Countries in the Middle Eastern and North African (MENA) region are among the most water-scarce regions in the world, and their dryland soils are usually poor in organic carbon content (<0.5%). In this study, we su...Countries in the Middle Eastern and North African (MENA) region are among the most water-scarce regions in the world, and their dryland soils are usually poor in organic carbon content (<0.5%). In this study, we summarize examples of how people in the few oases of the MENA region overcome environmental challenges by sustainably managing economically important date production. On the basis of the limited studies found in the existing literature, this mini-review focuses on the role of traditional soil organic matter amendments beneath the soil surface as a key tool in land restoration. We conclude that soil organic matter amendments can be very successful in restoring soil water and preventing the soil from salinization.展开更多
Forest soil carbon is a major carbon pool of terrestrial ecosystems,and accurate estimation of soil organic carbon(SOC)stocks in forest ecosystems is rather challenging.This study compared the prediction performance o...Forest soil carbon is a major carbon pool of terrestrial ecosystems,and accurate estimation of soil organic carbon(SOC)stocks in forest ecosystems is rather challenging.This study compared the prediction performance of three empirical model approaches namely,regression kriging(RK),multiple stepwise regression(MSR),random forest(RF),and boosted regression trees(BRT)to predict SOC stocks in Northeast China for 1990 and 2015.Furthermore,the spatial variation of SOC stocks and the main controlling environmental factors during the past 25 years were identified.A total of 82(in 1990)and 157(in 2015)topsoil(0–20 cm)samples with 12 environmental factors(soil property,climate,topography and biology)were selected for model construction.Randomly selected80%of the soil sample data were used to train the models and the other 20%data for model verification using mean absolute error,root mean square error,coefficient of determination and Lin's consistency correlation coefficient indices.We found BRT model as the best prediction model and it could explain 67%and 60%spatial variation of SOC stocks,in 1990,and 2015,respectively.Predicted maps of all models in both periods showed similar spatial distribution characteristics,with the lower SOC in northeast and higher SOC in southwest.Mean annual temperature and elevation were the key environmental factors influencing the spatial variation of SOC stock in both periods.SOC stocks were mainly stored under Cambosols,Gleyosols and Isohumosols,accounting for 95.6%(1990)and 95.9%(2015).Overall,SOC stocks increased by 471 Tg C during the past 25 years.Our study found that the BRT model employing common environmental factors was the most robust method for forest topsoil SOC stocks inventories.The spatial resolution of BRT model enabled us to pinpoint in which areas of Northeast China that new forest tree planting would be most effective for enhancing forest C stocks.Overall,our approach is likely to be useful in forestry management and ecological restoration at and beyond the regional scale.展开更多
Due to the recent system developments for the electromagnetic characterization of the subsurface, fast and easy acquisition is made feasible due to the fast measurement speed, easy coupling with GPS systems, and the a...Due to the recent system developments for the electromagnetic characterization of the subsurface, fast and easy acquisition is made feasible due to the fast measurement speed, easy coupling with GPS systems, and the availability of multi-channel electromagnetic induction（EMI） and ground penetrating radar（GPR） systems. Moreover, the increasing computer power enables the use of accurate forward modeling programs in advanced inversion algorithms where no approximations are used and the full information content of the measured data can be exploited. Here, recent developments of large-scale quantitative EMI inversion and full-waveform GPR inversion are discussed that yield higher resolution of quantitative medium properties compared to conventional approaches. In both cases a detailed forward model is used in the inversion procedure that is based on Maxwell＇s equations. The multi-channel EMI data that have different sensing depths for the different source-receiver offset are calibrated using a short electrical resistivity tomography（ERT） calibration line which makes it possible to invert for electrical conductivity changes with depth over large areas. The crosshole GPR full-waveform inversion yields significant higher resolution of the permittivity and conductivity images compared to ray-based inversion results.展开更多
The accurate quantification and source partitioning of CO_(2)emitted from carbonate(i.e.,Haplustalf)and non-carbonate(i.e.,Hapludult)soils are critically important for understanding terrestrial carbon(C)cycling.The tw...The accurate quantification and source partitioning of CO_(2)emitted from carbonate(i.e.,Haplustalf)and non-carbonate(i.e.,Hapludult)soils are critically important for understanding terrestrial carbon(C)cycling.The two main methods to capture CO_(2)released from soils are the alkali trap method and the direct gas sampling method.A 25-d laboratory incubation experiment was conducted to compare the efficacies of these two methods to analyze CO_(2)emissions from the non-carbonate and carbonate-rich soils.An isotopic fraction was introduced into the calculations to determine the impacts on partitioning of the sources of CO_(2)into soil organic carbon(SOC)and soil inorganic carbon(SIC)and into C3 and/or C4 plant-derived SOC.The results indicated that CO_(2)emissions from the non-carbonate soil measured using the alkali trap and gas sampling methods were not significantly different.For the carbonate-rich soil,the CO_(2)emission measured using the alkali trap method was significantly higher than that measured using the gas sampling method from the 14 th day of incubation onwards.Although SOC and SIC each accounted for about 50%of total soil C in the carbonate-rich soil,SOC decomposition contributed 57%–72%of the total CO_(2)emitted.For both non-carbonate and carbonate-rich soils,the SOC derived from C4 plants decomposed faster than that originated from C3 plants.We propose that for carbonate soil,CO_(2)emission may be overestimated using the alkali trap method because of decreasing CO_(2)pressure within the incubation jar,but underestimated using the direct gas sampling method.The gas sampling interval and ambient air may be important sources of error,and steps should be taken to mitigate errors related to these factors in soil incubation and CO_(2)quantification studies.展开更多
In Tunisia, the coastal Chenini oasis is characterized by a lush vegetation cover, whereas more inland continental oases(e.g., the Guettaya oasis) have a very scarce vegetation cover. For sustaining date palm producti...In Tunisia, the coastal Chenini oasis is characterized by a lush vegetation cover, whereas more inland continental oases(e.g., the Guettaya oasis) have a very scarce vegetation cover. For sustaining date palm production in these areas, organic fertilizers are applied,either spread on the soil surface(in Chenini) or buried under a sand layer(in Guettaya). We examined at a molecular level how these management techniques affect soil organic matter composition in oasis systems. A dominance of fresh plant input for Guettaya was indicated by solid-state 13C nuclear magnetic resonance spectroscopy signals, which was most pronounced in the uppermost soil close to palms. Evidence for more degraded organic matter was found in deeper soil near the palms, as well as in the soil distant from the palms. Amino sugar contents were low in the uppermost Guettaya soil near the palms. The overall microbial amino sugar residue contents were similar in range as those found in other dryland environments. With increasing distance from trees, the amino sugar contents declined in Guettaya, where the palms grow on bare soil, but this was not the case for Chenini, which has multi-layer vegetation cover under palms. In agreement with the results from previous dryland studies, the soil microbial community in both oasis systems was dominated by fungi in topsoil, and a shift toward bacteria-derived residues in subsurface soil. This might be due to higher variability of temperature and moisture in topsoil and/or lower degradability of fungal remains;however, further research is required to confirm this hypothesis.展开更多
