This paper proposes a new algorithm for determining the starting points of contour lines. The new algorithm is based on the interval tree. The result improves the algorithm＇s efficiency remarkably. Further, a new str...This paper proposes a new algorithm for determining the starting points of contour lines. The new algorithm is based on the interval tree. The result improves the algorithm＇s efficiency remarkably. Further, a new strategy is designed to constrain the direction of threading and the resulting contour bears more meaningful information.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
Tree failure is an international problem,a major risk to public safety,and of growing concern because of extreme weather events.Tree biomechanics can inform the probability of tree failure,but empirical data from trop...Tree failure is an international problem,a major risk to public safety,and of growing concern because of extreme weather events.Tree biomechanics can inform the probability of tree failure,but empirical data from tropical settings are scarce.As a case study,we analyze the biomechanics(safety factor)of large heritage trees in public spaces in Indonesia.We examined critical buckling height using the Euler and Ylinen bending stress method.Tree morphometry(height,diameter at breast height,crown diameter),stability(modulus of elasticity),critical buckling height,and safety factor were quantified during this study.We found that large heritage trees in public spaces with buttresses have taller and larger morphometry and higher trunk and crown weights than small trees without buttresses.These trees are highly stable against external pressure.The presence of buttresses protects the target tree from rain and wind,resulting in a higher critical buckling height(H_(cr))of large(58.9 m)and buttressed target trees(58.8)than small(33.5 m)and unbuttressed trees(42.6 m),and a safety factor level of 68%safer.We make recommendations for selecting and managing trees in public spaces in a way that(i)can enhance wellbeing and biodiversity in urban planning,and(ii)is informed by risk to public safety.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
Tree trunk instance segmentation is crucial for under-canopy unmanned aerial vehicles(UAVs)to autonomously extract standing tree stem attributes.Using cameras as sensors makes these UAVs compact and lightweight,facili...Tree trunk instance segmentation is crucial for under-canopy unmanned aerial vehicles(UAVs)to autonomously extract standing tree stem attributes.Using cameras as sensors makes these UAVs compact and lightweight,facilitating safe and flexible navigation in dense forests.However,their limited onboard computational power makes real-time,image-based tree trunk segmentation challenging,emphasizing the urgent need for lightweight and efficient segmentation models.In this study,we present RT-Trunk,a model specifically designed for real-time tree trunk instance segmentation in complex forest environments.To ensure real-time performance,we selected SparseInst as the base framework.We incorporated ConvNeXt-T as the backbone to enhance feature extraction for tree trunks,thereby improving segmentation accuracy.We further integrate the lightweight convolutional block attention module(CBAM),enabling the model to focus on tree trunk features while suppressing irrelevant information,which leads to additional gains in segmentation accuracy.To enable RT-Trunk to operate effectively under diverse complex forest environments,we constructed a comprehensive dataset for training and testing by combining self-collected data with multiple public datasets covering different locations,seasons,weather conditions,tree species,and levels of forest clutter.Com-pared with the other tree trunk segmentation methods,the RT-Trunk method achieved an average precision of 91.4%and the fastest inference speed of 32.9 frames per second.Overall,the proposed RT-Trunk provides superior trunk segmentation performance that balances speed and accu-racy,making it a promising solution for supporting under-canopy UAVs in the autonomous extraction of standing tree stem attributes.The code for this work is available at https://github.com/NEFU CVRG/RT Trunk.展开更多
