[Objective]Vegetation restoration is an effective strategy for ecological improvement;however,inappropriate vegetation establishment can induce soil desiccation,thereby threatening ecosystem stability.Therefore,elucid...[Objective]Vegetation restoration is an effective strategy for ecological improvement;however,inappropriate vegetation establishment can induce soil desiccation,thereby threatening ecosystem stability.Therefore,elucidating the global response patterns of soil moisture to vegetation restoration and identifying research hotspots are critical for guiding ecological construction in arid regions.[Methods]We reviewed 6,152 articles concerning soil moisture and vegetation retrieved from the Web of Science platform.Using VOSviewer,we conducted analyses of keyword co-occurrence,publication trends,and research hotspots to systematically delineate the evolving trends in this field.[Results]The results indicate a significant increasing trend in the number of publications since 2000.Global research keywords are categorized into seven clusters,including vegetation,soil moisture,rainfall-erosion-infiltration,spatial heterogeneity,and climate change.In terms of highly cited papers in 2024,China and the United States maintain a significant lead.Global research demonstrates a strong dependency on typical regional geographical features(such as climate types and topography),exhibiting differentiated research focuses.Furthermore,studies extend beyond soil moisture itself to deeply couple with ecological processes such as vegetation restoration,soil respiration,carbon cycling,and hydrothermal conditions.[Conclusions]The long-term ecological effects of afforestation in arid regions remain unclear,and empirical data from key regions highlight the current urgency.Future research should integrate climate change dynamics,innovate monitoring methodologies,and deepen the understanding of regional differentiation to provide scientific support for the adaptive management of vegetation in arid regions.展开更多
The root-to-shoot(R/S)ratio is a critical indicator of the balance between root biomass and shoot biomass,representing the ecological strategies and adaptive responses of plants to environmental conditions.However,the...The root-to-shoot(R/S)ratio is a critical indicator of the balance between root biomass and shoot biomass,representing the ecological strategies and adaptive responses of plants to environmental conditions.However,the patterns of change in community R/S ratios during forest succession and their response to moisture levels across broad geographic gradients remains unclear.Based on forest biomass data from a national field inventory of 5,825 plots conducted across China between 2011 and 2015,this study looked into allocating biomass shoots and roots at the early,middle,and late stages of growth in plantations and succession in natural forests,and evaluated how moisture availability influences this allocation.The results revealed a significant decline in R/S ratios from early to late stages for both plantations and natural forests.Shoot and root biomass in plantations grew isometrically during the early and middle succession stages but shifted to allometric growth in the late stage,with the slope of the log-transformed shoot-root biomass relationship differing significantly across growth stages.Natural forests,in contrast,maintained isometric growth across successional stages,showing no significant variation in the slope of the log-transformed shoot-root biomass relationship.Environmental factors,particularly moisture levels,strongly influenced R/S ratios.Moisture levels significantly affected size-corrected R/S ratios,particularly in the middle stage of plantations and the early and middle stages of natural forests,supporting the hypothesis of optimal allocation.These findings suggest that in water-limited regions,forest management should prioritize drought-tolerant,deep-rooted native species,encourage mixed-species planting in the early stage,and reduce logging intensity in mature plantations.Conserving natural forests to maintain successional dynamics is essential for long-term ecological resilience.These findings emphasize the importance of balancing productivity with ecological sustainability by adapting practices to specific environments and forest types under climate change.展开更多
Moisture electricity generation(MEG)has emerged as a sustainable and versatile energy-harvesting technology capable of converting ubiquitous environmental moisture into electrical energy,which holds great promise for ...Moisture electricity generation(MEG)has emerged as a sustainable and versatile energy-harvesting technology capable of converting ubiquitous environmental moisture into electrical energy,which holds great promise for renewable energy and constructing self-powered electronics.In this review,we begin by outlining the fundamental mechanisms—ion diffusion,electric double layer formation,and streaming potential—that govern charge transport for MEG in moist environments.A comprehensive survey of material innovations follows,highlighting breakthroughs in carbon-based materials,conductive polymers,hydrogels,and bio-inspired systems that enhance MEG performance,scalability,and biocompatibility.We then explore a range of device architectures,from planar and layered systems to flexible,miniaturized,and textile-integrated designs,engineered for both energy conversion and sensor integration.Key challenges are analyzed,along with strategies for overcoming them.We conclude with a forward-looking perspective on future directions,including hybrid energy systems,AI-assisted material design,and real-world deployment.This review presents a timely and comprehensive overview of MEG technologies and their trajectory toward practical and sustainable energy solutions.展开更多
Sichuan sausages with moisture contents of 40%,45%,50%,and 60% were stored at-18℃for durations of 0,2,4,6,and 8 weeks to evaluate the effect of moisture content on the quality attributes of Sichuan sausages during fr...Sichuan sausages with moisture contents of 40%,45%,50%,and 60% were stored at-18℃for durations of 0,2,4,6,and 8 weeks to evaluate the effect of moisture content on the quality attributes of Sichuan sausages during frozen storage.Product indicators including pH,colour,thiobarbituric acid reactive substances(TBARS),total volatile basic nitrogen(TVB-N),texture,electronic nose(E-nose)response,and water-holding capacity(thawing and cooking losses)were determined.The results indicated that as storage time increased,water retention in Sichuan sausages with different moisture contents decreased,while the degree of protein and lipid oxidation increased.This led to an increase in pH value,a colour shift from red-bright to grey-brown,and a deterioration in palatability.Among the samples,sausages with 50% moisture content exhibited the lowest thawing and cooking losses,indicating superior water-holding capacity.After 8 weeks of storage,TBARS and TVB-N values for the 50% moisture group were 19.5%and 2.5%lower,respectively,than those of the 40%and 45%moisture groups,indicating a reduced degree of oxidation.Furthermore,Sichuan sausage with 50%moisture content demonstrated an appropriate pH and colour difference,along with excellent texture and flavour,as evidenced by its higher toughness and satisfactory hardness.In conclusion,Sichuan sausage with 50% moisture content demonstrated the highest overall quality under frozen storage conditions.展开更多
Soil moisture(SM)is a critical variable in terrestrial ecosystems,especially in arid and semi-arid areas where water sources are limited.Despite its importance,understanding the spatiotemporal variations and influenci...Soil moisture(SM)is a critical variable in terrestrial ecosystems,especially in arid and semi-arid areas where water sources are limited.Despite its importance,understanding the spatiotemporal variations and influencing factors of SM in these areas remains insufficient.This study investigated the spatiotemporal variations and influencing factors of SM in arid and semi-arid areas of China by utilizing the extended triple collation(ETC),Mann-Kendall test,Theil-Sen estimator,ridge regression analysis,and other relevant methods.The following findings were obtained:(1)at the pixel scale,the long-term monthly SM data from the European Space Agency Climate Change Initiative(ESA CCI)exhibited the highest correlation coefficient of 0.794 and the lowest root mean square error(RMSE)of 0.014 m^(3)/m^(3);(2)from 2000 to 2022,the study area experienced significant increase in annual average SM,with a rate of 0.408×10^(-3)m^(3)/(m^(3)•a).Moreover,higher altitudes showed a notable upward trend,with SM increasing rates at 0.210×10^(-3)m^(3)/(m^(3)•a)between 1000 and 2000 m,0.530×10^(-3)m^(3)/(m^(3)•a)between 2000 and 4000 m,and 0.760×10^(-3)m^(3)/(m^(3)•a)at altitudes above 4000 m;(3)land surface temperature(LST),root zone soil moisture(RSM)(10-40 cm depth),and normalized difference vegetation index(NDVI)were identified as the primary factors influencing annual average SM,which accounted for 34.37%,24.16%,and 22.64%relative contributions,respectively;and(4)absolute contribution of LST was more significant in subareas at higher altitudes,with average absolute contributions of 0.800×10^(-3)m^(3)/(m^(3)•a)between 2000 and 4000 m and 0.500×10^(-2) m^(3)/(m^(3)•a)above 4000 m.This study reveals the spatiotemporal variations and main influencing factors of SM in Chinese arid and semi-arid areas,highlighting the more pronounced absolute contribution of LST to SM in high-altitude areas,providing valuable insights for ecological research and water resource management in these areas.展开更多
