This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for ...This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.展开更多
Purpose–This paper focuses on studying the reliability allocation for the railway system,aiming to improve the overall reliability of the railway system and ensure safety operation.Design/methodology/approach–In vie...Purpose–This paper focuses on studying the reliability allocation for the railway system,aiming to improve the overall reliability of the railway system and ensure safety operation.Design/methodology/approach–In view of the complex structure of the railway system,involving many subsystems,this paper analyzes the close dynamic coupling effect between railway subsystems.Based on this,taking the railway system failure as the top event,a fault tree is constructed in this paper.Then,a reliability allocation method based on the fault tree is employed to allocate the reliability index.Finally,a numerical experiment is implemented to show the performance of the reliability allocation method.Findings–The results showed that each subsystem needs to improve its reliability to meet the specified railway system reliability requirements,and the traction power supply system is the most important subsystem,which is the most efficient in improving the reliability of the railway system.Originality/value–For the first time,starting from a holistic perspective of the system,reliability allocation is carried out based on the importance of each railway subsystem.展开更多
When making assessments of forest resources,there is nearly ubiquitous interest in quantifying current status and trends in tree biomass and carbon stocks.While important at various spatial scales,typical estimations ...When making assessments of forest resources,there is nearly ubiquitous interest in quantifying current status and trends in tree biomass and carbon stocks.While important at various spatial scales,typical estimations pertinent to broad forest management and policy issues are conducted for large areas such as state,regional,and national perspectives.These assessments are usually accomplished using large-area forest inventory data collected by National Forest Inventory(NFI)programs.While NFI efforts commonly collect size data for individual trees,there is often limited information for tree seedlings,e.g.,frequency by species.To fully describe the tree population across the entire range of sizes present,this study proposes methods to predict individual seedling groundline diameter and height using models developed from trees having a diameter at breast height(DBH)less than 7.62 cm.These attributes are subsequently used for the prediction of seedling stem volume,total aboveground biomass,and carbon content.The results suggest a smooth transition in tree attributes as size increases to where direct measurement of individual trees and prediction of their volume,biomass,and carbon are implemented as part of standard inventory protocols.Analyses including the full spectrum of tree sizes show that seedlings contribute roughly 0.6%–0.7%of the total tree volume/mass.This additional suite of information provides opportunities for more holistic assessments across the full spectrum of the tree resource or for specialized subdomains that include the seedling component.展开更多
Polygonal fault systems(PFS),characterized by multi-directional fault patterns within layered sequences,are well-documented features in global continental margin basins.While the geometry and formation mechanisms of P...Polygonal fault systems(PFS),characterized by multi-directional fault patterns within layered sequences,are well-documented features in global continental margin basins.While the geometry and formation mechanisms of PFS have been extensively studied in the northern South China Sea,the PFS in the Zhongjiannan Basin(western South China Sea)remain relatively unexplored,with a lack of quantitative analysis regarding their propagation.This study addresses this gap by using high-resolution three-dimensional(3D)seismic data and conducting a quantitative fault analysis to thoroughly examine the planform,cross-sectional geometry,and evolution of PFS in the northern Zhongjiannan Basin.The absence of a dominant strike direction among these polygonal faults suggests that their evolution is not controlled by anisotropic stress.Our interpretation of seismic data,constrained by the spatial relationship among PFS,gullies,and pockmarks,indicates that PFS mainly developed within the Miocene strata,with their initiation occurring during the late Miocene.Furthermore,the PFS act as key conduits connecting gullies to pockmarks in this area.The formation and development of PFS may be primarily driven by thermally triggered processes within siliceous sediments.The necessary heat source is probably associated with the abundant submarine magmatism observed in the Zhongjiannan Basin.To reconstruct the regional geological history,a four-stage evolutionary model,incorporating the formation of PFS,is presented.This research significantly improves our understanding of the regional geological evolution of the Zhongjiannan Basin,providing critical insights into the initiation and development of PFS in the western South China Sea.展开更多
The Guanxian-Anxian fault zone in the Longmen Shan,Sichuan,China,exhibits long-term creep-slip but ruptured during the 2008 Wenchuan earthquake,challenging the view that creeping faults rarely generate strong earthqua...The Guanxian-Anxian fault zone in the Longmen Shan,Sichuan,China,exhibits long-term creep-slip but ruptured during the 2008 Wenchuan earthquake,challenging the view that creeping faults rarely generate strong earthquakes.To investigate the transition from creep-slip to stick-slip,we analyzed fault rocks from the WFSD-3,using microstructural observations,XRD,μXRF,Raman spectroscopy,and quartz grain size statistics.Fault rocks show intense foliation,pressure-solution structures,and abundant clay minerals,reflecting long-term aseismic creep.At the interface between black and gray fault gouges at~1249.98 m,microstructures indicate stick-slip behavior,including truncated grains,angular fragments,and finer grain sizes.Here,clay content drops sharply while strong minerals(quartz,feldspar,calcite,dolomite)increase.Elemental mapping shows Al and K enriched in black gouge,whereas Ca and Si in gray gouge;Raman spectroscopy indicates possible graphitization;the finest quartz grains occur in black gouge.These features mark co-seismic principal slip zone of the Wenchuan earthquake.We propose that fluid-driven transformation of strong minerals into clays facilitates creep-slip,whereas localized precipitation of strong minerals strengthens the fault,causing stress accumulation and controlling the creep-slip to stick-slip transition.This mechanism has implications for reassessing seismic hazards of creeping faults.展开更多
