Volume models for the long-term management of Okomu National Park in Nigeria are not available. The main challenge in assessing forest resources is the lack of accurate, species-specific baseline data and updated info...Volume models for the long-term management of Okomu National Park in Nigeria are not available. The main challenge in assessing forest resources is the lack of accurate, species-specific baseline data and updated information on volume models, growth rates, and disturbances. This complicates the development of effective management plans. This study addresses this by modelling tree volume using temporary sample plots laid out using a systematic line transect method Data was collected from 16 40 m × 50 m plots using a Spiegel relascope. DBH, top, middle, and base diameters, and overall height were measured for trees ≤ 10 cm DBH. Newton’s formula calculated volume of each tree, and per hectare estimates generated. The results showed an average of 132 trees per hectare. Population densities of individual species ranged from 1–11/ha, indicating a low density. Strombosia pustulata was the most abundant species. For coefficients that form the basis for species grouping, species-specific volume equations were developed and grouped into three clusters. Regression equations were fitted and selected based on specific statistical metrics. The volume models showed that generalized (V_(i)=b_(0)+b_(1)(D_(i)^(2)H_(i))+ε_(i)) functions, based on the statistical metrics, performed more effectively. The generalized functions exhibited superior performance, evidenced by the uniform residual plot distribution for DBH^(2)H, implying consistent experimental error and adherence to regression assumptions. A t-test at 95% confidence showed that the discrepancy between predicted and actual values was insignificant. This study indicates that the prediction models provide effective management tools for climate mitigation and determining carbon sequestration by a tropical forest.展开更多
Forest volume, the major component of forest biomass, is an important issue in forest resource monitoring.It is estimated from tree volume tables or equations. Based on tree volume data of 1840 sample trees from Chine...Forest volume, the major component of forest biomass, is an important issue in forest resource monitoring.It is estimated from tree volume tables or equations. Based on tree volume data of 1840 sample trees from Chinese fir （Cunninghamia lanceolata） plantations in Guizhou Province in southwestern China, parallel one- and two-variable tree volume tables and tree height curves for central and other areas were constructed using an error-in-variable modeling method. The results show that, although the one-variable tree volume equations and height curves between the central and other areas were significantly different, the two-variable volume equations were sufficiently close, so that a generalized two-variable tree volume equation could be established for the entire province.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
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
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
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
We investigated the impact of convexity and isoperimetric deficits on the accuracy of sectional area estimates of tree stems using traditional methods(caliper,tape,formulas based on stem diameter and circumference).In...We investigated the impact of convexity and isoperimetric deficits on the accuracy of sectional area estimates of tree stems using traditional methods(caliper,tape,formulas based on stem diameter and circumference).In two complementary experiments,the use of photographs to estimate cross-sectional areas was first validated,then the use of a caliper and diameter tape was computer-simulated.The results indicated that the photographic method offers high precision,with mean relative errors below 0.1%,minimal deviation,and no significant bias,and the traditional methods led to substantial and systematic errors,with deviations from circularity and convexity significantly increasing the errors in area estimation.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
