Sand and dust storms (SDSs) are natural disasters that frequently occur during spring in arid and semi-arid areas., causing serious impacts on human health, air quality, transportation, and agricultural production. Accurately simulating the occurrence and evolution of SDSs is of great significance for identifying dust sources and formulating effective disaster prevention measures. In this study, numerical simulations were conducted to reveal the dynamic spatiotemporal evolution and transport of dust load across East Asia. Using the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) and European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) data, the most severe SDS events in the spring of 2023 in East Asia were numerically simulated. The simulated results were compared and validated using meteorological observations and multisource remote sensing data. The results showed that the simulated dust load in the peak regions showed close agreement with ground-based observations during the events. The primary dust sources in spring 2023 were identified as the western desert of Mongolia, the Gobi Desert, and the Taklimakan Desert in Xinjiang Uygur Autonomous Region of China. Peak dust load and maximum wind speed occurred almost simultaneously, indicating that high wind speed was the primary driver of sand and dust mobilization during individual SDS events. Increased surface vegetation covers partially mitigated wind-driven dust emissions. In April, strong winds over the Gobi Desert on the Mongolian Plateau predominantly drove cross-border SDSs along northwestern and northward transport pathways. Dust originating from Mongolia exerts a substantial influence on particulate dust load in the central and eastern parts of Inner Mongolia Autonomous Region of China. In contrast, their impact on the northwestern regions of China remains relatively limited. These findings contribute to understanding the source areas of SDS events in East Asia by simulating the dynamic evolution of SDSs and elucidating the relationships between SDS events and local geographical and environmental factors.

Sand control engineering plays a pivotal role in ensuring the safe operation of transportation corridors that traverse desertified areas. Evaluating the effectiveness of these interventions provides a crucial scientific basis for mitigating aeolian hazards and guiding the sustainable management of fragile and arid ecosystems. In this study, we investigated a representative section of Highway S315, which is prone to windblown sand hazards, in Ejin Banner, northern China. By integrating segmented measurements with unmanned aerial vehicle (UAV)-based oblique photogrammetry, we quantitatively characterized the spatial and temporal evolution of sand accumulation around multiple sand control structures and assessed their blocking efficiency. Complementary road sand-removal records and meteorological observations were analyzed to evaluate the long-term performance of engineering measures. Our results showed that sand accumulation behind high vertical sand barriers typically exhibited a triangular cross-sectional morphology, with a gently inclined stoss slope and a steep lee slope. The shape and volume of these deposits evolved dynamically in response to variations in the prevailing wind regime, reflecting strong feedback between barrier geometry and local airflow redistribution. In contrast, the low-profile checkerboard sand barriers displayed a three-stage morphological trajectory—initial accumulation, edge intensification, and functional decline—indicating a progressive loss of sand-trapping capacity as burial proceeded. Sand accumulation was markedly greater on the highway's western (upwind) side than on the eastern (downwind) side, with 70.0%-90.0% of the airborne sediment flux intercepted by the upwind structures. From 2015 to 2020, mean annual wind speeds remained stable (2.68±0.04 m/s), while precipitation varied from 22.6 to 103.7 mm. However, the annual sand removal volume from the road decreased consistently, confirming the enhanced mitigation effect of multi-level protective system. These findings highlight the coupled interactions between engineering design, wind-sand dynamics, and topographic context. Beyond their immediate protective role, well-designed sand control systems also contribute to the prevention of regional desertification by stabilizing mobile dunes and fostering conditions favorable for ecological restoration. The insights gained here provide both theoretical and practical support for optimizing sand control engineering and advancing sustainable hazard mitigation in arid and semi-arid areas.