Experiments using electrical resistivity tomography(ERT) have shown promising results in reducing the uncertainty of solute plume characteristics related to estimates based on the analysis of local point measurements ...Experiments using electrical resistivity tomography(ERT) have shown promising results in reducing the uncertainty of solute plume characteristics related to estimates based on the analysis of local point measurements only.To explore the similarities and differences between two cross-borehole ERT inversion approaches for characterizing salt tracer plumes,namely the classical smoothness-constrained inversion and a geostatistically based approach,we performed two-dimensional synthetic experiments.Simplifying assumptions about the solute transport model and the electrical forward and inverse model allowed us to study the sensitivity of the ERT inversion approaches towards a variety of basic conditions,including the number of boreholes,measurement schemes,contrast between the plume and background electrical conductivity,use of a priori knowledge,and point conditioning.The results show that geostatistically based and smoothness-constrained inversions of electrical resistance data yield plume characteristics of similar quality,which can be further improved when point measurements are incorporated and advantageous measurement schemes are chosen.As expected,an increased number of boreholes included in the ERT measurement layout can highly improve the quality of inferred plume characteristics,while in this case the benefits of point conditioning and advantageous measurement schemes diminish.Both ERT inversion approaches are similarly sensitive to the noise level of the data and the contrast between the solute plume and background electrical conductivity,and robust with regard to biased input parameters,such as mean concentration,variance,and correlation length of the plume.Although sophisticated inversion schemes have recently become available,in which flow and transport as well as electrical forward models are coupled,these schemes effectively rely on a relatively simple geometrical parameterization of the hydrogeological model.Therefore,we believe that standard uncoupled ERT inverse approaches,like the ones discussed and assessed in this paper,will continue to be important to the imaging and characterization of solute plumes in many real-world applications.展开更多
Nitrate (NO-3) and nitrite (NO2-) leaching threatens groundwater quality.Soil C:N ratio,i.e.,the ratio of soil organic carbon to total nitrogen,affects mineralization,nitrification,and denitrification;however,its mech...Nitrate (NO-3) and nitrite (NO2-) leaching threatens groundwater quality.Soil C:N ratio,i.e.,the ratio of soil organic carbon to total nitrogen,affects mineralization,nitrification,and denitrification;however,its mechanism for driving soil NO-3and NO-2accumulation and leaching remains unclear.Here,a field investigation in a fluvo-aquic soil and a soil column experiment were performed to explore the relationships between soil C:N ratio and soil NO-3and NO-2leaching in three soil layers (0–20,20–40,and 40–60 cm) under heavy rainfall (rainfall rate>25 mm d-1).The field investigation results showed that both soil NO-3-N and NO-2-N contents decreased exponentially (P<0.001) with increasing soil C:N ratio in each soil layer.Furthermore,negative exponential relationships (P<0.001) were found between soil C:N ratio and both NO-3-N and NO-2-N concentrations in soil solution in each soil layer under heavy rainfall.The soil column divided into three layers was leached with simulated heavy rainfall;the results confirmed negative exponential relationships (P<0.05) between soil C:N ratio and both NO-3-N and NO-2-N concentrations in the leachate from each soil layer.A total of 18 soil samples obtained from three depths at six field sites during the rainy season were used to elucidate the microbial mechanisms induced by soil C:N ratio using high-throughput sequencing and real-time polymerase chain reaction.High abundances of ammonifying bacteria (Flavobacterium,Bacillu,and Pseudomonas),ammonia-oxidizing bacteria (Nitrosospira),and nirS/K gene were observed when soil C:N was low,concomitant with low abundances of NO-2-oxidizing bacteria (Nitrospira) and narG gene.Partial least squares path modeling showed that the high NO-3and NO-2levels at low soil C:N ratio might be attributed to the inhibition of NO-3reduction (i.e.,low narG gene) and NO-2oxidation (i.e.,low Nitrospira) and thus the accumulation of soil NO-3and NO-2,respectively.Therefore,the leaching of NO-2and NO-3in low C:N soils requires more attention during the rainy season.展开更多
Within a collaborative project between Slovenian Environment Agency （ARSO） and Research Center Jfilich （FZJ）, nitrogen reduction levels necessary to reach groundwater quality targets in Slovenia were assessed. For...Within a collaborative project between Slovenian Environment Agency （ARSO） and Research Center Jfilich （FZJ）, nitrogen reduction levels necessary to reach groundwater quality targets in Slovenia were assessed. For this purpose the hydrological model GROWA- DENUZ was coupled with agricultural N balances and applied consistently to the whole territory of Slovenia in a spatial resolution of 100 x 100 m. GROWA was used to determine the water balance in Slovenia for the hydrologic period 1971-2000. Simultaneously, the displaceable N load in soft was assessed from agricultural Slovenian N surpluses for 2011 and the atmospheric N deposition. Subsequently, the DENUZ model was used to assess the nitrate degradation in soil and, in combination with the percolation water rates from the GROWA model, to determine nitrate concentration in the leachate. The areas showing predicted nitrate concentrations in the leachate above the EU groundwater quality standard of 50 mg NO3/L have been identified as priority areas for implementing nitrogen reduction measures. For these ＂hot spot＂ areas DENUZ was used in a backward mode to quantify the maximal permissible nitrogen surplus levels in agriculture to guarantee a nitrate concentration in percolation water below 50 mg NO3/L. Model results indicate that additional N reduction measures should be implemented in priority areas rather than area-covering. Research work will directly support the implementation of the European Union Water Framework Directive in Slovenia, e.g., by using the maximal permissible nitrogen surplus levels as a framework for the derivation of regionally adapted and hence effective nitrogen reduction measures.展开更多
Groundwater levels and water samples were collected from 20 drinking water pumping and piezometer wells in the urban area of Dakar coastal region in the year 2019. The pH-value, electrical conductivity, as well as cal...Groundwater levels and water samples were collected from 20 drinking water pumping and piezometer wells in the urban area of Dakar coastal region in the year 2019. The pH-value, electrical conductivity, as well as calcium, magnesium, sodium, potassium, chloride, sulfate, bicarbonate, and nitrate concentrations were measured to assess the hydrochemical quality of the infrabasaltic aquifer in the area. The present work carried out a hydrochemical analysis to interpret the groundwater chemistry of the aquifer. The results of this chemical analysis indicate that Na<sup>+</sup> > Mg<sup>2+</sup> > Ca<sup>2+</sup> > K<sup>+</sup> was the most dominant cation sequence in the groundwater, while Cl<sup>-</sup> > HCO<sub>3</sub><sup>-</sup> > SO<sub>4</sub><sup>2-</sup> > NO<sub>3</sub><sup>-</sup> was the most dominant one for anions. The chemical analysis of our samples showed, that the Cl-Ca-Mg facies was dominant in the aquifer, while Cl-Na-K and HCO<sub>3</sub>-Na-K facies represent 20% and 10% of the groundwater sampled, respectively. A comparison of the measured groundwater quality in relation to WHO drinking water quality standards revealed that 80% of the water samples are suitable for drinking purposes. Ca enrichment, Simpson ratio, ratio of sodium chloride, and calculating Base Exchange (BEX) indices for the samples revealed that the groundwater is mainly affected by three factors: seawater intrusion due to aquifer overexploitation on one hand, and freshening processes and nitrate pollution, on the other, mainly caused by the groundwater flow from the unconfined aquifer.展开更多
The aggregation of multi-walled carbon nanotubes （MWCNTs） in the aqueous phase not only inhibits their extensive utilization in various aspects but also dominates their environmental fate and transport.The role of s...The aggregation of multi-walled carbon nanotubes （MWCNTs） in the aqueous phase not only inhibits their extensive utilization in various aspects but also dominates their environmental fate and transport.The role of surfactants at low concentration in the aggregation of MWCNTs has been studied,however the effect of perfluorinated surfactants at low concentration is uncertain.To understand this interfacial phenomenon,the influences of perfluorooctanoic acid （PFOA）,and sodium dodecyl sulfate （SDS） as a control,on MWCNT aggregation in the aqueous phase were examined by the UV absorbency method.Influences of pH and cationic species on the critical coagulation concentration （CCC） value were evaluated.The CCC values were dependent on the concentration of PFOA,however a pronounced effect of SDS concentration on the CCC values was not observed.The CCC values of the MWCNTs were 51.6 mmol/L in NaCl and 0.28 mmol/L in CaCl 2 solutions,which suggested pronounced differences in the effects of Na＋ and Ca2＋ ions on the aggregation of the MWCNTs.The presence of both PFOA and SDS significantly decreased the CCC values of the MWCNTs in NaCl solution.The aggregation of the MWCNTs took place under acidic conditions and was not notably altered under neutral and alkaline conditions due to the electrostatic repulsion of deprotonated functional groups on the surface of the MWCNTs.展开更多