Transforming urban spatial structures to promote green and low-carbon development is an effective strategy.Although prior studies have examined the impact of urban polycentricity on carbon emissions and economic devel...Transforming urban spatial structures to promote green and low-carbon development is an effective strategy.Although prior studies have examined the impact of urban polycentricity on carbon emissions and economic development,research on its role in the synergistic relationship between these factors regarding carbon emission efficiency is limited.Furthermore,existing literature often overlooks nonlinear effects and interactions with other urban variables.This paper analyzed data from 295 Chinese cities in 2020,calculating urban population polycentricity,population dispersion indices,and carbon emission efficiency.Utilizing local spatial autocorrelation tools,we reveal interactions among urban population polycentricity,dispersion,carbon emissions,and carbon emission efficiency.We then employ a gradient boosting decision tree model(GBDT)to explore nonlinear and synergistic effects of polycentric urbanization.Key findings include:1)polycentric urbanization in Chinese cities exhibits significant spatial differentiation characteristics.The Polycentricity index is relatively high in economically developed eastern coastal regions with an overall low level,carbon emissions are concentrated in industrialized north-central cities and some Yangtze River Delta hubs,and carbon emission efficiency is the highest in the Yangtze River Delta while relatively low in Northeast China;there are significant spatially heterogeneous interaction characteristics among population polycentricity,population dispersion,carbon emissions,and carbon emission efficiency.2)Urban population polycentricity contributes 9.42%to total carbon emissions and 6.24%to carbon emission efficiency.3)The polycentricity index has a nonlinear impact on carbon emissions and carbon emission efficiency:no significant effect when below 0.50 or above 0.55,increased carbon emissions in 0.50-0.53,and reduced carbon emissions with improved efficiency in 0.53-0.55.4)The polycentricity index has an interaction effect with other variables;specifically,when the polycentricity index is between 0.53 and 0.55,its interaction with urban gross domestic product(GDP),urban population,urban built-up area,green coverage rate in built-up areas,urban technological expenditure,and the proportion of the output value of the secondary industry will reduce carbon emissions and improve carbon emission efficiency.These findings enhance the understanding of urban spatial structures and carbon emissions,providing valuable insights for policymakers in developing green and low-carbon strategies.展开更多
Underwater images frequently suffer from chromatic distortion,blurred details,and low contrast,posing significant challenges for enhancement.This paper introduces AquaTree,a novel underwater image enhancement(UIE)meth...Underwater images frequently suffer from chromatic distortion,blurred details,and low contrast,posing significant challenges for enhancement.This paper introduces AquaTree,a novel underwater image enhancement(UIE)method that reformulates the task as a Markov Decision Process(MDP)through the integration of Monte Carlo Tree Search(MCTS)and deep reinforcement learning(DRL).The framework employs an action space of 25 enhancement operators,strategically grouped for basic attribute adjustment,color component balance,correction,and deblurring.Exploration within MCTS is guided by a dual-branch convolutional network,enabling intelligent sequential operator selection.Our core contributions include:(1)a multimodal state representation combining CIELab color histograms with deep perceptual features,(2)a dual-objective reward mechanism optimizing chromatic fidelity and perceptual consistency,and(3)an alternating training strategy co-optimizing enhancement sequences and network parameters.We further propose two inference schemes:an MCTS-based approach prioritizing accuracy at higher computational cost,and an efficient network policy enabling real-time processing with minimal quality loss.Comprehensive evaluations on the UIEB Dataset and Color correction and haze removal comparisons on the U45 Dataset demonstrate AquaTree’s superiority,significantly outperforming nine state-of-the-art methods across five established underwater image quality metrics.展开更多
In this paper, the new formulae of tree height curve and volume cdrie were derived from the theory of column buckling. They were applied to artificial Pine (Pinus sylvestris var. mongolica) and Larch (Larix principis ...In this paper, the new formulae of tree height curve and volume cdrie were derived from the theory of column buckling. They were applied to artificial Pine (Pinus sylvestris var. mongolica) and Larch (Larix principis rupprechtii). The results demonsed that the new formulae wee more effeCtive and precise than conventional formulae of height curve and volume curve.展开更多
