Characterization of the spatial and temporal variability of stable isotopes in surface water is essential for interpreting hydrological processes. In this study, we collected the water samples of river water, groundwater, and reservoir water in the Burqin River Basin of the Altay Mountains, China in 2021, and characterized the oxygen and hydrogen isotope variations in different water bodies via instrumental analytics and modeling. Results showed significant seasonal variations in stable isotope ratios of oxygen and hydrogen (δ¹⁸O and δ²H, respectively) and significant differences in δ¹⁸O and δ²H among different water bodies. Higher δ¹⁸O and δ²H values were mainly found in river water, while groundwater and reservoir water had lower isotope ratios. River water and groundwater showed different δ¹⁸O-δ²H relationships with the local meteoric water line, implying that river water and groundwater are controlled by evaporative enrichment and multi-source recharge processes. The evaporative enrichment experienced by reservoir water was less significant and largely influenced by topography, recharge sources, local moisture cycling, and anthropogenic factors. Higher deuterium excess (d-excess) value of 14.34‰ for river water probably represented the isotopic signature of combined contributions from direct precipitation, snow and glacial meltwater, and groundwater recharge. The average annual d-excess values of groundwater (10.60‰) and reservoir water (11.49‰) were similar to the value of global precipitation (10.00‰). The findings contribute to understanding the hydroclimatic information reflected in the month-by-month variations in stable isotopes in different water bodies and provide a reference for the study of hydrological processes and climate change in the Altay Mountains, China.

In the context of changes in global climate and land uses, biodiversity patterns and plant species distributions have been significantly affected. Soil salinization is a growing problem, particularly in the arid areas of Northwest China. Halophytes are ideal for restoring soil salinization because of their adaptability to salt stress. In this study, we collected the current and future bioclimatic data released by the WorldClim database, along with soil data from the Harmonized World Soil Database (v1.2) and A Big Earth Data Platform for Three Poles. Using the maximum entropy (MaxEnt) model, the potential suitable habitats of six halophytic plant species (Halostachys caspica (Bieb.) C. A. Mey., Halogeton glomeratus (Bieb.) C. A. Mey., Kalidium foliatum (Pall.) Moq., Halocnemum strobilaceum (Pall.) Bieb., Salicornia europaea L., and Suaeda salsa (L.) Pall.) were assessed under the current climate conditions (average for 1970-2000) and future (2050s, 2070s, and 2090s) climate scenarios (SSP245 and SSP585, where SSP is the Shared Socio-economic Pathway). The results revealed that all six halophytic plant species exhibited the area under the receiver operating characteristic curve values higher than 0.80 based on the MaxEnt model, indicating the excellent performance of the MaxEnt model. The suitability of the six halophytic plant species significantly varied across regions in the arid areas of Northwest China. Under different future climate change scenarios, the suitable habitat areas for the six halophytic plant species are expected to increase or decrease to varying degrees. As global warming progresses, the suitable habitat areas of K. foliatum, S. salsa, and H. strobilaceum exhibited an increasing trend. In contrast, the suitable habitat areas of H. glomeratus, S. europaea, and H. caspica showed an opposite trend. Furthermore, considering the ongoing global warming trend, the centroids of the suitable habitat areas for various halophytic plant species would migrate to different degrees, and four halophytic plant species, namely, S. salsa, H. strobilaceum, H. glomeratus, and H. capsica, would migrate to higher latitudes. Temperature, precipitation, and soil factors affected the possible distribution ranges of these six halophytic plant species. Among them, precipitation seasonality (coefficient of variation), precipitation of the warmest quarter, mean temperature of the warmest quarter, and exchangeable Na⁺ significantly affected the distribution of halophytic plant species. Our findings are critical to comprehending and predicting the impact of climate change on ecosystems. The findings of this study hold significant theoretical and practical implications for the management of soil salinization and for the utilization, protection, and management of halophytes in the arid areas of Northwest China.

Savanna, semi-deserts, and hot deserts characterize the Saharo-Arabian region, which includes Morocco, Mauretania, Algeria, Tunisia, Libya, Egypt, Palestine, Kuwait, Saudi Arabia, Qatar, Bahrain, the United Arab Emirates, Oman, Yemen, southern Jordan, Syria, Iraq, Iran, Afghanistan, Pakistan, and northern India. Its neighboring regions, the Sudano-Zambezian region belonging to the Paleotropical Kingdom and the Mediterranean and Irano-Turanian regions included in the Holarctic Kingdom, share a large portion of their flora with the Saharo-Arabian region. Despite the widespread acknowledgment of the region's global importance for plant diversity, an up to date list of the Saharo-Arabian endemics is still unavailable. The available data are frequently insufficient or out of date at both the whole global and the national scales. Therefore, the present study aims at screening and verifying the Saharo-Arabian endemic plants and determining the phytogeographical distribution of these taxa in the Egyptian flora. Hence, a preliminary list of 429 Saharo-Arabian endemic plants in Egypt was compiled from the available literature. Indeed, by excluding the species that were recorded in any countries or regions outside the Saharo-Arabian region based on different literature, database reviews, and websites, the present study has reduced this number to 126 taxa belonging to 87 genera and 37 families. Regarding the national geographic distribution, South Sinai is the richest region with 83 endemic species compared with other eight phytogeographic regions in Egypt, followed by the Isthmic Desert (the middle of Sinai Peninsula, 53 taxa). Sahara regional subzone (SS1) distributes all the 126 endemic species, Arabian regional subzone (SS2) owns 79 taxa, and Nubo-Sindian subzone (SS3) distributes only 14 endemics. Seven groups were recognized at the fourth level of classification as a result of the application of the two-way indicator species analysis (TWINSPAN) to the Saharo-Arabian endemic species in Egypt, i.e., I Asphodelus refractus group, II Agathophora alopecuroides var. papillosa group, III Anvillea garcinii group, IV Reseda muricata group, V Agathophora alopecuroides var. alopecuroides group, VI Scrophularia deserti group, and VII Astragalus schimperi group. It's crucial to clearly define the Saharo-Arabian endemics and illustrate an updated verified database of these taxa for a given territory for providing future management plans that support the conservation and sustainable use of these valuable species under current thought-provoking devastating impacts of rapid anthropogenic and climate change in this region.