Aeolian sediments in the eastern Qinghai Lake region, China serve as sensitive paleoclimate archives, offering an ideal window into past environmental conditions. This study investigated the Dashuitang (QDST) profile in the eastern Qinghai Lake region by integrating sediment grain size, chroma, and magnetic susceptibility (MS) proxies to reconstruct the regional environmental evolution since the Last Glacial Interstadial and to investigate its relationship with the water level fluctuations of Qinghai Lake. Grain size end-member modeling analysis (EMMA) identified three end-members: end-member 1 (EM1) represented fine-grained material transported over longer distances through mixing processes, which could reveal the regional moisture conditions; end-member 2 (EM2) primarily consisted of coarse-grained material from nearby sources transported via saltation or creep, indicating the intensity of the winter monsoon; and end-member 3 (EM3) mainly reflected deposition from dust storm events controlled by regional low-altitude wind systems. In addition, the regional environmental sequence demonstrated coherence with other records, collectively elucidating the sub-orbital-scale dynamics of the Asian monsoon. The environmental sequence was divided into four principal phases on the basis of sedimentary characteristics and climatic responses: the late Last Glacial Interstadial, Last Glacial Maximum, Last Deglaciation, and Holocene phases. Additionally, the results of this study revealed that there is a close linkage between desertification and lake evolution in the eastern Qinghai Lake region. Since the Last Glacial Interstadial, desertification and lake evolution processes have generally exhibited a trade-off relationship, wherein lake level decline and desert expansion exhibited a direct positive feedback. However, during the early period of the Late Holocene (approximately 2.80-1.50 ka BP), a synergistic response pattern emerged, characterized by relatively high lake levels alongside moderate desert expansion, reflecting an asymmetric decoupling mechanism between the hydrological processes and aeolian dynamics during climatic transition periods. This study provides important insights for predicting the future evolution trends of lake-desert systems under climate change.

Northwest China serves as a critical ecological barrier region for maintaining national water, energy, and food security, as well as transboundary ecological governance. However, under the dual pressures of climate change and human activities, ecosystem services (ESs) are facing severe challenges in this region. Based on multi-source remote sensing and statistical data during 2000-2020, this study investigated the spatiotemporal evolution characteristics of four key ESs (water yield, habitat quality, carbon storage, and food provisioning) in Northwest China using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. Integrating morphological spatial pattern analysis (MSPA) and circuit theory, we identified ecological sources, corridors, pinch points, and barriers, and further designed three optimization scenarios (bottleneck optimization, high-resistance corridor buffering, and barrier removal optimization) to enhance landscape connectivity. The results revealed that ES supply and demand exhibited marked spatial heterogeneity, with high-supply areas concentrated in the southeastern sectors. Ecological sources primarily distributed in the southeastern and northern sectors, and ecological resistance surfaces continuously intensified. Water yield and habitat quality demands were increasing, food provisioning demand was decreasing, and carbon storage demand was surging. A total of 61 ecological sources (8% of the study area), 142 ecological corridors (24,957 km in total length), 237 ecological pinch points, and 89 barrier zones were identified. Among the three optimization scenarios, barrier removal achieved optimal connectivity improvement across all distance thresholds, with the probability of connectivity index improvement reaching up to 4%. This study provides scientific foundations and spatial decision support for ecological network optimization and sustainable governance in arid and semi-arid areas.

Within the context of global climate change and rapid urbanization, increasing urban resilience (UR) is especially important in the arid region of Northwest China (ANC), where fragile ecosystems and an uneven water distribution create significant sustainability challenges. In this study, a coupled UR-water ecosystem services (WESs) framework was developed on the basis of 1-km resolution remote sensing data for the 2000-2020 period obtained from the Landsat series, Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS), and Global Precipitation Measurement (GPM), among other sources. Within the framework, the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was incorporated to provide a WES indicator system. Moreover, entropy weighting was employed to quantify both UR and WES indicators; the coupling coordination degree (CCD) model was used to measure the coupled relationship between UR and WESs; an extreme gradient boosting (XGBoost)-SHapley Additive exPlanations (SHAP) interpretation approach was adopted to identify key drivers and underlying mechanisms; and Geographically Weighted Regression (GWR) was applied to capture spatial distribution characteristics of major driving factors. The results indicated that UR steadily increased from 4.60×10^-3 to 10.24×10^-3, whereas WESs followed an inverted V-shaped trend, with a peak value observed in 2010 (11.84×10^-3). The CCD remained consistently low (mean: 0.0166-0.0246) and exhibited considerable spatial heterogeneity. Notably, the degree of coordination was greater in the oasis and mountain core areas but significantly lower at desert areas. XGBoost-SHAP model analysis revealed six key drivers influencing various states of the CCD between UR and WESs systems. The contributions of these factors could be ranked as follows: water yield (WY; 24.30%)>farmland area per capita (FP; 21.10%)>gross domestic product (GDP) per capita (GDPC; 19.00%)>soil retention (SR; 14.90%)>population density (PD; 5.42%)>water purification (WP; 4.40%). In contrast, in UR system, WP (53.66%) and SR (31.62%) served as the dominant drivers. Moreover, the dominant drivers shifted from a combination of natural and socioeconomic factors in State I (sustainable high resilience) to primarily socioeconomic factors in State III (unsustainable low resilience). SR and WP exerted positive moderating effects, whereas socioeconomic factors such as GDPC and PD exerted inhibitory effects on the coordination relationship. This research highlights that UR in the ANC region is limited mainly by water scarcity, weak feedback loops, and spatial variability, emphasizing the need for tailored intervention strategies.