Tree growth synchrony serves as a valuable ecological indicator of forest resilience to climate stress and disturbances.However,our understanding of how increasing temperature affects tree growth synchrony during rapi...Tree growth synchrony serves as a valuable ecological indicator of forest resilience to climate stress and disturbances.However,our understanding of how increasing temperature affects tree growth synchrony during rapidly and slowly warming periods in ecosystems with varying climatic conditions remains limited.By using tree-ring data from temperate broadleaf(Fraxinus mandshurica,Phellodendron amurense,Quercus mongolica,and Juglans mandshurica)and Korean pine(Pinus koraiensis)mixed forests in northeast China,we investigated the effects of climate change,particularly warming,on the growth synchrony of five dominant temperate tree species across contrasting warm-dry and cool-wet climate conditions.Results show that temperature over water availability was the primary factor driving the growth and growth synchrony of the five species.Growth synchrony was significantly higher in warm-dry than in cool-wet areas,primarily due to more uniform climate conditions and higher climate sensitivity in the former.Rapid warming from the 1960s to the 1990s significantly enhanced tree growth synchrony in both areas,followed by a marked reversal as temperatures exceeded a certain threshold or warming slowed down,particularly in the warm-dry area.The growth synchrony variation patterns of the five species were highly consistent over time,although broadleaves exhibited higher synchrony than conifers,suggesting potential risks to forest resilience and stability under future climate change scenarios.Growing season temperatures and non-growing season temperatures and precipitation had a stronger positive effect on tree growth in the cool-wet area compared to the warm-dry area.High relative humidity hindered growth in the cool-wet area but enhanced it in the warm-dry area.Overall,our study highlights that the diversity and sensitivity of climate-growth relationships directly determine spatiotemporal growth synchrony.Temperature,along with water availability,shape long-term forest dynamics by affecting tree growth and synchrony.These results provide crucial insights for forest management practice to enhance structural diversity and resilience capacity against climate changeinduced synchrony shifts.展开更多
With a mixed look of both Homo erectus and Homo sapiens,Yunxian Man,who could have connected different ancestors of ours,helps unveil a stage of fast diversification in human evolution.
The Darjeeling Himalayan region,characterized by its complex topography and vulnerability to multiple environmental hazards,faces significant challenges including landslides,earthquakes,flash floods,and soil loss that...The Darjeeling Himalayan region,characterized by its complex topography and vulnerability to multiple environmental hazards,faces significant challenges including landslides,earthquakes,flash floods,and soil loss that critically threaten ecosystem stability.Among these challenges,soil erosion emerges as a silent disaster-a gradual yet relentless process whose impacts accumulate over time,progressively degrading landscape integrity and disrupting ecological sustainability.Unlike catastrophic events with immediate visibility,soil erosion’s most devastating consequences often manifest decades later through diminished agricultural productivity,habitat fragmentation,and irreversible biodiversity loss.This study developed a scalable predictive framework employing Random Forest(RF)and Gradient Boosting Tree(GBT)machine learning models to assess and map soil erosion susceptibility across the region.A comprehensive geo-database was developed incorporating 11 erosion triggering factors:slope,elevation,rainfall,drainage density,topographic wetness index,normalized difference vegetation index,curvature,soil texture,land use,geology,and aspect.A total of 2,483 historical soil erosion locations were identified and randomly divided into two sets:70%for model building and 30%for validation purposes.The models revealed distinct spatial patterns of erosion risks,with GBT classifying 60.50%of the area as very low susceptibility,while RF identified 28.92%in this category.Notable differences emerged in high-risk zone identification,with GBT highlighting 7.42%and RF indicating 2.21%as very high erosion susceptibility areas.Both models demonstrated robust predictive capabilities,with GBT achieving 80.77%accuracy and 0.975 AUC,slightly outperforming RF’s 79.67%accuracy and 0.972 AUC.Analysis of predictor variables identified elevation,slope,rainfall and NDVI as the primary factors influencing erosion susceptibility,highlighting the complex interrelationship between geo-environmental factors and erosion processes.This research offers a strategic framework for targeted conservation and sustainable land management in the fragile Himalayan region,providing valuable insights to help policymakers implement effective soil erosion mitigation strategies and support long-term environmental sustainability.展开更多