Extreme temperature events have intensified across Jordan over the past 40 a, increasing risks to agriculture, water availability, urban infrastructure, and public health. The purpose of this study is to assess the long-term spatial trends and regime shifts in extreme temperature indicators across Jordan's climate zones to explore climate adaptation strategies. This study presents a high-resolution and spatially explicit assessment of thermal extremes using daily data from 1982 to 2024 across 45 grid-based study points in Jordan. Thirteen temperature indices, including percentile-based thresholds, duration metrics, and absolute extremes, were computed using RClimDex and analyzed across four Köppen climate zones: hot desert (BWh), hot semi-arid (BSh), cold desert (BWk), and Mediterranean (Csa) climates. The analysis confirmed a statistically significant warming trend: annual mean maximum temperatures increased by 2.198°C, while annual mean minimum temperatures rose by 2.035°C. Cold extremes have sharply declined, with cold days (TX10p) decreasing by 70.0%-80.0%, and the cold spell duration indicator (CSDI) dropping from 12.6 to 4.0 d/a, particularly in the BWk zone. Heat indices intensified across all zones, with warm days (TX90p) increasing by over 300.0% in BWh, warm nights (TN90p) rising by 38.1%, and the warm spell duration indicator (WSDI) extending fourfold, indicating prolonged exposure to heatwaves. Mean value of maximum temperature (TXx) reached 45.600°C in most arid areas, while minimum temperature (TNx) exceeded 31.600°C, highlighting increased nocturnal heat stress. Change-point analysis indicated that 1998 was a pivotal year, marking a structural transition in both cold and warm temperature indices. Subsequent intensifications after 2010 in TN90p, TNx, and mean of daily maximum temperature (T_maxmean) reflected an ongoing trend toward sustained thermal extremes. In addition to time-series trends, the study employed network-based correlation analysis to explore the coherence among climate indices. Strong positive correlations were observed among TXx, TX90p, and mean of daily minimum temperature (T_minmean) (r≥0.94), as well as among TN90p, T_minmean, and TNx (r≥0.87), indicating a tightly clustered heat subsystem. Duration metrics like the WSDI showed a close alignment with percentile extremes (between WSDI and TX90p; r=0.88), suggesting integrated heatwave behavior. In contrast, cold indices (TX10p, TN90p, frost days, and CSDI) exhibited weak or negative correlations and displayed peripheral positioning in the climate network, indicating their limited role under a warming regime. Absolute extremes showed weak internal linkages, suggesting episodic rather than systemic response characteristics. This structural realignment indicated a shift from a previously balanced thermal profile to a heat-dominated climate system. Regional variations revealed that BWh and BSh were experiencing the steepest warming, while Csa was transitioning more slowly but was showing signs of reduced winter cooling and increased irrigation demands. The findings establish a robust climate baseline for Jordan and offer actionable insights for climate adaptation planning. Recommended measures include precision irrigation, the development of heat-resilient crops, improvements to urban cooling infrastructure, and early warning systems for thermal extremes. By integrating spatial climate zoning, regime shift analysis, and inter-index correlation structures, this study provides a replicable framework for monitoring climatic transformations and informing resilience strategies in arid and semi-arid areas.

Since the 1950s, numerous soil and water conservation measures have been implemented to control severe soil erosion in the Liuhe River Basin (LRB), China. While these measures have protected the upstream soil and water ecological environment, they have led to a sharp reduction in the downstream flow and the deterioration of the river ecological environment. Therefore, it is important to evaluate the impact of soil and water conservation measures on hydrological processes to assess long-term runoff changes. Using the Soil and Water Assessment Tool (SWAT) models and sensitivity analyses based on the Budyko hypothesis, this study quantitatively evaluated the effects of climate change, direct water withdrawal, and soil and water conservation measures on runoff in the LRB during different periods, including different responses to runoff discharge, hydrological regime, and flood processes. The runoff series were divided into a baseline period (1956-1969) and two altered periods, i.e., period 1 (1970-1999) and period 2 (2000-2020). Human activities were the main cause of the decrease in runoff during the altered periods, contributing 86.03% (-29.61 mm), while the contribution of climate change was only 13.70% (-4.70 mm). The impact of climate change manifests as a decrease in flood volume caused by a reduction in precipitation during the flood season. Analysis of two flood cases indicated a 66.00%-84.00% reduction in basin runoff capacity due to soil and water conservation measures in the upstream area. Soil and water conservation measures reduced the peak flow and total flood volume in the upstream runoff area by 77.98% and 55.16%, respectively, even with nearly double the precipitation. The runoff coefficient in the reservoir area without soil and water conservation measures was 4.0 times that in the conservation area. These results contribute to the re-evaluation of soil and water conservation hydrological effects and provide important guidance for water resource planning and water conservation policy formulation in the LRB.

Desertification is a global crucial ecological and environmental issue, and China is among the countries most seriously affected by desertification. In recent decades, numerous independent studies on desertification dynamics have been carried out using remote sensing technology, but there has been a lack of systematic research on desertification trends in China. This study employed the meta-analysis to integrate the findings of 140 published research cases and examined the dynamics of desertification in the eight major deserts, four major sandy lands, and their surrounding areas in China from 1970 to 2019, with a comparative analysis of differences between the eastern (including the Mu Us Sandy Land, the Otindag Sandy Land, the Hulunbuir Sandy Land, the Horqin Sandy Land, and the Hobq Desert) and western (including the Taklimakan Desert, the Gurbantunggut Desert, the Kumtagh Desert, the Ulan Buh Desert, the Qaidam Basin Desert, the Badain Jaran Desert, and the Tengger Desert) regions. The results revealed that from 1970 to 2019, desertification first expanded and then reversed in the whole region. Specifically, desertification expanded from 1980 to 1999 and reversed after 2000. The desertification trend exhibited distinct spatio-temporal variations between the eastern and western regions. From 1970 to 2019, the western region experienced relatively minor changes in desertified land area compared to the eastern region. In the context of global climate change, beneficial climatic conditions and ecological construction projects played a crucial role in reversing desertification. These findings provide valuable insights for understanding the development patterns of desertification in the most representative deserts and sandy lands in China and formulating effective desertification control strategies.

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

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

The Mongolian Plateau in East Asia is one of the largest contingent arid and semi-arid areas of the world. Under the impacts of climate change and human activities, desertification is becoming increasingly severe on the Mongolian Plateau. Understanding the vegetation dynamics in this region can better characterize its ecological changes. In this study, based on Moderate Resolution Imaging Spectroradiometer (MODIS) images, we calculated the kernel normalized difference vegetation index (kNDVI) on the Mongolian Plateau from 2000 to 2023, and analyzed the changes in kNDVI using the Theil-Sen median trend analysis and Mann-Kendall significance test. We further investigated the impact of climate change on kNDVI change using partial correlation analysis and composite correlation analysis, and quantified the effects of climate change and human activities on kNDVI change by residual analysis. The results showed that kNDVI on the Mongolian Plateau was increasing overall, and the vegetation recovery area in the southern region was significantly larger than that in the northern region. About 50.99% of the plateau showed dominant climate-driven effects of temperature, precipitation, and wind speed on kNDVI change. Residual analysis showed that climate change and human activities together contributed to 94.79% of the areas with vegetation improvement. Appropriate human activities promoted the recovery of local vegetation, and climate change inhibited vegetation growth in the northern part of the Mongolian Plateau. This study provides scientific data for understanding the regional ecological environment status and future changes and developing effective ecological protection measures on the Mongolian Plateau.

Understanding the response of vegetation variation to climate change and human activities is critical for addressing future conflicts between humans and the environment, and maintaining ecosystem stability. Here, we aimed to identify the determining factors of vegetation variation and explore the sensitivity of vegetation to temperature (SVT) and the sensitivity of vegetation to precipitation (SVP) in the Shiyang River Basin (SYRB) of China during 2001-2022. The climate data from climatic research unit (CRU), vegetation index data from Moderate Resolution Imaging Spectroradiometer (MODIS), and land use data from Landsat images were used to analyze the spatial-temporal changes in vegetation indices, climate, and land use in the SYRB and its sub-basins (i.e., upstream, midstream, and downstream basins) during 2001-2022. Linear regression analysis and correlation analysis were used to explore the SVT and SVP, revealing the driving factors of vegetation variation. Significant increasing trends (P<0.05) were detected for the enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI) in the SYRB during 2001-2022, with most regions (84%) experiencing significant variation in vegetation, and land use change was determined as the dominant factor of vegetation variation. Non-significant decreasing trends were detected in the SVT and SVP of the SYRB during 2001-2022. There were spatial differences in vegetation variation, SVT, and SVP. Although NDVI and EVI exhibited increasing trends in the upstream, midstream, and downstream basins, the change slope in the downstream basin was lower than those in the upstream and midstream basins, the SVT in the upstream basin was higher than those in the midstream and downstream basins, and the SVP in the downstream basin was lower than those in the upstream and midstream basins. Temperature and precipitation changes controlled vegetation variation in the upstream and midstream basins while human activities (land use change) dominated vegetation variation in the downstream basin. We concluded that there is a spatial heterogeneity in the response of vegetation variation to climate change and human activities across different sub-basins of the SYRB. These findings can enhance our understanding of the relationship among vegetation variation, climate change, and human activities, and provide a reference for addressing future conflicts between humans and the environment in the arid inland river basins.