Soil desiccation cracking is a common phenomenon on the earth surface.Numerical modeling is an effective approach to study the desiccation cracking mechanism of soil.This work develops a novel 3D moisture diffusion di...Soil desiccation cracking is a common phenomenon on the earth surface.Numerical modeling is an effective approach to study the desiccation cracking mechanism of soil.This work develops a novel 3D moisture diffusion discrete model that is capable of dynamically assessing the effect of cracking on moisture diffusion and allowing moisture to be discontinuous on both sides of the cracks.Then,the parametric analysis of the moisture exchange coefficient in the 3D moisture diffusion discrete model is carried out for moisture diffusion in continuous media,and the selection criterion of the moisture exchange coefficient for the unbroken cohesive element is given.Subsequently,an example of moisture migration in a medium with one crack is provided to illustrate the crack hindering effect on moisture migration.Finally,combining the 3D moisture diffusion discrete model with the finite-discrete element method(FDEM),the moisture diffusion-fracture coupling model is built to study the desiccation cracking in a strip soil and the crack pattern of a rectangular soil.The evolution of crack area and volume with moisture content is quantitatively analyzed.The modeling number and average width of cracks in the strip soil show a good consistency with the experimental results,and the crack pattern of the rectangular soil matches well with the existing numerical results,validating the coupled moisture diffusion-fracture model.Additionally,the parametric study of soil desiccation cracking is performed.The developed model offers a powerful tool for exploring soil desiccation cracking.展开更多
Southerly moisture surges over the central South China Sea(SCS)are characterized by the strengthening of lowlevel southerlies that transport moisture northward from the Pacific or Indian Oceans to South China.These su...Southerly moisture surges over the central South China Sea(SCS)are characterized by the strengthening of lowlevel southerlies that transport moisture northward from the Pacific or Indian Oceans to South China.These surge events typically occur for days in the early-summer season(from April to June)and can lead to heavy rains in South China.This study categorizes surge events into three types of flow patterns and examines their multiscale variations and impacts on rainfall.The first type occurs mainly in April,with the southeasterlies enhanced by a deepening trough in South China and the western Pacific subtropical high established over the SCS.The second type of surge events mostly appears in June,featuring the prevailing southwesterlies of summer monsoon from the Indian Ocean during the active phases of intraseasonal oscillations.Most surge events exhibit semi-diurnal variations with morning and afternoon peaks of northward moisture fluxes.Specifically,the first type features a dominant afternoon peak,while the second type shows a dominant early-morning peak,which is induced by thermal contrast between the Indochina Peninsula and the SCS.In general,the surge events enhance moisture convergence and increase rainfall downstream in South China,but they show some regional differences.The second type strengthens moisture convergence and rainfall in coastal regions with a morning peak.In contrast,the first type enhances inland rainfall with a morning peak,while moisture divergence dominates coastal regions.The third type of surge events denotes transitional conditions between the first two types,in terms of atmospheric circulations,diurnal cycles,and rainfall patterns.These results highlight a diversity of regional moisture surges and related rainfall ranging from diurnal to sub-seasonal scales.展开更多
Mountainous areas are the priority for forest restoration in semiarid regions,with hillslopes serving as the basic units of mountains.Precipitation is the only water source in these regions,and the uneven distribution...Mountainous areas are the priority for forest restoration in semiarid regions,with hillslopes serving as the basic units of mountains.Precipitation is the only water source in these regions,and the uneven distribution of hillslope soil moisture replenishment after precipitation determines vegetation survival and growth.Therefore,in this study experiments were performed on a hillslope in the Liupan Mountains,Ningxia Hui Autonomous Region,China,to quantify the unevenness of soil moisture replenishment.Soil water content(SWC)in the 0–60 cm layer and precipitation were monitored throughout the growing season in 2020 and 2021.The results showed that(1)Annual soil moisture replenishment was the highest at the mid-slope position,with an average of 309.9 mm,especially under moderate and heavy rain grade conditions,reaching 38.7% and 30.8% of the total replenishment,respectively;(2)Vertical replenishment played a dominant role in the total replenishment,accounting for 82.8%;lateral replenishment played an important but lesser role,accounting for up to 17.2% of the total replenishment;(3)Based on a soil moisture replenishment model established in this study,the maximal replenishment occurred at 90 m from the top of the slope;(4)The dominant factors contributing to the soil moisture replenishment were rainfall amount and saturated hydraulic conductivity(Ks).These findings suggest that attention should be given to both vertical and lateral soil moisture replenishment,and the mid-slope position could be preferred for site selection to achieve precise and integrated forest-water management on hillslopes in semi-arid mountainous regions.展开更多
Moisture-enabled electricity generation(MEG)has emerged as a promising sustainable energy harvesting technology,comparable to photovoltaics,thermoelectrics,and triboelectrics[1].MEGs generate electricity by converting...Moisture-enabled electricity generation(MEG)has emerged as a promising sustainable energy harvesting technology,comparable to photovoltaics,thermoelectrics,and triboelectrics[1].MEGs generate electricity by converting the chemical potential of moisture into electric energy through interactions with hygroscopic materials and nanostructured interfaces.Unlike solar or thermal harvesters,MEGs operate continuously by utilizing ubiquitous atmospheric moisture,granting them unique spatial and temporal adaptability.Despite nearly a decade of progress and the exploration of diverse material systems for MEG,the overall output power remains significantly limited due to inherently low charge carrier concentrations and restricted ion diffusion fluxes[2].As a result,standalone MEG devices often deliver low and unstable output,limiting practical applications.To enhance performance and versatility,recent efforts have explored hybridization of MEG with other ambient energy sources such as triboelectric or thermoelectric effects.展开更多
The article examines the impact of increased aridization of the territory due to an increase in air temperature,reduced precipitation,and the formation of moisture deficiency on grain yields in Northern Kazakhstan.The...The article examines the impact of increased aridization of the territory due to an increase in air temperature,reduced precipitation,and the formation of moisture deficiency on grain yields in Northern Kazakhstan.The most important result of the work is the revealed inverse relationship between grain yields and the temperature of the growing season:low-yielding years are associated with high temperatures and droughts,and high-yielding years are associated with lower temperatures and an optimal ratio of heat and moisture.The novelty of this study is the use of the method of hydrological and climatic calculations in identifying the nature of temperature variability and precipitation in the territory of Northern Kazakhstan for the modern period(1991–2020)compared with the base period(1961–1990).At all the studied meteorological stations,there is a tendency for the average annual temperature and the temperature of the growing season to increase:in the forest-steppe zone with an average warming intensity of 0.3–0.33℃ per decade;in the steppe zone by 0.2–0.43℃ per decade;and in the growing season by 0.2–0.7℃ per decade.The air temperature in the steppe zone is rising more intensively than in the forest-steppe zone,and precipitation in the forest-steppe zone has changed more than in the steppe zone.An increase in the average annual air temperature during the growing season(May–August),combined with a shortage of atmospheric moisture or a constant amount of it,led to an increase in the degree of aridization of the territory,an increase in the frequency of droughts in the steppe zone of Northern Kazakhstan.展开更多
Heatwaves are becoming increasingly frequent and severe,posing escalating risks to ecosystems and human well-being.While soil moisture(SM)deficits are recognized as important contributors to heatwave amplification,the...Heatwaves are becoming increasingly frequent and severe,posing escalating risks to ecosystems and human well-being.While soil moisture(SM)deficits are recognized as important contributors to heatwave amplification,their spatially heterogeneous impacts across the Northern Hemisphere remain insufficiently understood.In this study,we analyze ERA5 reanalysis data(1980-2022)to investigate trends in heatwave frequency,intensity,and duration,as well as their sensitivity to SM variability.Our results show robust increases in heatwave occurrence(0.76 events per decade),intensity(0.81℃per decade),and average duration(0.40 days per decade),with extreme events,as represented by maximum intensity and duration,rising at even faster rates(2.18℃per decade and 0.83 days per decade,respectively).Strong negative correlations are observed between SM deficits and heatwave metrics,with the magnitude of this relationship varying across land cover types and heatwave severity levels.Quantile regression reveals that SM reductions have a greater impact at higher quantiles for most indicators.Cropland exhibits the highest sensitivity to SM anomalies,whereas forests show more resilience due to their superior water retention capacities.These findings underscore the crucial role of land-atmosphere interactions in shaping heatwave extremes,providing a scientific basis for enhancing early warning and adaptation strategies in the context of ongoing climate change.展开更多