We investigated the distribution and frequency of damage to tree stands adjacent to low-volume roads according to the type of hillside materials involved（soil or rock） and hillside gradient in mountainous forests of...We investigated the distribution and frequency of damage to tree stands adjacent to low-volume roads according to the type of hillside materials involved（soil or rock） and hillside gradient in mountainous forests of northern Iran. A total of 80 plots were systematically and randomly sampled to record damaged trees（bending,crushing and wounding） by class of hillside gradient and materials at the edge of road. Tree wounding and crushing at rock slopes was significantly greater than at hillsides with a mix of clay soil（p ／ 0.05）. Damage on hillsides with slope gradients[45% were 2, 8.5 and 2.3 times more frequent than on hillsides with slope gradient／15% for bending, crushing and wounding, respectively. The damage distribution varied according by type and the most frequent damage was tree wounding（p ／ 0.05）. The damage distribution was measured at distances of 4, 5 and 8 m from the road fillslope for tree bending, crushing and wounding, respectively. Using hydraulic excavators and physical barriers（wooden obstruction and synthetic holder） during earthworks for road construction could reduce these damage.展开更多
Urban tree species provide various essential ecosystem services in cities,such as regulating urban temperatures,reducing noise,capturing carbon,and mitigating the urban heat island effect.The quality of these services...Urban tree species provide various essential ecosystem services in cities,such as regulating urban temperatures,reducing noise,capturing carbon,and mitigating the urban heat island effect.The quality of these services is influenced by species diversity,tree health,and the distribution and the composition of trees.Traditionally,data on urban trees has been collected through field surveys and manual interpretation of remote sensing images.In this study,we evaluated the effectiveness of multispectral airborne laser scanning(ALS)data in classifying 24 common urban roadside tree species in Espoo,Finland.Tree crown structure information,intensity features,and spectral data were used for classification.Eight different machine learning algorithms were tested,with the extra trees(ET)algorithm performing the best,achieving an overall accuracy of 71.7%using multispectral LiDAR data.This result highlights that integrating structural and spectral information within a single framework can improve the classification accuracy.Future research will focus on identifying the most important features for species classification and developing algorithms with greater efficiency and accuracy.展开更多
Agrobacterium tumefaciens-mediated transformation has been widely adopted for plant genetic engineering and the study of gene function(Krenek et al.,2015).This method is prevalent in the genetic transformation of herb...Agrobacterium tumefaciens-mediated transformation has been widely adopted for plant genetic engineering and the study of gene function(Krenek et al.,2015).This method is prevalent in the genetic transformation of herbaceous plants,with notable applications in species such as Arabidopsis(Yin et al.,2024),soybean(Zhang et al.,2024),rice(Zhang et al.,2020),and Chinese cabbage(Li et al.,2021).However,its application in fruit trees is limited.This is primarily due to their long growth cycles and lack of rapid,efficient,and stable transgenic systems,which severely hinders foundational research involving plant genetic transformation(Mei et al.,2024).Furthermore,for subtropical fruit trees,the presence of recalcitrant seeds adds an extra layer of difficulty to genetic transformation(Umarani et al.,2015),as most methods rely on seed germination as a basis for transformation.展开更多
Tree endophytic fungi play an important role in reducing insect herbivory,either by repelling them or kill-ing them directly.Identifying which fungi show such activ-ity could lead to new environmentally friendly pesti...Tree endophytic fungi play an important role in reducing insect herbivory,either by repelling them or kill-ing them directly.Identifying which fungi show such activ-ity could lead to new environmentally friendly pesticides.In this study,the Mediterranean basin climate conditions are projected to harshen in the next decades,will increase vulnerability of tree species to pest invasions.Endophytic fungi were isolated from wood and leaves of Quercus pyr-enaica,Q.ilex and Q.suber and tested for virulence against adults of the mealworm beetle,Tenebrio molitor L.using a direct contact method.Only 3 of 111 sporulating isolates had entomopathogenic activity,all identified as Lecanicillium lecanii.The pathogenicity of L.lecanii on T.molitor resulted in a median lethal time(TL50)of 14-16 d.Compared with commercial products,L.lecanii caused faster insect death than the nematode Steinernema carpocapsae and nuclear polyhedrosis virus(no effect on T.molitor survival),and slower than Beauveria bassiana(TL50=5),Beauveria pseu-dobassiana(TL50=8d)and Bacillus thuriengensis(80%mortality first day after inoculation).Mortality was also accelerated under water stress,reducing TL50 by an addi-tional 33%.Remarkably,water stress alone had a comparable effect on mortality to that of L.lecanii isolates.This study confirms T.molitor as a good model insect for pathogenicity testing and agrees with management policies proposed in the EU Green Deal.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