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

Wind erosion is a geomorphic process in arid and semi-arid areas and has substantial implications for regional climate and desertification. In the Columbia Plateau of northwestern United States, the emissions from fine particles of loessial soils often contribute to the exceedance of inhalable particulate matter (PM) with an aerodynamic diameter of 10 μm or less (PM10) according to the air quality standards. However, little is known about the threshold friction velocity (TFV) for particles of different sizes that comprise these soils. In this study, soil samples of two representative soil types (Warden sandy loam and Ritzville silt loam) collected from the Columbia Plateau were sieved to seven particle size fractions, and an experiment was then conducted to determine the relationship between TFV and particle size fraction. The results revealed that soil particle size significantly affected the initiation of soil movement and TFV; TFV ranged 0.304-0.844 and 0.249-0.739 m/s for different particle size fractions of Ritzville silt loam and Warden sandy loam, respectively. PM10 and total suspended particulates (TSP) emissions from a bed of 63-90 μm soil particles were markedly higher for Warden sandy loam than for Ritzville silt loam. Together with the lower TFV of Warden sandy loam, dust emissions from fine particles (<100 μm in diameter) of Warden sandy loam thus may be a main contributor to dust in the region's atmosphere, since the PM10 emissions from the soil erosion surfaces and its ensuing suspension within the atmosphere constitute an essential process of soil erosion in the Columbia Plateau. Developing and implementing strategic land management practices on sandy loam soils is therefore necessary to control dust emissions in the Columbia Plateau.

The characteristics of drought in Xinjiang Uygur Autonomous Region (Xinjiang), China have changed due to changes in the spatiotemporal patterns of temperature and precipitation, however, the effects of temperature and precipitation—the two most important factors influencing drought—have not yet been thoroughly explored in this region. In this study, we first calculated the standard precipitation evapotranspiration index (SPEI) in Xinjiang from 1980 to 2020 based on the monthly precipitation and monthly average temperature. Then the spatiotemporal characteristics of temperature, precipitation, and drought in Xinjiang from 1980 to 2020 were analyzed using the Theil-Sen median trend analysis method and Mann-Kendall test. A series of SPEI-based scenario-setting experiments by combining the observed and detrended climatic factors were utilized to quantify the effects of individual climatic factor (i.e., temperature and precipitation). The results revealed that both temperature and precipitation had experienced increasing trends at most meteorological stations in Xinjiang from 1980 to 2020, especially the spring temperature and winter precipitation. Due to the influence of temperature, trends of intensifying drought have been observed at spring, summer, autumn, and annual scales. In addition, the drought trends in southern Xinjiang were more notable than those in northern Xinjiang. From 1980 to 2020, temperature trends exacerbated drought trends, but precipitation trends alleviated drought trends in Xinjiang. Most meteorological stations in Xinjiang exhibited temperature-dominated drought trend except in winter; in winter, most stations exhibited precipitation-dominated wetting trend. The findings of this study highlight the importance of the impact of temperature on drought in Xinjiang and deepen the understanding of the factors influencing drought.

With ongoing global climate change, drought has become the primary threat constraining food security in China. Traditional assessment frameworks based on administrative boundaries or macro-climatic zoning overlook variation in vulnerability affected by key agronomic practices, such as crop phenology and cropping systems, thereby limiting their accuracy. To address this research gap, this study developed and validated a novel drought risk assessment framework based on agricultural cropping zones (single-, double-, and triple-cropping zones). The framework coupled a Geographical and Temporal Neural Network Weighted Regression (GTNNWR) model for forecasting future crop vegetation dynamics with the Standardized Precipitation Evapotranspiration Index (SPEI) to assess drought risk under historical (2001-2020) and projected future (2021-2100) scenarios. The GTNNWR model achieved R² values ranging from 0.72 to 0.82 and RMSE values between 0.11 and 0.14 for NDVI prediction, significantly outperforming conventional models. Historical drought risk assessment revealed that drought events were most frequent during summer and concentrated in single-cropping and double-cropping zones. Future projections indicate a substantial intensification of drought risk. Under the Shared Socioeconomic Pathway (SSP)126 scenario, drought risk is projected to increase in the triple-cropping zones of the middle and lower reaches of the Yangtze River Plain. Under the SSP245 scenario, the frequency of spring and winter droughts is anticipated to rise markedly. Under the SSP585 scenario, drought intensity is projected to intensify in central-eastern single-cropping zones and southwestern double-cropping zones. This assessment framework based on agricultural cropping zones can precisely identify drought risks and facilitate adaptation in agricultural management, such as optimizing irrigation systems and adjusting crop structures.

The Three-River Source Region (TRSR) in China holds a vital position and exhibits an irreplaceable strategic importance in ecological preservation at the national level. On the basis of an in-depth study of the vegetation evolution in the TRSR from 2000 to 2022, we conducted a detailed analysis of the feedback mechanism of vegetation growth to climate change and human activity for different vegetation types. During the growing season, the spatiotemporal variations of normalized difference vegetation index (NDVI) for different vegetation types in the TRSR were analyzed using the Moderate Resolution Imaging Spectroradiometer (MODIS)-NDVI data and meteorological data from 2000 to 2022. In addition, the response characteristics of vegetation to temperature, precipitation, and human activity were assessed using trend analysis, partial correlation analysis, and residual analysis. Results indicated that, after in-depth research, from 2000 to 2022, the TRSR's average NDVI during the growing season was 0.3482. The preliminary ranking of the average NDVI for different vegetation types was as follows: shrubland (0.5762)>forest (0.5443)>meadow (0.4219)>highland vegetation (0.2223)>steppe (0.2159). The NDVI during the growing season exhibited a fluctuating growth trend, with an average growth rate of 0.0018/10a (P<0.01). Notably, forests displayed a significant development trend throughout the growing season, possessing the fastest rate of change in NDVI (0.0028/10a). Moreover, the upward trends in NDVI for forests and steppes exhibited extensive spatial distributions, with significant increases accounting for 95.23% and 93.80%, respectively. The sensitivity to precipitation was significantly enhanced in other vegetation types other than highland vegetation. By contrast, steppes, meadows, and highland vegetation demonstrated relatively high vulnerability to temperature fluctuations. A further detailed analysis revealed that climate change had a significant positive impact on the TRSR from 2000 to 2022, particularly in its northwestern areas, accounting for 85.05% of the total area. Meanwhile, human activity played a notable positive role in the southwestern and southeastern areas of the TRSR, covering 62.65% of the total area. Therefore, climate change had a significantly higher impact on NDVI during the growing season in the TRSR than human activity.