Accurate fault modeling is essential for understanding earthquake rupture processes and improving seismic hazard assessment.We present a unified framework that integrates geodetic data with multidisciplinary constrain...Accurate fault modeling is essential for understanding earthquake rupture processes and improving seismic hazard assessment.We present a unified framework that integrates geodetic data with multidisciplinary constraints,including relocated aftershocks,geological observations,and geophysical information,to adaptively model fault geometry and slip in diverse scenarios such as multi-segment and multi-event ruptures.The framework combines adaptive fault construction with a scenario-driven Bayesian joint inversion approach.Fault geometries are first built from prior constraints,such as surface ruptures and aftershocks,and then refined through probabilistic inference when such data are inadequate.To enhance computational efficiency,we introduce a Sequential Monte Carlo Fukuda-Johnson(SMC-FJ)strategy.This separates nonlinear parameters-including geometry,data weights,and smoothing factors-from linear slip parameters,which are conditionally solved via constrained least squares.Geometry updates follow a hierarchical adjustment scheme based on point,line,and structural units,enabling flexibility across rupture complexities.Synthetic tests and four case studies,including the 2022 Menyuan,2023 Türkiye,2022 Luding,and 2019 Ridgecrest earthquakes,demonstrate robustness under various constraints.For the Menyuan earthquake,full Bayesian inversion confirms that the fault geometry constrained by relocated aftershocks is highly accurate and needs only minor adjustment to match the observed surface deformation.The results further show that gradual changes in fault strike and dip modulated rupture arrest and postseismic stress accumulation,highlighting the critical role of inherited geometric structure in controlling rupture termination and delayed seismic activation.展开更多
Soil organic carbon in forest affects nutrient availability,microbial processes,and organic matter inputs.Dominant tree species have increasingly shifted from ectomycorrhizal to arbuscular mycorrhizal associations in ...Soil organic carbon in forest affects nutrient availability,microbial processes,and organic matter inputs.Dominant tree species have increasingly shifted from ectomycorrhizal to arbuscular mycorrhizal associations in subtropical forests.However,the consequences of this shift for soil organic carbon is poorly understood.To address this,a field study was conducted across a natural gradient of arbuscular tree associations to investigate how different mycorrhizal associations affect soil organic carbon quantity,composition,chemical stability,and related soil properties.Soil organic carbon fractions,functional groups,microbial enzyme activities were analyzed.Results showed that increasing arbuscular mycorrhizal dominance was associated with declines in total soil organic carbon,particularly in recalcitrant and aromatic carbon forms.Ectomycorrhizaldominated forests exhibited higher nitrogen availability and elevated nitrogen-hydrolyzing enzyme activity,suggesting enhanced nitrogen acquisition strategies that suppress soil organic carbon decomposition and promote carbon retention.These findings indicate that mycorrhizal-mediated shifts in tree composition may significantly alter soil carbon sequestration potential.Incorporating mycorrhizal functional traits into forest management and carbon modeling could improve predictions of soil organic carbon responses under future environmental change.展开更多
This study investigated biomass allocation in young stands of European beech(Fagus sylvatica L.)and Norway spruce(Picea abies(L.)Karst.)across 31 forest sites in the Western Carpathians,Slovakia.A total of 541 trees a...This study investigated biomass allocation in young stands of European beech(Fagus sylvatica L.)and Norway spruce(Picea abies(L.)Karst.)across 31 forest sites in the Western Carpathians,Slovakia.A total of 541 trees aged 2–10 years,originating from natural regeneration and planting,were destructively sampled to quantify biomass in four components:foliage,branches,stems,and roots.Generalized non-linear least squares(GNLS)models with a weighing variance function outperformed log-transformed seemingly unrelated regression(SUR)models in terms of accuracy and robustness,especially for foliage and branch biomass.When using height as the predictor,SUR models tended to underestimate biomass in planted beech,leading to notable underprediction of aboveground and total biomass.Biomass allocation patterns varied significantly by species and regeneration origin.Using a non-linear system of equations and component ratio modelling,we found out that planted spruce displayed low variability and a consistent dominance of needle biomass,while naturally regenerated beech showed greater variability and a higher proportion of stem biomass,reflecting stronger competition-driven vertical growth.Interspecific differences in total biomass were more pronounced when using tree height,with spruce generally exhibiting greater biomass than beech at equivalent heights.Overall,stem base diameter marginally outperformed tree height as a predictor of biomass.However,tree height-based models showed strong performance and are particularly suitable for integration with remote sensing applications.These findings can directly support forest managers and modellers in comparing regeneration methods and biomass estimation approaches for early-stage stand development,carbon accounting,and remote sensing calibration.展开更多
With the rapid development of large-scale offshore wind farms,efficient and reliable power transmission systems are urgently needed.Hybrid high-voltage direct current(HVDC)configurations combining a diode rectifier un...With the rapid development of large-scale offshore wind farms,efficient and reliable power transmission systems are urgently needed.Hybrid high-voltage direct current(HVDC)configurations combining a diode rectifier unit(DRU)and a modular multilevel converter(MMC)have emerged as a promising solution,offering advantages in cost-effectiveness and control capability.However,the uncontrollable nature of the DRU poses significant challenges for systemstability under offshore AC fault conditions,particularly due to its inability to provide fault current or voltage support.This paper investigates the offshore AC fault characteristics and fault ride-through(FRT)strategy of a hybrid offshore wind power transmission system based on a diode rectifier unit DRU and MMC.First,the dynamic response of the hybrid system under offshore symmetrical three-phase faults is analyzed.It is demonstrated that due to the unidirectional conduction nature of the DRU,its AC current rapidly drops to zero during faults,and the fault current is solely contributed by the wind turbine generators(WTGs)and wind farm MMC(WFMMC).Based on this analysis,a coordinated FRT strategy is proposed,which combines a segmented current limiting control for the wind-turbine(WT)grid-side converters(GSCs)and a constant AC current control for the WFMMC.The strategy ensures effective voltage support during the fault and prevents MMC current saturation during fault recovery,enabling fast and stable system restoration.Electromagnetic transient simulations in PSCAD/EMTDC verify the feasibility of the proposed fault ride-through strategy.展开更多
Allometric equations are fundamental tools in ecological research and forestry management,widely used for estimating above-ground biomass and production,serving as the core foundations of dynamic vegetation models.Usi...Allometric equations are fundamental tools in ecological research and forestry management,widely used for estimating above-ground biomass and production,serving as the core foundations of dynamic vegetation models.Using global datasets from Tallo(a tree allometry and crown architecture database encompassing thousands of species)and TRY(a plant traits database),we fit B ayesian hierarchical models with three alternative functional forms(powerlaw,generalized Michaelis-Menten(gMM),and Weibull)to characterize how diameter at breast height(DBH),tree height(H),and crown radius(CR)scale with and without wood density as a species-level predictor.Our analysis revealed that the saturating Weibull function best captured the relationship between tree height and DBH in both functional groups,whereas the CR-DBH relationship was best predicted by a power-law function in angiosperms and by the gMM function in gymnosperms.Although including wood density did not significantly improve predictive performance,it revealed important ecological trade-offs:lighter-wood angiosperms achieve taller mature heights more rapidly,and denser wood promotes wider crown expansion across clades.We also found that accurately estimating DBH required considering both height and crown size,highlighting how these variables together distinguish trees of similar height but differing trunk diameters.Our results emphasize the importance of applying saturating functions for large trees to improve forest biomass estimates and show that wood density,though not always predictive at broad scales,helps illuminate the biomechanical and ecological constraints underlying diverse tree architectures.These findings offer practical pathways for integrating height-and crown-based metrics into existing carbon monitoring programs worldwide.展开更多