Leaf turgor loss point has been recognized as an important plant physiological trait explaining a species’drought tolerance( π_(tlp)).Less is known about the variation of π_(tlp) in time and how seasonal or interan...Leaf turgor loss point has been recognized as an important plant physiological trait explaining a species’drought tolerance( π_(tlp)).Less is known about the variation of π_(tlp) in time and how seasonal or interannual differences in water availability are affecting π_(tlp) as a static trait.I monitored the seasonal variation of π_(tlp) during a drought year starting in early spring with juvenile leaves and assessed the interannual variation in π_(tlp) of fully matured leaves among years with diverting water availability for three temperate broad-leaved tree species.The largest seasonal changes in π_(tlp) occurred during leaf unfolding until leaves were fully developed and matured.After leaves matured,no significant changes occurred for the rest of the vegetation period.Interannual variation that could be related to water availability was only present in one of the three tree species.The results suggest that the investigated species have a rapid period of osmotic adjustment early in the growing season followed by a period of relative stability,when π_(tlp) can be considered as a static trait.展开更多
The problem of collision avoidance for non-cooperative targets has received significant attention from researchers in recent years.Non-cooperative targets exhibit uncertain states and unpredictable behaviors,making co...The problem of collision avoidance for non-cooperative targets has received significant attention from researchers in recent years.Non-cooperative targets exhibit uncertain states and unpredictable behaviors,making collision avoidance significantly more challenging than that for space debris.Much existing research focuses on the continuous thrust model,whereas the impulsive maneuver model is more appropriate for long-duration and long-distance avoidance missions.Additionally,it is important to minimize the impact on the original mission while avoiding noncooperative targets.On the other hand,the existing avoidance algorithms are computationally complex and time-consuming especially with the limited computing capability of the on-board computer,posing challenges for practical engineering applications.To conquer these difficulties,this paper makes the following key contributions:(A)a turn-based(sequential decision-making)limited-area impulsive collision avoidance model considering the time delay of precision orbit determination is established for the first time;(B)a novel Selection Probability Learning Adaptive Search-depth Search Tree(SPL-ASST)algorithm is proposed for non-cooperative target avoidance,which improves the decision-making efficiency by introducing an adaptive-search-depth mechanism and a neural network into the traditional Monte Carlo Tree Search(MCTS).Numerical simulations confirm the effectiveness and efficiency of the proposed method.展开更多
文摘Volume models for the long-term management of Okomu National Park in Nigeria are not available. The main challenge in assessing forest resources is the lack of accurate, species-specific baseline data and updated information on volume models, growth rates, and disturbances. This complicates the development of effective management plans. This study addresses this by modelling tree volume using temporary sample plots laid out using a systematic line transect method Data was collected from 16 40 m × 50 m plots using a Spiegel relascope. DBH, top, middle, and base diameters, and overall height were measured for trees ≤ 10 cm DBH. Newton’s formula calculated volume of each tree, and per hectare estimates generated. The results showed an average of 132 trees per hectare. Population densities of individual species ranged from 1–11/ha, indicating a low density. Strombosia pustulata was the most abundant species. For coefficients that form the basis for species grouping, species-specific volume equations were developed and grouped into three clusters. Regression equations were fitted and selected based on specific statistical metrics. The volume models showed that generalized (V_(i)=b_(0)+b_(1)(D_(i)^(2)H_(i))+ε_(i)) functions, based on the statistical metrics, performed more effectively. The generalized functions exhibited superior performance, evidenced by the uniform residual plot distribution for DBH^(2)H, implying consistent experimental error and adherence to regression assumptions. A t-test at 95% confidence showed that the discrepancy between predicted and actual values was insignificant. This study indicates that the prediction models provide effective management tools for climate mitigation and determining carbon sequestration by a tropical forest.