Stable water isotopes are natural tracers quantifying the contribution of moisture recycling to local precipitation, i.e., the moisture recycling ratio, but various isotope-based models usually lead to different results, which affects the accuracy of local moisture recycling. In this study, a total of 18 stations from four typical areas in China were selected to compare the performance of isotope-based linear and Bayesian mixing models and to determine local moisture recycling ratio. Among the three vapor sources including advection, transpiration, and surface evaporation, the advection vapor usually played a dominant role, and the contribution of surface evaporation was less than that of transpiration. When the abnormal values were ignored, the arithmetic averages of differences between isotope-based linear and the Bayesian mixing models were 0.9% for transpiration, 0.2% for surface evaporation, and -1.1% for advection, respectively, and the medians were 0.5%, 0.2%, and -0.8%, respectively. The importance of transpiration was slightly less for most cases when the Bayesian mixing model was applied, and the contribution of advection was relatively larger. The Bayesian mixing model was found to perform better in determining an efficient solution since linear model sometimes resulted in negative contribution ratios. Sensitivity test with two isotope scenarios indicated that the Bayesian model had a relatively low sensitivity to the changes in isotope input, and it was important to accurately estimate the isotopes in precipitation vapor. Generally, the Bayesian mixing model should be recommended instead of a linear model. The findings are useful for understanding the performance of isotope-based linear and Bayesian mixing models under various climate backgrounds.

Understanding the dynamics of surface water area and their drivers is crucial for human survival and ecosystem stability in inland arid and semi-arid areas. This study took Gansu Province, China, a typical area with complex terrain and variable climate, as the research subject. Based on Google Earth Engine, we used Landsat data and the Open-surface Water Detection Method with Enhanced Impurity Control method to monitor the spatiotemporal dynamics of surface water area in Gansu Province from 1985 to 2022, and quantitatively analyzed the main causes of regional differences in surface water area. The findings revealed that surface water area in Gansu Province expanded by 406.88 km² from 1985 to 2022. Seasonal surface water area exhibited significant fluctuations, while permanent surface water area showed a steady increase. Notably, terrestrial water storage exhibited a trend of first decreasing and then increasing, correlated with the dynamics of surface water area. Climate change and human activities jointly affected surface hydrological processes, with the impact of climate change being slightly higher than that of human activities. Spatially, climate change affected the 'source' of surface water to a greater extent, while human activities tended to affect the 'destination' of surface water. Challenges of surface water resources faced by inland arid and semi-arid areas like Gansu Province are multifaceted. Therefore, we summarized the surface hydrology patterns typical in inland arid and semi-arid areas and tailored surface water 'supply-demand' balance strategies. The study not only sheds light on the dynamics of surface water area in Gansu Province, but also offers valuable insights for ecological protection and surface water resource management in inland arid and semi-arid areas facing water scarcity.

Atmospheric deposition of nitrogen (N) plays a significant role in shaping the structure and functioning of various terrestrial ecosystems worldwide. However, the magnitude of N deposition on grassland ecosystems in Central Asia still remains highly uncertain. In this study, a multi-data approach was adopted to analyze the distribution and amplitude of N deposition effects in Central Asia from 1979 to 2014 using a process-based denitrification decomposition (DNDC) model. Results showed that total vegetation carbon (C) in Central Asia was 0.35 (±0.09) Pg C/a and the averaged water stress index (WSI) was 0.20 (±0.02) for the whole area. Increasing N deposition led to an increase in the vegetation C of 65.56 (±83.03) Tg C and slightly decreased water stress in Central Asia. Findings of this study will expand both our understanding and predictive capacity of C characteristics under future increases in N deposition, and also serve as a valuable reference for decision-making regarding water resources management and climate change mitigation in arid and semi-arid areas globally.

The Keriya River Basin is located in an extremely arid climate zone on the southern edge of the Tarim Basin of Northwest China, exhibiting typical mountain-oasis-desert distribution characteristics. In recent decades, climate change and human activities have exerted significant impacts on the service functions of watershed ecosystems. However, the trade-offs and synergies between ecosystem services (ESs) have not been thoroughly examined. This study aims to reveal the spatiotemporal changes in ESs within the Keriya River Basin from 1995 to 2020 as well as the trade-offs and synergies between ESs. Leveraging the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) and Revised Wind Erosion Equation (RWEQ) using land use/land cover (LULC), climate, vegetation, soil, and hydrological data, we quantified the spatiotemporal changes in the five principal ESs (carbon storage, water yield, food production, wind and sand prevention, and habitat quality) of the watershed from 1995 to 2020. Spearman correlation coefficients were used to analyze the trade-offs and synergies between ES pairs. The findings reveal that water yield, carbon storage, and habitat quality exhibited relatively high levels in the upstream, while food production and wind and sand prevention dominated the midstream and downstream, respectively. Furthermore, carbon storage, food production, wind and sand prevention, and habitat quality demonstrated an increase at the watershed scale while water yield exhibited a decline from 1995 to 2020. Specifically, carbon storage, wind and sand prevention, and habitat quality presented an upward trend in the upstream but downward trend in the midstream and downstream. Food production in the midstream showed a continuously increasing trend during the study period. Trade-off relationships were identified between water yield and wind and sand prevention, water yield and carbon storage, food production and water yield, and habitat quality and wind and sand prevention. Prominent temporal and spatial synergistic relationships were observed between different ESs, notably between carbon storage and habitat quality, carbon storage and food production, food production and wind and sand prevention, and food production and habitat quality. Water resources emerged as a decisive factor for the sustainable development of the basin, thus highlighting the intricate trade-offs and synergies between water yield and the other four services, particularly the relationship with food production, which warrants further attention. This research is of great significance for the protection and sustainable development of river basins in arid areas.

Soil erosion caused by unsustainable grazing is a major driver of grassland ecosystem degradation in many semi-arid hilly areas in China. Thus, grazing exclusion is considered as an effective method for solving this issue in such areas. However, some ecological and economic problems, such as slow grassland rejuvenation and limited economic conditions, have become obstacles for the sustainable utilization of grassland ecosystem. Accordingly, we hypothesized that the conflict between grassland use and soil conservation may be balanced by a reasonable grazing intensity. In this study, a two-year grazing fence experiment with five grazing intensity gradients was conducted in a typical grassland of the Loess Plateau in China to evaluate the responses of vegetation characteristics and soil and water losses to grazing intensity. The five grazing intensity gradients were 2.2, 3.0, 4.2, 6.7, and 16.7 goats/hm², which were represented by G1-G5, respectively, and no grazing was used as control. The results showed that a reasonable grazing intensity was conducive to the sustainable utilization of grassland resources. Vegetation biomass under G1-G4 grazing intensity significantly increased by 51.9%, 42.1%, 36.9%, and 36.7%, respectively, compared with control. In addition, vegetation coverage increased by 19.6% under G1 grazing intensity. Species diversity showed a single peak trend with increasing grazing intensity. The Shannon-Wiener diversity index under G1-G4 grazing intensities significantly increased by 22.8%, 22.5%, 13.3%, and 8.3%, respectively, compared with control. Furthermore, grazing increased the risk of soil erosion. Compared with control, runoff yields under G1-G5 grazing intensities increased by 1.4, 2.6, 2.8, 4.3, and 3.9 times, respectively, and sediment yields under G1-G5 grazing intensities were 3.0, 13.0, 20.8, 34.3, and 37.7 times greater, respectively, than those under control. This result was mainly attributed to a visible decrease in litter biomass after grazing, which decreased by 50.5%, 72.6%, 79.0%, 80.0%, and 76.9%, respectively, under G1-G5 grazing intensities. By weighing the grassland productivity and soil conservation function, we found that both two aims were achieved at a low grazing intensity of less than 3.5 goats/hm². Therefore, it is recommended that grassland should be moderately utilized with grazing intensity below 3.5 goats/hm² in semi-arid hilly areas to achieve the dual goals of ecological and economic benefits. The results provide a scientific basis for grassland utilization and health management in semi-arid hilly areas from the perspective of determining reasonable grazing intensity to maintain both grassland production and soil conservation functions.