From 26 October to 2 November 2024,Spain experienced a record-breaking rainfall event,with the most intense episode appearing in Valencia Province.During the event,Turis station recorded a historic 24-hour precipitati...From 26 October to 2 November 2024,Spain experienced a record-breaking rainfall event,with the most intense episode appearing in Valencia Province.During the event,Turis station recorded a historic 24-hour precipitation of 710.8 mm,exceeding the national annual average.This resulting flood led to widespread disruption and significant societal impacts.Synoptic analyses reveal that the event was dominated by a deep cut-off low extending through the entire troposphere and persisting for approximately 186 h.Background conditions were characterized by upper-level divergence,mid-tropospheric warm advection,and a strong southeasterly low-level jet,which promoted vertical motion and sustained moisture transport.The steep,funnel-shaped terrain along the eastern Iberian coast further triggered and enhanced the local convection.A 10-day backward Lagrangian moisture tracing using the HYSPLIT model identified the Mediterranean Sea as the primary moisture source(78.1%),followed by northwestern Africa(8.5%)and central-eastern Europe/the Black Sea(6.2%).Low-level moisture transport was mainly driven by the cut-off low and a persistent Mediterranean high,while mid-to upper-level trajectories were associated with a preceding low-pressure system over the Mediterranean and the subtropical Atlantic high.These systems acted in sequence to relay moisture toward the Valencia region,and under the influence of the strongly rotating and convergent cut-off low—along with terrain-induced lifting—this moisture was rapidly uplifted,ultimately triggering the extreme rainfall event.展开更多
Understanding the ecological processes shaping competitive interactions among forest trees is crucial for predicting ecosystem productivity and climate change resilience.However,few studies have investigated how the b...Understanding the ecological processes shaping competitive interactions among forest trees is crucial for predicting ecosystem productivity and climate change resilience.However,few studies have investigated how the biological attributes of tropical species may affect competitive outcomes under varying resource conditions.We collected and analysed a 10-year dataset of radial growth rates in canopy trees from a network of forest inventory plots located in divergent forest types over an extensive meteorological gradient in Ghana,West Africa.We used nonlinear models to estimate the relative reduction in potential growth(basal area increment)of individual target trees of a given species as a consequence of the combined effects of(1)target tree size,(2)variation in crowding levels by neighbouring trees,(3)the functional attributes of those neighbours(wood density and shade tolerance),and(4)local soil moisture levels.Analyses were conducted separately for the 15 most common species in the inventory network.In opposition to neutral theory,our findings indicate that the strength of interactions among competing species was distinctly asymmetric and dynamic.Wood density was an important characteristic that modified competitive outcomes for most species,particularly under varying levels of resource availability.Specifically,dense wood was an attribute that conferred comparatively stronger competitive ability in moisture-limited conditions.Larger individuals were notably less sensitive to the effects of moisture-dependent competition.Our results suggest that attributes such as wood density may reflect divergent life history strategies that differentiate species’fitness and competitive ability in varying environments.The dynamic nature of competition,influenced by a complex interplay of biological and abiotic factors,implies that more prevalent dry periods,which have been forecast for tropical Africa,may impact the physiognomy and function of future forest communities in the region.展开更多
This study aimed to explore the relationship between Soil-Plant Analysis Development(SPAD)values and key environmental factors in cucumber(Cucumis sativus L.)cultivation in a greenhouse.SPAD values,indicative of chlor...This study aimed to explore the relationship between Soil-Plant Analysis Development(SPAD)values and key environmental factors in cucumber(Cucumis sativus L.)cultivation in a greenhouse.SPAD values,indicative of chlorophyll content,reflect plant health and productivity.The analysis revealed strong positive correlations between SPADvalues and both indoor light intensity(ILI,r=0.59,p<0.001)and outdoor light intensity(OLI,r=0.62,p<0.001),suggesting that higher light intensities were associated with enhanced SPAD values.In contrast,significant negative correlations were found between SPAD values and soil temperature at 15-30 cm depth(ST1530,r=−0.47,p<0.001)and volumetric soil moisture content at the same depth(SM1530,r=−0.52,p<0.001),with higher soil temperatures(e.g.,28℃)and excessive moisture(e.g.,25%)leading to reduced SPAD values.Multiple regression analysis identified ST1530 and SM1530 as significant negative predictors of SPAD,with coefficients of−0.97(p=0.05)and−0.34(p=0.05),respectively,suggesting that increases in soil temperature and moisture result in lower SPAD values.Indoor light intensity(e.g.,600-800μmol/m^(2)/s)emerged as a significant positive contributor,with a coefficient of 0.01(p<0.001),highlighting its role in promoting chlorophyll synthesis.Additionally,relative humidity(r=0.27,p<0.01)showed a positive,although less pronounced,association with SPAD.These results underscore the importance of both direct and indirect environmental factors in influencing SPAD variability and,by extension,plant health and productivity in cucumber cultivation.展开更多
The source region of the Yellow River(SRYR),with its semi-humid to semi-arid climate,is crucial for understanding water resource dynamics.Precipitation is key for replenishing surface water and balancing the ecosystem...The source region of the Yellow River(SRYR),with its semi-humid to semi-arid climate,is crucial for understanding water resource dynamics.Precipitation is key for replenishing surface water and balancing the ecosystem’s water cycle.However,the soil moisture response to precipitation across climate zones and soil layers remains poorly understood due to limited long-term data.This study examines the response of soil moisture to precipitation at multiple time scales in the SRYR,using data from Maqu,Mado,Ngoring Lake sites,and the Maqu monitoring network(MMN),along with CN05.1 precipitation and GLEAM v3.8a soil moisture data.Results show that the semi-humid area requires more precipitation to trigger soil moisture responses compared to the semi-arid area in the SRYR.Surface soil at Maqu,MMN,Ngoring Lake,and Mado sites require at least 8.6,8.4,5.2,and 2.84 mm of precipitation,respectively,for effective replenishment.Significant responses to precipitation events were observed in soil layers at 40 cm and above in the semi-humid area,while at 20 cm and above in the semi-arid area.Precipitation volume is the primary factor influencing soil moisture,affecting both the increment and time lag to maximum moisture.Precipitation intensity and pre-rain moisture have no direct effect.In the central SRYR,accumulated precipitation has a greater impact.Root-zone soil moisture has a weaker correlation with precipitation compared to surface soil moisture but persists longer,responding for up to 10 days,while surface soil moisture responds more immediately but only lasts about 5 days.展开更多
Mn-based P2-type oxides are considered as promising cathodes for Na-ion batteries;however,they face significant challenges,including structural degradation when charged at high cutoff voltages and structural changes u...Mn-based P2-type oxides are considered as promising cathodes for Na-ion batteries;however,they face significant challenges,including structural degradation when charged at high cutoff voltages and structural changes upon storing in a humid atmosphere.In response to these issues,we have designed an oxide with co-doping of Cu and Al which can balance both cost and structural stability.The redox reaction of Cu^(2+/3+)can provide certain charge compensation,and the introduction of Al can further suppress the Jahn-Teller effect of Mn,thereby achieving superior long-term cycling performance.The ex-situ XRD testing indicates that Cu/Al co-doping can effectively suppress the phase transition of P2-O2 at high voltage,thereby explaining the improvement in electrochemical performance.DFT calculations reveal a high chemical tolerance to moisture,with lower adsorption energy for H_(2)O compared to pure Na_(0.67)Cu_(0.25)Mn_(0.75)O_(2).A representative Na_(0.67)Cu_(0.20)Al_(0.05)Mn_(0.75)O_(2)cathode demonstrates impressive reversible capacities of 148.7 mAh/g at 0.2 C,along with a remarkable capacity retention of 79.1%(2 C,500 cycles).展开更多
