基于FP-tree的新能源汽车产业国际竞争力影响因素关联挖掘算法

为充分挖掘新能源汽车产业国际竞争力影响因素、探究价值增长点,提出了基于FP-tree的影响因素关联挖掘算法。通过构建国际竞争力各指标影响因素的关联规则,分析任意事务数据集中的关联数据,利用最小支持度参数minsup按照从上到下的方式搜索,确定最长的频繁项目集,采用FP-tree关联频繁项目集,设定分支关联性挖掘标准,实现了新能源汽车产业国际竞争力影响因素的挖掘。测试结果表明,设计算法的最小支持度和数据关联挖掘时间较短,置信度分析具有较高的稳定性。

Risk Assessment of Deep-Water Horizontal X-Tree Installation

Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.

Remaining Useful Life Prediction Method for Multi-Component System Considering Maintenance:Subsea Christmas Tree System as A Case Study

Maintenance is an important technical measure to maintain and restore the performance status of equipment and ensure the safety of the production process in industrial production,and is an indispensable part of prediction and health management.However,most of the existing remaining useful life(RUL)prediction methods assume that there is no maintenance or only perfect maintenance during the whole life cycle;thus,the predicted RUL value of the system is obviously lower than its actual operating value.The complex environment of the system further increases the difficulty of maintenance,and its maintenance nodes and maintenance degree are limited by the construction period and working conditions,which increases the difficulty of RUL prediction.An RUL prediction method for a multi-omponent system based on the Wiener process considering maintenance is proposed.The performance degradation model of components is established by a dynamic Bayesian network as the initial model,which solves the uncertainty of insufficient data problems.Based on the experience of experts,the degree of degradation is divided according to Poisson process simulation random failure,and different maintenance strategies are used to estimate a variety of condition maintenance factors.An example of a subsea tree system is given to verify the effectiveness of the proposed method.

Parkland trees on smallholder farms ameliorate soil physical-chemical properties in the semi-arid area of Tigray,Ethiopia

Proposed agroforestry options should begin with the species that farmers are most familiar with,which would be the native multipurpose trees that have evolved under smallholder farms and socioeconomic conditions.The African birch(Anogeissus leiocarpa(DC.)Guill.&Perr.)and pink jacaranda(Stereospermum kunthianum Cham.)trees are the dominant species in the agroforestry parkland system in the drylands of Tigray,Ethiopia.Smallholder farmers highly value these trees for their multifunctional uses including timber,firewood,charcoal,medicine,etc.These trees also could improve soil fertility.However,the amount of soil physical and chemical properties enhanced by the two species must be determined to maintain the sustainable conservation of the species in the parklands and to scale up to similar agroecological systems.Hence,we selected twelve isolated trees,six from each species that had similar dendrometric characteristics and were growing in similar environmental conditions.We divided the canopy cover of each tree into three radial distances:mid-canopy,canopy edge,and canopy gap(control).At each distance,we took soil samples from three different depths.We collected 216 soil samples(half disturbed and the other half undisturbed)from each canopy position and soil depth.Bulk density(BD),soil moisture content(SMC),soil organic carbon(SOC),total nitrogen(TN),available phosphorus(AP),available potassium(AK),p H,electrical conductivity(EC),and cation exchange capacity(CEC)were analysed.Results revealed that soil physical and chemical properties significantly improved except for soil texture and EC under both species,CEC under A.leiocarpus,and soil p H under S.kunthianum,all the studied soils were improved under both species canopy as compared with canopy gap.SMC,TN,AP,and AK under canopy of these trees were respectively 24.1%,11.1%,55.0%,and 9.3% higher than those soils under control.The two parkland agroforestry species significantly enhanced soil fertility near the canopy of topsoil through improving soil physical and chemical properties.These two species were recommended in the drylands with similar agro-ecological systems.