Increasing human disturbance and climate change have threatened ecological connectivity and structural stability, especially in semi-arid mountain areas with sparse vegetation and weak hydrological regulation. Large-scale ecological restoration, such as adding ecological sources or corridors, is difficult in such environments and often faces poor operability and high implementation costs in practice. Taking the southern slope of the Qilian Mountains in China as the study area and 2020 as the baseline, this study integrated weighted complex network theory into the "ecological source-resistance surface-corridor" framework to construct a heterogeneous ecological network (EN). Circuit theory was integrated with weighted betweenness to identify critical barrier points for locally differentiated restoration, followed by assessment of the network optimization effects. The results revealed that 494 ecological sources and 1308 ecological corridors were identified in the study area. Fifty-one barrier points with restoration potential were identified along key ecological corridors and locally restored. After optimization, the network gained 11 additional ecological corridors, and the total ecological corridor length increased by approximately 1143 km. Under simulated attacks, the decline rates of maximum connected subgraph (MCS) and network efficiency (Ne) slowed compared with pre-restoration conditions, indicating improved robustness. These findings demonstrate that targeted local restoration can enhance network connectivity and stability while minimizing disturbance to the overall landscape pattern, providing a practical pathway for ecological restoration and sustainable management in semi-arid mountain areas.

To comprehensively evaluate the alterations in water ecosystem service functions within arid watersheds, this study focused on the Bosten Lake Basin, which is situated in the arid region of Northwest China. The research was based on land use/land cover (LULC), natural, socioeconomic, and accessibility data, utilizing the Patch-level Land Use Simulation (PLUS) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) models to dynamically assess LULC change and associated variations in water yield and water conservation. The analyses included the evaluation of contribution indices of various land use types and the investigation of driving factors that influence water yield and water conservation. The results showed that the change of LULC in the Bosten Lake Basin from 2000 to 2020 showed a trend of increasing in cultivated land and construction land, and decreasing in grassland, forest, and unused land. The unused land of all the three predicted scenarios of 2030 (S1, a natural development scenario; S2, an ecological protection scenario; and S3, a cultivated land protection scenario) showed a decreasing trend. The scenarios S1 and S3 showed a trend of decreasing in grassland and increasing in cultivated land; while the scenario S2 showed a trend of decreasing in cultivated land and increasing in grassland. The water yield of the Bosten Lake Basin exhibited an initial decline followed by a slight increase from 2000 to 2020. The areas with higher water yield values were primarily located in the northern section of the basin, which is characterized by higher altitude. Water conservation demonstrated a pattern of initial decrease followed by stabilization, with the northeastern region demonstrating higher water conservation values. In the projected LULC scenarios of 2030, the estimated water yield under scenarios S1 and S3 was marginally greater than that under scenario S2; while the level of water conservation across all three scenarios remained rather consistent. The results showed that Hejing County is an important water conservation function zone, and the eastern part of the Xiaoyouledusi Basin is particularly important and should be protected. The findings of this study offer a scientific foundation for advancing sustainable development in arid watersheds and facilitating efficient water resource management.

Crude oil pollution is a significant global environmental challenge. The eastern Gansu Province on the Loess Plateau, an important agricultural region containing the Changqing Oilfield, is facing increasing crude oil contamination. Understanding how microbial communities respond to varying pollution levels is critical for developing effective bioremediation strategies. This study examined how different concentrations of crude oil affect soil properties and microbial communities in Qingyang City, eastern Gansu Province, China by comparing lightly polluted (1895.84-2696.54 mg/kg total petroleum hydrocarbons (TPH)), heavily polluted (4964.25-7153.61 mg/kg TPH), and uncontaminated (CK) soils. Results revealed that petroleum contamination significantly increased total organic carbon (TOC), pH, C:N:P ratio, and the activities of dehydrogenase (DHA) and polyphenol oxidase (PPO), while reducing total nitrogen (TN), available nitrogen (AN), total phosphorus (TP), available phosphorus (AP), available potassium (AK), soil organic matter (SOM), soil water content (SWC), the activities of urease (URE) and alkaline phosphatase (APA), and microbial alpha diversity (P<0.050). Light pollution (LP) soils demonstrated an increase in culturable microorganisms, whereas heavy pollution (HP) soils exhibited increased hydrocarbon-degrading microbes and higher expression of key functional genes, such as alkane monooxygenase (AlkB), cytochrome P450 alkane hydroxylases (P450), catechol 2,3-dioxygenase (C23O), and naphthalene dioxygenase (Nah) (P<0.050). Non-metric multidimensional scaling (NMDS) and redundancy analysis (RDA) indicated evident variations in microbial community structure across different oil contamination levels. LP soils were dominated by bacterial genera Pseudoxanthomonas and Solimonadaceae, whereas Pseudomonas, Nocardioides, and hydrocarbon-degrading genera (Marinobacter, Idiomarina, and Halomonas) were predominant in HP soils. The fungal genus Pseudallescheria exhibited the most pronounced abundance shift between LP and HP soils (P<0.050). Environmental factor analysis identified AN, SWC, TN, SOM, and alpha diversity indices (Shannon index and Chao1 index) as the key differentiators of CK soils, whereas the pollutant levels and metal content were characterized in HP soils. Hydrocarbon-degrading microbial abundance was a defining trait of HP soils. Metabolic pathway analysis revealed enhanced aromatic hydrocarbon degradation in HP soils, indicating microbial adaptation to severe contamination. These findings demonstrated that crude oil pollution suppressed soil nutrients while reshaping the structure and function of microbial communities. Pollution intensity directly affected microbial composition and degradation potential. This study offers valuable insights into microbial responses across contamination gradients and supports the development of targeted bioremediation strategies for oil-contaminated loess soils.

Vapor pressure deficit (VPD) plays a crucial role in determining plant physiological functions and exerts a substantial influence on vegetation, second only to carbon dioxide (CO₂). As a robust indicator of atmospheric water demand, VPD has implications for global water resources, and its significance extends to the structure and functioning of ecosystems. However, the influence of VPD on vegetation growth under climate change remains unclear in China. This study employed empirical equations to estimate the VPD in China from 2000 to 2020 based on meteorological reanalysis data of the Climatic Research Unit (CRU) Time-Series version 4.06 (TS4.06) and European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA-5). Vegetation growth status was characterized using three vegetation indices, namely gross primary productivity (GPP), leaf area index (LAI), and near-infrared reflectance of vegetation (NIRv). The spatiotemporal dynamics of VPD and vegetation indices were analyzed using the Theil-Sen median trend analysis and Mann-Kendall test. Furthermore, the influence of VPD on vegetation growth and its relative contribution were assessed using a multiple linear regression model. The results indicated an overall negative correlation between VPD and vegetation indices. Three VPD intervals for the correlations between VPD and vegetation indices were identified: a significant positive correlation at VPD below 4.820 hPa, a significant negative correlation at VPD within 4.820-9.000 hPa, and a notable weakening of negative correlation at VPD above 9.000 hPa. VPD exhibited a pronounced negative impact on vegetation growth, surpassing those of temperature, precipitation, and solar radiation in absolute magnitude. CO₂ contributed most positively to vegetation growth, with VPD offsetting approximately 30.00% of the positive effect of CO₂. As the rise of VPD decelerated, its relative contribution to vegetation growth diminished. Additionally, the intensification of spatial variations in temperature and precipitation accentuated the spatial heterogeneity in the impact of VPD on vegetation growth in China. This research provides a theoretical foundation for addressing climate change in China, especially regarding the challenges posed by increasing VPD.