The Tibetan Plateau(TP)has been the focus of numerous studies examining the energy and water cycle variations,but there is still a lack of long-term,quantitative precise assessments of evapotranspiration.This research...The Tibetan Plateau(TP)has been the focus of numerous studies examining the energy and water cycle variations,but there is still a lack of long-term,quantitative precise assessments of evapotranspiration.This research first provided two sets of long-term comprehensive observational datasets,and an advanced monitoring technique to measure soil moisture,which can improve the estimation accuracy of evapotranspiration.Subsequently,using microwave data,the Surface Energy Balance System model and Machine Learning methods,it calculated a complete set of long-term evapotranspiration data.At the same time,based on reasonable assumptions,it also estimated the total evaporation from plateau lakes.These findings contribute significantly to the understanding of the relationship between the Asian monsoon,the TP’s physical characteristics,and its atmosphere,thereby improving predictions of water resource variability in the TP.The study’s innovative methodologies and synthesis of diverse data sources provide critical information for informed and sustainable water management strategies in the region.展开更多
准确评估雪层体积含水量和体积密度对于理解雪的水文过程、降低雪崩风险以及冰冻圈监测具有重要意义。本文提出一种新型双参数反演框架,该框架集成了合成电磁建模、降维方法和机器学习算法,用于从探地雷达(GPR)数据中提取相对介电常数...准确评估雪层体积含水量和体积密度对于理解雪的水文过程、降低雪崩风险以及冰冻圈监测具有重要意义。本文提出一种新型双参数反演框架,该框架集成了合成电磁建模、降维方法和机器学习算法,用于从探地雷达(GPR)数据中提取相对介电常数和对数电阻率。传统雪层测量方法具有侵入性、劳动强度大且仅限于点位观测等局限性。为克服上述局限,建立了一种非侵入性、可扩展且数据驱动的框架,利用合成GPR数据集来表示具有不同含水量和密度分布的多样化雪层条件。使用先进电磁模拟器gprMax,通过有限差分时域模拟生成合成的一维时序反射(A扫描)。随后采用主成分分析(PCA)将每个A扫描进行压缩,得到低维且信息保真的特征集,从而显著提升模型训练效率。基于经过主成分分析(PCA)降维处理的特征集,训练了随机森林、神经网络、支持向量机和极限梯度提升四种机器学习模型。其中,神经网络模型性能最佳,介电常数为R^(2)>0.97,电阻率为R^(2)>0.92。合成数据中引入高斯噪声(信噪比约为6 dB),并通过针对特定领域进行改进,以提高其在实地数据的泛化能力。模型在中国阿尔泰山脉的两条典型GPR剖面(湿雪T750和饱和雪G125)上进行了验证。神经网络模型预测结果与GPR反演、Snowfork测量及人工雪坑数据高度一致,体积含水量偏差不超过1.5%,体积密度误差在30–84 kg m-3范围内。结果表明,基于机器学习的反演方法在结合真实模拟与数据增强的条件下,能够实现可扩展、非侵入式的雪层特性反演,在水文预报、雪情监测及气候敏感型水资源管理中具有重要应用价值。展开更多
Accurate assessment of snowpack volumetric liquid water content and bulk density is essential for understanding snow hydrology,avalanche risk management,and monitoring cryosphere changes.This study presents a novel du...Accurate assessment of snowpack volumetric liquid water content and bulk density is essential for understanding snow hydrology,avalanche risk management,and monitoring cryosphere changes.This study presents a novel dual-parameter inversion framework that integrates synthetic electromagnetic modelling,dimensionality reduction,and machine learning algorithms to extract relative permittivity and log-resistivity from ground-penetrating radar(GPR)data.Traditional snowpack measurements are invasive,labor-intensive,and limited to point observations.To overcome these limitations,we developed a non-invasive,scalable,and data-driven framework that uses synthetic GPR datasets representing diverse snowpack conditions with variable moisture and density profiles.Synthetic 1D time series reflections(A-scans)are generated using finite-difference time-domain simulations in the state-of-the-art electromagnetic simulator gprMax.Principal component analysis(PCA)is applied to compress each A-scan while preserving key features,which significantly improved and enhanced the model training efficiency.Four machine learning models,including random forest,neural network,support vector machine,and eXtreme gradient boosting,are trained on PCA-reduced features.Among these,the neural network model achieved the best performance,with R^(2)>0.97 for permittivity and R 2>0.92 for resistivity.Gaussian noise(signal-to-noise ratio of 6 dB)is introduced to the synthetic data,and then targeted domain adaptation is employed to enhance generalization to field data.The framework is validated on two contrasting GPR transects in the Altay Mountains of the Chinese mainland,representing moist(T750)and wet(G125)snowpack conditions.The neural network model predictions are most consistent with the GPR derived estimates,Snowfork measurements,and snow pit data,achieving volumetric liquid water content deviation of≤1.5% and bulk density error within the range of 30-84 kg m^(-3).The results demonstrate that machine learning-based inversion,supported by realistic simulations and data augmentation enables scalable,non-invasive snowpack characterization with significant applications in hydrological forecasting,snow monitoring,and water resource management.展开更多
Background:Soil fungi play crucial roles in ecosystem functions.However,how snow cover change associated with winter warming affects soil fungal communities remains unclear in the Tibetan forest.Methods:We conducted a...Background:Soil fungi play crucial roles in ecosystem functions.However,how snow cover change associated with winter warming affects soil fungal communities remains unclear in the Tibetan forest.Methods:We conducted a snow manipulation experiment to explore immediate and legacy effects of snow exclusion on soil fungal community diversity and composition in a spruce forest on the eastern Tibetan Plateau.Soil fungal communities were performed by the high throughput sequencing of gene-fragments.Results:Ascomycota and Basidiomycota were the two dominant fungal phyla and Archaeorhizomyces,Aspergillus and Amanita were the three most common genera across seasons and snow manipulations.Snow exclusion did not affect the diversity and structure of soil fungal community in both snow-covered and snow-free seasons.However,the relative abundance of some fungal communities was different among seasons.Soil fungal groups were correlated with environmental factors(i.e.,temperature and moisture)and soil biochemical variables(i.e.,ammonium and enzyme).Conclusions:These results suggest that the season-driven variations had stronger impacts on soil fungal community than short-term snow cover change.Such findings may have important implications for soil microbial processes in Tibetan forests experiencing significant decreases in snowfall.展开更多
The increasing global demand for timber and forest products has triggered the widespread conversion of subtropical forests into secondary forests and plantations.Soil fauna,the active angel in material cycling,are sen...The increasing global demand for timber and forest products has triggered the widespread conversion of subtropical forests into secondary forests and plantations.Soil fauna,the active angel in material cycling,are sensitive to changes in food resources and soil environments.However,the impact of forest conversion on soil fauna abundance and diversity remains insufficiently understood.To address this,we conducted seasonal soil fauna sampling in a subtropical region of China during July and November 2022,as well as January and March 2023.The sampling covered secondary forests,Castanopsis carlesii(broadleaved)plantations,and Cunninghamia lanceolata(fir)plantations,with natural forests serving as the control.We assessed soil fauna diversity including taxonomic and functional composition,along with soil physicochemical properties.Overall,forest conversion led to a decline in soil fauna abundance and biodiversity,with litter quality and soil moisture emerging as primary drivers according to Post hoc Least Significant Difference tests.Macrofauna demonstrated higher sensitivity to forest conversion than meso-and microfauna,with their abundance decreasing by 10%in secondary forests,18%in broadleaved plantations,and 27%in fir plantations.Moreover,the number of predator and saprophage groups declined more significantly when natural forests were converted into fir plantations(by 24%and 15%,respectively)than into broadleaved plantations(by 16%and 10%,respectively).Additionally,soil fauna showed more sensitive responses to forest conversion in spring and summer,especially in the case of the conversion into fir plantations.Our findings underscore the negative impacts of forest conversion on soil fauna biodiversity,particularly the reduction in predators and saprophages,which may disrupt the food web and increase ecosystem vulnerability to pests and diseases,thereby indicating potential risks to the stability of forest ecosystems.展开更多
This article describes an immersive virtual reality reconstruction tool for root system architectures from 3D scans of soil columns.In practical scenarios,experimental conditions will be adapted to fit the need of the...This article describes an immersive virtual reality reconstruction tool for root system architectures from 3D scans of soil columns.In practical scenarios,experimental conditions will be adapted to fit the need of the data analysis pipeline,including sieving and drying the soil before scanning.Based on previous reports of automatic systems that do not represent what experts would annotate,we developed a virtual reality system to assist with the extraction of root systems in cases in which automated approaches fall short of expert knowledge.The aim of the present study is to evaluate whether our immersive method is superior to classical annotation approaches when tested on synthetic data sets using untrained participants.Our laboratory user study consists of evaluating the root extractions of participants,along with their rating on central user experience and usability measures.We show significant improvement in F1 score across conditions(noisy or clear data)as well as an improved usability.Our study highlights that using virtual reality in root extraction improves accuracy,and we perform an in-depth evaluation of biases that occur when users trace roots in soil volumes.展开更多