Aging Mongolian pine plantations face high risks of drought-induced growth decline:evidence from both individual tree and forest stand measurements

Discerning vulnerability differences among different aged trees to drought-driven growth decline or to mortality is critical to implement age-specific countermeasures for forest management in water-limited areas.An important species for afforestation in dry environments of northern China,Mongolian pine(Pinus sylvestris var.mongolica Litv.)has recently exhibited growth decline and dieback on many sites,particularly pronounced in old-growth plantations.However,changes in response to drought stress by this species with age as well as the underlying mechanisms are poorly understood.In this study,tree-ring data and remotely sensed vegetation data were combined to investigate variations in growth at individual tree and stand scales for young(9-13 years)and aging(35-52 years)plantations of Mongolian pine in a water-limited area of northern China.A recent decline in tree-ring width in the older plantation also had lower values in satellited-derived normalized difference vegetation indices and normalized difference water indices relative to the younger plantations.In addition,all measured growth-related metrics were strongly correlated with the self-calibrating Palmer drought severity index during the growing season in the older plantation.Sensitivity of growth to drought of the older plantation might be attributed to more severe hydraulic limitations,as reflected by their lower sapwood-and leaf-specific hydraulic conductivities.Our study presents a comprehensive view on changes of growth with age by integrating multiple methods and provides an explanation from the perspective of plant hydraulics for growth decline with age.The results indicate that old-growth Mongolian pine plantations in water-limited environments may face increased growth declines under the context of climate warming and drying.

Improved Data Stream Clustering Method: Incorporating KD-Tree for Typicality and Eccentricity-Based Approach

Data stream clustering is integral to contemporary big data applications.However,addressing the ongoing influx of data streams efficiently and accurately remains a primary challenge in current research.This paper aims to elevate the efficiency and precision of data stream clustering,leveraging the TEDA(Typicality and Eccentricity Data Analysis)algorithm as a foundation,we introduce improvements by integrating a nearest neighbor search algorithm to enhance both the efficiency and accuracy of the algorithm.The original TEDA algorithm,grounded in the concept of“Typicality and Eccentricity Data Analytics”,represents an evolving and recursive method that requires no prior knowledge.While the algorithm autonomously creates and merges clusters as new data arrives,its efficiency is significantly hindered by the need to traverse all existing clusters upon the arrival of further data.This work presents the NS-TEDA(Neighbor Search Based Typicality and Eccentricity Data Analysis)algorithm by incorporating a KD-Tree(K-Dimensional Tree)algorithm integrated with the Scapegoat Tree.Upon arrival,this ensures that new data points interact solely with clusters in very close proximity.This significantly enhances algorithm efficiency while preventing a single data point from joining too many clusters and mitigating the merging of clusters with high overlap to some extent.We apply the NS-TEDA algorithm to several well-known datasets,comparing its performance with other data stream clustering algorithms and the original TEDA algorithm.The results demonstrate that the proposed algorithm achieves higher accuracy,and its runtime exhibits almost linear dependence on the volume of data,making it more suitable for large-scale data stream analysis research.

Rising utilization of stable isotopes in tree rings for climate change and forest ecology

Analyses of stable isotopes(C,O,H)in tree rings are increasingly important cross-disciplinary programs.The rapid development in this field documented in an increasing number of publications requires a comprehensive review.This study includes a bibliometric analysis-based review to better understand research trends in tree ring stable isotope research.Overall,1475 publications were selected from the Web of Science Core Collection for 1974-2023.The findings are that:(1)numbers of annual publications and citations increased since 1974.From 1974 to 1980,there were around two relevant publications per year.However,from 2020 to 2022,this rose sharply to 109 publications per year.Likewise,average article citations were less than four per year before 1990,but were around four per article per year after 2000;(2)the major subjects using tree ring stable isotopes include forestry,geosciences,and environmental sciences,contributing to 42.5%of the total during 1974-2023;(3)the top three most productive institutions are the Chinese Academy of Sciences(423),the Swiss Federal Institute for Forest,Snow and Landscape Research(227),and the University of Arizona(204).These achievements result from strong collaborations;(4)review papers,for example,(Dawson et al.,Annu Rev Ecol Syst 33:507-559,2002)and(McCarroll and Loader,Quat Sci Rev 23:771-801,2004),are among the most cited,with more than 1000 citations;(5)tree ring stable isotope studies mainly focus on climatology and ecology,with atmospheric CO_(2) one of the most popular topics.Since 2010,precipitation and drought have received increasing attention.Based on this analysis,the research stages,key findings,debated issues,limitations and direc-tions for future research are summarized.This study serves as an important attempt to understand the progress on the use of stable isotopes in tree rings,providing scientific guid-ance for young researchers in this field.