Background The full lifespan of long-lived trees includes a seedling phase,during which a seed germinates and grows to a size large enough to be measured in forest inventories.Seedling populations are usually studied ...Background The full lifespan of long-lived trees includes a seedling phase,during which a seed germinates and grows to a size large enough to be measured in forest inventories.Seedling populations are usually studied separately from adult trees,and the seedling lifespan,from seed to sapling,is poorly known.In the 50-ha Barro Colorado forest plot,we started intensive censuses of seeds and seedlings in 1994 in order to merge seedling and adult demography and document complete lifespans.Methods In 17 species abundant in seedling censuses,we subdivided populations into six size classes from seed to 1cm dbh,including seeds plus five seedling stages.The smallest seedling class was subdivided by age.Censuses in two consecutive years provided transition matrices describing the probability that a seedling in one stage moved to another one year later.For each species,we averaged the transition matrix across 25 censuses and used it to project the seedling lifespan,from seed until 1cm dbh or death.Results The predicted mean survival rate of seeds to 1cm dbh varied 1000-fold across species,from 2.9×10^(−6)to 4.4×10^(−3);the median was 2.0×10^(−4).The seedling lifespan,or the average time it takes a seed to grow to 1cm dbh,varied across species from 5.1 to 53.1 years,with a median of 20.3 years.In the median species,the 10%fastest-growing seeds would reach 1cm dbh in 9.0 years,and the slowest 10%in 34.6 years.Conclusions Combining seedling results with our previous study of lifespan after 1cm dbh,we estimate that the focal species have full lifespans varying from 41 years in a gap-demanding pioneer to 320 years in one shade-tolerant species.Lifetime demography can contribute precise survival rates and lifespans to forestry models.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
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
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
The goal of this study was to determine the spatiotemporal characteristics of mangrove distribution and fragmentation patterns from 1988 through 2019 in Dongzhaigang.Land cover datasets were generated for Dongzhaigang...The goal of this study was to determine the spatiotemporal characteristics of mangrove distribution and fragmentation patterns from 1988 through 2019 in Dongzhaigang.Land cover datasets were generated for Dongzhaigang for multiple years via a decision tree method based on a classification and regression tree(CART)algorithm using Landsat time series images.Spatiotemporal transform and fragmentation patterns of mangrove distribution were separately assessed with a transfer matrix of land cover types and a landscape pattern index.The classification method combined with multi-band images showed good accuracy,with overall accuracy higher than 90%.Mangrove areas in 1988,1999,2009,and 2019 were 2050,1875,1818,and 1750 ha,respectively,with decreases mainly due to conversion to aquaculture ponds and farmland.A mangrove growth index(MGI)was proposed,reflecting the water-mangrove relationship,showing positive mangrove growth from 1988–2009 and negative growth from 2009–2019.Study results indicated anthropogenic factors play a leading role in the extent and scale of mangrove effects over the past 30 years.According to the analysis results,corresponding management and protection measures are proposed to provide reference for the sustainable development of Dongzhaigang Mangrove Wetland ecosystem.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
[Objectives]To analyze the microbial community structure and diversity in the rhizosphere soil of peach trees in the Tangshan area of Hebei Province,identify the dominant microbial groups,and explore their potential e...[Objectives]To analyze the microbial community structure and diversity in the rhizosphere soil of peach trees in the Tangshan area of Hebei Province,identify the dominant microbial groups,and explore their potential ecological functions.[Methods]Amplification sequencing analysis of bacterial and fungal communities in the rhizosphere soil of a peach orchard in Qian'an County,Tangshan City,Hebei Province,was performed using Illumina MiSeq high-throughput sequencing technology.