Drought significantly constrains vegetation growth and reduces terrestrial carbon sinks.Currently,the spatiotemporal patterns and mechanisms of the differential impacts of soil and meteorological droughts on vegetatio...Drought significantly constrains vegetation growth and reduces terrestrial carbon sinks.Currently,the spatiotemporal patterns and mechanisms of the differential impacts of soil and meteorological droughts on vegetation productivity remain inadequately understood.In this study,we analyzed soil moisture(SM),vapor pressure deficit(VPD),and gross primary productivity(GPP)to investigate their spatiotemporal patterns and the combined effects on GPP over China.The results revealed that:(1)Soil drought and meteorological drought generally exhibited temporally synchronous trends across China.(2)GPP was predominantly affected by the combined and synchronous effects of both SM and VPD,although their effects displayed directional variability differences in certain regions.(3)SM demonstrated a greater relative importance on GPP than VPD across more than half of the regions in China,whereas deciduous broadleaf forests were the only vegetation type primarily affected by VPD.(4)Under the lag effects,both SM and VPD exhibited bidirectional Granger causality with GPP,with the interaction between VPD and GPP proving more pronounced than that of SM.Our research provides valuable insights into the mechanisms through which SM and VPD influence GPP,contributing to improved predictions vegetation productivity and implementing ecological restoration.展开更多
Moisture accumulation within road pavements,particularly in unbound granular materials with or without thin sprayed seals,presents significant challenges in high-rainfall regions such as Queensland.This infiltration o...Moisture accumulation within road pavements,particularly in unbound granular materials with or without thin sprayed seals,presents significant challenges in high-rainfall regions such as Queensland.This infiltration often leads to various forms of pavement distress,eventually causing irreversible damage to the pavement structure.The moisture content within pavements exhibits considerable dynamism and directly influenced by environmental factors such as precipitation,air temperature,and relative humidity.This variability underscores the importance of monitoring moisture changes using real-time climatic data to assess pavement conditions for operational management or incorporating these effects during pavement design based on historical climate data.Consequently,there is an increasing demand for advanced,technology-driven methodologies to predict moisture variations based on climatic inputs.Addressing this gap,the present study employs five traditional machine learning(ML)algorithms,K-nearest neighbors(KNN),regression trees,random forest,support vector machines(SVMs),and gaussian process regression(GPR),to forecast moisture levels within pavement layers over time,with varying algorithm complexities.Using data collected from an instrumented road in Brisbane,Australia,which includes pavement moisture and climatic factors,the study develops predictive models to forecast moisture content at future time steps.The approach incorporates current moisture content,rather than averaged values,along with seasonality(both daily and annual),and key climatic factors to predict next step moisture.Model performance is evaluated using R2,MSE,RMSE,and MAPE metrics.Results show that ML algorithms can reliably predict long-term moisture variations in pavements,provided optimal hyperparameters are selected for each algorithm.The best-performing algorithms include KNN(the number of neighbours equals to 15),medium regression tree,medium random forest,coarse SVM,and simple GPR,with medium random forest outperforming the others.The study also identifies the optimal hyperparameter combinations for each algorithm,offering significant advancements in moisture prediction tools for pavement technology。展开更多
Soil moisture is a key parameter in the exchange of energy and water between the land surface and the atmosphere.This parameter plays an important role in the dynamics of permafrost on the Qinghai-Xizang Plateau,China...Soil moisture is a key parameter in the exchange of energy and water between the land surface and the atmosphere.This parameter plays an important role in the dynamics of permafrost on the Qinghai-Xizang Plateau,China,as well as in the related ecological and hydrological processes.However,the region's complex terrain and extreme climatic conditions result in low-accuracy soil moisture estimations using traditional remote sensing techniques.Thus,this study considered parameters of the backscatter coefficient of Sentinel-1A ground range detected(GRD)data,the polarization decomposition parameters of Sentinel-1A single-look complex(SLC)data,the normalized difference vegetation index(NDVI)based on Sentinel-2B data,and the topographic factors based on digital elevation model(DEM)data.By combining these parameters with a machine learning model,we established a feature selection rule.A cumulative importance threshold was derived for feature variables,and those variables that failed to meet the threshold were eliminated based on variations in the coefficient of determination(R^(2))and the unbiased root mean square error(ubRMSE).The eight most influential variables were selected and combined with the CatBoost model for soil moisture inversion,and the SHapley Additive exPlanations(SHAP)method was used to analyze the importance of these variables.The results demonstrated that the optimized model significantly improved the accuracy of soil moisture inversion.Compared to the unfiltered model,the optimal feature combination led to a 0.09 increase in R^(2)and a 0.7%reduction in ubRMSE.Ultimately,the optimized model achieved a R²of 0.87 and an ubRMSE of 5.6%.Analysis revealed that soil particle size had significant impact on soil water retention capacity.The impact of vegetation on the estimated soil moisture on the Qinghai-Xizang Plateau was considerable,demonstrating a significant positive correlation.Moreover,the microtopographical features of hummocks interfered with soil moisture estimation,indicating that such terrain effects warrant increased attention in future studies within the permafrost regions.The developed method not only enhances the accuracy of soil moisture retrieval in the complex terrain of the Qinghai-Xizang Plateau,but also exhibits high computational efficiency(with a relative time reduction of 18.5%),striking an excellent balance between accuracy and efficiency.This approach provides a robust framework for efficient soil moisture monitoring in remote areas with limited ground data,offering critical insights for ecological conservation,water resource management,and climate change adaptation on the Qinghai-Xizang Plateau.展开更多
Proton exchange membrane fuel cell(PEMFC)is a promising clean energy source,but its performance and stability are vulnerable to the negative effects of humidity conditions.The gas diffusion substrate(GDS)plays a pivot...Proton exchange membrane fuel cell(PEMFC)is a promising clean energy source,but its performance and stability are vulnerable to the negative effects of humidity conditions.The gas diffusion substrate(GDS)plays a pivotal role in regulating the moisture and gas transport.The single pore structure of traditionally designed GDS often leads to the pathway competition between moisture and gas,which effects the efficiency of fuel cells.In this study,we report on a hierarchical fibrous paper with tunable hierarchical pores for a sustainable GDS.This design offers gas permeability under wet conditions,by separating the gas pathway from the moisture pathway,thus mitigating their pathway competition.In addition,this paper forms a multi-scale scaffold that absorbs moisture under high humidity conditions and releases it under dry conditions.It is allowed to maintain an optimal internal humidity and further enhances the humidity adaptability.Furthermore,the carbon footprint is only 15.97%,significantly lower than commercial alternatives.This feature makes it a sustainable solution to stabilize PEMFCs under diverse humidity conditions.展开更多
文摘[Objective]Vegetation restoration is an effective strategy for ecological improvement;however,inappropriate vegetation establishment can induce soil desiccation,thereby threatening ecosystem stability.Therefore,elucidating the global response patterns of soil moisture to vegetation restoration and identifying research hotspots are critical for guiding ecological construction in arid regions.[Methods]We reviewed 6,152 articles concerning soil moisture and vegetation retrieved from the Web of Science platform.Using VOSviewer,we conducted analyses of keyword co-occurrence,publication trends,and research hotspots to systematically delineate the evolving trends in this field.[Results]The results indicate a significant increasing trend in the number of publications since 2000.Global research keywords are categorized into seven clusters,including vegetation,soil moisture,rainfall-erosion-infiltration,spatial heterogeneity,and climate change.In terms of highly cited papers in 2024,China and the United States maintain a significant lead.Global research demonstrates a strong dependency on typical regional geographical features(such as climate types and topography),exhibiting differentiated research focuses.Furthermore,studies extend beyond soil moisture itself to deeply couple with ecological processes such as vegetation restoration,soil respiration,carbon cycling,and hydrothermal conditions.[Conclusions]The long-term ecological effects of afforestation in arid regions remain unclear,and empirical data from key regions highlight the current urgency.Future research should integrate climate change dynamics,innovate monitoring methodologies,and deepen the understanding of regional differentiation to provide scientific support for the adaptive management of vegetation in arid regions.
