significant. Conversely, plant K⁺, K⁺/Na⁺, and N content decreased as irrigation water mineralization or SAR increased. Additionally, plant height, stem thickness, leaf area index, and dry matter mass all showed a significant decreasing trend with increased irrigation water mineralization and SAR, with significant inhibition of dry matter accumulation observed. Irrigation water mineralization and SAR significantly affected the number of bolls per plant, boll weight, seed cotton yield, and water consumption (ET). Moreover, irrigation water SAR significantly affected water use efficiency (WUE). Compared to the CK treatment, yield and WUE increased by 3.27% and 1.09% in T3S10, 2.54% and 0.47% in T5S10, and 1.18% in T3S15, respectively. This increase indicated that moderately reducing the irrigation water SAR can help mitigate yield reduction in cotton due to increased mineralization. Different levels of mineralization and SAR in irrigation water increased the Na⁺ content in cotton plants while reduced K⁺ and N nutrient uptake, and increased the K⁺/Na⁺ ratio. Consequently, cotton plant height, stem thickness, leaf area, and dry matter accumulation gradually decreased as irrigation water mineralization or SAR increased. The number of bolls per plant and boll weight increased in the T3S10, T3S15, and T5S10 treatments compared to the CK treatment. In conclusion, using brackish water with an irrigation water mineralization of 3 g·L^-1 and SAR below 15 (mmol·L^-1)^1/2, or an irrigation water mineralization of 5 g·L^-1 with SAR below 10 (mmol·L^-1)^1/2, can ensure cotton yield. These findings provide a theoretical basis and reference for the efficient use of brackish water in Xinjiang and other extreme arid regions.

The linear tendency, cumulative anomaly, and Mann-Kendall test were used to analyze the temporal and spatial variation of temperature in Dunhuang, Guazhou, and Yumen stations in the Shule River Basin from 1951 to 2020. The results revealed that (1) all stations experienced a significant upward trend in average temperature, with tendency rates of 0.244 °C·(10a)^-1 (P<0.05) for Dunhuang station, 0.209 °C·(10a)^-1 (P<0.05) for Guazhou station, and 0.195 °C·(10a)^-1 (P<0.05) for Yumen station. (2) Dunhuang and Yumen stations exhibited a significant upward trend in average temperature across all seasons, except for a nonsignificant upward trend in summer. (3) the mutation years for average temperature at Dunhuang, Guazhou, and Yumen stations were 1998, 1997, and 1995, respectively, with the first main cycles being 58 a, 30 a, and 13 a, respectively. (4) and annual and seasonal average temperatures gradually increased from east to west in the Shule River Basin, with decreasing nonuniformity coefficients and concentration degrees also observed.

Malus sieversii, a state-protected species and the progenitor of cultivated apples, is an important germplasm resource within the genus Malus. In this study, we aimed to compare the structural characteristics of chloroplast genomes across various populations of M. sieversii, clarify the lineage divergence pattern, and trace the evolutionary history of this species. We used the Illumina NovaSeq platform to conduct whole-genome sequencing of individuals from 16 different populations, with one sample representing each population. After conducting quality control on the sequencing data, we conducted genome assembly and functional annotation. Subsequently, we conducted a comprehensive structural analysis and lineage differentiation studies on the assembled genomes. The chloroplast genome length in M. sieversii ranged from 160195 to 160279 base pairs (bp), exhibiting a typical tetrad structure. In total, 131 genes were identified within the chloroplast genome, along with 48-58 long repeats and 93-101 simple sequence repeats. Notably, variations in the IR region between M. sieversii and other species in the genus were minimal, predominantly occurring in noncoding regions. Phylogenetic analysis revealed that M. sieversii clusters into three distinct lineages: lineage I, primarily occupying the eastern part of the distribution range, and lineages II and III, predominantly found in the west. The divergence time between lineages I and II was approximately 1.74 million years ago (Ma), while the divergence between lineages I, II, and III was around 2.28 Ma. These findings indicate that the lineage divergences of M. sieversii were significantly influenced by climate changes during the Quaternary period. Compared to internationally distributed populations, M. sieversii in China shows relatively low genetic diversity. Therefore, tailored conservation strategies should be implemented for M. sieversii across different regions, with particular emphasis on protecting genetically diverse populations in the Tacheng area.

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.