Ecological network analysis reveals complex responses of tree species life stage interactions to stand variables

Tree interactions are essential for the structure,dynamics,and function of forest ecosystems,but variations in the architecture of life-stage interaction networks(LSINs)across forests is unclear.Here,we constructed 16 LSINs in the mountainous forests of northwest Hebei,China based on crown overlap from four mixed forests with two dominant tree species.Our results show that LSINs decrease the complexity of stand densities and basal areas due to the interaction cluster differentiation.In addition,we found that mature trees and saplings play different roles,the first acting as“hub”life stages with high connectivity and the second,as“bridges”controlling information flow with high centrality.Across the forests,life stages with higher importance showed better parameter stability within LSINs.These results reveal that the structure of tree interactions among life stages is highly related to stand variables.Our efforts contribute to the understanding of LSIN complexity and provide a basis for further research on tree interactions in complex forest communities.

Comprehensive analyses of the proteome and ubiquitome revealed mechanism of high temperature accelerating petal abscission in tree peony

Tree peony(Paeonia suffruticosa Andrews)is a well-known ornamental plant with high economic value,but the short fluorescence is a key obstacle to its ornamental value and industry development.High temperature accelerates flower senescence and abscission,but the associated mechanisms are poorly understood.In this study,the tandem mass tag(TMT)proteome and label-free quantitative ubiquitome from tree peony cut flowers treated with 20℃for 0 h(RT0),20℃or 28℃for 60 h(RT60 or HT60)were examined based on morphological observation,respectively.Totally,6970 proteins and 1545 lysine ubiquitinated(Kub)sites in 844 proteins were identified.Hydrophilic residues(such as glutamate and aspartate)neighboring the Kub sites were in preference,and 36.01%of the Kub sites were located on the protein surface.The differentially expressed proteins(DEPs)and Kub-DEPs in HT60 vs RT60 were mainly enriched in ribosomal protein,protein biosynthesis,secondary metabolites biosynthesis,flavonoid metabolism,carbohydrate catabolism,and auxin biosynthesis and signaling revealed by GO and KEGG analysis,accompanying the increase of endogenous abscisic acid(ABA)accumulation and decrease of endogenous indoleacetic acid(IAA)level.Additionally,the expression patterns of six enzymes(SAMS,ACO,YUC,CHS,ANS and PFK)putatively with Kub modifications were analyzed by proteome and real-time quantitative RT-PCR.The cell-free degradation assays showed PsSAMS and PsACO proteins could be degraded via the 26 S proteasome system in tree peony flowers.Finally,a working model was proposed for the acceleration of flower senescence and abscission by high temperature.In summary,all results contributed to understanding the mechanism of flower senescence induced by high temperature and prolonging fluorescence in tree peony.

Role of outdoor trees on pedestrian wind and thermal conditions around a pre-education building for sustainable energy management

Finding sustainable energy resources is essential to face the increasing energy demand.Trees are an important part of ancient architecture but are becoming rare in urban areas.Trees can control and tune the pedestrian-level wind velocity and thermal condition.In this study,a numerical investigation is employed to assess the role of trees planted in the windward direction of the building complex on the thermal and pedestrian wind velocity conditions around/inside a pre-education building located in the center of the complex.Compared to the previous studies(which considered only outside buildings),this work considers the effects of trees on microclimate change both inside/outside buildings.Effects of different parameters including the leaf area density and number of trees,number of rows,far-field velocity magnitude,and thermal condition around the main building are assessed.The results show that the flow velocity in the spacing between the first-row buildings is reduced by 30%-40% when the one-row trees with 2 m height are planted 15 m farther than the buildings.Furthermore,two rows of trees are more effective in higher velocities and reduce the maximum velocity by about 50%.The investigation shows that trees also could reduce the temperature by about 1℃around the building.