The Yingxiu-Beichuan fault zone(YBFZ)has long been active and experienced repeated large earthquakes.The physicochemical properties of the deep fault zone(>1000 m)are the key to understanding the deformation mechan...The Yingxiu-Beichuan fault zone(YBFZ)has long been active and experienced repeated large earthquakes.The physicochemical properties of the deep fault zone(>1000 m)are the key to understanding the deformation mechanism of large earthquakes.This study uses rock magnetic,microstructural,and geochemical analyses of representative samples exposed in FZ1681 within the Wenchuan Earthquake Fault Scientific Drilling borehole 2(WFSD-2)cores.Fault gouge and fault breccia have higher magnetic susceptibility values than wall rocks,and they contain abundant paramagnetic minerals and small quantities of magnetite and monoclinic pyrrhotite.The magnetite and monoclinic pyrrhotite in the fault gouge were mainly formed by coseismic frictional heating,indicating that large earthquakes with frictional heating temperatures of~500-900℃once occurred in the YBFZ.The seismogenic and coseismic environment was reducing with a relatively high sulfur content.The monoclinic pyrrhotite in the fault breccia was formed mainly by low-temperature hydrothermal fluid.This indicates that the fault zone experienced reducing and low-temperature(<400℃)hydrothermal fluid with a relatively high sulfur content after the earthquake.The YBFZ,which experiences frequent large earthquakes,is weakly oxidizing environment at different depths,but the effect of the low-temperature hydrothermal fluid is weaker at depth.展开更多
Background 3D botanical tree reconstruction from a single image plays a vital role in the field of computer graphics.However,accurately capturing the intricate branching patterns and detailed morphologies of trees rem...Background 3D botanical tree reconstruction from a single image plays a vital role in the field of computer graphics.However,accurately capturing the intricate branching patterns and detailed morphologies of trees remains a challenge.Methods In this study,we proposed a novel approach for single-image tree reconstruction using a conditional generative adversarial network to infer the 3D skeleton of a tree in the form of a 2D skeleton depth map.Based on the 2D skeleton depth map,a corresponding branching structure(3D skeleton)that inherits the tree shape in the input image and leaves can be generated using a procedural modeling technique.Result Experimental results show that the proposed method accurately reconstructs diverse tree structures across species.Both quantitative and qualitative evaluations demonstrate improved skeleton completeness,branching accuracy,and visual realism over baseline methods,while requiring no user input.Conclusions Our proposed approach for generating lifelike 3D tree models from a single image with no user input shows its proficiency in achieving efficient and reliable reconstruction.These results showcase the capability of the proposed model to recreate complex tree architectures while capturing their visual authenticity.展开更多
Grid-Forming(GFM)converters are prone to fault-induced overcurrent and power angle instability during grid fault-induced voltage sags.To address this,this paper develops a multi-loop coordinated fault ridethrough(FRT)...Grid-Forming(GFM)converters are prone to fault-induced overcurrent and power angle instability during grid fault-induced voltage sags.To address this,this paper develops a multi-loop coordinated fault ridethrough(FRT)control strategy based on a power outer loop and voltage-current inner loops,aiming to enhance the stability and current-limiting capability of GFM converters during grid fault conditions.During voltage sags,the GFM converter’s voltage source behavior is maintained by dynamically adjusting the reactive power reference to provide voltage support,thereby effectively suppressing the steady-state component of the fault current.To address the active power imbalance induced by voltage sags,a dynamic active power reference correction method based on apparent power is designed to mitigate power angle oscillations and limit transient current.Moreover,an adaptive virtual impedance loop is implemented to enhance dynamic transient current-limiting performance during the fault initiation phase.This approach improves the responsiveness of the inner loop and ensures safe system operation under various fault severities.Under asymmetric fault conditions,a negative-sequence reactive current compensation strategy is incorporated to further suppress negative-sequence voltage and improve voltage symmetry.The proposed control scheme enables coordinated operation of multiple control objectives,including voltage support,current suppression,and power angle stability,across different fault scenarios.Finally,MATLAB/Simulink simulation results validate the effectiveness of the proposed strategy,showcasing its superior performance in current limiting and power angle stability,thereby significantly enhancing the system’s fault ride-through capability.展开更多
The critical components of gas turbines suffer from prolonged exposure to factors such as thermal oxidation,mechanical wear,and airflow disturbances during prolonged operation.These conditions can lead to a series of ...The critical components of gas turbines suffer from prolonged exposure to factors such as thermal oxidation,mechanical wear,and airflow disturbances during prolonged operation.These conditions can lead to a series of issues,including mechanical faults,air path malfunctions,and combustion irregularities.Traditional modelbased approaches face inherent limitations due to their inability to handle nonlinear problems,natural factors,measurement uncertainties,fault coupling,and implementation challenges.The development of artificial intelligence algorithms has provided an effective solution to these issues,sparking extensive research into data-driven fault diagnosis methodologies.The review mechanism involved searching IEEE Xplore,ScienceDirect,and Web of Science for peerreviewed articles published between 2019 and 2025,focusing on multi-fault diagnosis techniques.A total of 220 papers were identified,with 123 meeting the inclusion criteria.This paper provides a comprehensive review of diagnostic methodologies,detailing their operational principles and distinctive features.It analyzes current research hotspots and challenges while forecasting future trends.The study systematically evaluates the strengths and limitations of various fault diagnosis techniques,revealing their practical applicability and constraints through comparative analysis.Furthermore,this paper looks forward to the future development direction of this field and provides a valuable reference for the optimization and development of gas turbine fault diagnosis technology in the future.展开更多