基金supported by the China National Science Foundation(No.42130506,42071031)the Special Technology Innovation Fund of Carbon Peak and Carbon Neutrality in Jiangsu Province(BK20231515)+1 种基金the Spanish Government grant PID2022-140808NB-I00 funded by MICIU/AEI/https://doi.org/10.13039/501100011033the Catalan Government grants SGR 2021-1333 and AGAUR2023 CLIMA 00118.
文摘The root-to-shoot(R/S)ratio is a critical indicator of the balance between root biomass and shoot biomass,representing the ecological strategies and adaptive responses of plants to environmental conditions.However,the patterns of change in community R/S ratios during forest succession and their response to moisture levels across broad geographic gradients remains unclear.Based on forest biomass data from a national field inventory of 5,825 plots conducted across China between 2011 and 2015,this study looked into allocating biomass shoots and roots at the early,middle,and late stages of growth in plantations and succession in natural forests,and evaluated how moisture availability influences this allocation.The results revealed a significant decline in R/S ratios from early to late stages for both plantations and natural forests.Shoot and root biomass in plantations grew isometrically during the early and middle succession stages but shifted to allometric growth in the late stage,with the slope of the log-transformed shoot-root biomass relationship differing significantly across growth stages.Natural forests,in contrast,maintained isometric growth across successional stages,showing no significant variation in the slope of the log-transformed shoot-root biomass relationship.Environmental factors,particularly moisture levels,strongly influenced R/S ratios.Moisture levels significantly affected size-corrected R/S ratios,particularly in the middle stage of plantations and the early and middle stages of natural forests,supporting the hypothesis of optimal allocation.These findings suggest that in water-limited regions,forest management should prioritize drought-tolerant,deep-rooted native species,encourage mixed-species planting in the early stage,and reduce logging intensity in mature plantations.Conserving natural forests to maintain successional dynamics is essential for long-term ecological resilience.These findings emphasize the importance of balancing productivity with ecological sustainability by adapting practices to specific environments and forest types under climate change.
基金supported by the National Natural Science Foundation of China(52305388,BE0200030)Shanghai Pujiang Program(22PJ1407600)+1 种基金SJTU Explore X programShanghai Jiao Tong University Initiative Scientific Research Program(WH220402021)。
文摘Moisture electricity generation(MEG)has emerged as a sustainable and versatile energy-harvesting technology capable of converting ubiquitous environmental moisture into electrical energy,which holds great promise for renewable energy and constructing self-powered electronics.In this review,we begin by outlining the fundamental mechanisms—ion diffusion,electric double layer formation,and streaming potential—that govern charge transport for MEG in moist environments.A comprehensive survey of material innovations follows,highlighting breakthroughs in carbon-based materials,conductive polymers,hydrogels,and bio-inspired systems that enhance MEG performance,scalability,and biocompatibility.We then explore a range of device architectures,from planar and layered systems to flexible,miniaturized,and textile-integrated designs,engineered for both energy conversion and sensor integration.Key challenges are analyzed,along with strategies for overcoming them.We conclude with a forward-looking perspective on future directions,including hybrid energy systems,AI-assisted material design,and real-world deployment.This review presents a timely and comprehensive overview of MEG technologies and their trajectory toward practical and sustainable energy solutions.
基金Supported by National Modern Agricultural Industry Technology System Sichuan Pig Innovation Team(SCCXTD-2026-8)Sichuan Science and Technology Program(2025ZYD0049)"Challenge and Leadership"Project for Key Core Technologies of Sui Ning in Sichuan(2025SNKBZ19).
文摘Sichuan sausages with moisture contents of 40%,45%,50%,and 60% were stored at-18℃for durations of 0,2,4,6,and 8 weeks to evaluate the effect of moisture content on the quality attributes of Sichuan sausages during frozen storage.Product indicators including pH,colour,thiobarbituric acid reactive substances(TBARS),total volatile basic nitrogen(TVB-N),texture,electronic nose(E-nose)response,and water-holding capacity(thawing and cooking losses)were determined.The results indicated that as storage time increased,water retention in Sichuan sausages with different moisture contents decreased,while the degree of protein and lipid oxidation increased.This led to an increase in pH value,a colour shift from red-bright to grey-brown,and a deterioration in palatability.Among the samples,sausages with 50% moisture content exhibited the lowest thawing and cooking losses,indicating superior water-holding capacity.After 8 weeks of storage,TBARS and TVB-N values for the 50% moisture group were 19.5%and 2.5%lower,respectively,than those of the 40%and 45%moisture groups,indicating a reduced degree of oxidation.Furthermore,Sichuan sausage with 50%moisture content demonstrated an appropriate pH and colour difference,along with excellent texture and flavour,as evidenced by its higher toughness and satisfactory hardness.In conclusion,Sichuan sausage with 50% moisture content demonstrated the highest overall quality under frozen storage conditions.
基金supported by the Natural Science Foundation of Henan Province(252300421290)the National Natural Science Foundation of China(41771438)+1 种基金the Program for Innovative Research Team(in Science and Technology)of Henan University(22IRTSTHN010)the Postgraduate Education Reform and Quality Improvement Project of Henan Province(HNYJS2020JD14).
文摘Soil moisture(SM)is a critical variable in terrestrial ecosystems,especially in arid and semi-arid areas where water sources are limited.Despite its importance,understanding the spatiotemporal variations and influencing factors of SM in these areas remains insufficient.This study investigated the spatiotemporal variations and influencing factors of SM in arid and semi-arid areas of China by utilizing the extended triple collation(ETC),Mann-Kendall test,Theil-Sen estimator,ridge regression analysis,and other relevant methods.The following findings were obtained:(1)at the pixel scale,the long-term monthly SM data from the European Space Agency Climate Change Initiative(ESA CCI)exhibited the highest correlation coefficient of 0.794 and the lowest root mean square error(RMSE)of 0.014 m^(3)/m^(3);(2)from 2000 to 2022,the study area experienced significant increase in annual average SM,with a rate of 0.408×10^(-3)m^(3)/(m^(3)•a).Moreover,higher altitudes showed a notable upward trend,with SM increasing rates at 0.210×10^(-3)m^(3)/(m^(3)•a)between 1000 and 2000 m,0.530×10^(-3)m^(3)/(m^(3)•a)between 2000 and 4000 m,and 0.760×10^(-3)m^(3)/(m^(3)•a)at altitudes above 4000 m;(3)land surface temperature(LST),root zone soil moisture(RSM)(10-40 cm depth),and normalized difference vegetation index(NDVI)were identified as the primary factors influencing annual average SM,which accounted for 34.37%,24.16%,and 22.64%relative contributions,respectively;and(4)absolute contribution of LST was more significant in subareas at higher altitudes,with average absolute contributions of 0.800×10^(-3)m^(3)/(m^(3)•a)between 2000 and 4000 m and 0.500×10^(-2) m^(3)/(m^(3)•a)above 4000 m.This study reveals the spatiotemporal variations and main influencing factors of SM in Chinese arid and semi-arid areas,highlighting the more pronounced absolute contribution of LST to SM in high-altitude areas,providing valuable insights for ecological research and water resource management in these areas.
