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This paper proposes a new meta-heuristic optimization algorithm, the crown growth optimizer (CGO), inspired by the tree crown growth process. CGO innovatively combines global search and local optimization strategies by simulating the growing, sprouting, and pruning mechanisms in tree crown growth. The pruning mechanism balances the exploration and exploitation of the two stages of growing and sprouting, inspired by Ludvig's law and the Fibonacci series. We performed a comprehensive performance evaluation of CGO on the standard testbed CEC2017 and the real-world problem set CEC2020-RW and compared it to a variety of mainstream algorithms such as SMA, SKA, DBO, GWO, MVO, HHO, WOA, EWOA, and AVOA. The best result of CGO after Friedman testing was 1.6333/10, and the significance level of all comparison results under Wilcoxon testing was lower than 0.05. The experimental results show that the mean and standard deviation of repeated CGO experiments are better than those of the comparison algorithm. In addition, CGO also achieved excellent results in specific applications of robot path planning and photovoltaic parameter extraction, further verifying its effectiveness and broad application potential in practical engineering problems. [ABSTRACT FROM AUTHOR]

This paper introduces a novel method for accurately calculating the upper biomass of single trees using Light Detection and Ranging (LiDAR) point cloud data. The proposed algorithm involves classifying the tree point cloud into two distinct ones: the trunk point cloud and the crown point cloud. Each part is then processed using specific techniques to create a 3D model and determine its volume. The trunk point cloud is segmented based on individual stems, each of which is further divided into slices that are modeled as cylinders. On the other hand, the crown point cloud is analyzed by calculating its footprint and gravity center. The footprint is further divided into angular sectors, with each being used to create a rotating surface around the vertical line passing through the gravity center. All models are represented in a matrix format, simplifying the process of minimizing and calculating the tree's upper biomass, consisting of crown biomass and trunk biomass. To validate the proposed approach, both terrestrial and airborne datasets are utilized. A comparison with existing algorithms in the literature confirms the effectiveness of the new method. For a tree dimensions estimation, the study shows that the proposed algorithm achieves an average fit between 0.01 m and 0.49 m for individual trees. The maximum absolute quantitative accuracy equals 0.49 m, and the maximum relative absolute error equals 0.29%. [ABSTRACT FROM AUTHOR]

Abstract Forest above‐ground biomass (AGB) is often estimated by converting the observed tree size using allometric scaling between the dry weight and size of an organism. However, the variations in biomass allocation and scaling between tree crowns and stems due to survival competition during a tree's lifecycle remain unclear. This knowledge gap can improve the understanding of modelling tree biomass allometry because traditional allometries ignore the dynamics of allocation. Herein, we characterised allometric scaling using the dynamic ratio (r) of the stem biomass (SB) to AGB and a dynamic exponent. The allometric models were biologically parameterised by the r values for initial, intermediate and final ages rather than only a regression result. The scaling was tested using field measurements of 421 species and 2213 different‐sized trees in pantropical regions worldwide. We found that the scaling fluctuated with tree size, and this fluctuation was driven by the trade‐off relationship of biomass allocation between the tree crown and stem depending on the dynamic crown trait. The allometric scaling between SB and AGB varied from 0.8 to 1.0 for a tree during its entire lifecycle. The fluctuations presented a general law for the allometric scaling of the pantropical tree biomass and size. Our model quantified the trade‐off and explained 94.1% of the allometric relationship between the SB and AGB (93.8% of which between D2H and AGB) for pantropical forests, which resulted in a better fit than that of the traditional model. Considering the effects of the trade‐off on modelling, the actual biomass of large trees could be substantially greater than conventional estimates. These results highlight the importance of coupling growth mechanisms in modelling allometry and provide a theoretical foundation for better describing and predicting forest carbon accumulation.