Deep learning-based wind turbine blade fault diagnosis has been widely applied due to its advantages in end-to-end feature extraction.However,several challenges remain.First,signal noise collected during blade operati...Deep learning-based wind turbine blade fault diagnosis has been widely applied due to its advantages in end-to-end feature extraction.However,several challenges remain.First,signal noise collected during blade operation masks fault features,severely impairing the fault diagnosis performance of deep learning models.Second,current blade fault diagnosis often relies on single-sensor data,resulting in limited monitoring dimensions and ability to comprehensively capture complex fault states.To address these issues,a multi-sensor fusion-based wind turbine blade fault diagnosis method is proposed.Specifically,a CNN-Transformer Coupled Feature Learning Architecture is constructed to enhance the ability to learn complex features under noisy conditions,while a Weight-Aligned Data Fusion Module is designed to comprehensively and effectively utilize multi-sensor fault information.Experimental results of wind turbine blade fault diagnosis under different noise interferences show that higher accuracy is achieved by the proposed method compared to models with single-source data input,enabling comprehensive and effective fault diagnosis.展开更多
To ensure the safe and stable operation of rotating machinery,intelligent fault diagnosis methods hold significant research value.However,existing diagnostic approaches largely rely on manual feature extraction and ex...To ensure the safe and stable operation of rotating machinery,intelligent fault diagnosis methods hold significant research value.However,existing diagnostic approaches largely rely on manual feature extraction and expert experience,which limits their adaptability under variable operating conditions and strong noise environments,severely affecting the generalization capability of diagnostic models.To address this issue,this study proposes a multimodal fusion fault diagnosis framework based on Mel-spectrograms and automated machine learning(AutoML).The framework first extracts fault-sensitive Mel time–frequency features from acoustic signals and fuses them with statistical features of vibration signals to construct complementary fault representations.On this basis,automated machine learning techniques are introduced to enable end-to-end diagnostic workflow construction and optimal model configuration acquisition.Finally,diagnostic decisions are achieved by automatically integrating the predictions of multiple high-performance base models.Experimental results on a centrifugal pump vibration and acoustic dataset demonstrate that the proposed framework achieves high diagnostic accuracy under noise-free conditions and maintains strong robustness under noisy interference,validating its efficiency,scalability,and practical value for rotating machinery fault diagnosis.展开更多
Litter decomposition is an essential ecosystem process influenced by multiple factors,including substrate quality,climate,edaphic environment,and decomposer communities.However,the role of canopy species identity and ...Litter decomposition is an essential ecosystem process influenced by multiple factors,including substrate quality,climate,edaphic environment,and decomposer communities.However,the role of canopy species identity and diversity on leaf litter decomposition in forests remains understudied.By controlling for macroclimate,soil properties,and litter substrate in a mature common garden,we investigated whether a three-month tea bag incubation of standardized green and rooibos tea substrate is driven by canopy tree species characteristics and diversity.Our study hypothesized two primary pathways:a chemical engineering effect,where trees alter soil properties and decomposer communities through litter input,and a physical engineering effect,where tree canopy structure modulates the local microclimate.The results showed that even under uniform macroclimatic and initial soil conditions,mass loss rates varied widely for green tea(27.4%–73.2%)and rooibos tea(6.1%–34.7%),comparable as found in other research between distinct biomes.While substrate quality was the dominant factor,both engineering pathways and,to a minor extent,tree diversity modulated mass losses.For green tea,tree chemical and physical characteristics seemed equally important,while the physical environment showed an increased importance for rooibos.Incubation depth played a key role,where forest floor decomposition rates are more susceptible to temporal climate variations,and soil-layer decomposition rates are less susceptible to climate variations and more determined by tree species identity.Our findings suggest that tea bag experiments focusing solely on topsoil burial may underestimate processes in the forest floor and the mineralorganic boundary layer.This study underscores the critical role of litter substrate quality in decomposition while demonstrating that tree community composition and the associated herbaceous layer,through both chemical and physical engineering pathways,strongly modulate decomposition rates.展开更多
Urban forests are highly multifunctional and provide numerous ecological functions.Plant functional traits individually or jointly influence the ecological multifunctionality of tree species(TS-EMF)and can also modify...Urban forests are highly multifunctional and provide numerous ecological functions.Plant functional traits individually or jointly influence the ecological multifunctionality of tree species(TS-EMF)and can also modify TSEMF in response to environmental changes.However,there has been limited exploration of multitrait combinations for predicting TS-EMF across seasons and of trait thresholds that enhance TS-EMF.Here,for 10 dominant tree species in urban forests of Northeast China,14 traits were measured and four aboveground and three belowground ecological functions assessed in three seasons.Ecological functions and TS-EMF differed significantly throughout the seasons(P<0.05).Synergistic relationships were found between carbon sequestration and oxygen release,between cooling and humidification,and between organic carbon accumulation and nutrient cycling.Notably,aboveground multifunctionality played a leading role in TS-EMF.With seasonal changes,resource allocation shifted toward traits related to resource acquisition rather than conservation to maintain TS-EMF.The combination of traits that predicted TS-EMF varied by type,accounting for up to 66.45%of the variation.TS-EMF was primarily driven by leaf structure in spring and by nutrient accumulation in autumn.Leaf carbon content(LCC)consistently served as a stabilizing factor for predicting TS-EMF across seasons.At 36.5-36.8 mg g^(-1),LCC had its optimal effect on TS-EMF.Other traits in combination that positively influence total TS-EMF include leaf nitrogen content(3.43-3.45 mg g^(-1)),leaf phosphorus content(0.80-0.83 mg g^(-1)),and leaf area(65.86-68.43 cm^(2)).Within these specified trait thresholds,Morus alba and Quercus mongolica were identified as key species.These findings suggest that the trade-off between various ecological functions can be managed by altering plant traits across seasons.This approach could provide a theoretical foundation for enhancing the TS-EMF of urban forests through trait-based management,offering practical guidance for selecting tree species.展开更多
基金supported by Istanbul Technical University(Project No.45698)supported through the“Young Researchers’Career Development Project-training of doctoral students”of the Croatian Science Foundation.