Hot arid zones represent vital reservoirs of unique species and ecosystems, holding significant importance for biodiversity. This study aimed to explore the plant diversity associated with tree plantations in urban ecosystems under hyper-arid climatic conditions in the Sahara Desert of Algeria. In May 2022, 30 quadrats measuring 1 m² each were established at the base of Phoenix dactylifera, Leucaena leucocephala, and Tamarix aphylla, corresponding to the dominant tree species in each of three plantations. In each quadrat, the plant quantitative inventory was conducted to measure plant diversity and similarity among the studied plantations. Based on this, we assessed the plant functional traits and rarity/abundance status of the flora. The findings revealed a diverse flora associated with the studied plantations, comprising 29 plant species grouped into 27 genera and 12 families. Notably, Poaceae (accounting for 30.8% of the flora), Asteraceae (25.0%), and Zygophyllaceae (21.6%) were well-represented. With an overall density of approximately 555 individuals/m², Zygophyllum album (120 individuals/m²) and Polypogon monspeliensis (87 individuals/m²) emerged as the most abundant species. Functional trait analysis underscored the pivotal role of therophytes (constituting over 50.0% of the flora) and anemochorous species (33.0%-62.5%). Phytogeographic analysis emphasized the prevalence of the Saharo-Arabic element (constituting over 31.0% of the flora) and the Mediterranean Saharo-Arabic element (9.5%-21.5%). The Cosmopolitan element thrived under disturbance factors, recording percentages from 13.0% to 20.0% of the plant community. The rarity/abundance status of the flora emphasized the significance of rare, common, and very common species in the studied plantations. These findings could provide fundamental data for the effective control and management of biodiversity in hot hyper-arid urban ecosystems.

Methane (CH₄) is a potent greenhouse gas that has a substantial impact on global warming due to its substantial influence on the greenhouse effect. Increasing extreme precipitation events, such as drought, attributable to global warming that caused by greenhouse gases, exert a profound impact on the intricate biological processes associated with CH₄ uptake. Notably, the timing of extreme drought occurrence emerges as a pivotal factor influencing CH₄ uptake, even when the degree of drought remains constant. However, it is still unclear how the growing season regulates the response of CH₄ uptake to extreme drought. In an effort to bridge this knowledge gap, we conducted a field manipulative experiment to evaluate the impact of extreme drought on CH₄ uptake during early, middle, and late growing stages in a temperate steppe of Inner Mongolia Autonomous Region, China. The result showed that all extreme drought consistently exerted positive effects on CH₄ uptake regardless of seasonal timing. However, the magnitude of this effect varied depending on the timing of season, as evidenced by a stronger effect in early growing stage than in middle and late growing stages. Besides, the pathways of CH₄ uptake were different from seasonal timing. Extreme drought affected soil physical-chemical properties and aboveground biomass (AGB), consequently leading to changes in CH₄ uptake. The structural equation model showed that drought both in the early and middle growing stages enhanced CH₄ uptake due to reduced soil water content (SWC), leading to a decrease in NO₃^--N and an increase in pmoA abundance. However, drought in late growing stage primarily enhanced CH₄ uptake only by decreasing SWC. Our results suggested that seasonal timing significantly contributed to regulate the impacts of extreme drought pathways and magnitudes on CH₄ uptake. The findings can provide substantial implications for understanding how extreme droughts affect CH₄ uptake and improve the prediction of potential ecological consequence under future climate change.

The Turpan-Hami (Tuha) Basin in Xinjiang Uygur Autonomous Region of China, holds significant strategic importance as a key economic artery of the ancient Silk Road and the Belt and Road Initiative, necessitating a holistic understanding of the spatiotemporal evolution of land use/land cover (LULC) to foster sustainable planning that is tailored to the region's unique resource endowments. However, existing LULC classification methods demonstrate inadequate accuracy, hindering effective regional planning. In this study, we established a two-level LULC classification system (8 primary types and 22 secondary types) for the Tuha Basin. By employing Landsat 5/7/8 imagery at 5-a intervals, we developed the LULC dataset of the Tuha Basin from 1990 to 2020, conducted the accuracy assessment and spatiotemporal evolution analysis, and simulated the future LULC under various scenarios via the Markov-Future Land Use Simulation (Markov-FLUS) model. The results revealed that the average overall accuracy values of our LULC dataset were 0.917 and 0.864 for the primary types and secondary types, respectively. Compared with the seven mainstream LULC products (GlobeLand30, Global 30-meter Land Cover with Fine Classification System (GLC_FCS30), Finer Resolution Observation and Monitoring of Global Land Cover PLUS (FROM_GLC PLUS), ESA Global Land Cover (ESA_LC), Esri Land Cover (ESRI_LC), China Multi-Period Land Use Land Cover Change Remote Sensing Monitoring Dataset (CNLUCC), and China Annual Land Cover Dataset (CLCD)) in 2020, our LULC data exhibited dramatically elevated overall accuracy and provided more precise delineations for land features, thereby yielding high-quality data backups for land resource analyses within the basin. In 2020, unused land (78.0% of the study area) and grassland (18.6%) were the dominant LULC types of the basin; although cropland and construction land constituted less than 1.0% of the total area, they played a vital role in arid land development and primarily situated within oases that form the urban cores of the cities of Turpan and Hami. Between 1990 and 2020, cropland and construction land exhibited a rapid expansion, and the total area of water body decreased yet resurging after 2015 due to an increase in areas of reservoir and pond. In future scenario simulations, significant increases in areas of construction land and cropland are anticipated under the business-as-usual scenario, whereas the wetland area will decrease, suggesting the need for ecological attention under this development pathway. In contrast, the economic development scenario underscores the fast-paced expansion of construction land, primarily from the conversion of unused land, highlighting the significant developmental potential of unused land with a slowing increase in cropland. Special attention should thus be directed toward ecological and cropland protection during development. This study provides data supports and policy recommendations for the sustainable development goals of Tuha Basin and other similar arid areas.

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

Territorial spatial ecological restoration is a crucial prerequisite for optimizing the territorial spatial patterns, enhancing the ecosystem functions, and achieving sustainable development at the regional scale. The Qaidam Basin, located in the alpine arid region of the Qinghai-Xizang Plateau, China, is experiencing desertification, biodiversity loss, soil erosion, and environmental pollution. Selecting the Qaidam Basin as the study area, we identified 9 ecological sources in the region using the Morphological Spatial Pattern Analysis (MSPA) method and the landscape connectivity assessment, and extracted 10 significant corridors and 26 general corridors using the Minimum Cumulative Resistance (MCR) and Gravity models. Then, we determined 114 ecological "pinch points" and 42 ecological barrier points by employing the Circuit Theory, thereby constructing the ecological security pattern of the area. Further, we evaluated the ecosystem health of the Qaidam Basin during 2003-2023 using the Vitality-Organization-Resilience-Service (VORS) model. Finally, we integrated ecosystem health assessment and ecological security pattern to comprehensively identify the key areas for ecological restoration in the Qaidam Basin. The results revealed that the ecosystem in the basin fluctuated toward a healthier state from 2003 to 2023. The average ecosystem health index (EHI) for the basin decreased from 0.34 in 2003 to 0.28 in 2013, followed by a substantial recovery to 0.36 in 2023. Higher EHI values were found in the northeastern, southeastern, and southwestern fringes and lower values were located in the basin interior and northwestern region. During 2003-2023, the areas that exhibited a decrease in EHI were primarily located in the interior and northwestern regions of the basin, while those that exhibited an increase in EHI were located in the northeastern, southeastern, and southwestern fringes, demonstrating expanded spatial differences. This may be attributed to the fact that once an eco-environment is damaged, the ecological recovery of the vulnerable areas within the eco-environment will be slow and difficult. This study identified four types of ecological restoration areas, including corridor connectivity, artificial restoration, ecological recovery, and ecological enhancement zones, covering a total area of 6034.7 km², and proposed targeted ecological restoration strategies according to these different categories. Our findings can serve as a valuable reference for optimizing the territorial spatial patterns, enhancing the ecosystem functions, and promoting sustainable development in the Qaidam Basin.