[Results]The indices of Sobs,Chao,ACE,and Shannon for soil bacteria in the rhizosphere soil of peach trees were all higher than those for fungi,indicating a more uniform and diverse bacterial community structure.At the phylum level,the bacteria with relatively high abundance included Pseudomonadota(28.29%),Acidobacteriota(18.10%),Bacillota(12.17%),and Actinomycetota(11.73%).In contrast,the fungi with relatively high abundance were Ascomycota(64.64%),Basidiomycota(14.22%),and Mortierellomycota(14.09%).At the genus level,the bacteria with relatively high abundance comprised Sphingomonas(5.00%),Priestia(3.38%),Nitrospira(2.05%),etc.The fungi with relatively high abundance included Fusarium(13.13%),Mortierella(12.86%),Tausonia(6.97%),Neocosmospora(4.77%),etc.[Conclusions]This study offers a foundational dataset and theoretical reference for the regulation of rhizosphere microecology and the management of soil health in peach orchards in Tangshan.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
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 Heat Island(UHI)effects are exacerbated by the expansion of impervious surfaces and loss of vegetation in urban centers,leading to elevated air and surface temperatures and reduced thermal comfort.Urban trees,th...Urban Heat Island(UHI)effects are exacerbated by the expansion of impervious surfaces and loss of vegetation in urban centers,leading to elevated air and surface temperatures and reduced thermal comfort.Urban trees,through shading and evapotranspiration,are among the most effective Nature-based Solutions(NbS)for passive cooling.This study assesses the cooling potential of selected tree species by analyzing their morphological and physiological traits using a combination of ENVI-met microclimate simulations and multiple regression modeling.A total of 15 urban tree species were selected from the literature and analyzed based on their dependency of their cooling efficacy.Later validated in urban setting by Envi-met simulations.Key traits,such as Leaf Area Index(LAI),canopy density,transpiration rate,tree height,rooting depth,and water availability,were analyzed.Multiple linear regression analysis was conducted to quantify the contribution of each trait to ambient temperature reduction.Results revealed that LAI(R^(2)=0.76,p<0.001)and transpiration rate(R^(2)=0.71,p<0.001)were the most significant predictors of daytime cooling,while canopy openness and tree height were more strongly correlated with nighttime heat dissipation.High-performing species,such as Ficus benghalensis,Azadirachta indica,and Samanea saman,demonstrated a maximum temperature reduction of 2.5-4.2℃,especially in compact,low-rise,and mid-rise zones.The study provides a quantitative trait-based framework for tree selection in urban greening initiatives and offers evidence to guide landscape planning and UHI mitigation strategies through scientifically informed plantation design.展开更多
基金Grant from LIESMARS (No.WKL(06)0302)the Basic Research Grant of CASM(No.G7721)
文摘This paper proposes a new algorithm for determining the starting points of contour lines. The new algorithm is based on the interval tree. The result improves the algorithm＇s efficiency remarkably. Further, a new strategy is designed to constrain the direction of threading and the resulting contour bears more meaningful information.
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Tree failure is an international problem,a major risk to public safety,and of growing concern because of extreme weather events.Tree biomechanics can inform the probability of tree failure,but empirical data from tropical settings are scarce.As a case study,we analyze the biomechanics(safety factor)of large heritage trees in public spaces in Indonesia.We examined critical buckling height using the Euler and Ylinen bending stress method.Tree morphometry(height,diameter at breast height,crown diameter),stability(modulus of elasticity),critical buckling height,and safety factor were quantified during this study.We found that large heritage trees in public spaces with buttresses have taller and larger morphometry and higher trunk and crown weights than small trees without buttresses.These trees are highly stable against external pressure.The presence of buttresses protects the target tree from rain and wind,resulting in a higher critical buckling height(H_(cr))of large(58.9 m)and buttressed target trees(58.8)than small(33.5 m)and unbuttressed trees(42.6 m),and a safety factor level of 68%safer.We make recommendations for selecting and managing trees in public spaces in a way that(i)can enhance wellbeing and biodiversity in urban planning,and(ii)is informed by risk to public safety.
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 in part by the National Natural Science Foundation of China(No.31470714 and 61701105).