Forest above‐ground biomass (AGB) is often estimated by converting the observed tree size using allometric scaling between the dry weight and size of an organism. However, the variations in biomass allocation and scaling between tree crowns and stems due to survival competition during a tree's lifecycle remain unclear. This knowledge gap can improve the understanding of modelling tree biomass allometry because traditional allometries ignore the dynamics of allocation.Herein, we characterised allometric scaling using the dynamic ratio (r) of the stem biomass (SB) to AGB and a dynamic exponent. The allometric models were biologically parameterised by the r values for initial, intermediate and final ages rather than only a regression result. The scaling was tested using field measurements of 421 species and 2213 different‐sized trees in pantropical regions worldwide.We found that the scaling fluctuated with tree size, and this fluctuation was driven by the trade‐off relationship of biomass allocation between the tree crown and stem depending on the dynamic crown trait. The allometric scaling between SB and AGB varied from 0.8 to 1.0 for a tree during its entire lifecycle. The fluctuations presented a general law for the allometric scaling of the pantropical tree biomass and size. Our model quantified the trade‐off and explained 94.1% of the allometric relationship between the SB and AGB (93.8% of which between D2H and AGB) for pantropical forests, which resulted in a better fit than that of the traditional model. Considering the effects of the trade‐off on modelling, the actual biomass of large trees could be substantially greater than conventional estimates.These results highlight the importance of coupling growth mechanisms in modelling allometry and provide a theoretical foundation for better describing and predicting forest carbon accumulation. [ABSTRACT FROM AUTHOR]

Purpose: The passive accumulation of silicon (Si) generally depends on the regulation of plant transpiration rates after its uptake. It is challenging to comprehend how plants use Si to adapt to shady habitats where they have low transpiration rates and photothermal energy. Therefore, we speculated that Si accumulation is not entirely dependent on the transpiration rate. Methods: To test this speculation, the concentrations of Si and total minerals and water status at various positions of shady shoots (stems and their foliage) and stems within the crown of Juniperus chinensis L. were examined to determine whether shady shoots or stems had a preferred allocation to resist shade. Results: The concentrations of total minerals and Si in the shoots were consistently higher in shady areas than in areas within the same crown, regardless of the position within the crown or shoot age. However, shoot Si accumulation displayed a greater dependence on available light or photothermal supply, which is linked to crown orientation. Additionally, stem Si accumulation displayed a weak dependence on available light. Compared with the bound water content, the water potential and free water content of shady shoots were higher than those of sunny shoots. In light of the fact that water prefers to move readily towards regions with low water potential, these results demonstrate that the movement of minerals and water is not fully coupled in the same crowns. Conclusion: Therefore, the accumulation of Si and minerals in shady foliage is partially independent of water flow, which helps to offset the low-carbon supply due to the photothermal decrease in the shady crown area. [ABSTRACT FROM AUTHOR]

Somatic mutations potentially play a role in plant evolution, but common expectations pertaining to plant somatic mutations remain insufficiently tested. Unlike in most animals, the plant germline is assumed to be set aside late in development, leading to the expectation that plants accumulate somatic mutations along growth. Therefore, several predictions were made on the fate of somatic mutations: mutations have generally low frequency in plant tissues; mutations at high frequency have a higher chance of intergenerational transmission; branching topology of the tree dictates mutation distribution; and exposure to UV (ultraviolet) radiation increases mutagenesis. To provide insights into mutation accumulation and transmission in plants, we produced two high-quality reference genomes and a unique dataset of 60 high-coverage whole-genome sequences of two tropical tree species, Dicorynia guianensis (Fabaceae) and Sextonia rubra (Lauraceae). We identified 15,066 de novo somatic mutations in D. guianensis and 3,208 in S. rubra, surprisingly almost all found at low frequency. We demonstrate that 1) low-frequency mutations can be transmitted to the next generation; 2) mutation phylogenies deviate from the branching topology of the tree; and 3) mutation rates and mutation spectra are not demonstrably affected by differences in UV exposure. Altogether, our results suggest far more complex links between plant growth, aging, UV exposure, and mutation rates than commonly thought. [ABSTRACT FROM AUTHOR]

Despite intensive studies on plant functional traits, the intraspecific variation and their co-variation at the multi-scale remains poorly studied, which holds the potential to unveil plant responses to changing environmental conditions. In this study, intraspecific variations of 16 leaf functional traits of a common fig species, Ficus tinctoria G. Frost. , were investigated in relation to different scales: habitat types (hemiepiphytic and terrestrial), growth stages (small, medium and large) and tree crown positions (upper, middle and lower) in Xishuangbanna, Southwest China. Remarkable intraspecific variation was observed in leaf functional traits, which was mainly influenced by tree crown position, growth stage and their interaction. Stable nitrogen isotope (δ15N) and leaf area (LA) showed large variations, while stable carbon isotope (δ13C), stomata width and leaf water content showed relatively small variations, suggesting that light- and nitrogen-use strategies of F. tinctoria were plastic, while the water-use strategies have relatively low plasticity. The crown layers are formed with the growth of figs, and leaves in the lower crown increase their chlorophyll concentration and LA to improve the light energy conversion efficiency and the ability to capture weak light. Meanwhile, leaves in the upper crown increase the water-use efficiency to maintain their carbon assimilation. Moreover, hemiepiphytic medium (transitional stage) and large (free-standing stage) figs exhibited more significant trait differentiation (chlorophyll concentration, δ13C, stomata density, etc.) within the crown positions, and stronger trait co-variation compared with their terrestrial counterparts. This pattern demonstrates their acclimation to the changing microhabitats formed by their hemiepiphytic life history. Our study emphasizes the importance of multi-scaled intraspecific variation and co-variation in trait-based strategies of hemiepiphyte and terrestrial F. tinctoria , which facilitate them to cope with different environmental conditions. [ABSTRACT FROM AUTHOR]

