喜马拉雅山拥有全球中低纬度带规模最大的山地冰川群，其冰川补给直接影响南亚水系水资源安全。全球变暖背景下，喜马拉雅山冰川响应存在空间分异特征，但21世纪以来冰川动态演化路径及其水文效应仍存在整体上的认知空白。本研究利用偏差校正的CMIP6气候数据集与改进型Global PyGEM-OGGM模型，综合考虑冰川动力学过程与表碛热力学效应，分析预测2000—2100年SSP2-4.5和SSP5-8.5情景下喜马拉雅山冰川系统多参数响应。结果表明：(1)经偏差校正后，CMIP6多模式集合数据在喜马拉雅山的适用性显著提升(1961—2014年),气温(偏差：-0.02℃,均方根误差：0.41℃)和降水(偏差：-22.31 mm,均方根误差：136.55 mm)的模拟误差显著降低，同时基于多源卫星融合数据验证的Global PyGEM-OGGM冰川数据集(2000—2019年)在冰川质量变化时空模拟中表现优异(相关系数分别为0.59、0.99,均方根误差为0.97 Gt、0.002 Gt),证实二者可为区域气候变化与冰川物质平衡研究提供可靠数据支撑。(2)在SSP2-4.5和SSP5-8.5情景下，...

The Tibetan Plateau (TP) covers the largest regions under low- and mid-latitude permafrost. The evolution of permafrost has significantly affected the hydrology, biogeochemistry, and infrastructure of Asia. However, model reconstructions of long-term permafrost evolution with high accuracy and reliability are insufficient. Here, spatial changes in mean annual ground temperature at the depth where the annual amplitude is zero (MAGT) on the TP since 1981 were modeled and validated based on temperature records from 155 boreholes, and future changes were predicted under scenarios from the Climate Model Intercomparison Project 6 (CMIP6). The results indicated that the MAGT on the TP was approximately 1.5 degrees C (2010 - 2018), and the corresponding permafrost extent on the TP is estimated to be approximately 1.03 x 106 km2, which is projected to decrease to 0.77 x 106, 0.50 x 106, 0.30 x 106, and 0.17 x 106 km2 under the scenarios of shared socioeconomic pathway (SSP)126, SSP245, SSP370, and SSP585, respectively, by 2100. As predicted in the SSP585 scenario, permafrost is predicted to largely disappear from many basins of major Asian rivers, such as the Yarlung Zangpo-Brahmaputra, NuSalween, and Lancang-Mekong Rivers, between 2041 and 2060, followed by the Yellow and Yangtze Rivers between 2061 and 2080. Moreover, the original stable permafrost in the West Kunlun Mountains will change to transitional and unstable conditions. Our study offers comprehensive datasets of year-to-year ground temperatures and permafrost extent maps for the TP, which can serve as a fundamental resource for further investigations on the hydrogeology, engineering geology, ecology, and geochemistry of the TP.

An experimental study was carried out to understand the physico-chemical and mechanical properties of marine clay reconstituted with different pore fluids. Three different pore fluids namely distilled water, 0.4 M NaCl and 1.0 M NaCl solutions, and 0.4 M CaCl2 solution were used in this study. The specimens were prepared using a 1D slurry consolidation technique at 50 kPa vertical pressure. This paper mainly includes the microstructural studies conducted using Scanning electron microscopic (SEM) images and Mercury intrusion porosimetry (MIP) tests. Furthermore, cyclic triaxial and resonant column tests were carried out on the marine clay specimens reconstituted with 0.4 M NaCl and 0.4 M CaCl2 solutions subjected to different confining pressures. The experimental results illustrated that with an increase in concentration of pore fluid the cyclic properties of reconstituted Chennai marine clay increases for strain amplitude varying between 0.001 and 1%.

Tylenchulus semipenetrans is a soil-borne pathogen that causes substantial damage and economic losses to citrus crops worldwide. Due to the high toxicity of chemical nematicides to humans and the environment, biocontrol bacteria have emerged as a promising alternative for managing citrus nematodes. This study aimed to screen bacterial strains for their efficacy to control T. semipenetrans and assess their impact on citrus plant growth. A total of 107 bacterial strains were isolated from the soil and roots of infested citrus trees. Among these, five strains exhibited significant nematicidal activity against T. semipenetrans. Four bacterial densities were tested for each strain: 3.6 x 10(5), 2.5 x 10(4), 3.6 x 10(3), and 1.2 x 10(3) cells/ml. These strains were tested both individually and in combination to evaluate their efficacy. The five strains were identified as Variovorax paradoxus, Bacillus pseudomycoides, Bacillus simplex, Bacillus cereus, and Paracoccus speluncae based on physiological, biochemical, and molecular (16S rRNA gene sequences) analyses. Juvenile mortality (J2s) and egg hatching inhibition were positively correlated with bacterial concentration and exposure duration. The highest juvenile mortality (100%) was observed with a combination of all five bacteria (3.6 x 10(5) cells/ml) after 96 h, while B. cereus alone achieved 98.98% mortality. The maximum nematicidal activities of the bacterial filtrates were generally observed between the 4th and 6th days of incubation, coinciding with peak bacterial growth and biomass production. The selected isolates also demonstrated the ability to produce indole acetic acid and solubilize phosphorus. In greenhouse experiments, the five isolates reduced T. semipenetrans populations by up to 62.96% compared to the control. Additionally, all rhizosphere bacteria and their combination significantly enhanced plant growth parameters (p < 0.0001). Notably, P. speluncae BR21 has not previously been tested for nematicidal effects on any nematode, making this the first documented report of its nematicidal potential.