Antimicrobial resistance poses a major challenge to modern medicine and jeopardizes the ability to maintain a robust global public health response against persistent infectious disease threats.A 2024 Lancet series on ...Antimicrobial resistance poses a major challenge to modern medicine and jeopardizes the ability to maintain a robust global public health response against persistent infectious disease threats.A 2024 Lancet series on antimicrobial resistance estimated that bacterial antimicrobial resistance was associated with 4.71 million deaths globally in 2021,including 1.14 million deaths directly attributable to resistant infections.If not actively addressed,antimicrobial resistance might result in an annual reduction of the global gross domestic product by$3.4 trillion and push an additional 24 million individuals into extreme poverty within the next decade.Antibiotic resistance genes(ARGs)are the key culprits behind antimicrobial resistance,widely disseminating among bacterial populations,particularly in medical,agricultural,and veterinary sectors.Furthermore,anthropogenic activities,such as wastewater discharge,trade,tourism,and chemical contamination,have reshaped microbial biogeography,creating an unforeseen global platform for ARG mobilization.This exacerbates the existing antimicrobial resistance crisis and enhances risks to global public health and environmental stability.展开更多
The widespread use of agricultural plastic films has made micro-and nanoplastics(MNPs)and phthalate esters(PAEs)contaminants of emerging concern in agroecosystems.However,the interactive mechanisms underlying their co...The widespread use of agricultural plastic films has made micro-and nanoplastics(MNPs)and phthalate esters(PAEs)contaminants of emerging concern in agroecosystems.However,the interactive mechanisms underlying their combined pollution in soil-plant systems remain elusive.To fill this gap,this study investigated the interaction between submicron plastics(SMPs,0.01%and 0.1%w/w)and di(2-ethylhexyl)phthalate(DEHP)in soil-lettuce systems.Contrary to the anticipated synergistic toxicity,DEHP significantly reduced SMP uptake into and by cracked surface cells of lettuce roots(with root concentration factors decreasing by 19%-64%),i.e.,DEHP alleviated SMP-induced oxidative stress,as evidenced by reduced levels of reactive oxygen species(-26.8%and-66.7%)and antioxidant enzyme activities(-118%and-128%).Metabolomic profiling revealed that SMP exposure significantly dysregulated multiple metabolic pathways(amino acid,carbohydrate,energy,glycan,lipid,and nucleotide metabolism),while SMP+DEHP co-exposure selectively attenuated these metabolic disturbances,showing enrichment only in glycan biosynthesis/metabolism and suppressing SMP-induced perturbations in other pathways(biosynthesis of secondary metabolites,energy metabolism,and signal transduction).Microbial community analysis showed that high-level SMP exposure significantly diminished bacterialα-diversity and amplicon sequence variant(ASV)richness,whereas DEHP supplementation enhanced those of Myxococcota in the soil,potentially counterbalancing SMP-induced microbial dysbiosis.These findings collectively demonstrate that co-contamination by MNPs and plastic additives may produce antagonistic interactions rather than uniformly synergistic effects,and provide a more comprehensive evaluation of the risks of PAEs and MNPs to food security,human health,and ecological environment.展开更多
A significant number of emerging pollutants(EPs)resulting from point and diffuse pollution is present in the aquatic environment.These are chemicals that are not commonly monitored but have the potential to enter the ...A significant number of emerging pollutants(EPs)resulting from point and diffuse pollution is present in the aquatic environment.These are chemicals that are not commonly monitored but have the potential to enter the environment and cause adverse ecological and human health effects.According to the NORMAN network,at least 700 substances categorized into 20 classes,have been identified in the European aquatic environment.In light of their potential impact action is urgently required.In this study,we present a concept that shows the current state of art and challenges for monitoring programs,fate and risk assessment tools and requirements for policies with respect to emerging pollutants as a base for sustainable water resource management.Currently,methods for sampling and analysis are not harmonized,being typically focused on certain EP classes.For a number of known highly hazardous EPs detection limits are too high to allow proper risk assessment.For other EPs such as microplastics method development is in its infancy.Advanced ultra-sensitive instrumental techniques should be used for quantitative determination of prioritized EPs in water,suspended matter,soil and biota.Data on EPs'and their metabolites'properties that determine their fate in the environment are often not available.National surveys on water quality often use different parameters for water quality assessment and often do not include EPs.A harmonized monitoring of surface and groundwater is not yet achieved and urgently required.Specific component integrated into models assessing the fate of EPs in a multi compartment environmental approach are missing and must be developed.The main goal of risk assessment is the overall protection of ecological communities in the aquatic environment and human health.New methods for assessing the cumulative risks from combined exposures to several stressors,including mixtures of EPs in a multi-scale approach are required.A combination of regulations and management measures with respect to use/emissions of EPs into the environment,as well as to their occurrence in the environment are fundamental to reach an efficient water resource management.展开更多
Integrated observation platforms have been set up to investigate consequences of global change within a terrestrial network of observatories （TERENO） in Germany. The aim of TERENO is to foster the understanding of w...Integrated observation platforms have been set up to investigate consequences of global change within a terrestrial network of observatories （TERENO） in Germany. The aim of TERENO is to foster the understanding of water, energy, and matter fluxes in terrestrial systems, as well as their biological and physical drivers. Part of the Lower Rhine Valley-Eifel observatory of TERENO is located within the Eifel National Park. Recently, the National Park forest management started to promote the nat- ural regeneration of near-natural beech forest by removing a significant proportion of the spruce forest that was established for timber production after World War II. Within this context, the effects of such a disturbance on forest ecosystem functioning are currently investigated in a deforestation experiment in the Wtistebach catchment, which is one of the key experimental re- search sites within the Lower Rhine Valley-Eifel observatory. Here, we present the integrated observation system of the Wiistebach test site to exemplarily demonstrate the terrestrial observatory concept of TERENO that allows for a detailed mon- itoring of changes in hydrological and biogeochemical states and fluxes triggered by environmental disturbances. We present the observation platforms and the soil sampling campaign, as well as preliminary results including an analysis of data con- sistency. We specifically highlight the capability of integrated datasets to enable improved process understanding of the post-deforestation changes in ecosystem functioning.展开更多
基金supported by the Exploratory Grant(STC_TUNGER-006/INTOASES)as part of the Bilateral Scientific and Technological Cooperation between the Republic of Tunisia and the Federal Republic of Germany
文摘Countries in the Middle Eastern and North African (MENA) region are among the most water-scarce regions in the world, and their dryland soils are usually poor in organic carbon content (<0.5%). In this study, we summarize examples of how people in the few oases of the MENA region overcome environmental challenges by sustainably managing economically important date production. On the basis of the limited studies found in the existing literature, this mini-review focuses on the role of traditional soil organic matter amendments beneath the soil surface as a key tool in land restoration. We conclude that soil organic matter amendments can be very successful in restoring soil water and preventing the soil from salinization.