More tree growth reduction due to consecutive drought and its legacy effect for a semiarid larch plantation in Northwest China

Extreme climate has increasingly led to negative impacts on forest ecosystems globally,especially in semiarid areas where forest ecosystems are more vulnerable.However,it is poorly understood how tree growth is affected by different drought events.In 2006–2009,the larch plantations in the semiarid areas of Northwest China were negatively affected by four consecutive dry years,which was a very rare phenomenon that may occur frequently under future climate warming.In this study,we analyzed the effect of these consecutive dry years on tree growth based on the data of the tree rings in the dominant layer of the forest canopy on a larch plantation.We found that the tree-ring width index(RWI)in dry years was lower than that in normal years,and it experienced a rapidly decreasing trend from 2006 to 2009(slope=-0.139 year^(-1),r=-0.94)due to water supply deficits in those dry years.Drought induced legacy effects of tree growth reduction,and consecutive dry years corresponded with greater growth reductions and legacy effects.Growth reductions and legacy effects were significantly stronger in the third and fourth consecutive dry years than that of single dry year(p<0.05),which might have been due to the cumulative stress caused by consecutive dry years.Our results showed that larch trees experienced greater tree growth reduction due to consecutive dry years and their legacy effect,and the trees had lower recovery rates after consecutive dry years.Our results highlight that consecutive dry years pose a new threat to plantations under climate warming,and thus,the effect of climate extremes on tree growth should be considered in growth models in semiarid areas.

Physics-Constrained Robustness Enhancement for Tree Ensembles Applied in Smart Grid

With the widespread use of machine learning(ML)technology,the operational efficiency and responsiveness of power grids have been significantly enhanced,allowing smart grids to achieve high levels of automation and intelligence.However,tree ensemble models commonly used in smart grids are vulnerable to adversarial attacks,making it urgent to enhance their robustness.To address this,we propose a robustness enhancement method that incorporates physical constraints into the node-splitting decisions of tree ensembles.Our algorithm improves robustness by developing a dataset of adversarial examples that comply with physical laws,ensuring training data accurately reflects possible attack scenarios while adhering to physical rules.In our experiments,the proposed method increased robustness against adversarial attacks by 100%when applied to real grid data under physical constraints.These results highlight the advantages of our method in maintaining efficient and secure operation of smart grids under adversarial conditions.

Exploring Trees Diversity and Ecological Value of Mountain Forests in the Blue Nile Region of Sudan

We carried out this research at Abu-Gaddaf Natural Forest Reserve (ANFR) which is located east of Blue Nile River, in Blue Nile State, Sudan. It aims at exploring tree composition assessing their diversity indices, and ecological importance values. For survey of types and estimation of density of tree species in the forest, we randomly distributed 97 circular sample plots (0.1 hectare (ha)). In each sample plot we identified all trees to the species level, recorded their frequencies and computed species diversity and importance value indices (IVI). A total of 13 tree species, which belong to 12 genera and nine families, were identified in the tree layer of the forest. Mean tree density in ANFR was 116 trees/ha, composed mainly of Boswellia papyrifera (Del.) Hochst. (48), followed by Combretum hartmannianu (19) and Lannea fruticosa (18). Fabaceae was the most common family followed by Combretaceae and Malvaceae. B. papyrifera Delile Hochst was the most abundant while Acacia seyal was the least abundant species. Species richness (R = 1.71), evenness (E = 0.69), dominance (0.24) indices and Simpson’s Index of Diversity (D' = 0.76) suggest a moderate diversity, moderate numbers of individuals in each species and a moderate community stability. The research provides empirical results on diversity and ecological importance value of species, signifies the urging need to safeguard threatened species and to prioritize them for conservation, as well as the need to promote management of abundant species to provide multiple forest ecosystem services.

Human-like adrenal features in Chinese tree shrews revealed by multi-omics analysis of adrenal cell populations and steroid synthesis

The Chinese tree shrew(Tupaia belangeri chinensis)has emerged as a promising model for investigating adrenal steroid synthesis,but it is unclear whether the same cells produce steroid hormones and whether their production is regulated in the same way as in humans.Here,we comprehensively mapped the cell types and pathways of steroid metabolism in the adrenal gland of Chinese tree shrews using single-cell RNA sequencing,spatial transcriptome analysis,mass spectrometry,and immunohistochemistry.We compared the transcriptomes of various adrenal cell types across tree shrews,humans,macaques,and mice.Results showed that tree shrew adrenal glands expressed many of the same key enzymes for steroid synthesis as humans,including CYP11B2,CYP11B1,CYB5A,and CHGA.Biochemical analysis confirmed the production of aldosterone,cortisol,and dehydroepiandrosterone but not dehydroepiandrosterone sulfate in the tree shrew adrenal glands.Furthermore,genes in adrenal cell types in tree shrews were correlated with genetic risk factors for polycystic ovary syndrome,primary aldosteronism,hypertension,and related disorders in humans based on genome-wide association studies.Overall,this study suggests that the adrenal glands of Chinese tree shrews may consist of closely related cell populations with functional similarity to those of the human adrenal gland.Our comprehensive results(publicly available at http://gxmujyzmolab.cn:16245/scAGMap/)should facilitate the advancement of this animal model for the investigation of adrenal gland disorders.