基金supported by the Agricultural Science and Technique Foundation of Guizhou Province, China (No. 2008-3059)the Research Funds of Forestry Administration of Guizhou Province, China (Nos. 2010-01-08, 2010-01, 200625)
文摘Forest volume, the major component of forest biomass, is an important issue in forest resource monitoring.It is estimated from tree volume tables or equations. Based on tree volume data of 1840 sample trees from Chinese fir （Cunninghamia lanceolata） plantations in Guizhou Province in southwestern China, parallel one- and two-variable tree volume tables and tree height curves for central and other areas were constructed using an error-in-variable modeling method. The results show that, although the one-variable tree volume equations and height curves between the central and other areas were significantly different, the two-variable volume equations were sufficiently close, so that a generalized two-variable tree volume equation could be established for the entire province.
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 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.
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.
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.
文摘We investigated the impact of convexity and isoperimetric deficits on the accuracy of sectional area estimates of tree stems using traditional methods(caliper,tape,formulas based on stem diameter and circumference).In two complementary experiments,the use of photographs to estimate cross-sectional areas was first validated,then the use of a caliper and diameter tape was computer-simulated.The results indicated that the photographic method offers high precision,with mean relative errors below 0.1%,minimal deviation,and no significant bias,and the traditional methods led to substantial and systematic errors,with deviations from circularity and convexity significantly increasing the errors in area estimation.
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.
基金Under the auspices of National Natural Science Foundation of China(No.42571300)。
文摘Transforming urban spatial structures to promote green and low-carbon development is an effective strategy.Although prior studies have examined the impact of urban polycentricity on carbon emissions and economic development,research on its role in the synergistic relationship between these factors regarding carbon emission efficiency is limited.Furthermore,existing literature often overlooks nonlinear effects and interactions with other urban variables.This paper analyzed data from 295 Chinese cities in 2020,calculating urban population polycentricity,population dispersion indices,and carbon emission efficiency.Utilizing local spatial autocorrelation tools,we reveal interactions among urban population polycentricity,dispersion,carbon emissions,and carbon emission efficiency.We then employ a gradient boosting decision tree model(GBDT)to explore nonlinear and synergistic effects of polycentric urbanization.Key findings include:1)polycentric urbanization in Chinese cities exhibits significant spatial differentiation characteristics.The Polycentricity index is relatively high in economically developed eastern coastal regions with an overall low level,carbon emissions are concentrated in industrialized north-central cities and some Yangtze River Delta hubs,and carbon emission efficiency is the highest in the Yangtze River Delta while relatively low in Northeast China;there are significant spatially heterogeneous interaction characteristics among population polycentricity,population dispersion,carbon emissions,and carbon emission efficiency.2)Urban population polycentricity contributes 9.42%to total carbon emissions and 6.24%to carbon emission efficiency.3)The polycentricity index has a nonlinear impact on carbon emissions and carbon emission efficiency:no significant effect when below 0.50 or above 0.55,increased carbon emissions in 0.50-0.53,and reduced carbon emissions with improved efficiency in 0.53-0.55.4)The polycentricity index has an interaction effect with other variables;specifically,when the polycentricity index is between 0.53 and 0.55,its interaction with urban gross domestic product(GDP),urban population,urban built-up area,green coverage rate in built-up areas,urban technological expenditure,and the proportion of the output value of the secondary industry will reduce carbon emissions and improve carbon emission efficiency.These findings enhance the understanding of urban spatial structures and carbon emissions,providing valuable insights for policymakers in developing green and low-carbon strategies.
基金supported by theHubei Provincial Technology Innovation Special Project and the Natural Science Foundation of Hubei Province under Grants 2023BEB024,2024AFC066,respectively.
文摘Underwater images frequently suffer from chromatic distortion,blurred details,and low contrast,posing significant challenges for enhancement.This paper introduces AquaTree,a novel underwater image enhancement(UIE)method that reformulates the task as a Markov Decision Process(MDP)through the integration of Monte Carlo Tree Search(MCTS)and deep reinforcement learning(DRL).The framework employs an action space of 25 enhancement operators,strategically grouped for basic attribute adjustment,color component balance,correction,and deblurring.Exploration within MCTS is guided by a dual-branch convolutional network,enabling intelligent sequential operator selection.Our core contributions include:(1)a multimodal state representation combining CIELab color histograms with deep perceptual features,(2)a dual-objective reward mechanism optimizing chromatic fidelity and perceptual consistency,and(3)an alternating training strategy co-optimizing enhancement sequences and network parameters.We further propose two inference schemes:an MCTS-based approach prioritizing accuracy at higher computational cost,and an efficient network policy enabling real-time processing with minimal quality loss.Comprehensive evaluations on the UIEB Dataset and Color correction and haze removal comparisons on the U45 Dataset demonstrate AquaTree’s superiority,significantly outperforming nine state-of-the-art methods across five established underwater image quality metrics.