基金funded by the National Key R&D Program of China(Grant No.2021YFD1500200)National Natural Science Foundation of China(Grant No.42077149)+4 种基金China Postdoctoral Science Foundation(Grant No.2019M660782)National Science and Technology Basic Resources Survey Program of China(Grant No.2019FY101300)Doctoral research start-up fund project of Liaoning Provincial Department of Science and Technology(Grant No.2021-BS-136)China Scholarship Council(201908210132)Young Scientific and Technological Talents Project of Liaoning Province(Grant Nos.LSNQN201910 and LSNQN201914)。
文摘Forest soil carbon is a major carbon pool of terrestrial ecosystems,and accurate estimation of soil organic carbon(SOC)stocks in forest ecosystems is rather challenging.This study compared the prediction performance of three empirical model approaches namely,regression kriging(RK),multiple stepwise regression(MSR),random forest(RF),and boosted regression trees(BRT)to predict SOC stocks in Northeast China for 1990 and 2015.Furthermore,the spatial variation of SOC stocks and the main controlling environmental factors during the past 25 years were identified.A total of 82(in 1990)and 157(in 2015)topsoil(0–20 cm)samples with 12 environmental factors(soil property,climate,topography and biology)were selected for model construction.Randomly selected80%of the soil sample data were used to train the models and the other 20%data for model verification using mean absolute error,root mean square error,coefficient of determination and Lin's consistency correlation coefficient indices.We found BRT model as the best prediction model and it could explain 67%and 60%spatial variation of SOC stocks,in 1990,and 2015,respectively.Predicted maps of all models in both periods showed similar spatial distribution characteristics,with the lower SOC in northeast and higher SOC in southwest.Mean annual temperature and elevation were the key environmental factors influencing the spatial variation of SOC stock in both periods.SOC stocks were mainly stored under Cambosols,Gleyosols and Isohumosols,accounting for 95.6%(1990)and 95.9%(2015).Overall,SOC stocks increased by 471 Tg C during the past 25 years.Our study found that the BRT model employing common environmental factors was the most robust method for forest topsoil SOC stocks inventories.The spatial resolution of BRT model enabled us to pinpoint in which areas of Northeast China that new forest tree planting would be most effective for enhancing forest C stocks.Overall,our approach is likely to be useful in forestry management and ecological restoration at and beyond the regional scale.
文摘Due to the recent system developments for the electromagnetic characterization of the subsurface, fast and easy acquisition is made feasible due to the fast measurement speed, easy coupling with GPS systems, and the availability of multi-channel electromagnetic induction（EMI） and ground penetrating radar（GPR） systems. Moreover, the increasing computer power enables the use of accurate forward modeling programs in advanced inversion algorithms where no approximations are used and the full information content of the measured data can be exploited. Here, recent developments of large-scale quantitative EMI inversion and full-waveform GPR inversion are discussed that yield higher resolution of quantitative medium properties compared to conventional approaches. In both cases a detailed forward model is used in the inversion procedure that is based on Maxwell＇s equations. The multi-channel EMI data that have different sensing depths for the different source-receiver offset are calibrated using a short electrical resistivity tomography（ERT） calibration line which makes it possible to invert for electrical conductivity changes with depth over large areas. The crosshole GPR full-waveform inversion yields significant higher resolution of the permittivity and conductivity images compared to ray-based inversion results.
基金supported by the National Key Research and Development Program of China(No.2016YFD0201200)the National Natural Science Foundation of China(Nos.31370527,31261140367,and 30870414)the Chinese Scholarship Council(No.201706350210)for the support of the work。
文摘The accurate quantification and source partitioning of CO_(2)emitted from carbonate(i.e.,Haplustalf)and non-carbonate(i.e.,Hapludult)soils are critically important for understanding terrestrial carbon(C)cycling.The two main methods to capture CO_(2)released from soils are the alkali trap method and the direct gas sampling method.A 25-d laboratory incubation experiment was conducted to compare the efficacies of these two methods to analyze CO_(2)emissions from the non-carbonate and carbonate-rich soils.An isotopic fraction was introduced into the calculations to determine the impacts on partitioning of the sources of CO_(2)into soil organic carbon(SOC)and soil inorganic carbon(SIC)and into C3 and/or C4 plant-derived SOC.The results indicated that CO_(2)emissions from the non-carbonate soil measured using the alkali trap and gas sampling methods were not significantly different.For the carbonate-rich soil,the CO_(2)emission measured using the alkali trap method was significantly higher than that measured using the gas sampling method from the 14 th day of incubation onwards.Although SOC and SIC each accounted for about 50%of total soil C in the carbonate-rich soil,SOC decomposition contributed 57%–72%of the total CO_(2)emitted.For both non-carbonate and carbonate-rich soils,the SOC derived from C4 plants decomposed faster than that originated from C3 plants.We propose that for carbonate soil,CO_(2)emission may be overestimated using the alkali trap method because of decreasing CO_(2)pressure within the incubation jar,but underestimated using the direct gas sampling method.The gas sampling interval and ambient air may be important sources of error,and steps should be taken to mitigate errors related to these factors in soil incubation and CO_(2)quantification studies.
基金the German Federal Ministry of Education and Research(Bundesministerium für Bildung und Forschung,BMBF)for the Exploratory Grant(No.STC TUNGER-006/INTOASES)as a part of the Bilateral Scientific and Technological Cooperation between the Republic of Tunisia and the Federal Republic of Germanythe patience and hospitality of the oasis farmers at Chenini and Guettaya oases in Tunisia,as well as technical support by the technicians at the Institute of Crop Science and Resource Conservation of the University of Bonn and the Agrosphere Institute(IBG-3)of Forschungszentrum Jülich GmbH,Germany
文摘In Tunisia, the coastal Chenini oasis is characterized by a lush vegetation cover, whereas more inland continental oases(e.g., the Guettaya oasis) have a very scarce vegetation cover. For sustaining date palm production in these areas, organic fertilizers are applied,either spread on the soil surface(in Chenini) or buried under a sand layer(in Guettaya). We examined at a molecular level how these management techniques affect soil organic matter composition in oasis systems. A dominance of fresh plant input for Guettaya was indicated by solid-state 13C nuclear magnetic resonance spectroscopy signals, which was most pronounced in the uppermost soil close to palms. Evidence for more degraded organic matter was found in deeper soil near the palms, as well as in the soil distant from the palms. Amino sugar contents were low in the uppermost Guettaya soil near the palms. The overall microbial amino sugar residue contents were similar in range as those found in other dryland environments. With increasing distance from trees, the amino sugar contents declined in Guettaya, where the palms grow on bare soil, but this was not the case for Chenini, which has multi-layer vegetation cover under palms. In agreement with the results from previous dryland studies, the soil microbial community in both oasis systems was dominated by fungi in topsoil, and a shift toward bacteria-derived residues in subsurface soil. This might be due to higher variability of temperature and moisture in topsoil and/or lower degradability of fungal remains;however, further research is required to confirm this hypothesis.
文摘Experiments using electrical resistivity tomography(ERT) have shown promising results in reducing the uncertainty of solute plume characteristics related to estimates based on the analysis of local point measurements only.To explore the similarities and differences between two cross-borehole ERT inversion approaches for characterizing salt tracer plumes,namely the classical smoothness-constrained inversion and a geostatistically based approach,we performed two-dimensional synthetic experiments.Simplifying assumptions about the solute transport model and the electrical forward and inverse model allowed us to study the sensitivity of the ERT inversion approaches towards a variety of basic conditions,including the number of boreholes,measurement schemes,contrast between the plume and background electrical conductivity,use of a priori knowledge,and point conditioning.The results show that geostatistically based and smoothness-constrained inversions of electrical resistance data yield plume characteristics of similar quality,which can be further improved when point measurements are incorporated and advantageous measurement schemes are chosen.As expected,an increased number of boreholes included in the ERT measurement layout can highly improve the quality of inferred plume characteristics,while in this case the benefits of point conditioning and advantageous measurement schemes diminish.Both ERT inversion approaches are similarly sensitive to the noise level of the data and the contrast between the solute plume and background electrical conductivity,and robust with regard to biased input parameters,such as mean concentration,variance,and correlation length of the plume.Although sophisticated inversion schemes have recently become available,in which flow and transport as well as electrical forward models are coupled,these schemes effectively rely on a relatively simple geometrical parameterization of the hydrogeological model.Therefore,we believe that standard uncoupled ERT inverse approaches,like the ones discussed and assessed in this paper,will continue to be important to the imaging and characterization of solute plumes in many real-world applications.