基金supported by the State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering(Grant No.SKLGDUEK2206)National Natural Science Foundation of China(Grant No.11872340).
文摘Soil desiccation cracking is a common phenomenon on the earth surface.Numerical modeling is an effective approach to study the desiccation cracking mechanism of soil.This work develops a novel 3D moisture diffusion discrete model that is capable of dynamically assessing the effect of cracking on moisture diffusion and allowing moisture to be discontinuous on both sides of the cracks.Then,the parametric analysis of the moisture exchange coefficient in the 3D moisture diffusion discrete model is carried out for moisture diffusion in continuous media,and the selection criterion of the moisture exchange coefficient for the unbroken cohesive element is given.Subsequently,an example of moisture migration in a medium with one crack is provided to illustrate the crack hindering effect on moisture migration.Finally,combining the 3D moisture diffusion discrete model with the finite-discrete element method(FDEM),the moisture diffusion-fracture coupling model is built to study the desiccation cracking in a strip soil and the crack pattern of a rectangular soil.The evolution of crack area and volume with moisture content is quantitatively analyzed.The modeling number and average width of cracks in the strip soil show a good consistency with the experimental results,and the crack pattern of the rectangular soil matches well with the existing numerical results,validating the coupled moisture diffusion-fracture model.Additionally,the parametric study of soil desiccation cracking is performed.The developed model offers a powerful tool for exploring soil desiccation cracking.
基金Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)National Natural Science Foundation of China(42475003)Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(SML2023SP209)。
文摘Southerly moisture surges over the central South China Sea(SCS)are characterized by the strengthening of lowlevel southerlies that transport moisture northward from the Pacific or Indian Oceans to South China.These surge events typically occur for days in the early-summer season(from April to June)and can lead to heavy rains in South China.This study categorizes surge events into three types of flow patterns and examines their multiscale variations and impacts on rainfall.The first type occurs mainly in April,with the southeasterlies enhanced by a deepening trough in South China and the western Pacific subtropical high established over the SCS.The second type of surge events mostly appears in June,featuring the prevailing southwesterlies of summer monsoon from the Indian Ocean during the active phases of intraseasonal oscillations.Most surge events exhibit semi-diurnal variations with morning and afternoon peaks of northward moisture fluxes.Specifically,the first type features a dominant afternoon peak,while the second type shows a dominant early-morning peak,which is induced by thermal contrast between the Indochina Peninsula and the SCS.In general,the surge events enhance moisture convergence and increase rainfall downstream in South China,but they show some regional differences.The second type strengthens moisture convergence and rainfall in coastal regions with a morning peak.In contrast,the first type enhances inland rainfall with a morning peak,while moisture divergence dominates coastal regions.The third type of surge events denotes transitional conditions between the first two types,in terms of atmospheric circulations,diurnal cycles,and rainfall patterns.These results highlight a diversity of regional moisture surges and related rainfall ranging from diurnal to sub-seasonal scales.
基金financially supported by the Central Public-Interest Scientific Institution Basal Research Fund of Chinese Academy of Forestry(CAFYBB2021ZW002)the National Key Research and Development Program of China(2022YFF1300404)the National Natural Science Foundation of China(U21A2005)。
文摘Mountainous areas are the priority for forest restoration in semiarid regions,with hillslopes serving as the basic units of mountains.Precipitation is the only water source in these regions,and the uneven distribution of hillslope soil moisture replenishment after precipitation determines vegetation survival and growth.Therefore,in this study experiments were performed on a hillslope in the Liupan Mountains,Ningxia Hui Autonomous Region,China,to quantify the unevenness of soil moisture replenishment.Soil water content(SWC)in the 0–60 cm layer and precipitation were monitored throughout the growing season in 2020 and 2021.The results showed that(1)Annual soil moisture replenishment was the highest at the mid-slope position,with an average of 309.9 mm,especially under moderate and heavy rain grade conditions,reaching 38.7% and 30.8% of the total replenishment,respectively;(2)Vertical replenishment played a dominant role in the total replenishment,accounting for 82.8%;lateral replenishment played an important but lesser role,accounting for up to 17.2% of the total replenishment;(3)Based on a soil moisture replenishment model established in this study,the maximal replenishment occurred at 90 m from the top of the slope;(4)The dominant factors contributing to the soil moisture replenishment were rainfall amount and saturated hydraulic conductivity(Ks).These findings suggest that attention should be given to both vertical and lateral soil moisture replenishment,and the mid-slope position could be preferred for site selection to achieve precise and integrated forest-water management on hillslopes in semi-arid mountainous regions.
基金the financial support of the National Natural Science Foundation of China(No.22205165).
文摘Moisture-enabled electricity generation(MEG)has emerged as a promising sustainable energy harvesting technology,comparable to photovoltaics,thermoelectrics,and triboelectrics[1].MEGs generate electricity by converting the chemical potential of moisture into electric energy through interactions with hygroscopic materials and nanostructured interfaces.Unlike solar or thermal harvesters,MEGs operate continuously by utilizing ubiquitous atmospheric moisture,granting them unique spatial and temporal adaptability.Despite nearly a decade of progress and the exploration of diverse material systems for MEG,the overall output power remains significantly limited due to inherently low charge carrier concentrations and restricted ion diffusion fluxes[2].As a result,standalone MEG devices often deliver low and unstable output,limiting practical applications.To enhance performance and versatility,recent efforts have explored hybridization of MEG with other ambient energy sources such as triboelectric or thermoelectric effects.
文摘The article examines the impact of increased aridization of the territory due to an increase in air temperature,reduced precipitation,and the formation of moisture deficiency on grain yields in Northern Kazakhstan.The most important result of the work is the revealed inverse relationship between grain yields and the temperature of the growing season:low-yielding years are associated with high temperatures and droughts,and high-yielding years are associated with lower temperatures and an optimal ratio of heat and moisture.The novelty of this study is the use of the method of hydrological and climatic calculations in identifying the nature of temperature variability and precipitation in the territory of Northern Kazakhstan for the modern period(1991–2020)compared with the base period(1961–1990).At all the studied meteorological stations,there is a tendency for the average annual temperature and the temperature of the growing season to increase:in the forest-steppe zone with an average warming intensity of 0.3–0.33℃ per decade;in the steppe zone by 0.2–0.43℃ per decade;and in the growing season by 0.2–0.7℃ per decade.The air temperature in the steppe zone is rising more intensively than in the forest-steppe zone,and precipitation in the forest-steppe zone has changed more than in the steppe zone.An increase in the average annual air temperature during the growing season(May–August),combined with a shortage of atmospheric moisture or a constant amount of it,led to an increase in the degree of aridization of the territory,an increase in the frequency of droughts in the steppe zone of Northern Kazakhstan.