Study of tree shrew biology and models: A booming and prosperous field for biomedical research

The tree shrew(Tupaia belangeri)has long been proposed as a suitable alternative to non-human primates(NHPs)in biomedical and laboratory research due to its close evolutionary relationship with primates.In recent years,significant advances have facilitated tree shrew studies,including the determination of the tree shrew genome,genetic manipulation using spermatogonial stem cells,viral vector-mediated gene delivery,and mapping of the tree shrew brain atlas.However,the limited availability of tree shrews globally remains a substantial challenge in the field.Additionally,determining the key questions best answered using tree shrews constitutes another difficulty.Tree shrew models have historically been used to study hepatitis B virus(HBV)and hepatitis C virus(HCV)infection,myopia,and psychosocial stress-induced depression,with more recent studies focusing on developing animal models for infectious and neurodegenerative diseases.Despite these efforts,the impact of tree shrew models has not yet matched that of rodent or NHP models in biomedical research.This review summarizes the prominent advancements in tree shrew research and reflects on the key biological questions addressed using this model.We emphasize that intensive dedication and robust international collaboration are essential for achieving breakthroughs in tree shrew studies.The use of tree shrews as a unique resource is expected to gain considerable attention with the application of advanced techniques and the development of viable animal models,meeting the increasing demands of life science and biomedical research.

Enhancing PDF Malware Detection through Logistic Model Trees

Malware is an ever-present and dynamic threat to networks and computer systems in cybersecurity,and because of its complexity and evasiveness,it is challenging to identify using traditional signature-based detection approaches.The study article discusses the growing danger to cybersecurity that malware hidden in PDF files poses,highlighting the shortcomings of conventional detection techniques and the difficulties presented by adversarial methodologies.The article presents a new method that improves PDF virus detection by using document analysis and a Logistic Model Tree.Using a dataset from the Canadian Institute for Cybersecurity,a comparative analysis is carried out with well-known machine learning models,such as Credal Decision Tree,Naïve Bayes,Average One Dependency Estimator,Locally Weighted Learning,and Stochastic Gradient Descent.Beyond traditional structural and JavaScript-centric PDF analysis,the research makes a substantial contribution to the area by boosting precision and resilience in malware detection.The use of Logistic Model Tree,a thorough feature selection approach,and increased focus on PDF file attributes all contribute to the efficiency of PDF virus detection.The paper emphasizes Logistic Model Tree’s critical role in tackling increasing cybersecurity threats and proposes a viable answer to practical issues in the sector.The results reveal that the Logistic Model Tree is superior,with improved accuracy of 97.46%when compared to benchmark models,demonstrating its usefulness in addressing the ever-changing threat landscape.

Stress-assisted corrosion mechanism of 3Ni steel by using gradient boosting decision tree machining learning method

Traditional 3Ni weathering steel cannot completely meet the requirements for offshore engineering development,resulting in the design of novel 3Ni steel with the addition of microalloy elements such as Mn or Nb for strength enhancement becoming a trend.The stress-assisted corrosion behavior of a novel designed high-strength 3Ni steel was investigated in the current study using the corrosion big data method.The information on the corrosion process was recorded using the galvanic corrosion current monitoring method.The gradi-ent boosting decision tree(GBDT)machine learning method was used to mine the corrosion mechanism,and the importance of the struc-ture factor was investigated.Field exposure tests were conducted to verify the calculated results using the GBDT method.Results indic-ated that the GBDT method can be effectively used to study the influence of structural factors on the corrosion process of 3Ni steel.Dif-ferent mechanisms for the addition of Mn and Cu to the stress-assisted corrosion of 3Ni steel suggested that Mn and Cu have no obvious effect on the corrosion rate of non-stressed 3Ni steel during the early stage of corrosion.When the corrosion reached a stable state,the in-crease in Mn element content increased the corrosion rate of 3Ni steel,while Cu reduced this rate.In the presence of stress,the increase in Mn element content and Cu addition can inhibit the corrosion process.The corrosion law of outdoor-exposed 3Ni steel is consistent with the law based on corrosion big data technology,verifying the reliability of the big data evaluation method and data prediction model selection.