基金funded by the National Key Research and Development Project of China (No. 2016YFD0800100-04)。
文摘Nitrate (NO-3) and nitrite (NO2-) leaching threatens groundwater quality.Soil C:N ratio,i.e.,the ratio of soil organic carbon to total nitrogen,affects mineralization,nitrification,and denitrification;however,its mechanism for driving soil NO-3and NO-2accumulation and leaching remains unclear.Here,a field investigation in a fluvo-aquic soil and a soil column experiment were performed to explore the relationships between soil C:N ratio and soil NO-3and NO-2leaching in three soil layers (0–20,20–40,and 40–60 cm) under heavy rainfall (rainfall rate>25 mm d-1).The field investigation results showed that both soil NO-3-N and NO-2-N contents decreased exponentially (P<0.001) with increasing soil C:N ratio in each soil layer.Furthermore,negative exponential relationships (P<0.001) were found between soil C:N ratio and both NO-3-N and NO-2-N concentrations in soil solution in each soil layer under heavy rainfall.The soil column divided into three layers was leached with simulated heavy rainfall;the results confirmed negative exponential relationships (P<0.05) between soil C:N ratio and both NO-3-N and NO-2-N concentrations in the leachate from each soil layer.A total of 18 soil samples obtained from three depths at six field sites during the rainy season were used to elucidate the microbial mechanisms induced by soil C:N ratio using high-throughput sequencing and real-time polymerase chain reaction.High abundances of ammonifying bacteria (Flavobacterium,Bacillu,and Pseudomonas),ammonia-oxidizing bacteria (Nitrosospira),and nirS/K gene were observed when soil C:N was low,concomitant with low abundances of NO-2-oxidizing bacteria (Nitrospira) and narG gene.Partial least squares path modeling showed that the high NO-3and NO-2levels at low soil C:N ratio might be attributed to the inhibition of NO-3reduction (i.e.,low narG gene) and NO-2oxidation (i.e.,low Nitrospira) and thus the accumulation of soil NO-3and NO-2,respectively.Therefore,the leaching of NO-2and NO-3in low C:N soils requires more attention during the rainy season.
文摘Within a collaborative project between Slovenian Environment Agency （ARSO） and Research Center Jfilich （FZJ）, nitrogen reduction levels necessary to reach groundwater quality targets in Slovenia were assessed. For this purpose the hydrological model GROWA- DENUZ was coupled with agricultural N balances and applied consistently to the whole territory of Slovenia in a spatial resolution of 100 x 100 m. GROWA was used to determine the water balance in Slovenia for the hydrologic period 1971-2000. Simultaneously, the displaceable N load in soft was assessed from agricultural Slovenian N surpluses for 2011 and the atmospheric N deposition. Subsequently, the DENUZ model was used to assess the nitrate degradation in soil and, in combination with the percolation water rates from the GROWA model, to determine nitrate concentration in the leachate. The areas showing predicted nitrate concentrations in the leachate above the EU groundwater quality standard of 50 mg NO3/L have been identified as priority areas for implementing nitrogen reduction measures. For these ＂hot spot＂ areas DENUZ was used in a backward mode to quantify the maximal permissible nitrogen surplus levels in agriculture to guarantee a nitrate concentration in percolation water below 50 mg NO3/L. Model results indicate that additional N reduction measures should be implemented in priority areas rather than area-covering. Research work will directly support the implementation of the European Union Water Framework Directive in Slovenia, e.g., by using the maximal permissible nitrogen surplus levels as a framework for the derivation of regionally adapted and hence effective nitrogen reduction measures.
文摘Groundwater levels and water samples were collected from 20 drinking water pumping and piezometer wells in the urban area of Dakar coastal region in the year 2019. The pH-value, electrical conductivity, as well as calcium, magnesium, sodium, potassium, chloride, sulfate, bicarbonate, and nitrate concentrations were measured to assess the hydrochemical quality of the infrabasaltic aquifer in the area. The present work carried out a hydrochemical analysis to interpret the groundwater chemistry of the aquifer. The results of this chemical analysis indicate that Na<sup>+</sup> > Mg<sup>2+</sup> > Ca<sup>2+</sup> > K<sup>+</sup> was the most dominant cation sequence in the groundwater, while Cl<sup>-</sup> > HCO<sub>3</sub><sup>-</sup> > SO<sub>4</sub><sup>2-</sup> > NO<sub>3</sub><sup>-</sup> was the most dominant one for anions. The chemical analysis of our samples showed, that the Cl-Ca-Mg facies was dominant in the aquifer, while Cl-Na-K and HCO<sub>3</sub>-Na-K facies represent 20% and 10% of the groundwater sampled, respectively. A comparison of the measured groundwater quality in relation to WHO drinking water quality standards revealed that 80% of the water samples are suitable for drinking purposes. Ca enrichment, Simpson ratio, ratio of sodium chloride, and calculating Base Exchange (BEX) indices for the samples revealed that the groundwater is mainly affected by three factors: seawater intrusion due to aquifer overexploitation on one hand, and freshening processes and nitrate pollution, on the other, mainly caused by the groundwater flow from the unconfined aquifer.
基金supported by the National Natural Science Foundation of China(No.20977043,20777033)the Opening Funding of State Key Laboratory of Pollution Control and Resource Reuse(No.PCRRF12012)
文摘The aggregation of multi-walled carbon nanotubes （MWCNTs） in the aqueous phase not only inhibits their extensive utilization in various aspects but also dominates their environmental fate and transport.The role of surfactants at low concentration in the aggregation of MWCNTs has been studied,however the effect of perfluorinated surfactants at low concentration is uncertain.To understand this interfacial phenomenon,the influences of perfluorooctanoic acid （PFOA）,and sodium dodecyl sulfate （SDS） as a control,on MWCNT aggregation in the aqueous phase were examined by the UV absorbency method.Influences of pH and cationic species on the critical coagulation concentration （CCC） value were evaluated.The CCC values were dependent on the concentration of PFOA,however a pronounced effect of SDS concentration on the CCC values was not observed.The CCC values of the MWCNTs were 51.6 mmol/L in NaCl and 0.28 mmol/L in CaCl 2 solutions,which suggested pronounced differences in the effects of Na＋ and Ca2＋ ions on the aggregation of the MWCNTs.The presence of both PFOA and SDS significantly decreased the CCC values of the MWCNTs in NaCl solution.The aggregation of the MWCNTs took place under acidic conditions and was not notably altered under neutral and alkaline conditions due to the electrostatic repulsion of deprotonated functional groups on the surface of the MWCNTs.
基金supported in part by the ESA MOST Dragon 5 Program[project:Monitoring and Modelling Climate Change in Water,Energy and Carbon Cycles in the Pan-Third Pole Environment[CLIMATE-Pan-TPE]]the National Natural Science Foundation of China[grant no.U2242208]the Second Tibetan Plateau Scientific Expedition and Research(STEP)program[grant no.2019QZKK0103].
文摘The Tibetan Plateau(TP)has been the focus of numerous studies examining the energy and water cycle variations,but there is still a lack of long-term,quantitative precise assessments of evapotranspiration.This research first provided two sets of long-term comprehensive observational datasets,and an advanced monitoring technique to measure soil moisture,which can improve the estimation accuracy of evapotranspiration.Subsequently,using microwave data,the Surface Energy Balance System model and Machine Learning methods,it calculated a complete set of long-term evapotranspiration data.At the same time,based on reasonable assumptions,it also estimated the total evaporation from plateau lakes.These findings contribute significantly to the understanding of the relationship between the Asian monsoon,the TP’s physical characteristics,and its atmosphere,thereby improving predictions of water resource variability in the TP.The study’s innovative methodologies and synthesis of diverse data sources provide critical information for informed and sustainable water management strategies in the region.