基金National Key Research and Development Plan of China,No.2023YFF0805703National Natural Science Foundation of China,No.42271268。
文摘Heatwaves are becoming increasingly frequent and severe,posing escalating risks to ecosystems and human well-being.While soil moisture(SM)deficits are recognized as important contributors to heatwave amplification,their spatially heterogeneous impacts across the Northern Hemisphere remain insufficiently understood.In this study,we analyze ERA5 reanalysis data(1980-2022)to investigate trends in heatwave frequency,intensity,and duration,as well as their sensitivity to SM variability.Our results show robust increases in heatwave occurrence(0.76 events per decade),intensity(0.81℃per decade),and average duration(0.40 days per decade),with extreme events,as represented by maximum intensity and duration,rising at even faster rates(2.18℃per decade and 0.83 days per decade,respectively).Strong negative correlations are observed between SM deficits and heatwave metrics,with the magnitude of this relationship varying across land cover types and heatwave severity levels.Quantile regression reveals that SM reductions have a greater impact at higher quantiles for most indicators.Cropland exhibits the highest sensitivity to SM anomalies,whereas forests show more resilience due to their superior water retention capacities.These findings underscore the crucial role of land-atmosphere interactions in shaping heatwave extremes,providing a scientific basis for enhancing early warning and adaptation strategies in the context of ongoing climate change.
基金supported by the National Natural Science Foundation of China(42475008)Strategy Priority Research Program of Chinese Academy of Sciences(XDB0760400).
文摘From 26 October to 2 November 2024,Spain experienced a record-breaking rainfall event,with the most intense episode appearing in Valencia Province.During the event,Turis station recorded a historic 24-hour precipitation of 710.8 mm,exceeding the national annual average.This resulting flood led to widespread disruption and significant societal impacts.Synoptic analyses reveal that the event was dominated by a deep cut-off low extending through the entire troposphere and persisting for approximately 186 h.Background conditions were characterized by upper-level divergence,mid-tropospheric warm advection,and a strong southeasterly low-level jet,which promoted vertical motion and sustained moisture transport.The steep,funnel-shaped terrain along the eastern Iberian coast further triggered and enhanced the local convection.A 10-day backward Lagrangian moisture tracing using the HYSPLIT model identified the Mediterranean Sea as the primary moisture source(78.1%),followed by northwestern Africa(8.5%)and central-eastern Europe/the Black Sea(6.2%).Low-level moisture transport was mainly driven by the cut-off low and a persistent Mediterranean high,while mid-to upper-level trajectories were associated with a preceding low-pressure system over the Mediterranean and the subtropical Atlantic high.These systems acted in sequence to relay moisture toward the Valencia region,and under the influence of the strongly rotating and convergent cut-off low—along with terrain-induced lifting—this moisture was rapidly uplifted,ultimately triggering the extreme rainfall event.
基金We express our gratitude to the Internal Grant Agency of the Faculty of Forestry and Wood Sciences,Czech University of Life Sciences,Prague(Grant No.IGA A_24_24)the Ministry of Education,Youth and Sports of the Czech Republic(Grant INTER-TRANSFER No.LTT20017)for funding this study.
文摘Understanding the ecological processes shaping competitive interactions among forest trees is crucial for predicting ecosystem productivity and climate change resilience.However,few studies have investigated how the biological attributes of tropical species may affect competitive outcomes under varying resource conditions.We collected and analysed a 10-year dataset of radial growth rates in canopy trees from a network of forest inventory plots located in divergent forest types over an extensive meteorological gradient in Ghana,West Africa.We used nonlinear models to estimate the relative reduction in potential growth(basal area increment)of individual target trees of a given species as a consequence of the combined effects of(1)target tree size,(2)variation in crowding levels by neighbouring trees,(3)the functional attributes of those neighbours(wood density and shade tolerance),and(4)local soil moisture levels.Analyses were conducted separately for the 15 most common species in the inventory network.In opposition to neutral theory,our findings indicate that the strength of interactions among competing species was distinctly asymmetric and dynamic.Wood density was an important characteristic that modified competitive outcomes for most species,particularly under varying levels of resource availability.Specifically,dense wood was an attribute that conferred comparatively stronger competitive ability in moisture-limited conditions.Larger individuals were notably less sensitive to the effects of moisture-dependent competition.Our results suggest that attributes such as wood density may reflect divergent life history strategies that differentiate species’fitness and competitive ability in varying environments.The dynamic nature of competition,influenced by a complex interplay of biological and abiotic factors,implies that more prevalent dry periods,which have been forecast for tropical Africa,may impact the physiognomy and function of future forest communities in the region.
文摘This study aimed to explore the relationship between Soil-Plant Analysis Development(SPAD)values and key environmental factors in cucumber(Cucumis sativus L.)cultivation in a greenhouse.SPAD values,indicative of chlorophyll content,reflect plant health and productivity.The analysis revealed strong positive correlations between SPADvalues and both indoor light intensity(ILI,r=0.59,p<0.001)and outdoor light intensity(OLI,r=0.62,p<0.001),suggesting that higher light intensities were associated with enhanced SPAD values.In contrast,significant negative correlations were found between SPAD values and soil temperature at 15-30 cm depth(ST1530,r=−0.47,p<0.001)and volumetric soil moisture content at the same depth(SM1530,r=−0.52,p<0.001),with higher soil temperatures(e.g.,28℃)and excessive moisture(e.g.,25%)leading to reduced SPAD values.Multiple regression analysis identified ST1530 and SM1530 as significant negative predictors of SPAD,with coefficients of−0.97(p=0.05)and−0.34(p=0.05),respectively,suggesting that increases in soil temperature and moisture result in lower SPAD values.Indoor light intensity(e.g.,600-800μmol/m^(2)/s)emerged as a significant positive contributor,with a coefficient of 0.01(p<0.001),highlighting its role in promoting chlorophyll synthesis.Additionally,relative humidity(r=0.27,p<0.01)showed a positive,although less pronounced,association with SPAD.These results underscore the importance of both direct and indirect environmental factors in influencing SPAD variability and,by extension,plant health and productivity in cucumber cultivation.
基金supported by the National Natural Science Foundation of China(Grant No.42325502,and 42275045)the West Light Foundation of the Chi-nese Academy of Sciences(Grant No.xbzg-zdsys-202215)+1 种基金the Sci-ence and Technology Research Plan of Gansu Province(Grant Nos.23JRRA654 and 20JR10RA070)iLEAPs(Integrated Land Ecosystem-Atmosphere Processes Study).
文摘The source region of the Yellow River(SRYR),with its semi-humid to semi-arid climate,is crucial for understanding water resource dynamics.Precipitation is key for replenishing surface water and balancing the ecosystem’s water cycle.However,the soil moisture response to precipitation across climate zones and soil layers remains poorly understood due to limited long-term data.This study examines the response of soil moisture to precipitation at multiple time scales in the SRYR,using data from Maqu,Mado,Ngoring Lake sites,and the Maqu monitoring network(MMN),along with CN05.1 precipitation and GLEAM v3.8a soil moisture data.Results show that the semi-humid area requires more precipitation to trigger soil moisture responses compared to the semi-arid area in the SRYR.Surface soil at Maqu,MMN,Ngoring Lake,and Mado sites require at least 8.6,8.4,5.2,and 2.84 mm of precipitation,respectively,for effective replenishment.Significant responses to precipitation events were observed in soil layers at 40 cm and above in the semi-humid area,while at 20 cm and above in the semi-arid area.Precipitation volume is the primary factor influencing soil moisture,affecting both the increment and time lag to maximum moisture.Precipitation intensity and pre-rain moisture have no direct effect.In the central SRYR,accumulated precipitation has a greater impact.Root-zone soil moisture has a weaker correlation with precipitation compared to surface soil moisture but persists longer,responding for up to 10 days,while surface soil moisture responds more immediately but only lasts about 5 days.
基金supported by National Natural Science Youth Foundation of China(No.22308294)National Natural Science Foundation of China(No.22179077)+1 种基金Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.SJCX23_1868)Qing Lan Project of Jiangsu University and the Funding for school-level research projects of Yancheng Institute of Technology.