文摘This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.
基金supported by the Research Project of China Academy of Railway Sciences Corporation Limited under Grant 2023YJ252.
文摘Purpose–This paper focuses on studying the reliability allocation for the railway system,aiming to improve the overall reliability of the railway system and ensure safety operation.Design/methodology/approach–In view of the complex structure of the railway system,involving many subsystems,this paper analyzes the close dynamic coupling effect between railway subsystems.Based on this,taking the railway system failure as the top event,a fault tree is constructed in this paper.Then,a reliability allocation method based on the fault tree is employed to allocate the reliability index.Finally,a numerical experiment is implemented to show the performance of the reliability allocation method.Findings–The results showed that each subsystem needs to improve its reliability to meet the specified railway system reliability requirements,and the traction power supply system is the most important subsystem,which is the most efficient in improving the reliability of the railway system.Originality/value–For the first time,starting from a holistic perspective of the system,reliability allocation is carried out based on the importance of each railway subsystem.
文摘When making assessments of forest resources,there is nearly ubiquitous interest in quantifying current status and trends in tree biomass and carbon stocks.While important at various spatial scales,typical estimations pertinent to broad forest management and policy issues are conducted for large areas such as state,regional,and national perspectives.These assessments are usually accomplished using large-area forest inventory data collected by National Forest Inventory(NFI)programs.While NFI efforts commonly collect size data for individual trees,there is often limited information for tree seedlings,e.g.,frequency by species.To fully describe the tree population across the entire range of sizes present,this study proposes methods to predict individual seedling groundline diameter and height using models developed from trees having a diameter at breast height(DBH)less than 7.62 cm.These attributes are subsequently used for the prediction of seedling stem volume,total aboveground biomass,and carbon content.The results suggest a smooth transition in tree attributes as size increases to where direct measurement of individual trees and prediction of their volume,biomass,and carbon are implemented as part of standard inventory protocols.Analyses including the full spectrum of tree sizes show that seedlings contribute roughly 0.6%–0.7%of the total tree volume/mass.This additional suite of information provides opportunities for more holistic assessments across the full spectrum of the tree resource or for specialized subdomains that include the seedling component.
基金financially supported by the National Key Research and Development Program of China(No.2021YFC3100700)the National Natural Science Foundation of China(No.42376070)+1 种基金the Natural Science Foundation of Guangdong Province(No.2024A1515012371)the Rising Star Foundation of the South China Sea Institute of Oceanology(No.NHXX2019DZ0201)。
文摘Polygonal fault systems(PFS),characterized by multi-directional fault patterns within layered sequences,are well-documented features in global continental margin basins.While the geometry and formation mechanisms of PFS have been extensively studied in the northern South China Sea,the PFS in the Zhongjiannan Basin(western South China Sea)remain relatively unexplored,with a lack of quantitative analysis regarding their propagation.This study addresses this gap by using high-resolution three-dimensional(3D)seismic data and conducting a quantitative fault analysis to thoroughly examine the planform,cross-sectional geometry,and evolution of PFS in the northern Zhongjiannan Basin.The absence of a dominant strike direction among these polygonal faults suggests that their evolution is not controlled by anisotropic stress.Our interpretation of seismic data,constrained by the spatial relationship among PFS,gullies,and pockmarks,indicates that PFS mainly developed within the Miocene strata,with their initiation occurring during the late Miocene.Furthermore,the PFS act as key conduits connecting gullies to pockmarks in this area.The formation and development of PFS may be primarily driven by thermally triggered processes within siliceous sediments.The necessary heat source is probably associated with the abundant submarine magmatism observed in the Zhongjiannan Basin.To reconstruct the regional geological history,a four-stage evolutionary model,incorporating the formation of PFS,is presented.This research significantly improves our understanding of the regional geological evolution of the Zhongjiannan Basin,providing critical insights into the initiation and development of PFS in the western South China Sea.
基金supported by the National Natural Science Foundation of China(42230312,42272270,42172262,42372266)the Deep Earth Probe and Mineral Resources Exploration-National Science and Technology Major Project(2024ZD1000500)the China Geological Survey Project(DD20240041).
文摘The Guanxian-Anxian fault zone in the Longmen Shan,Sichuan,China,exhibits long-term creep-slip but ruptured during the 2008 Wenchuan earthquake,challenging the view that creeping faults rarely generate strong earthquakes.To investigate the transition from creep-slip to stick-slip,we analyzed fault rocks from the WFSD-3,using microstructural observations,XRD,μXRF,Raman spectroscopy,and quartz grain size statistics.Fault rocks show intense foliation,pressure-solution structures,and abundant clay minerals,reflecting long-term aseismic creep.At the interface between black and gray fault gouges at~1249.98 m,microstructures indicate stick-slip behavior,including truncated grains,angular fragments,and finer grain sizes.Here,clay content drops sharply while strong minerals(quartz,feldspar,calcite,dolomite)increase.Elemental mapping shows Al and K enriched in black gouge,whereas Ca and Si in gray gouge;Raman spectroscopy indicates possible graphitization;the finest quartz grains occur in black gouge.These features mark co-seismic principal slip zone of the Wenchuan earthquake.We propose that fluid-driven transformation of strong minerals into clays facilitates creep-slip,whereas localized precipitation of strong minerals strengthens the fault,causing stress accumulation and controlling the creep-slip to stick-slip transition.This mechanism has implications for reassessing seismic hazards of creeping faults.
基金supported by the National Natural Science Foundation of China(Grant Nos.42130101,42474002,42374003&42564002)the Jiangxi Provincial Natural Science Foundation(Grant No.20252BAC240262).