Terrestrial ecosystems are vital for maintaining equilibrium in the global carbon cycle. Land use and land cover change (LUCC), which is influenced mainly by urbanization and ecological policies, impacts terrestrial ecosystem carbon storage significantly. In this study, spatiotemporal carbon storage changes in the urban belt along the Yellow River in the Ningxia Hui Autonomous Region, China, were estimated through a model that integrated patch-generating land use simulation (PLUS) and integrated valuation of ecosystem services and tradeoffs (InVEST) models from 1993 to 2033. The results revealed that: (1) from 1993 to 2023, the expansion of built-up land and cropland was derived mainly from unused land and grassland, whereas water body and woodland remained relatively stable. Projections to 2033 have indicated that LUCC will continue and be concentrated primarily in the Ningxia Plain; (2) carbon storage increased by a net 5.01×10⁶ Mg C from 1993 to 2023; (3) the spatial distribution of carbon storage revealed that high-value areas were predominantly located in the Helan Mountains and the Ningxia Plain, whereas low-value areas were found in the Tengger Desert; (4) scenario projections indicated that by 2033, the ecological protection scenario (EPS) would achieve a 0.18×10⁶ Mg C increase by reducing the conversion of woodland to cropland and grassland to built-up land, while increasing the conversion of unused land to grassland. In contrast, the natural development scenario (NDS), cropland protection scenario (CPS), and urban development scenario (UDS) decreased carbon storage by 0.60×10⁶, 0.21×10⁶, and 0.42×10⁶ Mg C, respectively; and (5) spatial autocorrelation analysis revealed that high-high carbon storage clusters formed belt-like patterns along the Ningxia Plain and the Helan Mountains, whereas the low-low carbon storage clusters were concentrated in northern Zhongwei City, western Qingtongxia City, western Dawukou District, and the urbanized areas within the central Ningxia Plain. Overall, the study results revealed the close coupling relationship between LUCC and carbon storage functions. Furthermore, the study establishes a framework for carbon management that balances ecological protection with coordinated urban development for the urban belt as well as for similar arid and semi-arid areas. On the basis of these findings, this study provides decision-makers with guidance to optimize ecosystem carbon storage via land use, which plays a key role in developing future land use policies and achieving the ''dual carbon'' goals.

Soil aggregation is a fundamental process that influences various soil properties, including structure, porosity, water infiltration, and resistance to erosion. In the Caatinga biome, preserving the soil's physical quality is crucial to the development of sustainable agriculture. In this biome, soil aggregation is critical due to the susceptibility of the semi-arid area to erosion and degradation. This study aims to evaluate the impact of converting native vegetation (NV; dense Caatinga) into two grasslands and two integrated livestock-forestry (ILF) systems on soil organic carbon (SOC) content and soil physical quality through water-stable aggregate (WSA) classes (macroaggregates, mesoaggregates, and microaggregates) and aggregation indices (mean weight diameter (MWD), geometric mean diameter (GMD), and aggregate stability index (ASI)). Soil samples were collected at 0-10, 10-20, 20-30, 30-50, 50-70, and 70-100 cm layers in Nossa Senhora da Glória Municipality, Sergipe State, Brazil. The land use systems analyzed in this study included NV, an ILF system with Gliricidia (Gliricidia sepium (Jacq.) Kunth ex Walp.)+Urochloa (Urochloa decumbens (Stapf) R.D. Webster) under no-tillage (ILFug), another ILF system with Gliricidia+forage cactus (Opuntia cochenillifera (Linnaeus) Miller) under convention tillage (ILFcg), improved pasture (ImpP), and degraded pasture (DegP). Almost all parameters studied were significantly correlated with SOC content, demonstrating that soil organic matter (SOM) is a primary agent in binding soil particles together, influencing the variation in WSA and aggregation indices. The ImpP and DegP exhibited similar SOC content; however, the ImpP showed a higher ASI and increased amount of macroaggregates (particle diameter>2.000 mm). The highest SOC content was found in the ILFug system across the soil profile. There was a predominance of macroaggregates in topsoil (0-10 cm layer) regardless of land use, with the highest proportion found in NV (78.7%); while the lowest was observed in the ILFcg system (59.0%). The ILFug system also showed the greatest ASI at almost all soil layers; the exception was the 0-10 and 50-70 cm layers, where the NV had the highest values of 89.1% and 90.5%, respectively. This study demonstrates that implementing integrated systems under no-tillage as a nature-based solution can enhance SOC content and stability of soil aggregates in semi-arid environments.