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Tree stability relies on the characteristics of both root and crown structures. However, studying root systems is challenging due to their underground location, often requiring destructive methods for assessment. Non-destructive approaches offer potential solutions, such as the root detector tool. However, research in this area remains limited and requires further development. This study aims to evaluate the root detector tool by inspecting the radial root distribution in trees with different tree crown shapes, both excurrent (Agathis loranthifolia) and decurrent (Samanea saman), which grow in various soil slopes and soil slope positions. In addition, we establish correlations between tree morphometry, the physical properties of soil, root attributes, sound wave velocity, and their relationship. Based on the results, it was found that the root detector tool is effective in evaluating root distribution, including identifying the main root. The slope position of the tree in a slope class influences the radial distribution of the main roots. This is related to the crown growth as indicated by the direction of its crown. Principal Component Analysis (PCA) findings suggest that parameter morphometric and soil and root properties data clustering align with slope position rather than slope class. [ABSTRACT FROM AUTHOR]

This paper proposes a new meta-heuristic optimization algorithm, the crown growth optimizer (CGO), inspired by the tree crown growth process. CGO innovatively combines global search and local optimization strategies by simulating the growing, sprouting, and pruning mechanisms in tree crown growth. The pruning mechanism balances the exploration and exploitation of the two stages of growing and sprouting, inspired by Ludvig’s law and the Fibonacci series. We performed a comprehensive performance evaluation of CGO on the standard testbed CEC2017 and the real-world problem set CEC2020-RW and compared it to a variety of mainstream algorithms such as SMA, SKA, DBO, GWO, MVO, HHO, WOA, EWOA, and AVOA. The best result of CGO after Friedman testing was 1.6333/10, and the significance level of all comparison results under Wilcoxon testing was lower than 0.05. The experimental results show that the mean and standard deviation of repeated CGO experiments are better than those of the comparison algorithm. In addition, CGO also achieved excellent results in specific applications of robot path planning and photovoltaic parameter extraction, further verifying its effectiveness and broad application potential in practical engineering problems.

This paper introduces a novel method for accurately calculating the upper biomass of single trees using Light Detection and Ranging (LiDAR) point cloud data. The proposed algorithm involves classifying the tree point cloud into two distinct ones: the trunk point cloud and the crown point cloud. Each part is then processed using specific techniques to create a 3D model and determine its volume. The trunk point cloud is segmented based on individual stems, each of which is further divided into slices that are modeled as cylinders. On the other hand, the crown point cloud is analyzed by calculating its footprint and gravity center. The footprint is further divided into angular sectors, with each being used to create a rotating surface around the vertical line passing through the gravity center. All models are represented in a matrix format, simplifying the process of minimizing and calculating the tree’s upper biomass, consisting of crown biomass and trunk biomass. To validate the proposed approach, both terrestrial and airborne datasets are utilized. A comparison with existing algorithms in the literature confirms the effectiveness of the new method. For a tree dimensions estimation, the study shows that the proposed algorithm achieves an average fit between 0.01 m and 0.49 m for individual trees. The maximum absolute quantitative accuracy equals 0.49 m, and the maximum relative absolute error equals 0.29%.

Striving for climate neutrality and wider implementation of climate change mitigation measures including tree introduction in agricultural land, request for approaches and general allometric models for estimating carbon (C) stock in tree above-ground biomass (AGB) based on relatively easily obtainable remote sensing data is increasing. Here, we present estimates of individual trees' crown diameters (CDs) for Betula pendula Roth (B. pendula) and Populus tremuloides Michx. × Populus tremula L. (P. tremuloides × P. tremula) in 11-year-old tree plantations (tree height ranged up to 12.8 and 18.1 m, respectively) in the hemiboreal region of Europe (in Latvia). Individual trees' CDs were measured using a drone orthophoto map. Afterwards, linear equations were developed to predict individual trees' stem diameters at breast height (DBHs) and, consequently, tree AGB (which was then converted to C stock) from remote-sensed tree CD data. RMSEs of the prediction models of tree stem DBH were in the ranges of 1.87–2.12 cm for B. pendula and 2.50–3.12 cm for P. tremuloides × P. tremula. This demonstrated approach is applicable to carry out, for instance, a self-assessment and approximate C stock in the AGB of selected tree species by land owners, managers, and other implementers of climate change mitigation measures. [ABSTRACT FROM AUTHOR]