The presence of invasive plant species poses a substantial ecological impact, thus comprehensive evaluation of their potential range and risk under the influence of climate change is necessary. This study uses maximum entropy (MaxEnt) modeling to forecast the likelihood of Leucaena leucocephala (Lam.) de Wit invasion in Saudi Arabia under present and future climate change scenarios. Utilizing the MaxEnt modeling, we integrated climatic and soil data to predict habitat suitability for the invasive species. We conducted a detailed analysis of the distribution patterns of the species, using climate variables and ecological factors. We focused on the important influence of temperature seasonality, temperature annual range, and precipitation seasonality. The distribution modeling used robust measures of area under the curve (AUC) and receiver-operator characteristic (ROC) curves, to map the invasion extent, which has a high level of accuracy in identifying appropriate habitats. The complex interaction that influenced the invasion of L. leucocephala was highlighted by the environmental parameters using Jackknife test. Presently, the actual geographic area where L. leucocephala was found in Saudi Arabia was considerably smaller than the theoretical maximum range, suggesting that it had the capacity to expand further. The MaxEnt model exhibited excellent prediction accuracy and produced reliable results based on the data from the ROC curve. Precipitation and temperature were the primary factors influencing the potential distribution of L. leucocephala. Currently, an estimated area of 216,342 km² in Saudi Arabia was at a high probability of invasion by L. leucocephala. We investigated the potential for increased invasion hazards in the future due to climate change scenarios (Shared Socioeconomic Pathways (SSPs) 245 and 585). The analysis of key climatic variables, including temperature seasonality and annual range, along with soil properties such as clay composition and nitrogen content, unveiled their substantial influence on the distribution dynamic of L. leucocephala. Our findings indicated a significant expansion of high risk zones. High-risk zones for L. leucocephala invasion in the current climate conditions had notable expansions projected under future climate scenarios, particularly evident in southern Makkah, Al Bahah, Madina, and Asir areas. The results, backed by thorough spatial studies, emphasize the need to reduce the possible ecological impacts of climate change on the spread of L. leucocephala. Moreover, the study provides valuable strategic insights for the management of invasion, highlighting the intricate relationship between climate change, habitat appropriateness, and the risks associated with invasive species. Proactive techniques are suggested to avoid and manage the spread of L. leucocephala, considering its high potential for future spread. This study enhances the overall comprehension of the dynamics of invasive species by combining modeling techniques with ecological knowledge. It also provides valuable information for decision-making to implement efficient conservation and management strategies in response to changing environmental conditions.

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

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

Over the last three decades, more than half of the world's large lakes and wetlands have experienced significant shrinkage, primarily due to climate change and extensive water consumption for agriculture and other human needs. The desiccation of lakes leads to severe environmental, economic, and social repercussions. Urmia Lake, located in northwestern Iran and representing a vital natural ecosystem, has experienced a volume reduction of over 90.0%. Our research evaluated diverse water management strategies within the Urmia Lake basin and prospects of inter-basin water transfers. This study focused on strategies to safeguard the environmental water rights of the Urmia Lake by utilizing the modeling and simulating (MODSIM) model. The model simulated changes in the lake's water volume under various scenarios. These included diverting water from incoming rivers, cutting agricultural water use by 40.0%, releasing dam water in non-agricultural seasons, treated wastewater utilization, and inter-basin transfers. Analytical hierarchy process (AHP) was utilized to analyze the simulation results. Expert opinions with AHP analysis, acted as a multi-criteria decision-making tool to evaluate the simulation and determine the optimal water supply source priority for the Urmia Lake. Our findings underscore the critical importance of reducing agricultural water consumption as the foremost step in preserving the lake. Following this, inter-basin water transfers are suggested, with a detailed consideration of the inherent challenges and limitations faced by the source watersheds. It is imperative to conduct assessments on the impacts of these transfers on the downstream users and the potential environmental risks, advocating for a diplomatic and cooperative approach with adjacent country. This study also aims to forecast the volumes of water that can be transferred under different climatic conditions—drought, normal, and wet years—to inform strategic water management planning for the Urmia Lake. According to our projection, implementing the strategic scenarios outlined could significantly augment the lake's level and volume, potentially by 3.57×10⁹-9.38×10⁹ m³ over the coming 10 a and 3.57×10⁹-10.70×10⁹ m³ in the subsequent 15 a.

Understanding the distribution and dynamics of glaciers is of great significance to the management and allocation of regional water resources and socio-economic development in arid regions of Northwest China. In this study, based on 36 Landsat images, we extracted the glacier boundaries in the Manas River Basin, Northwest China from 2000 to 2020 using eCognition combined with band operation, GIS (geographic information system) spatial overlay techniques, and manual visual interpretation. We further analyzed the distribution and variation characteristics of glacier area, and simulated glacial runoff using a distributed degree-day model to explore the regulation of runoff recharge. The results showed that glacier area in the Manas River Basin as a whole showed a downward trend over the past 21 a, with a decrease of 10.86% and an average change rate of -0.54%/a. With the increase in glacier scale, the number of smaller glaciers decreased exponentially, and the number and area of larger glaciers were relatively stable. Glacier area showed a normal distribution trend of increasing first and then decreasing with elevation. About 97.92% of glaciers were distributed at 3700-4800 m, and 48.11% of glaciers were observed on the northern and northeastern slopes. The retreat rate of glaciers was the fastest (68.82%) at elevations below 3800 m. There was a clear rise in elevation at the end of glaciers. Glaciers at different slope directions showed a rapid melting trend from the western slope to the southern slope then to the northern slope. Glacial runoff in the basin showed a fluctuating upward trend in the past 21 a, with an increase rate of 0.03×10⁸ m³/a. The average annual glacial runoff was 4.80×10⁸ m³, of which 33.31% was distributed in the ablation season (June-September). The average annual contribution rate of glacial meltwater to river runoff was 35.40%, and glacial runoff accounted for 45.37% of the total runoff during the ablation season. In addition, precipitation and glacial runoff had complementary regulation patterns for river runoff. The findings can provide a scientific basis for water resource management in the Manas River Basin and other similar arid inland river basins.

Nature reserves play a significant role in providing ecosystem services and are key sites for biodiversity conservation. The Tianchi Bogda Peak Natural Reserve (TBPNR), located in Xinjiang Uygur Autonomous Region, China, is an important ecological barrier area in the temperate arid zone. The evaluation of its important ecosystem services is of great significance to improve the management level and ecological protection efficiency of the reserve. In the present study, we assessed the spatiotemporal variations of four ecosystem services (including net primary productivity (NPP), water yield, soil conservation, and habitat quality) in the TBPNR from 2000 to 2020 based on the environmental and social data using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model. In addition, the coldspot and hotspot areas of ecosystem services were identified by hotspot analysis, and the trade-off and synergistic relationships between ecosystem services were analyzed using factor analysis in a geographic detector. During the study period, NPP and soil conservation values in the reserve increased by 48.20% and 25.56%, respectively; conversely, water yield decreased by 16.56%, and there was no significant change in habitat quality. Spatially, both NPP and habitat quality values were higher in the northern part and lower in the southern part, whereas water yield showed an opposite trend. Correlation analysis revealed that NPP showed a synergistic relationship with habitat quality and soil conservation, and exhibited a trade-off relationship with water yield. Water yield and habitat quality also had a trade-off relationship. NPP and habitat quality were affected by annual average temperature and Normalized Difference Vegetation Index (NDVI), respectively, while water yield and soil conservation were more affected by digital elevation model (DEM). Therefore, attention should be paid to the spatial distribution and dynamics of trade-off and synergistic relationships between ecosystem services in future ecological management. The findings of the present study provide a reference that could facilitate the sustainable utilization of ecosystem services in the typical fragile areas of Northwest China.