Background: Pesticide residues can cause chronic toxicity to the human body and lead to a series of diseases that damage the liver. Therefore, developing a highly sensitive, selective, and low-cost pesticide residues detection method is of great significance for protecting human health and safety. Nowadays, commonly used methods for pesticide residue detection include gas chromatography, high-performance liquid chromatography, and fluorescence sensing. These methods have some typical shortcomings, such as long sample pretreatment time, expensive instruments, and poor controllability. It was thought that a sensing platform based on electrochemical analysis method and functional DNA molecules can eliminate the above drawbacks. Results: Herein, this study developed a simple and label-free electrochemical aptasensor based on a triple- stranded DNA molecular switch. Acetamiprid (ACE) was served as the analytical model, and its binding with the aptamer opened the triple-stranded DNA molecular switch, resulting in the in-situ formation of G-quadruplex/hemin complexes on the electrode surface, obtaining a significantly enhanced electrochemical signal and achieving high specificity and label-free detection of ACE, with a detection limit as low as 4.67 x 10-3 nM (S/N = 3). In addition, due to the specific recognition between the aptamer and the target, the aptasensor effectively avoided the interference of other pesticides and exhibited good specificity. Moreover, benefiting from the pH switchable of the triple-stranded DNA molecular switch and the programmability of DNA molecules, OR logic gate and OR-INHIBIT cascade logic circuit were successfully implemented. Significance: The proposed electrochemical aptasensor exhibited good accuracy and sensitivity in detecting acetamiprid in vegetable soil sample, indicating its practicality in the detection of pesticide residues in actual samples. Furthermore, the sensing system was reasonably programmed and successfully operated an OR logic gate and an OR-INHIBIT cascade logic circuit, demonstrating its potential application in intelligent sensing.

Surface albedo (SA) is crucial for understanding land surface processes and climate simulation. This study analyzed SA changes and its influencing factors in Central Asia from 2001 to 2020, with projections 2025 to 2100. Factors analyzed included snow cover fraction, fractional vegetation cover, soil moisture, average state climate indices (temperature and precipitation), and extreme climate indices (heatwave indices and extreme precipitation indices). Pearson correlation coefficient, geographical convergent cross mapping, and geographical detector were used to quantify the correlation, causal relationship strength, and impact degree between SA and the influencing factors. To address multicollinearity, ridge regression (RR), geographically weighted ridge regression (GWRR), and piecewise structural equation modeling (pSEM) were combined to construct RR-pSEM and GWRR-pSEM models. Results indicated that SA in Central Asia increased from 2001 to 2010 and decreased from 2011 to 2020, with a projected future decline. There is a strong correlation and significant causality between SA and each factor. Snow cover fraction was identified as the most critical factor influencing SA. Average temperature and precipitation had a greater impact on SA than extreme climate indices, with a 1 degrees C temperature increase corresponding to a 0.004 decrease in SA. This study enhances understanding of SA changes under climate change, and provides a methodological framework for analyzing complex systems with multicollinearity. The proposed models offer valuable tools for studying interrelated factors in Earth system science.

Flash floods represent a significant threat, triggering severe natural disasters and leading to extensive damage to properties and infrastructure, which in turn results in the loss of lives and significant economic damages. In this study, a comprehensive statistical approach was applied to future flood predictions in the coastal basin of North Al-Abatinah, Oman. In this context, the initial step involves analyzing eighteen General Circulation Models (GCMs) to identify the most suitable one. Subsequently, we assessed four CMIP6 scenarios for future rainfall analysis. Next, different Machine Learning (ML) algorithms were employed through H2O-AutoML to identify the best model for downscaling future rainfall predictions. Forty distribution functions were then fitted to the future daily rainfall, and the best-fit model was selected to project future Intensity-Duration-Frequency (IDF) curves. Finally, the Soil and Water Assessment Tool (SWAT) model was utilized with sub-daily time steps to make accurate flash flood predictions in the study area. The findings reveal that IITM-ESM is the most effective among GCM models. Additionally, the application of stacked ensemble ML model proved to be the most reliable in downscaling future rainfall. Furthermore, this study highlighted that floods entering urbanized areas could reach 20.33 and 20.70 m(3)/s under pessimistic scenarios during rainfall events with 100 and 200-year return periods, respectively. This hierarchical comprehensive approach provides reliable results by utilizing the most effective model at each step, offering in-depth insight into future flash flood prediction.