Natural precipitation is an important source of water for vegetation in arid areas. To explore the coping methods of desert shrubs under different precipitation conditions, this study selected typical desert shrubs as subject and determined their leaf morphological traits and stoichiomental characteristics under different precipitation condition. The overall characteristics of leaf functional traits and the relationship between individual functional properties and environmental factors were also analyzed. Results showed that (1) with the decrease in natural precipitation, the degree of fleshiness and water content of leaves of Reaumuria soongorica increased gradually and the tissue density of Kalidium foliatum increased. (2) Meanwhile, the C contents in the leaves of R. soongorica and Nitraria tangutorum and the N contents in the leaves of N. tangutorum and Salsola passerina showed an overall increasing trend with the increase in drought stress. In addition, the leaf N:P ratios of S. passerina and K. foliatum were all less than 14, indicating that the growth and development of these species were mainly restricted by nitrogen. (3) The leaf tissue density of R. soongorica, N. tangutorum, and K. foliatum was positively correlated with the average annual precipitation. The specific leaf area of R. soongorica and N. tangutorum and the P content of R soongorica, N. tangutorum, and S. passerina were negatively correlated with altitude. In arid environments, different plants exhibit different ecological adaptation strategies. To adapt to the desert environment of drought and less rainfall, K. foliatum reduces its specific leaf area and increases its tissue density, N. tangutorum increases the N content of its leaves, and R. soongorica increases the degree of fleshiness and water content of its leaves. Average annual precipitation and altitude are the main limiting factors affecting their growth and development.

Based on the data on forest and grass vegetation coverage from 2000 to 2019, the spatiotemporal change of forest and grass vegetation in Hetao Irrigation District over 20 years was analyzed, and the influence of various factors driving forest and grass vegetation coverage was quantitatively analyzed using a geographical detector. The results showed the following: (1) The area of forest and grassland in Hetao Irrigation District showed a decreasing trend in the studied 20 years, with a decrease of 966.15 km². The vegetation coverage level of forest and grassland showed an overall upward trend. The average annual vegetation coverage of forest and grassland was 28.3%. On the spatial scale, the vegetation coverage of forest and grassland in Hetao Irrigation District showed a spatial variation characteristic of decreasing from northeast to southwest. (2) In the studied 20 years, the centers of gravity of low forest and grass vegetation coverage and medium forest and grass vegetation coverage have mainly been located in the northeast of Yongji irrigation area and the southwest of Yichang irrigation area, respectively. The centers of gravity of forest and grass vegetation coverage at all levels show a decreasing trend from northeast to southwest, and all show a trend of migration to the southwest. The migration distance in each period was between 0.71 and 15.46 km. (3) Distance from water, groundwater depth, temperature, and precipitation are the dominant environmental factors affecting the forest and grass vegetation coverage in the region, with explanatory power of 0.427, 0.439, 0.318, and 0.368, respectively. The interaction between distance from water, groundwater depth, annual average precipitation, and other factors is generally higher, and the regional water content is the main driving force affecting the growth of forest and grassland in Hetao Irrigation District.

Soil nutrient levels and microbial community structures are critical indicators for evaluating the ecosystem services of artificial forests. In arid and semi-arid regions, which are the major distribution areas for artificial forests, the regulatory effects of stand density on soil nutrients and microbial communities remain poorly understood. This study analyzed a 30-year-old Robinia pseudoacacia plantation on the Loess Plateau’s eastern edge. Based on Reineke’s stand density effect law and regional management standards, the stands were categorized into low (950-1350 trees·hm^-2), medium (1600-2050 trees·hm^-2), and high (2400-3300 trees·hm^-2) density groups. Data were collected through field surveys, soil nutrient analyses, and high-throughput sequencing of 16S rRNA and ITS. These methods systematically assessed the soil nutrient characteristics and microbial community structures and diversity across different stand densities. The study’s findings indicate that as the stand density increases, the soil total nitrogen, nitrate nitrogen, total carbon, and organic carbon contents significantly increase, especially in the high-density group (P<0.05). Conversely, the available phosphorus content peaks in the medium-density group. The bacterial community was primarily composed of Proteobacteria (38.70%), Actinobacteria (19.37%), Gemmatimonadetes (8.23%), and Chloroflexi (7.71%), with Actinobacteria’s relative abundance significantly increasing alongside the stand density (P<0.05). In the fungal community, Ascomycota (51.79%), Mortierellomycota (30.70%), and Basidiomycota (10.07%) were the dominant phyla. In the high-density group, bacterial and fungal community diversity was significantly enhanced, as evidenced by notable increases in the Shannon and Chao1 indices (P<0.05). Principal Coordinates Analysis revealed that the bacterial community structures in the medium- and low-density groups exhibited significant clustering, distinctly differing from those in the high-density group (P<0.05). In contrast, the fungal community structures remained relatively stable across different stand densities. The Mantel test revealed that bacterial and fungal community structures were significantly associated with TN (P<0.05). Cooccurrence network analysis indicated that moderate stand density increases microbial interaction strength and network complexity. However, when the stand density exceeded 2400 trees·hm^-2, the network stability decreased, potentially hindering efficient resource utilization. Maintaining a stand density of 1600-2050 trees·hm^-2 improves soil nutrient levels and enhances microbial community diversity and stability, providing a scientific basis for the sustainable management of R. pseudoacacia plantations on the Loess Plateau.