文摘准确评估雪层体积含水量和体积密度对于理解雪的水文过程、降低雪崩风险以及冰冻圈监测具有重要意义。本文提出一种新型双参数反演框架,该框架集成了合成电磁建模、降维方法和机器学习算法,用于从探地雷达(GPR)数据中提取相对介电常数和对数电阻率。传统雪层测量方法具有侵入性、劳动强度大且仅限于点位观测等局限性。为克服上述局限,建立了一种非侵入性、可扩展且数据驱动的框架,利用合成GPR数据集来表示具有不同含水量和密度分布的多样化雪层条件。使用先进电磁模拟器gprMax,通过有限差分时域模拟生成合成的一维时序反射(A扫描)。随后采用主成分分析(PCA)将每个A扫描进行压缩,得到低维且信息保真的特征集,从而显著提升模型训练效率。基于经过主成分分析(PCA)降维处理的特征集,训练了随机森林、神经网络、支持向量机和极限梯度提升四种机器学习模型。其中,神经网络模型性能最佳,介电常数为R^(2)>0.97,电阻率为R^(2)>0.92。合成数据中引入高斯噪声(信噪比约为6 dB),并通过针对特定领域进行改进,以提高其在实地数据的泛化能力。模型在中国阿尔泰山脉的两条典型GPR剖面(湿雪T750和饱和雪G125)上进行了验证。神经网络模型预测结果与GPR反演、Snowfork测量及人工雪坑数据高度一致,体积含水量偏差不超过1.5%,体积密度误差在30–84 kg m-3范围内。结果表明,基于机器学习的反演方法在结合真实模拟与数据增强的条件下,能够实现可扩展、非侵入式的雪层特性反演,在水文预报、雪情监测及气候敏感型水资源管理中具有重要应用价值。
基金supported by the National Key R&D Program of China(Grant Nos.2023YFC3008300&2023YFC3008305)the National Natural Science Foundation of China(Grant No.42172320)+1 种基金the Key Laboratory of Mountain Hazards and Engineering Resilience,Institute of Mountain Hazards and Environment,Chinese Academy of Sciences(Grant Nos.KLMHER-Z06&KLMHER-T07)the Science and Technology Research Program of Institute of Mountain Hazards and Environment,Chinese Academy of Sciences(Grant No.IMHE-CXTD.04).
文摘Accurate assessment of snowpack volumetric liquid water content and bulk density is essential for understanding snow hydrology,avalanche risk management,and monitoring cryosphere changes.This study presents a novel dual-parameter inversion framework that integrates synthetic electromagnetic modelling,dimensionality reduction,and machine learning algorithms to extract relative permittivity and log-resistivity from ground-penetrating radar(GPR)data.Traditional snowpack measurements are invasive,labor-intensive,and limited to point observations.To overcome these limitations,we developed a non-invasive,scalable,and data-driven framework that uses synthetic GPR datasets representing diverse snowpack conditions with variable moisture and density profiles.Synthetic 1D time series reflections(A-scans)are generated using finite-difference time-domain simulations in the state-of-the-art electromagnetic simulator gprMax.Principal component analysis(PCA)is applied to compress each A-scan while preserving key features,which significantly improved and enhanced the model training efficiency.Four machine learning models,including random forest,neural network,support vector machine,and eXtreme gradient boosting,are trained on PCA-reduced features.Among these,the neural network model achieved the best performance,with R^(2)>0.97 for permittivity and R 2>0.92 for resistivity.Gaussian noise(signal-to-noise ratio of 6 dB)is introduced to the synthetic data,and then targeted domain adaptation is employed to enhance generalization to field data.The framework is validated on two contrasting GPR transects in the Altay Mountains of the Chinese mainland,representing moist(T750)and wet(G125)snowpack conditions.The neural network model predictions are most consistent with the GPR derived estimates,Snowfork measurements,and snow pit data,achieving volumetric liquid water content deviation of≤1.5% and bulk density error within the range of 30-84 kg m^(-3).The results demonstrate that machine learning-based inversion,supported by realistic simulations and data augmentation enables scalable,non-invasive snowpack characterization with significant applications in hydrological forecasting,snow monitoring,and water resource management.
基金funded by the National Natural Science Foundation of China(Nos.31700542,32071745,31870602,31800519 and 31901295)Program of Sichuan Excellent Youth Sci-Tech Foundation(No.2020JDJQ0052)the National Key Research and Development Program of China(Nos.2016YFC0502505 and 2017YFC0505003)。
文摘Background:Soil fungi play crucial roles in ecosystem functions.However,how snow cover change associated with winter warming affects soil fungal communities remains unclear in the Tibetan forest.Methods:We conducted a snow manipulation experiment to explore immediate and legacy effects of snow exclusion on soil fungal community diversity and composition in a spruce forest on the eastern Tibetan Plateau.Soil fungal communities were performed by the high throughput sequencing of gene-fragments.Results:Ascomycota and Basidiomycota were the two dominant fungal phyla and Archaeorhizomyces,Aspergillus and Amanita were the three most common genera across seasons and snow manipulations.Snow exclusion did not affect the diversity and structure of soil fungal community in both snow-covered and snow-free seasons.However,the relative abundance of some fungal communities was different among seasons.Soil fungal groups were correlated with environmental factors(i.e.,temperature and moisture)and soil biochemical variables(i.e.,ammonium and enzyme).Conclusions:These results suggest that the season-driven variations had stronger impacts on soil fungal community than short-term snow cover change.Such findings may have important implications for soil microbial processes in Tibetan forests experiencing significant decreases in snowfall.
基金supported by the National Natural Science Foundation of China(Grant No.32471713)Fujian Natural Science Foundation(Grant No.2022J01642).
文摘The increasing global demand for timber and forest products has triggered the widespread conversion of subtropical forests into secondary forests and plantations.Soil fauna,the active angel in material cycling,are sensitive to changes in food resources and soil environments.However,the impact of forest conversion on soil fauna abundance and diversity remains insufficiently understood.To address this,we conducted seasonal soil fauna sampling in a subtropical region of China during July and November 2022,as well as January and March 2023.The sampling covered secondary forests,Castanopsis carlesii(broadleaved)plantations,and Cunninghamia lanceolata(fir)plantations,with natural forests serving as the control.We assessed soil fauna diversity including taxonomic and functional composition,along with soil physicochemical properties.Overall,forest conversion led to a decline in soil fauna abundance and biodiversity,with litter quality and soil moisture emerging as primary drivers according to Post hoc Least Significant Difference tests.Macrofauna demonstrated higher sensitivity to forest conversion than meso-and microfauna,with their abundance decreasing by 10%in secondary forests,18%in broadleaved plantations,and 27%in fir plantations.Moreover,the number of predator and saprophage groups declined more significantly when natural forests were converted into fir plantations(by 24%and 15%,respectively)than into broadleaved plantations(by 16%and 10%,respectively).Additionally,soil fauna showed more sensitive responses to forest conversion in spring and summer,especially in the case of the conversion into fir plantations.Our findings underscore the negative impacts of forest conversion on soil fauna biodiversity,particularly the reduction in predators and saprophages,which may disrupt the food web and increase ecosystem vulnerability to pests and diseases,thereby indicating potential risks to the stability of forest ecosystems.
基金The authors would like to acknowledge funding provided by the German government to the Gauss Centre for Supercomputing via the InHPC-DE project(01-H17001)This work has partly been funded by the EUROCC2 project funded by the European High-Performance Computing Joint Undertaking(JU)and EU/EEA states under grant agreement No 101101903+2 种基金This work has partly been funded by the German Research Foundation under Germany's Excel-lence Strategy,EXC-2070-390732324-PhenoRobthe German Federal Ministry of Education and Research(BMBF)in the framework of the funding initiative Soil as a Sustainable Resource for the Bioeconomy BonaRes,the project BonaRes(Module A):Sustainable Subsoil Management-Soil3subproject 3(grant 031B1066C).