文摘Accurate fault modeling is essential for understanding earthquake rupture processes and improving seismic hazard assessment.We present a unified framework that integrates geodetic data with multidisciplinary constraints,including relocated aftershocks,geological observations,and geophysical information,to adaptively model fault geometry and slip in diverse scenarios such as multi-segment and multi-event ruptures.The framework combines adaptive fault construction with a scenario-driven Bayesian joint inversion approach.Fault geometries are first built from prior constraints,such as surface ruptures and aftershocks,and then refined through probabilistic inference when such data are inadequate.To enhance computational efficiency,we introduce a Sequential Monte Carlo Fukuda-Johnson(SMC-FJ)strategy.This separates nonlinear parameters-including geometry,data weights,and smoothing factors-from linear slip parameters,which are conditionally solved via constrained least squares.Geometry updates follow a hierarchical adjustment scheme based on point,line,and structural units,enabling flexibility across rupture complexities.Synthetic tests and four case studies,including the 2022 Menyuan,2023 Türkiye,2022 Luding,and 2019 Ridgecrest earthquakes,demonstrate robustness under various constraints.For the Menyuan earthquake,full Bayesian inversion confirms that the fault geometry constrained by relocated aftershocks is highly accurate and needs only minor adjustment to match the observed surface deformation.The results further show that gradual changes in fault strike and dip modulated rupture arrest and postseismic stress accumulation,highlighting the critical role of inherited geometric structure in controlling rupture termination and delayed seismic activation.
基金supported by the National Natural Science Foundation of China(grant numbers 32471851,32171759 and 32201533)Double Thousand Plan of Jiangxi Province(jxsq2023201058)Jiangxi Province Ganpo Juncai Support Plan(2024BCE50043).
文摘Soil organic carbon in forest affects nutrient availability,microbial processes,and organic matter inputs.Dominant tree species have increasingly shifted from ectomycorrhizal to arbuscular mycorrhizal associations in subtropical forests.However,the consequences of this shift for soil organic carbon is poorly understood.To address this,a field study was conducted across a natural gradient of arbuscular tree associations to investigate how different mycorrhizal associations affect soil organic carbon quantity,composition,chemical stability,and related soil properties.Soil organic carbon fractions,functional groups,microbial enzyme activities were analyzed.Results showed that increasing arbuscular mycorrhizal dominance was associated with declines in total soil organic carbon,particularly in recalcitrant and aromatic carbon forms.Ectomycorrhizaldominated forests exhibited higher nitrogen availability and elevated nitrogen-hydrolyzing enzyme activity,suggesting enhanced nitrogen acquisition strategies that suppress soil organic carbon decomposition and promote carbon retention.These findings indicate that mycorrhizal-mediated shifts in tree composition may significantly alter soil carbon sequestration potential.Incorporating mycorrhizal functional traits into forest management and carbon modeling could improve predictions of soil organic carbon responses under future environmental change.
基金funded by the grant“EVA4.0”,No.Z.02.1.01/0.0/0.0/16_019/0000803 supported by OP RDE as well as by the projects APVV-19-0387,APVV-22-0056,and APVV-23-0293 from the Slovak Research and Development Agencyco-funded by the European Commission under the Horizon Europe Teaming for Excellence action+1 种基金project Ligno Silvagrant agreement No.101059552。
文摘This study investigated biomass allocation in young stands of European beech(Fagus sylvatica L.)and Norway spruce(Picea abies(L.)Karst.)across 31 forest sites in the Western Carpathians,Slovakia.A total of 541 trees aged 2–10 years,originating from natural regeneration and planting,were destructively sampled to quantify biomass in four components:foliage,branches,stems,and roots.Generalized non-linear least squares(GNLS)models with a weighing variance function outperformed log-transformed seemingly unrelated regression(SUR)models in terms of accuracy and robustness,especially for foliage and branch biomass.When using height as the predictor,SUR models tended to underestimate biomass in planted beech,leading to notable underprediction of aboveground and total biomass.Biomass allocation patterns varied significantly by species and regeneration origin.Using a non-linear system of equations and component ratio modelling,we found out that planted spruce displayed low variability and a consistent dominance of needle biomass,while naturally regenerated beech showed greater variability and a higher proportion of stem biomass,reflecting stronger competition-driven vertical growth.Interspecific differences in total biomass were more pronounced when using tree height,with spruce generally exhibiting greater biomass than beech at equivalent heights.Overall,stem base diameter marginally outperformed tree height as a predictor of biomass.However,tree height-based models showed strong performance and are particularly suitable for integration with remote sensing applications.These findings can directly support forest managers and modellers in comparing regeneration methods and biomass estimation approaches for early-stage stand development,carbon accounting,and remote sensing calibration.
基金funded by the Science and Technology Projects of State Grid Zhejiang Electric Power Co.,Ltd.(5211DS24000G).
文摘With the rapid development of large-scale offshore wind farms,efficient and reliable power transmission systems are urgently needed.Hybrid high-voltage direct current(HVDC)configurations combining a diode rectifier unit(DRU)and a modular multilevel converter(MMC)have emerged as a promising solution,offering advantages in cost-effectiveness and control capability.However,the uncontrollable nature of the DRU poses significant challenges for systemstability under offshore AC fault conditions,particularly due to its inability to provide fault current or voltage support.This paper investigates the offshore AC fault characteristics and fault ride-through(FRT)strategy of a hybrid offshore wind power transmission system based on a diode rectifier unit DRU and MMC.First,the dynamic response of the hybrid system under offshore symmetrical three-phase faults is analyzed.It is demonstrated that due to the unidirectional conduction nature of the DRU,its AC current rapidly drops to zero during faults,and the fault current is solely contributed by the wind turbine generators(WTGs)and wind farm MMC(WFMMC).Based on this analysis,a coordinated FRT strategy is proposed,which combines a segmented current limiting control for the wind-turbine(WT)grid-side converters(GSCs)and a constant AC current control for the WFMMC.The strategy ensures effective voltage support during the fault and prevents MMC current saturation during fault recovery,enabling fast and stable system restoration.Electromagnetic transient simulations in PSCAD/EMTDC verify the feasibility of the proposed fault ride-through strategy.