文摘In this paper, the new formulae of tree height curve and volume cdrie were derived from the theory of column buckling. They were applied to artificial Pine (Pinus sylvestris var. mongolica) and Larch (Larix principis rupprechtii). The results demonsed that the new formulae wee more effeCtive and precise than conventional formulae of height curve and volume curve.
文摘We investigated the distribution and frequency of damage to tree stands adjacent to low-volume roads according to the type of hillside materials involved（soil or rock） and hillside gradient in mountainous forests of northern Iran. A total of 80 plots were systematically and randomly sampled to record damaged trees（bending,crushing and wounding） by class of hillside gradient and materials at the edge of road. Tree wounding and crushing at rock slopes was significantly greater than at hillsides with a mix of clay soil（p ／ 0.05）. Damage on hillsides with slope gradients[45% were 2, 8.5 and 2.3 times more frequent than on hillsides with slope gradient／15% for bending, crushing and wounding, respectively. The damage distribution varied according by type and the most frequent damage was tree wounding（p ／ 0.05）. The damage distribution was measured at distances of 4, 5 and 8 m from the road fillslope for tree bending, crushing and wounding, respectively. Using hydraulic excavators and physical barriers（wooden obstruction and synthetic holder） during earthworks for road construction could reduce these damage.
文摘Urban tree species provide various essential ecosystem services in cities,such as regulating urban temperatures,reducing noise,capturing carbon,and mitigating the urban heat island effect.The quality of these services is influenced by species diversity,tree health,and the distribution and the composition of trees.Traditionally,data on urban trees has been collected through field surveys and manual interpretation of remote sensing images.In this study,we evaluated the effectiveness of multispectral airborne laser scanning(ALS)data in classifying 24 common urban roadside tree species in Espoo,Finland.Tree crown structure information,intensity features,and spectral data were used for classification.Eight different machine learning algorithms were tested,with the extra trees(ET)algorithm performing the best,achieving an overall accuracy of 71.7%using multispectral LiDAR data.This result highlights that integrating structural and spectral information within a single framework can improve the classification accuracy.Future research will focus on identifying the most important features for species classification and developing algorithms with greater efficiency and accuracy.
基金funded by the Key-Area Research and Development Program of Guangdong Province(Grant No.2022B0202070002)the Guangxi Science and Technology Major Program(Grant No.GuikeAA23023007-2)+1 种基金the Guangdong Province Modern Agricultural Industry Technology System Innovation Team Construction Project(2024CXTD19)Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515010303)。
文摘Agrobacterium tumefaciens-mediated transformation has been widely adopted for plant genetic engineering and the study of gene function(Krenek et al.,2015).This method is prevalent in the genetic transformation of herbaceous plants,with notable applications in species such as Arabidopsis(Yin et al.,2024),soybean(Zhang et al.,2024),rice(Zhang et al.,2020),and Chinese cabbage(Li et al.,2021).However,its application in fruit trees is limited.This is primarily due to their long growth cycles and lack of rapid,efficient,and stable transgenic systems,which severely hinders foundational research involving plant genetic transformation(Mei et al.,2024).Furthermore,for subtropical fruit trees,the presence of recalcitrant seeds adds an extra layer of difficulty to genetic transformation(Umarani et al.,2015),as most methods rely on seed germination as a basis for transformation.