Soil moisture (SM) is a critical variable in terrestrial ecosystems, especially in arid and semi-arid areas where water sources are limited. Despite its importance, understanding the spatiotemporal variations and influencing factors of SM in these areas remains insufficient. This study investigated the spatiotemporal variations and influencing factors of SM in arid and semi-arid areas of China by utilizing the extended triple collation (ETC), Mann-Kendall test, Theil-Sen estimator, ridge regression analysis, and other relevant methods. The following findings were obtained: (1) at the pixel scale, the long-term monthly SM data from the European Space Agency Climate Change Initiative (ESA CCI) exhibited the highest correlation coefficient of 0.794 and the lowest root mean square error (RMSE) of 0.014 m³/m³; (2) from 2000 to 2022, the study area experienced significant increase in annual average SM, with a rate of 0.408×10^-3 m³/(m³•a). Moreover, higher altitudes showed a notable upward trend, with SM increasing rates at 0.210×10^-3 m³/(m³•a) between 1000 and 2000 m, 0.530×10^-3 m³/(m³•a) between 2000 and 4000 m, and 0.760×10^-3 m³/(m³•a) at altitudes above 4000 m; (3) land surface temperature (LST), root zone soil moisture (RSM) (10-40 cm depth), and normalized difference vegetation index (NDVI) were identified as the primary factors influencing annual average SM, which accounted for 34.37%, 24.16%, and 22.64% relative contributions, respectively; and (4) absolute contribution of LST was more significant in subareas at higher altitudes, with average absolute contributions of 0.800×10^-3 m³/(m³•a) between 2000 and 4000 m and 0.500×10^-2 m³/(m³•a) above 4000 m. This study reveals the spatiotemporal variations and main influencing factors of SM in Chinese arid and semi-arid areas, highlighting the more pronounced absolute contribution of LST to SM in high-altitude areas, providing valuable insights for ecological research and water resource management in these areas.

The vegetation growth status largely represents the ecosystem function and environmental quality. Hyperspectral remote sensing data can effectively eliminate the effects of surface spectral reflectance and atmospheric scattering and directly reflect the vegetation parameter information. In this study, the abandoned mining area in the Helan Mountains, China was taken as the study area. Based on hyperspectral remote sensing images of Zhuhai No. 1 hyperspectral satellite, we used the pixel dichotomy model, which was constructed using the normalized difference vegetation index (NDVI), to estimate the vegetation coverage of the study area, and evaluated the vegetation growth status by five vegetation indices (NDVI, ratio vegetation index (RVI), photochemical vegetation index (PVI), red-green ratio index (RGI), and anthocyanin reflectance index 1 (ARI1)). According to the results, the reclaimed vegetation growth status in the study area can be divided into four levels (unhealthy, low healthy, healthy, and very healthy). The overall vegetation growth status in the study area was generally at low healthy level, indicating that the vegetation growth status in the study area was not good due to short-time period restoration and harsh damaged environment such as high and steep rock slopes. Furthermore, the unhealthy areas were mainly located in Dawukougou where abandoned mines were concentrated, indicating that the original mining activities have had a large effect on vegetation ecology. After ecological restoration of abandoned mines, the vegetation coverage in the study area has increased to a certain extent, but the amplitude was not large. The situation of vegetation coverage in the northern part of the study area was worse than that in the southern part, due to abandoned mines mainly concentrating in the northern part of the Helan Mountains. The combination of hyperspectral remote sensing data and vegetation indices can comprehensively extract the characteristics of vegetation, accurately analyze the plant growth status, and provide technical support for vegetation health evaluation.

Flash drought is characterized by a period of rapid drought intensification with impacts on agriculture, water resources, ecosystems, and human environment. In the Qilian Mountains, northwestern China, flash droughts are becoming more frequently due to the global climate warming. However, the spatiotemporal variations and their driving factors of flash droughts are not clear in this region. In this study, the European Centre for Medium-range Weather Forecasts (ECMWF) Reanalysis v5-Land (ERA5-Land) dataset was utilized to identify two types of flash drought events (heatwave-induced and water scarcity-induced flash drought events) that occurred in the growing season (April‒September) during 1981-2020 in this area. The results showed that the frequency of heatwave-induced flash droughts has decreased since 2010, while the frequency of water scarcity-induced flash droughts has declined markedly. Spatially, heatwave-induced flash droughts were predominantly concentrated in the western Qilian Mountains, whereas water scarcity-induced flash droughts were primarily concentrated in the central and eastern Qilian Mountains. A significantly increasing temporal trend in both types of flash droughts in the eastern Qilian Mountains was found. Meanwhile, there was a decreasing temporal trend of heatwave-induced flash droughts in the southwestern part of the region. Additionally, the influence of two major atmospheric modes, i.e., the El Niño‒Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO), on these two types of flash droughts was explored by the Superposed Epoch Analysis. The ENSO mainly influences flash droughts in the central and eastern parts of the Qilian Mountains by altering the strength of the East Asian monsoon, while the NAO mainly affects flash droughts in the entire parts of the Qilian Mountains by inducing anomalous westerlies activity. Our findings have important implications for predicting the evolution of flash drought events in the Qilian Mountains region under continued climate warming.

Perennial grass-legume mixtures have been extensively used to restore degraded grasslands, increasing grassland productivity and forage quality. Tillage is crucial for seedbed preparation and sustainable weed management for the establishment of grass-legume mixtures. However, a common concern is that intensive tillage may alter soil characteristics, leading to losses in soil organic carbon (SOC). We investigated the plant community composition, SOC, soil microbial biomass carbon (MBC), soil enzyme activities, and soil properties in long-term perennial grass-legume mixtures under two different tillage intensities (once and twice) as well as in a fenced grassland (FG). The establishment of grass-legume mixtures increased plant species diversity and plant community coverage, compared with FG. Compared with once tilled grassland (OTG), twice tilled grassland (TTG) enhanced the coverage of high-quality leguminous forage species by 380.3%. Grass-legume mixtures with historical tillage decreased SOC and dissolved organic carbon (DOC) concentrations, whereas soil MBC concentrations in OTG and TTG increased by 16.0% and 16.4%, respectively, compared with FG. TTG significantly decreased the activity of N-acetyl-β-D-glucosaminidase (NAG) by 72.3%, whereas soil enzyme β-glucosidase (βG) in OTG and TTG increased by 55.9% and 27.3%, respectively, compared with FG. Correlation analysis indicated a close association of the increase in MBC and βG activities with the rapid decline in SOC. This result suggested that MBC was a key driving factor in soil carbon storage dynamics, potentially accelerating soil carbon cycling and facilitating biogeochemical cycling. The establishment of grass-legume mixtures effectively improves forage quality and boosts plant diversity, thereby facilitating the restoration of degraded grasslands. Although tillage assists in establishing legume-grass mixtures by controlling weeds, it accelerates microbial activity and organic carbon decomposition. Our findings provide a foundation for understanding the process and effectiveness of restoration management in degraded grasslands.

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