基金supported by the Xingdian Talent Support Program of Yunnan Province(E5YNR03B01)the Xishuangbanna State Rainforest Talent Support Program(E4BN041B01)the CAS President’s International Fellowship Initiative(2020FYB0003)。
文摘Allometric equations are fundamental tools in ecological research and forestry management,widely used for estimating above-ground biomass and production,serving as the core foundations of dynamic vegetation models.Using global datasets from Tallo(a tree allometry and crown architecture database encompassing thousands of species)and TRY(a plant traits database),we fit B ayesian hierarchical models with three alternative functional forms(powerlaw,generalized Michaelis-Menten(gMM),and Weibull)to characterize how diameter at breast height(DBH),tree height(H),and crown radius(CR)scale with and without wood density as a species-level predictor.Our analysis revealed that the saturating Weibull function best captured the relationship between tree height and DBH in both functional groups,whereas the CR-DBH relationship was best predicted by a power-law function in angiosperms and by the gMM function in gymnosperms.Although including wood density did not significantly improve predictive performance,it revealed important ecological trade-offs:lighter-wood angiosperms achieve taller mature heights more rapidly,and denser wood promotes wider crown expansion across clades.We also found that accurately estimating DBH required considering both height and crown size,highlighting how these variables together distinguish trees of similar height but differing trunk diameters.Our results emphasize the importance of applying saturating functions for large trees to improve forest biomass estimates and show that wood density,though not always predictive at broad scales,helps illuminate the biomechanical and ecological constraints underlying diverse tree architectures.These findings offer practical pathways for integrating height-and crown-based metrics into existing carbon monitoring programs worldwide.
基金supported by the Deep Earth Probe and Mineral Resources Exploration-National Science and Technology Major Project(2024ZD1000500)the National Natural Science Foundation of China(42172262 and 42372266)+1 种基金the China Geological Survey(DD20240041)the Fundamental Research Funds of the Institute of Geomechanics(DZLXJK202516).
文摘The Yingxiu-Beichuan fault zone(YBFZ)has long been active and experienced repeated large earthquakes.The physicochemical properties of the deep fault zone(>1000 m)are the key to understanding the deformation mechanism of large earthquakes.This study uses rock magnetic,microstructural,and geochemical analyses of representative samples exposed in FZ1681 within the Wenchuan Earthquake Fault Scientific Drilling borehole 2(WFSD-2)cores.Fault gouge and fault breccia have higher magnetic susceptibility values than wall rocks,and they contain abundant paramagnetic minerals and small quantities of magnetite and monoclinic pyrrhotite.The magnetite and monoclinic pyrrhotite in the fault gouge were mainly formed by coseismic frictional heating,indicating that large earthquakes with frictional heating temperatures of~500-900℃once occurred in the YBFZ.The seismogenic and coseismic environment was reducing with a relatively high sulfur content.The monoclinic pyrrhotite in the fault breccia was formed mainly by low-temperature hydrothermal fluid.This indicates that the fault zone experienced reducing and low-temperature(<400℃)hydrothermal fluid with a relatively high sulfur content after the earthquake.The YBFZ,which experiences frequent large earthquakes,is weakly oxidizing environment at different depths,but the effect of the low-temperature hydrothermal fluid is weaker at depth.
文摘Background 3D botanical tree reconstruction from a single image plays a vital role in the field of computer graphics.However,accurately capturing the intricate branching patterns and detailed morphologies of trees remains a challenge.Methods In this study,we proposed a novel approach for single-image tree reconstruction using a conditional generative adversarial network to infer the 3D skeleton of a tree in the form of a 2D skeleton depth map.Based on the 2D skeleton depth map,a corresponding branching structure(3D skeleton)that inherits the tree shape in the input image and leaves can be generated using a procedural modeling technique.Result Experimental results show that the proposed method accurately reconstructs diverse tree structures across species.Both quantitative and qualitative evaluations demonstrate improved skeleton completeness,branching accuracy,and visual realism over baseline methods,while requiring no user input.Conclusions Our proposed approach for generating lifelike 3D tree models from a single image with no user input shows its proficiency in achieving efficient and reliable reconstruction.These results showcase the capability of the proposed model to recreate complex tree architectures while capturing their visual authenticity.
文摘Grid-Forming(GFM)converters are prone to fault-induced overcurrent and power angle instability during grid fault-induced voltage sags.To address this,this paper develops a multi-loop coordinated fault ridethrough(FRT)control strategy based on a power outer loop and voltage-current inner loops,aiming to enhance the stability and current-limiting capability of GFM converters during grid fault conditions.During voltage sags,the GFM converter’s voltage source behavior is maintained by dynamically adjusting the reactive power reference to provide voltage support,thereby effectively suppressing the steady-state component of the fault current.To address the active power imbalance induced by voltage sags,a dynamic active power reference correction method based on apparent power is designed to mitigate power angle oscillations and limit transient current.Moreover,an adaptive virtual impedance loop is implemented to enhance dynamic transient current-limiting performance during the fault initiation phase.This approach improves the responsiveness of the inner loop and ensures safe system operation under various fault severities.Under asymmetric fault conditions,a negative-sequence reactive current compensation strategy is incorporated to further suppress negative-sequence voltage and improve voltage symmetry.The proposed control scheme enables coordinated operation of multiple control objectives,including voltage support,current suppression,and power angle stability,across different fault scenarios.Finally,MATLAB/Simulink simulation results validate the effectiveness of the proposed strategy,showcasing its superior performance in current limiting and power angle stability,thereby significantly enhancing the system’s fault ride-through capability.
基金funded by the Science and Technology Vice President Project in Changping District,Beijing(Project Name:Research on multi-scale optimization and intelligent control technology of integrated energy systemProject number:202302007013).
文摘The critical components of gas turbines suffer from prolonged exposure to factors such as thermal oxidation,mechanical wear,and airflow disturbances during prolonged operation.These conditions can lead to a series of issues,including mechanical faults,air path malfunctions,and combustion irregularities.Traditional modelbased approaches face inherent limitations due to their inability to handle nonlinear problems,natural factors,measurement uncertainties,fault coupling,and implementation challenges.The development of artificial intelligence algorithms has provided an effective solution to these issues,sparking extensive research into data-driven fault diagnosis methodologies.The review mechanism involved searching IEEE Xplore,ScienceDirect,and Web of Science for peerreviewed articles published between 2019 and 2025,focusing on multi-fault diagnosis techniques.A total of 220 papers were identified,with 123 meeting the inclusion criteria.This paper provides a comprehensive review of diagnostic methodologies,detailing their operational principles and distinctive features.It analyzes current research hotspots and challenges while forecasting future trends.The study systematically evaluates the strengths and limitations of various fault diagnosis techniques,revealing their practical applicability and constraints through comparative analysis.Furthermore,this paper looks forward to the future development direction of this field and provides a valuable reference for the optimization and development of gas turbine fault diagnosis technology in the future.