基金supported by LIFE project MYCORESTORE“Innovative use of mycological resources for resilient and productive Mediterranean forests threatened by climate change,LIFE18 CCA/ES/001110”projects VA178P23 and VA208P20 funded by JCYL(Spain),both co-financed by FEDER(UE)budget.
文摘Tree endophytic fungi play an important role in reducing insect herbivory,either by repelling them or kill-ing them directly.Identifying which fungi show such activ-ity could lead to new environmentally friendly pesticides.In this study,the Mediterranean basin climate conditions are projected to harshen in the next decades,will increase vulnerability of tree species to pest invasions.Endophytic fungi were isolated from wood and leaves of Quercus pyr-enaica,Q.ilex and Q.suber and tested for virulence against adults of the mealworm beetle,Tenebrio molitor L.using a direct contact method.Only 3 of 111 sporulating isolates had entomopathogenic activity,all identified as Lecanicillium lecanii.The pathogenicity of L.lecanii on T.molitor resulted in a median lethal time(TL50)of 14-16 d.Compared with commercial products,L.lecanii caused faster insect death than the nematode Steinernema carpocapsae and nuclear polyhedrosis virus(no effect on T.molitor survival),and slower than Beauveria bassiana(TL50=5),Beauveria pseu-dobassiana(TL50=8d)and Bacillus thuriengensis(80%mortality first day after inoculation).Mortality was also accelerated under water stress,reducing TL50 by an addi-tional 33%.Remarkably,water stress alone had a comparable effect on mortality to that of L.lecanii isolates.This study confirms T.molitor as a good model insect for pathogenicity testing and agrees with management policies proposed in the EU Green Deal.
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.
基金supported by the European Union as a mobility grant
文摘Leaf turgor loss point has been recognized as an important plant physiological trait explaining a species’drought tolerance( π_(tlp)).Less is known about the variation of π_(tlp) in time and how seasonal or interannual differences in water availability are affecting π_(tlp) as a static trait.I monitored the seasonal variation of π_(tlp) during a drought year starting in early spring with juvenile leaves and assessed the interannual variation in π_(tlp) of fully matured leaves among years with diverting water availability for three temperate broad-leaved tree species.The largest seasonal changes in π_(tlp) occurred during leaf unfolding until leaves were fully developed and matured.After leaves matured,no significant changes occurred for the rest of the vegetation period.Interannual variation that could be related to water availability was only present in one of the three tree species.The results suggest that the investigated species have a rapid period of osmotic adjustment early in the growing season followed by a period of relative stability,when π_(tlp) can be considered as a static trait.
基金co-supported by the Foundation of Shanghai Astronautics Science and Technology Innovation,China(No.SAST2022-114)the National Natural Science Foundation of China(No.62303378),the National Natural Science Foundation of China(Nos.124B2031,12202281)the Foundation of China National Key Laboratory of Science and Technology on Test Physics&Numerical Mathematics,China(No.08-YY-2023-R11)。
文摘The problem of collision avoidance for non-cooperative targets has received significant attention from researchers in recent years.Non-cooperative targets exhibit uncertain states and unpredictable behaviors,making collision avoidance significantly more challenging than that for space debris.Much existing research focuses on the continuous thrust model,whereas the impulsive maneuver model is more appropriate for long-duration and long-distance avoidance missions.Additionally,it is important to minimize the impact on the original mission while avoiding noncooperative targets.On the other hand,the existing avoidance algorithms are computationally complex and time-consuming especially with the limited computing capability of the on-board computer,posing challenges for practical engineering applications.To conquer these difficulties,this paper makes the following key contributions:(A)a turn-based(sequential decision-making)limited-area impulsive collision avoidance model considering the time delay of precision orbit determination is established for the first time;(B)a novel Selection Probability Learning Adaptive Search-depth Search Tree(SPL-ASST)algorithm is proposed for non-cooperative target avoidance,which improves the decision-making efficiency by introducing an adaptive-search-depth mechanism and a neural network into the traditional Monte Carlo Tree Search(MCTS).Numerical simulations confirm the effectiveness and efficiency of the proposed method.