文摘Tree trunk instance segmentation is crucial for under-canopy unmanned aerial vehicles(UAVs)to autonomously extract standing tree stem attributes.Using cameras as sensors makes these UAVs compact and lightweight,facilitating safe and flexible navigation in dense forests.However,their limited onboard computational power makes real-time,image-based tree trunk segmentation challenging,emphasizing the urgent need for lightweight and efficient segmentation models.In this study,we present RT-Trunk,a model specifically designed for real-time tree trunk instance segmentation in complex forest environments.To ensure real-time performance,we selected SparseInst as the base framework.We incorporated ConvNeXt-T as the backbone to enhance feature extraction for tree trunks,thereby improving segmentation accuracy.We further integrate the lightweight convolutional block attention module(CBAM),enabling the model to focus on tree trunk features while suppressing irrelevant information,which leads to additional gains in segmentation accuracy.To enable RT-Trunk to operate effectively under diverse complex forest environments,we constructed a comprehensive dataset for training and testing by combining self-collected data with multiple public datasets covering different locations,seasons,weather conditions,tree species,and levels of forest clutter.Com-pared with the other tree trunk segmentation methods,the RT-Trunk method achieved an average precision of 91.4%and the fastest inference speed of 32.9 frames per second.Overall,the proposed RT-Trunk provides superior trunk segmentation performance that balances speed and accu-racy,making it a promising solution for supporting under-canopy UAVs in the autonomous extraction of standing tree stem attributes.The code for this work is available at https://github.com/NEFU CVRG/RT Trunk.
基金supported by the National Natural Science Foundation of China(Nos.42107476 and 42177421)the China Postdoctoral International Exchange Fellowship Program(No.PC2021099)+1 种基金the Science and Technology Innovation Program of Hunan Province(No.2020RC2058)the China Scholarship Council(CSC,No.202206600004,to D.Yuan).
文摘Tree growth synchrony serves as a valuable ecological indicator of forest resilience to climate stress and disturbances.However,our understanding of how increasing temperature affects tree growth synchrony during rapidly and slowly warming periods in ecosystems with varying climatic conditions remains limited.By using tree-ring data from temperate broadleaf(Fraxinus mandshurica,Phellodendron amurense,Quercus mongolica,and Juglans mandshurica)and Korean pine(Pinus koraiensis)mixed forests in northeast China,we investigated the effects of climate change,particularly warming,on the growth synchrony of five dominant temperate tree species across contrasting warm-dry and cool-wet climate conditions.Results show that temperature over water availability was the primary factor driving the growth and growth synchrony of the five species.Growth synchrony was significantly higher in warm-dry than in cool-wet areas,primarily due to more uniform climate conditions and higher climate sensitivity in the former.Rapid warming from the 1960s to the 1990s significantly enhanced tree growth synchrony in both areas,followed by a marked reversal as temperatures exceeded a certain threshold or warming slowed down,particularly in the warm-dry area.The growth synchrony variation patterns of the five species were highly consistent over time,although broadleaves exhibited higher synchrony than conifers,suggesting potential risks to forest resilience and stability under future climate change scenarios.Growing season temperatures and non-growing season temperatures and precipitation had a stronger positive effect on tree growth in the cool-wet area compared to the warm-dry area.High relative humidity hindered growth in the cool-wet area but enhanced it in the warm-dry area.Overall,our study highlights that the diversity and sensitivity of climate-growth relationships directly determine spatiotemporal growth synchrony.Temperature,along with water availability,shape long-term forest dynamics by affecting tree growth and synchrony.These results provide crucial insights for forest management practice to enhance structural diversity and resilience capacity against climate changeinduced synchrony shifts.
文摘With a mixed look of both Homo erectus and Homo sapiens,Yunxian Man,who could have connected different ancestors of ours,helps unveil a stage of fast diversification in human evolution.