Soil improvement via cement-based stabilizers is often necessary to improve the workability and strength of problematic soils. However, understanding the underlying mechanisms of the stabilization process merits further study, particularly concerning changes in the microscale structure that affect macroscale behavior. Mercury intrusion porosimetry (MIP) and scanning electron microscopy (SEM) are often paired to characterize the microstructure and pore networks and can be used to quantitatively describe pore structure and surface complexity. Fractal geometry (e.g., fractal dimension and lacunarity) has been shown to provide a quantitative description of structural complexity in nature. Therefore, these fractal geometry fundamentals (fractal dimension and lacunarity) were implemented in the analysis of SEM micrographs and MIP results of a single-mineral kaolinitic soil (SA-1 kaolinite) stabilized with a portland cement stabilizer (portland cement Type I/II) to better understand the evolution of the soil microstructure with curing time. Particle size distributions (PSD) were developed based on image analysis of SEM micrographs collected at curing times of 1, 7, 14, 28, and 90 days. The surface fractal dimension obtained via analysis of MIP results was used to describe changes occurring in the pore network with curing time. The formation of cementitious products was inferred from changes in the PSD as gels first formed and then fused with clay surfaces. Box-counting fractal dimensions and lacunarity showed evidence of particle restructuring with cementation. The transition pore size between intraaggregate and interaggregate pores, obtained via fractal analysis of MIP data, decreased with curing time, indicating the formation of hydration products with stabilization. Using fractal geometry to help analyze the microstructural properties of stabilized clays may lead to better insight into their engineering scale behavior. Problematic soils pose an expensive problem to engineers and are often treated with cement-based stabilizers to improve strength and decrease compressibility or the potential to deform or collapse. However, the underlying mechanism causing problematic behavior, such as low strength or shrinking and swelling, is not well understood and techniques to characterize these soils at the microscopic level are needed to better prevent the damage posed to infrastructure. The current standard of practice utilizes only qualitative measurements of the soil structure and cannot be used in models attempting to predict clay behavior. Therefore, concepts from fractal geometry were used in this study to provide a quantitative, measured value of the soil and pore surface which can be used in future models. Analysis of images at the microscale provided a quantitative measurement of the change in soil structure as stabilization reactions occurred. Moreover, the geometric parameters obtained showed strong correlations with strength values, indicating the utility of the technique for predicting engineering behavior. The results of this study show promise for adapting the box-counting procedure to other, more complex soils. Additionally, because there was a good correlation between the fractal parameters and strength, the results should be correlated with other soil parameters.

Snow is an important factor controlling vegetation functions in high latitudes/altitudes. However, due to the lack of reliable in -situ measurements, the effects of snow on vegetation phenology remains poorly understood. Here, we examine the effects of snow cover duration (SCD) on the start of growing season (SOS) for different vegetation types. SOS and SCD were extracted from in -situ carbon flux and albedo data, respectively, at 51 eddy covariance flux sites in the northern mid -high latitudes. The effects of SCD on SOS vary substantially among different vegetation types. For grassland, preseason SCD outperforms other factors controlling grassland SOS. However, for forests and cropland, the preseason air temperature is the dominant factor in controlling SOS. Preseason SCD mainly influences the SOS by regulating preseason air and soil temperature rather than soil moisture. The CMIP6 Earth system models (ESMs) fail to capture the effect of SCD on SOS. Thus, Random Forest (RF) models were established to predict future SOS changing trends considering the effect of SCD. For grassland and evergreen needleleaf forest, the projected SOS advance rate is slower when SCD is considered. These findings can help us better understand impacts of snow on vegetation phenology and carbon -climate feedbacks in the warming world.

Permafrost degradation on the Tibetan Plateau (TP) is anticipated to result in the thaw of permafrost carbon. Existing studies have been conducted to assess the future thaw of frozen carbon on the TP, primarily focusing on the deepening of the active layer while neglecting the impact of permafrost area shrinkage. This oversight may lead to a significant underestimation of the potential thaw of frozen carbon. Our research underscores the pivotal role of permafrost area shrinkage in estimating the future thaw of frozen carbon. Our findings reveal that when the combined effects of permafrost area shrinkage and active layer deepening are considered, the thaw rates of frozen carbon in various radiative forcing scenarios are nearly four times those based on active layer deepening alone. Notably, our results demonstrate substantial thaw of frozen organic carbon in the TP permafrost area under all four future scenarios: In the low radiative forcing scenario SSP1-2.6, it is predicted that 55.4 % of the organic carbon in the permafrost area 0-10 m soils will be in a state of thaw by 2100, and more than 90 % in the high radiative forcing scenario SSP5-8.5. This substantial thaw is poised to diminish the TP's current carbon sink function significantly. Our study emphasizes that as global warming persists, frozen carbon in permafrost areas will play a more active role in global carbon cycle processes in the future. Furthermore, we stress the importance of considering permafrost area shrinkage in understanding the thaw of frozen carbon, providing valuable insights for carbon balance studies on the TP.