In the arid regions of Northwest China, vegetation cover plays a crucial role in maintaining unique terrestrial ecosystems. Vegetation growth is highly sensitive to variations in topographical factors, and the influence of topography on vegetation cover has attracted increasing attention. This study analyzed vegetation dynamics and their relationship with topography in the Tianshan Mountains of China using Landsat Normalized Difference Vegetation Index (NDVI) data during 2000-2022 and Shuttle Radar Topography Mission (SRTM)-derived topographical factors (elevation, slope, and aspect). Theil-Sen slope estimation and Mann-Kendall trend tests were applied to quantify temporal changes in vegetation, while a terrain area correction coefficient (K) was used to assess spatial associations of vegetation with topography. Random Forest (RF) regression and SHapley Additive exPlanations (SHAP) analysis evaluated the relative importance of topographical factors in shaping vegetation cover (multi-year mean NDVI) distribution. Key findings included that over the 23-a period, 59.46% of the vegetated area exhibited significant improvement (P<0.05), with the southern Tianshan Mountains showing the most pronounced increase (70.59%), whereas vegetation degradation (3.10%) was primarily concentrated in river valleys with intensive human activities. RF-SHAP analysis revealed that elevation is the primary driver of vegetation cover patterns, explaining 52.00% of the NDVI variation. The peak NDVI (0.42) occurred at elevations between 2800 and 3200 m. Slope and aspect also significantly influenced vegetation distribution, and higher NDVI values and greater improvement trends were observed on shady (north-facing) slopes compared to sunny (south-facing) slopes. K-index analysis indicated pronounced vegetation change—both degradation and improvement—in areas with elevations between 1100 and 2800 m and slopes exceeding 5°, particularly on sunny slopes. Low-elevation desert areas in the southern Tianshan Mountains were highly susceptible to degradation. This study underscores the critical role of topography in regulating vegetation cover and its spatiotemporal dynamics, providing a scientific basis for sustainable management of arid mountain ecosystems.

Soil water content and salinity critically regulate soil microbial composition, plant community structure, and ecosystem multifunctionality (EMF) in semi-arid grasslands. However, the mechanisms through which drought (D), saline-alkaline (SA), and their combined (DSA) stress influence these ecological components remain poorly understood. This study investigated these mechanisms along natural gradients in a semi-arid grassland of China by analyzing soil physical-chemical properties, microbial communities, and vegetation characteristics. The results showed that as the environmental stress shifted from the D group to the DSA group and then to the SA group, soil electrical conductivity significantly increased, while urease and phosphatase activities significantly decreased. Soil organic carbon, total nitrogen, total phosphorus, and microbial biomass carbon and nitrogen were lower in the D and SA groups than in the DSA group. Meanwhile, plant biomass showed an increasing trend along the treatment gradient, primarily driven by dominant species, while plant diversity did not exhibit significant differences. Further analysis identified the soil water content and salinity as the key determinants of soil microbial diversity and community complexity. Soil enzyme activities exhibited contrasting relationships with microbial composition, correlating positively with the richness of bacterial amplicon sequence variants (ASVs) but negatively with the richness of fungal ASVs. Notably, microbial biomass, which varied significantly across different groups, emerged as a key predictor of changes in EMF, with its critical role confirmed through structural equation modeling. These findings collectively elucidate the responses of ecological communities to synergistic soil hydro-saline stress in semi-arid ecosystems, while highlighting the critical role of microbial biomass in maintaining EMF.