文摘The Darjeeling Himalayan region,characterized by its complex topography and vulnerability to multiple environmental hazards,faces significant challenges including landslides,earthquakes,flash floods,and soil loss that critically threaten ecosystem stability.Among these challenges,soil erosion emerges as a silent disaster-a gradual yet relentless process whose impacts accumulate over time,progressively degrading landscape integrity and disrupting ecological sustainability.Unlike catastrophic events with immediate visibility,soil erosion’s most devastating consequences often manifest decades later through diminished agricultural productivity,habitat fragmentation,and irreversible biodiversity loss.This study developed a scalable predictive framework employing Random Forest(RF)and Gradient Boosting Tree(GBT)machine learning models to assess and map soil erosion susceptibility across the region.A comprehensive geo-database was developed incorporating 11 erosion triggering factors:slope,elevation,rainfall,drainage density,topographic wetness index,normalized difference vegetation index,curvature,soil texture,land use,geology,and aspect.A total of 2,483 historical soil erosion locations were identified and randomly divided into two sets:70%for model building and 30%for validation purposes.The models revealed distinct spatial patterns of erosion risks,with GBT classifying 60.50%of the area as very low susceptibility,while RF identified 28.92%in this category.Notable differences emerged in high-risk zone identification,with GBT highlighting 7.42%and RF indicating 2.21%as very high erosion susceptibility areas.Both models demonstrated robust predictive capabilities,with GBT achieving 80.77%accuracy and 0.975 AUC,slightly outperforming RF’s 79.67%accuracy and 0.972 AUC.Analysis of predictor variables identified elevation,slope,rainfall and NDVI as the primary factors influencing erosion susceptibility,highlighting the complex interrelationship between geo-environmental factors and erosion processes.This research offers a strategic framework for targeted conservation and sustainable land management in the fragile Himalayan region,providing valuable insights to help policymakers implement effective soil erosion mitigation strategies and support long-term environmental sustainability.
基金funded by the Environmental Seed Arrival and Interspecific Associations in Seedling Sciences Program of the Smithsonian Institutionthe National Science Foundation (DEB-0075102,DEB-0823728,DEB-0640386,DEB-1242622,DEB-1464389)the Andrew Mellon Foundation,The Ohio State University,and Yale University
文摘Background The full lifespan of long-lived trees includes a seedling phase,during which a seed germinates and grows to a size large enough to be measured in forest inventories.Seedling populations are usually studied separately from adult trees,and the seedling lifespan,from seed to sapling,is poorly known.In the 50-ha Barro Colorado forest plot,we started intensive censuses of seeds and seedlings in 1994 in order to merge seedling and adult demography and document complete lifespans.Methods In 17 species abundant in seedling censuses,we subdivided populations into six size classes from seed to 1cm dbh,including seeds plus five seedling stages.The smallest seedling class was subdivided by age.Censuses in two consecutive years provided transition matrices describing the probability that a seedling in one stage moved to another one year later.For each species,we averaged the transition matrix across 25 censuses and used it to project the seedling lifespan,from seed until 1cm dbh or death.Results The predicted mean survival rate of seeds to 1cm dbh varied 1000-fold across species,from 2.9×10^(−6)to 4.4×10^(−3);the median was 2.0×10^(−4).The seedling lifespan,or the average time it takes a seed to grow to 1cm dbh,varied across species from 5.1 to 53.1 years,with a median of 20.3 years.In the median species,the 10%fastest-growing seeds would reach 1cm dbh in 9.0 years,and the slowest 10%in 34.6 years.Conclusions Combining seedling results with our previous study of lifespan after 1cm dbh,we estimate that the focal species have full lifespans varying from 41 years in a gap-demanding pioneer to 320 years in one shade-tolerant species.Lifetime demography can contribute precise survival rates and lifespans to forestry models.