文摘This article describes an immersive virtual reality reconstruction tool for root system architectures from 3D scans of soil columns.In practical scenarios,experimental conditions will be adapted to fit the need of the data analysis pipeline,including sieving and drying the soil before scanning.Based on previous reports of automatic systems that do not represent what experts would annotate,we developed a virtual reality system to assist with the extraction of root systems in cases in which automated approaches fall short of expert knowledge.The aim of the present study is to evaluate whether our immersive method is superior to classical annotation approaches when tested on synthetic data sets using untrained participants.Our laboratory user study consists of evaluating the root extractions of participants,along with their rating on central user experience and usability measures.We show significant improvement in F1 score across conditions(noisy or clear data)as well as an improved usability.Our study highlights that using virtual reality in root extraction improves accuracy,and we perform an in-depth evaluation of biases that occur when users trace roots in soil volumes.
基金supported by the Institute of Soil Science,Chinese Academy of Sciences(ISSAS2419)National Natural Science Foundation of China(42307048)+4 种基金Natural Science Foundation of Jiangsu,China(BK20231099)International Atomic Energy Agency Coordinated Research Project(D15022)Center for Health Impacts of Agriculture of Michigan State University and Research Group Linkage project from Alexander von Humboldt Foundationthe German Science Foundation(FOR 5095)Chinese Academy of Sciences,President’s International Fellowship Initiative(2024DC0009).
文摘Antimicrobial resistance poses a major challenge to modern medicine and jeopardizes the ability to maintain a robust global public health response against persistent infectious disease threats.A 2024 Lancet series on antimicrobial resistance estimated that bacterial antimicrobial resistance was associated with 4.71 million deaths globally in 2021,including 1.14 million deaths directly attributable to resistant infections.If not actively addressed,antimicrobial resistance might result in an annual reduction of the global gross domestic product by$3.4 trillion and push an additional 24 million individuals into extreme poverty within the next decade.Antibiotic resistance genes(ARGs)are the key culprits behind antimicrobial resistance,widely disseminating among bacterial populations,particularly in medical,agricultural,and veterinary sectors.Furthermore,anthropogenic activities,such as wastewater discharge,trade,tourism,and chemical contamination,have reshaped microbial biogeography,creating an unforeseen global platform for ARG mobilization.This exacerbates the existing antimicrobial resistance crisis and enhances risks to global public health and environmental stability.
基金funded by National Key R&D Program of China(2024YFC3713900)the Institute of Soil Science,Chinese Academy of Sciences(ISSAS2419)+4 种基金the Natural Science Foundation of Jiang Su,China(BK20241702)International Atomic Energy Agency Coordinated Research Project(D15021)China Postdoctoral Science Foundation(BX20240388,2024M753327)the fellowship of Special Research Assistant Program of the Chinese Academy of Sciences,and the Jiangsu Funding Program for Excellent Postdoctoral Talent(2024ZB046)the Research Group Linkage project from Alexander von Humboldt foundation.Wulf Amelung and Matthias C.Rillig acknowledge the Chinese Academy of Sciences President's International Fellowship Initiative for Distinguished Scientists(2024DC0009,2025PD0073).
文摘The widespread use of agricultural plastic films has made micro-and nanoplastics(MNPs)and phthalate esters(PAEs)contaminants of emerging concern in agroecosystems.However,the interactive mechanisms underlying their combined pollution in soil-plant systems remain elusive.To fill this gap,this study investigated the interaction between submicron plastics(SMPs,0.01%and 0.1%w/w)and di(2-ethylhexyl)phthalate(DEHP)in soil-lettuce systems.Contrary to the anticipated synergistic toxicity,DEHP significantly reduced SMP uptake into and by cracked surface cells of lettuce roots(with root concentration factors decreasing by 19%-64%),i.e.,DEHP alleviated SMP-induced oxidative stress,as evidenced by reduced levels of reactive oxygen species(-26.8%and-66.7%)and antioxidant enzyme activities(-118%and-128%).Metabolomic profiling revealed that SMP exposure significantly dysregulated multiple metabolic pathways(amino acid,carbohydrate,energy,glycan,lipid,and nucleotide metabolism),while SMP+DEHP co-exposure selectively attenuated these metabolic disturbances,showing enrichment only in glycan biosynthesis/metabolism and suppressing SMP-induced perturbations in other pathways(biosynthesis of secondary metabolites,energy metabolism,and signal transduction).Microbial community analysis showed that high-level SMP exposure significantly diminished bacterialα-diversity and amplicon sequence variant(ASV)richness,whereas DEHP supplementation enhanced those of Myxococcota in the soil,potentially counterbalancing SMP-induced microbial dysbiosis.These findings collectively demonstrate that co-contamination by MNPs and plastic additives may produce antagonistic interactions rather than uniformly synergistic effects,and provide a more comprehensive evaluation of the risks of PAEs and MNPs to food security,human health,and ecological environment.
文摘A significant number of emerging pollutants(EPs)resulting from point and diffuse pollution is present in the aquatic environment.These are chemicals that are not commonly monitored but have the potential to enter the environment and cause adverse ecological and human health effects.According to the NORMAN network,at least 700 substances categorized into 20 classes,have been identified in the European aquatic environment.In light of their potential impact action is urgently required.In this study,we present a concept that shows the current state of art and challenges for monitoring programs,fate and risk assessment tools and requirements for policies with respect to emerging pollutants as a base for sustainable water resource management.Currently,methods for sampling and analysis are not harmonized,being typically focused on certain EP classes.For a number of known highly hazardous EPs detection limits are too high to allow proper risk assessment.For other EPs such as microplastics method development is in its infancy.Advanced ultra-sensitive instrumental techniques should be used for quantitative determination of prioritized EPs in water,suspended matter,soil and biota.Data on EPs'and their metabolites'properties that determine their fate in the environment are often not available.National surveys on water quality often use different parameters for water quality assessment and often do not include EPs.A harmonized monitoring of surface and groundwater is not yet achieved and urgently required.Specific component integrated into models assessing the fate of EPs in a multi compartment environmental approach are missing and must be developed.The main goal of risk assessment is the overall protection of ecological communities in the aquatic environment and human health.New methods for assessing the cumulative risks from combined exposures to several stressors,including mixtures of EPs in a multi-scale approach are required.A combination of regulations and management measures with respect to use/emissions of EPs into the environment,as well as to their occurrence in the environment are fundamental to reach an efficient water resource management.
基金the support by the SFB-TR32 "Patterns in SoilVegetation-Atmosphere Systems:Monitoring,Modelling and Data Assimilation" funded by the Deutsche Forschungsgemeinschaft (DFG)TERENO (Terrestrial Environmental Observatories) funded by the Helmholtz Association of German Research Centers
文摘Integrated observation platforms have been set up to investigate consequences of global change within a terrestrial network of observatories （TERENO） in Germany. The aim of TERENO is to foster the understanding of water, energy, and matter fluxes in terrestrial systems, as well as their biological and physical drivers. Part of the Lower Rhine Valley-Eifel observatory of TERENO is located within the Eifel National Park. Recently, the National Park forest management started to promote the nat- ural regeneration of near-natural beech forest by removing a significant proportion of the spruce forest that was established for timber production after World War II. Within this context, the effects of such a disturbance on forest ecosystem functioning are currently investigated in a deforestation experiment in the Wtistebach catchment, which is one of the key experimental re- search sites within the Lower Rhine Valley-Eifel observatory. Here, we present the integrated observation system of the Wiistebach test site to exemplarily demonstrate the terrestrial observatory concept of TERENO that allows for a detailed mon- itoring of changes in hydrological and biogeochemical states and fluxes triggered by environmental disturbances. We present the observation platforms and the soil sampling campaign, as well as preliminary results including an analysis of data con- sistency. We specifically highlight the capability of integrated datasets to enable improved process understanding of the post-deforestation changes in ecosystem functioning.