基金supported by the China Three Gorges Corporation(No.NBZZ202300860)the National Natural Science Foundation of China(No.52275104)the Science and Technology Innovation Program of Hunan Province(No.2023RC3097).
文摘Deep learning-based wind turbine blade fault diagnosis has been widely applied due to its advantages in end-to-end feature extraction.However,several challenges remain.First,signal noise collected during blade operation masks fault features,severely impairing the fault diagnosis performance of deep learning models.Second,current blade fault diagnosis often relies on single-sensor data,resulting in limited monitoring dimensions and ability to comprehensively capture complex fault states.To address these issues,a multi-sensor fusion-based wind turbine blade fault diagnosis method is proposed.Specifically,a CNN-Transformer Coupled Feature Learning Architecture is constructed to enhance the ability to learn complex features under noisy conditions,while a Weight-Aligned Data Fusion Module is designed to comprehensively and effectively utilize multi-sensor fault information.Experimental results of wind turbine blade fault diagnosis under different noise interferences show that higher accuracy is achieved by the proposed method compared to models with single-source data input,enabling comprehensive and effective fault diagnosis.
基金supported in part by the National Natural Science Foundation of China under Grants 52475102 and 52205101in part by the Guangdong Basic and Applied Basic Research Foundation under Grant 2023A1515240021+1 种基金in part by the Young Talent Support Project of Guangzhou Association for Science and Technology(QT-2024-28)in part by the Youth Development Initiative of Guangdong Association for Science and Technology(SKXRC2025254).
文摘To ensure the safe and stable operation of rotating machinery,intelligent fault diagnosis methods hold significant research value.However,existing diagnostic approaches largely rely on manual feature extraction and expert experience,which limits their adaptability under variable operating conditions and strong noise environments,severely affecting the generalization capability of diagnostic models.To address this issue,this study proposes a multimodal fusion fault diagnosis framework based on Mel-spectrograms and automated machine learning(AutoML).The framework first extracts fault-sensitive Mel time–frequency features from acoustic signals and fuses them with statistical features of vibration signals to construct complementary fault representations.On this basis,automated machine learning techniques are introduced to enable end-to-end diagnostic workflow construction and optimal model configuration acquisition.Finally,diagnostic decisions are achieved by automatically integrating the predictions of multiple high-performance base models.Experimental results on a centrifugal pump vibration and acoustic dataset demonstrate that the proposed framework achieves high diagnostic accuracy under noise-free conditions and maintains strong robustness under noisy interference,validating its efficiency,scalability,and practical value for rotating machinery fault diagnosis.
基金funded by the Global PhD Scholarship between KU Leuven and UCLouvain。
文摘Litter decomposition is an essential ecosystem process influenced by multiple factors,including substrate quality,climate,edaphic environment,and decomposer communities.However,the role of canopy species identity and diversity on leaf litter decomposition in forests remains understudied.By controlling for macroclimate,soil properties,and litter substrate in a mature common garden,we investigated whether a three-month tea bag incubation of standardized green and rooibos tea substrate is driven by canopy tree species characteristics and diversity.Our study hypothesized two primary pathways:a chemical engineering effect,where trees alter soil properties and decomposer communities through litter input,and a physical engineering effect,where tree canopy structure modulates the local microclimate.The results showed that even under uniform macroclimatic and initial soil conditions,mass loss rates varied widely for green tea(27.4%–73.2%)and rooibos tea(6.1%–34.7%),comparable as found in other research between distinct biomes.While substrate quality was the dominant factor,both engineering pathways and,to a minor extent,tree diversity modulated mass losses.For green tea,tree chemical and physical characteristics seemed equally important,while the physical environment showed an increased importance for rooibos.Incubation depth played a key role,where forest floor decomposition rates are more susceptible to temporal climate variations,and soil-layer decomposition rates are less susceptible to climate variations and more determined by tree species identity.Our findings suggest that tea bag experiments focusing solely on topsoil burial may underestimate processes in the forest floor and the mineralorganic boundary layer.This study underscores the critical role of litter substrate quality in decomposition while demonstrating that tree community composition and the associated herbaceous layer,through both chemical and physical engineering pathways,strongly modulate decomposition rates.
基金supported by the National Natural Science Foundation(32130068,32271634,and 32071597)CAS Key Laboratory of Forest Ecology and Silviculture,Institute of Applied Ecology,Chinese Academy of Sciences(KLFES-2025)。
文摘Urban forests are highly multifunctional and provide numerous ecological functions.Plant functional traits individually or jointly influence the ecological multifunctionality of tree species(TS-EMF)and can also modify TSEMF in response to environmental changes.However,there has been limited exploration of multitrait combinations for predicting TS-EMF across seasons and of trait thresholds that enhance TS-EMF.Here,for 10 dominant tree species in urban forests of Northeast China,14 traits were measured and four aboveground and three belowground ecological functions assessed in three seasons.Ecological functions and TS-EMF differed significantly throughout the seasons(P<0.05).Synergistic relationships were found between carbon sequestration and oxygen release,between cooling and humidification,and between organic carbon accumulation and nutrient cycling.Notably,aboveground multifunctionality played a leading role in TS-EMF.With seasonal changes,resource allocation shifted toward traits related to resource acquisition rather than conservation to maintain TS-EMF.The combination of traits that predicted TS-EMF varied by type,accounting for up to 66.45%of the variation.TS-EMF was primarily driven by leaf structure in spring and by nutrient accumulation in autumn.Leaf carbon content(LCC)consistently served as a stabilizing factor for predicting TS-EMF across seasons.At 36.5-36.8 mg g^(-1),LCC had its optimal effect on TS-EMF.Other traits in combination that positively influence total TS-EMF include leaf nitrogen content(3.43-3.45 mg g^(-1)),leaf phosphorus content(0.80-0.83 mg g^(-1)),and leaf area(65.86-68.43 cm^(2)).Within these specified trait thresholds,Morus alba and Quercus mongolica were identified as key species.These findings suggest that the trade-off between various ecological functions can be managed by altering plant traits across seasons.This approach could provide a theoretical foundation for enhancing the TS-EMF of urban forests through trait-based management,offering practical guidance for selecting tree species.