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)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financially supported by the National Natural Science Foundation of China(Nos.U2244225 and 42020104005)the Ministry of Education of China(111 Project)the Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)and China Geological Survey(No.DD20211391)。
文摘The goal of this study was to determine the spatiotemporal characteristics of mangrove distribution and fragmentation patterns from 1988 through 2019 in Dongzhaigang.Land cover datasets were generated for Dongzhaigang for multiple years via a decision tree method based on a classification and regression tree(CART)algorithm using Landsat time series images.Spatiotemporal transform and fragmentation patterns of mangrove distribution were separately assessed with a transfer matrix of land cover types and a landscape pattern index.The classification method combined with multi-band images showed good accuracy,with overall accuracy higher than 90%.Mangrove areas in 1988,1999,2009,and 2019 were 2050,1875,1818,and 1750 ha,respectively,with decreases mainly due to conversion to aquaculture ponds and farmland.A mangrove growth index(MGI)was proposed,reflecting the water-mangrove relationship,showing positive mangrove growth from 1988–2009 and negative growth from 2009–2019.Study results indicated anthropogenic factors play a leading role in the extent and scale of mangrove effects over the past 30 years.According to the analysis results,corresponding management and protection measures are proposed to provide reference for the sustainable development of Dongzhaigang Mangrove Wetland ecosystem.
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[Objectives]To analyze the microbial community structure and diversity in the rhizosphere soil of peach trees in the Tangshan area of Hebei Province,identify the dominant microbial groups,and explore their potential ecological functions.[Methods]Amplification sequencing analysis of bacterial and fungal communities in the rhizosphere soil of a peach orchard in Qian'an County,Tangshan City,Hebei Province,was performed using Illumina MiSeq high-throughput sequencing technology.[Results]The indices of Sobs,Chao,ACE,and Shannon for soil bacteria in the rhizosphere soil of peach trees were all higher than those for fungi,indicating a more uniform and diverse bacterial community structure.At the phylum level,the bacteria with relatively high abundance included Pseudomonadota(28.29%),Acidobacteriota(18.10%),Bacillota(12.17%),and Actinomycetota(11.73%).In contrast,the fungi with relatively high abundance were Ascomycota(64.64%),Basidiomycota(14.22%),and Mortierellomycota(14.09%).At the genus level,the bacteria with relatively high abundance comprised Sphingomonas(5.00%),Priestia(3.38%),Nitrospira(2.05%),etc.The fungi with relatively high abundance included Fusarium(13.13%),Mortierella(12.86%),Tausonia(6.97%),Neocosmospora(4.77%),etc.[Conclusions]This study offers a foundational dataset and theoretical reference for the regulation of rhizosphere microecology and the management of soil health in peach orchards in Tangshan.
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.
文摘Urban Heat Island(UHI)effects are exacerbated by the expansion of impervious surfaces and loss of vegetation in urban centers,leading to elevated air and surface temperatures and reduced thermal comfort.Urban trees,through shading and evapotranspiration,are among the most effective Nature-based Solutions(NbS)for passive cooling.This study assesses the cooling potential of selected tree species by analyzing their morphological and physiological traits using a combination of ENVI-met microclimate simulations and multiple regression modeling.A total of 15 urban tree species were selected from the literature and analyzed based on their dependency of their cooling efficacy.Later validated in urban setting by Envi-met simulations.Key traits,such as Leaf Area Index(LAI),canopy density,transpiration rate,tree height,rooting depth,and water availability,were analyzed.Multiple linear regression analysis was conducted to quantify the contribution of each trait to ambient temperature reduction.Results revealed that LAI(R^(2)=0.76,p<0.001)and transpiration rate(R^(2)=0.71,p<0.001)were the most significant predictors of daytime cooling,while canopy openness and tree height were more strongly correlated with nighttime heat dissipation.High-performing species,such as Ficus benghalensis,Azadirachta indica,and Samanea saman,demonstrated a maximum temperature reduction of 2.5-4.2℃,especially in compact,low-rise,and mid-rise zones.The study provides a quantitative trait-based framework for tree selection in urban greening initiatives and offers evidence to guide landscape planning and UHI mitigation strategies through scientifically informed plantation design.