文摘Mn-based P2-type oxides are considered as promising cathodes for Na-ion batteries;however,they face significant challenges,including structural degradation when charged at high cutoff voltages and structural changes upon storing in a humid atmosphere.In response to these issues,we have designed an oxide with co-doping of Cu and Al which can balance both cost and structural stability.The redox reaction of Cu^(2+/3+)can provide certain charge compensation,and the introduction of Al can further suppress the Jahn-Teller effect of Mn,thereby achieving superior long-term cycling performance.The ex-situ XRD testing indicates that Cu/Al co-doping can effectively suppress the phase transition of P2-O2 at high voltage,thereby explaining the improvement in electrochemical performance.DFT calculations reveal a high chemical tolerance to moisture,with lower adsorption energy for H_(2)O compared to pure Na_(0.67)Cu_(0.25)Mn_(0.75)O_(2).A representative Na_(0.67)Cu_(0.20)Al_(0.05)Mn_(0.75)O_(2)cathode demonstrates impressive reversible capacities of 148.7 mAh/g at 0.2 C,along with a remarkable capacity retention of 79.1%(2 C,500 cycles).
基金National Key Research and Development Program,No.2021xjkk0303。
文摘Drought significantly constrains vegetation growth and reduces terrestrial carbon sinks.Currently,the spatiotemporal patterns and mechanisms of the differential impacts of soil and meteorological droughts on vegetation productivity remain inadequately understood.In this study,we analyzed soil moisture(SM),vapor pressure deficit(VPD),and gross primary productivity(GPP)to investigate their spatiotemporal patterns and the combined effects on GPP over China.The results revealed that:(1)Soil drought and meteorological drought generally exhibited temporally synchronous trends across China.(2)GPP was predominantly affected by the combined and synchronous effects of both SM and VPD,although their effects displayed directional variability differences in certain regions.(3)SM demonstrated a greater relative importance on GPP than VPD across more than half of the regions in China,whereas deciduous broadleaf forests were the only vegetation type primarily affected by VPD.(4)Under the lag effects,both SM and VPD exhibited bidirectional Granger causality with GPP,with the interaction between VPD and GPP proving more pronounced than that of SM.Our research provides valuable insights into the mechanisms through which SM and VPD influence GPP,contributing to improved predictions vegetation productivity and implementing ecological restoration.
基金the financial and intellectual support provided by Queensland University of Technology(QUT),Australia,through its Higher Degree Research Program,which played a crucial role in the successful completion of this research study
文摘Moisture accumulation within road pavements,particularly in unbound granular materials with or without thin sprayed seals,presents significant challenges in high-rainfall regions such as Queensland.This infiltration often leads to various forms of pavement distress,eventually causing irreversible damage to the pavement structure.The moisture content within pavements exhibits considerable dynamism and directly influenced by environmental factors such as precipitation,air temperature,and relative humidity.This variability underscores the importance of monitoring moisture changes using real-time climatic data to assess pavement conditions for operational management or incorporating these effects during pavement design based on historical climate data.Consequently,there is an increasing demand for advanced,technology-driven methodologies to predict moisture variations based on climatic inputs.Addressing this gap,the present study employs five traditional machine learning(ML)algorithms,K-nearest neighbors(KNN),regression trees,random forest,support vector machines(SVMs),and gaussian process regression(GPR),to forecast moisture levels within pavement layers over time,with varying algorithm complexities.Using data collected from an instrumented road in Brisbane,Australia,which includes pavement moisture and climatic factors,the study develops predictive models to forecast moisture content at future time steps.The approach incorporates current moisture content,rather than averaged values,along with seasonality(both daily and annual),and key climatic factors to predict next step moisture.Model performance is evaluated using R2,MSE,RMSE,and MAPE metrics.Results show that ML algorithms can reliably predict long-term moisture variations in pavements,provided optimal hyperparameters are selected for each algorithm.The best-performing algorithms include KNN(the number of neighbours equals to 15),medium regression tree,medium random forest,coarse SVM,and simple GPR,with medium random forest outperforming the others.The study also identifies the optimal hyperparameter combinations for each algorithm,offering significant advancements in moisture prediction tools for pavement technology。
基金supported by the Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology(13230550)the Coal Industry Engineering Research Center of Mining Area Environmental and Disaster Cooperative Monitoring,Anhui University of Science and Technology(KSXTJC202305)+1 种基金the State Key Laboratory of Geodesy and Earth's Dynamics,Innovation Academy for Precision Measurement Science and Technology(SKLGED2023-5-1)the China Postdoctoral Science Foundation(2023M733604).
文摘Soil moisture is a key parameter in the exchange of energy and water between the land surface and the atmosphere.This parameter plays an important role in the dynamics of permafrost on the Qinghai-Xizang Plateau,China,as well as in the related ecological and hydrological processes.However,the region's complex terrain and extreme climatic conditions result in low-accuracy soil moisture estimations using traditional remote sensing techniques.Thus,this study considered parameters of the backscatter coefficient of Sentinel-1A ground range detected(GRD)data,the polarization decomposition parameters of Sentinel-1A single-look complex(SLC)data,the normalized difference vegetation index(NDVI)based on Sentinel-2B data,and the topographic factors based on digital elevation model(DEM)data.By combining these parameters with a machine learning model,we established a feature selection rule.A cumulative importance threshold was derived for feature variables,and those variables that failed to meet the threshold were eliminated based on variations in the coefficient of determination(R^(2))and the unbiased root mean square error(ubRMSE).The eight most influential variables were selected and combined with the CatBoost model for soil moisture inversion,and the SHapley Additive exPlanations(SHAP)method was used to analyze the importance of these variables.The results demonstrated that the optimized model significantly improved the accuracy of soil moisture inversion.Compared to the unfiltered model,the optimal feature combination led to a 0.09 increase in R^(2)and a 0.7%reduction in ubRMSE.Ultimately,the optimized model achieved a R²of 0.87 and an ubRMSE of 5.6%.Analysis revealed that soil particle size had significant impact on soil water retention capacity.The impact of vegetation on the estimated soil moisture on the Qinghai-Xizang Plateau was considerable,demonstrating a significant positive correlation.Moreover,the microtopographical features of hummocks interfered with soil moisture estimation,indicating that such terrain effects warrant increased attention in future studies within the permafrost regions.The developed method not only enhances the accuracy of soil moisture retrieval in the complex terrain of the Qinghai-Xizang Plateau,but also exhibits high computational efficiency(with a relative time reduction of 18.5%),striking an excellent balance between accuracy and efficiency.This approach provides a robust framework for efficient soil moisture monitoring in remote areas with limited ground data,offering critical insights for ecological conservation,water resource management,and climate change adaptation on the Qinghai-Xizang Plateau.
基金supported by the National Natural Science Foundation of China(Nos.U23A6005,22208112,and 32171721)the National Natural Science Foundation of China(No.22308109)+2 种基金Guangdong Basic and Applied Basic Research Foundation(No.2024A1515010678)the Fundamental Research Funds for the Central Universities(SCUT:2023ZYGXZR045)the State Key Laboratory of Pulp&Paper Engineering(Nos.2023ZD01,2023C02).
文摘Proton exchange membrane fuel cell(PEMFC)is a promising clean energy source,but its performance and stability are vulnerable to the negative effects of humidity conditions.The gas diffusion substrate(GDS)plays a pivotal role in regulating the moisture and gas transport.The single pore structure of traditionally designed GDS often leads to the pathway competition between moisture and gas,which effects the efficiency of fuel cells.In this study,we report on a hierarchical fibrous paper with tunable hierarchical pores for a sustainable GDS.This design offers gas permeability under wet conditions,by separating the gas pathway from the moisture pathway,thus mitigating their pathway competition.In addition,this paper forms a multi-scale scaffold that absorbs moisture under high humidity conditions and releases it under dry conditions.It is allowed to maintain an optimal internal humidity and further enhances the humidity adaptability.Furthermore,the carbon footprint is only 15.97%,significantly lower than commercial alternatives.This feature makes it a sustainable solution to stabilize PEMFCs under diverse humidity conditions.