The aim of this study is to explore light conditions under tree canopies and develop a logistic regression model based on the canopy structure of three forest trails in Buddhist temples located within the Gajisan Provincial Park of South Korea. Canopy structure variables related to light conditions under the canopy, including canopy openness, leaf area index, and solar radiation transmittance, were measured by digital hemispherical photography. Each point of photography, along with the center of the forest trail, had a gap distance of approximately 50 m. The characteristics of the canopy structure were expressed as 21% canopy openness, 1.79 m2m-2 of leaf area index, and 29% solar radiation transmittance. The logistic regression model showed that there were significant effects of canopy factors in identifying Naewonsa temple against Seongnamsa temple. The model implied that the canopy structure of Naewonsa temple had a more center-concentrated canopy density with upright leaves, compared to those of Seongnamsa temple. Effective ways of using the forest trails of Buddhist temples were suggested regarding forest ecology and environmental management for the purpose of healing and ecotourism. [ABSTRACT FROM AUTHOR]

The study of the leafmining moth of the chestnut miner (Cameraria ohridella Deschka & Dymić, 1986) was carried out through the planting of the common horse chestnut (Aesculus hippocastanum L.) in the Main Botanical Garden of the Russian Academy of Sciences. The effect of various degrees of insolation of horse chestnut plants on leaf morphology and the composition of secondary metabolites, as well as the relationship of these parameters with the number and density of C. ohridella populations during the growing season, was studied. The solar influence, it was noted, had a significant impact. Thus, the largest number of the pests was recorded on the leaves of the sunlit side of the tree crown, and the smallest on the leaves of the shady part of the crown. The low content of polyphenols in the pool of secondary metabolites in the tissues of the A. hippocastanum leaves did not deter C. ohridella and poorly protected the plants from this miner, while the significant content of carbohydrates in the leaves reduced the resistance of chestnut plants to damage by the Ohrid leaf miner. [ABSTRACT FROM AUTHOR]

Conventional methods in measuring tree height and crown diameter are time consuming compared to the advanced technology of unmanned aerial vehicle (UAV) multispectral imagery. UAV multispectral imagery is widely used in vegetation analysis such as crop analysis, vegetation monitoring, precise farming and vegetation health assessment. Thus, the purpose of this research is to extract the individual tree height and crown diameter from UAV-based multispectral imagery using the integration of geospatial techniques. Altogether, the total of 395 individual trees were extracted from the study area of Section U11, Shah Alam using the Support Vector Machine (SVM) classifier. Tree height values were extracted from normalized digital surface model (nDSM) using the zonal statistics tool with the tree height range between 1.568m to 27.850m. The range for derived crown diameters is between 0.919m to 24.506m. The final map shows the distribution of tree height and tree crown extraction from the UAV-based multispectral imagery. The spatial distribution data of tree height and crown diameter are beneficial especially in landscaping and identifying the potential of tree hazard in the urban area. [ABSTRACT FROM AUTHOR]

Tree stability relies on the characteristics of both root and crown structures. However, studying root systems is challenging due to their underground location, often requiring destructive methods for assessment. Non-destructive approaches offer potential solutions, such as the root detector tool. However, research in this area remains limited and requires further development. This study aims to evaluate the root detector tool by inspecting the radial root distribution in trees with different tree crown shapes, both excurrent (Agathis loranthifolia) and decurrent (Samanea saman), which grow in various soil slopes and soil slope positions. In addition, we establish correlations between tree morphometry, the physical properties of soil, root attributes, sound wave velocity, and their relationship. Based on the results, it was found that the root detector tool is effective in evaluating root distribution, including identifying the main root. The slope position of the tree in a slope class influences the radial distribution of the main roots. This is related to the crown growth as indicated by the direction of its crown. Principal Component Analysis (PCA) findings suggest that parameter morphometric and soil and root properties data clustering align with slope position rather than slope class.