Stability assessment of tree ring growth of Pinus armandii Franch in response to climate change based on slope directions at the Lubanling in the Funiu Mountains,China

Global warming will affect growth strategies and how trees will adapt.To compare the response of tree radial growth to climate warming in different slope directions,samples of Pinus armandii Franch were collected and tree-ring chronologies developed on northern and western slopes from the Lubanling in the Funiu Mountains.Correlation analyses showed that two chronologies were mainly limited by temperatures in the previous June-August and the com-bination of temperatures and moisture in the current May-July.The difference of the climate response to slopes was small but not negligible.Radial growth of the LBLO1 site on the northern slope was affected by the combined maximum and minimum temperatures,while that of the LBLO2 site was affected by maximum temperatures.With regards to moisture,radial growth of the trees on the north slope was influenced by the relative humidity in the current May-July,while on the western slope,it was affected by the relative humidity in the previous June-August,the current May-July and the precipitation in the current May-July.With the change in climate,the effects of the main limiting factors on growth on different slopes were visible to a certain extent,but the differences in response of trees on different slopes gradually decreased,which might be caused by factors such as different slope directions and the change in diurnal temperature range.These results may provide information for forest protection and ecological construction in this region,and a scientific reference for future climate reconstruction.

Stability assessment of tree ring growth of Pinus armandii Franch in response to climate change based on slope directions at the Lubanling in the Funiu Mountains,China

Global warming will affect growth strategies and how trees will adapt.To compare the response of tree radial growth to climate warming in different slope directions,samples of Pinus armandii Franch were collected and treering chronologies developed on northern and western slopes from the Lubanling in the Funiu Mountains.Correlation analyses showed that two chronologies were mainly limited by temperatures in the previous June–August and the combination of temperatures and moisture in the current May–July.The difference of the climate response to slopes was small but not negligible.Radial growth of the LBL01 site on the northern slope was affected by the combined maximum and minimum temperatures,while that of the LBL02 site was affected by maximum temperatures.With regards to moisture,radial growth of the trees on the north slope was influenced by the relative humidity in the current May–July,while on the western slope,it was affected by the relative humidity in the previous June–August,the current May–July and the precipitation in the current May–July.With the change in climate,the effects of the main limiting factors on growth on different slopes were visible to a certain extent,but the differences in response of trees on different slopes gradually decreased,which might be caused by factors such as different slope directions and the change in diurnal temperature range.These results may provide information for forest protection and ecological construction in this region,and a scientific reference for future climate reconstruction.

Seedling potential of trees species along the elevational gradient in temperate hill forest of central Nepal

Regeneration status of tree species along elevation gradient in temperate hill forest was not understood greatly.Present research examined the tree diversity and its regeneration patterns along an elevation gradient in temperate hill forest,central Nepal.Data were collected from 300 sample plots within vertical elevation bands of 10,ranging from 1365 to 2450 m asl.A random sampling method was used for data collection in three seasons,winter,pre-monsoon and post monsoon seasons.Diameter at breast height(DBH)was used to broadly categorize the plant individual into trees,saplings and seedlings.The tree species richness ranged from 12 to 25 with density of 350 to 1200 individuals per hectare.Species richness of tree and sapling showed statistically significant unimodal pattern,which peaked at mid-elevation.Elevation showed a strong and positive linear correlation with the seedling density(Deviance=0.99,p<0.001)and a significant hump-shaped relationship with sapling density(Deviance=0.95,p<0.001).Similarly,elevations showed a statistically significant negative hump-shaped relationship with all trees,saplings and seedling stages(Deviances=0.89,0.87 and 0.57).The highest values of the Shannon-Wiener index and the lowest value of the Simpson index were found at mid-elevation for all growth forms.Nearly 92%of tree species were found at regenerating stage;49%in a good renewal regeneration status,32%in fair renewal regeneration,and 11%at a poor regenerating condition.Nevertheless,4%of tree species were reported as non-regenerating stages and 4%were newly introduced species.Hence,the regeneration status of the study area was considered fairly well since sapling(78.5%)>seedling(10.6%)≤mature(10.9%).Among tested environmental variables,elevation and annual mean rainfall were the most influential factors in the regeneration of tree species.