The root system is important for supporting tree growth and stability. In this study, we analyzed the relationship between the main lateral root distribution pattern and vertical tree growth direction based on root detection and analysis of tree morphometry. Tree growth represented by morphometric data were measured directly, and the root distribution was identified using a sonic Root Detector. Sixteen targeted trees (eight Samanea saman and eight Delonix regia trees) in an urban area landscape were selected in this study. The Root Detector revealed that the average sonic velocity of lateral roots was 676.88 m∙s−1 for S. saman and 865.32 m∙s−1 for D. regia. For root distribution, Root Detector determined the average numbers of main lateral roots for S. saman and D. regia, which were 6 and 10, respectively. Based on correlation analysis, significant relationships were found between tree root sonic velocity and the degree of lean, height, and diameter of the tree; meanwhile the relationship between crown diameter and slenderness were not significant. Findings confirmed that, in relation to the root distribution and the growth direction of the trunk and crown, the lateral root is mainly distributed in the opposite direction of the tree lean rather than crown growth direction. [ABSTRACT FROM AUTHOR]

Variations in the structure of plant leaves are mainly due to environmental variability. In many cases the way to acclimatize to unfavorable conditions. It is documented that in Cuba the anatomical and morphological characteristics of P. caribaea needles differ between ecotopes with different edaphoclimatic conditions. In this study, the effect of the position in the tree crown on the anatomy of the needles is analyzed. For this purpose, needles were collected from the lower, middle and upper part of 30 trees. The variables analyzed were thickness of the chlorophyll parenchyma, thickness of the transfusion parenchyma, height of the conduction tissue and width of the conduction tissue, cuticle thickness, epidermis thickness, hypodermis thickness, number of layers of hypodermis cells, number of channels and number of stomat. The results of the analyzes show a greater differentiation of the morphology of the needles towards the upper part of the tree, which is expressed by the increase in the thickness of the protective tissues and related to the greater exposure to the sun and lower relative humidity than they are exposed. The variables that contribute the most to differentiate the needles according to their position in the tree are the number of stomata and the number of cells in the hypodermis. [ABSTRACT FROM AUTHOR]

The given work relates to the study of the light regime and the structure of the vegetative composition in the Golden Delicious Reinders and Red Velox apple tree varieties. The solar regime in the crown of the apple trees of the studied varieties in the 4th year after their planting differs depending on the position of the sun in the sky, the distance from the ground and the length of the tree rows. The intensity of the solar radiation gradually increases from 9 o'clock till 13-15 o'clock, then decreases. The penetration of the solar energy into the crown increases from the base of the crown to the top of the tree. Based on the data obtained during the study, it can be asserted that the orchards in which trees have a height of 3.5-4.0 m and a crown width at the base of 1.0-1.2 m which decreases towards the top up to 0.8-1.0 m, form well-lit fruit-growing ecosystems, which receive in all areas of the vegetative ensemble more than 0.2 cal/cm² x min, i.e. as much as it is necessary for the photosynthesis process. The volume of the crown of the studied varieties depends on the vigour of the variety and the size of the trees. It provides light penetration to all elements of the crown, which allows. [ABSTRACT FROM AUTHOR]

Testate amoebae (TA) are important components of soil ecosystems, where they play an essential role in belowground food webs. In this study, we examined species composition, diversity, and structure of TA assemblages in soils beneath tree crowns (microscale) at three slope positions (mesoscale) in subtropical urban parks in Shenzhen, China. Forty-two species of TA belonging to 18 genera were identified in 81 samples. TA assemblages were the most diverse and abundant in the center of the tree crown comparing with other under-tree habitats. Foot of the hills harbored higher TA abundance and diversity comparing with upper locations along the hillslopes. The distribution of TA was mostly driven by under-crown and hillside positions but not by elementary environmental conditions such as pH, moisture content and thickness of leaf litter layer. None of later factors were sufficient in shaping TA assemblage composition. The findings of our study suggest that in regional studies of soil microbial eukaryotes both micro- (i.e., under-crown) and mesoscale (i.e., the slope position) heterogeneity should be considered. [ABSTRACT FROM AUTHOR]

Striving for climate neutrality and wider implementation of climate change mitigation measures including tree introduction in agricultural land, request for approaches and general allometric models for estimating carbon (C) stock in tree above-ground biomass (AGB) based on relatively easily obtainable remote sensing data is increasing. Here, we present estimates of individual trees’ crown diameters (CDs) for Betula pendula Roth (B. pendula) and Populus tremuloides Michx. × Populus tremula L. (P. tremuloides × P. tremula) in 11-year-old tree plantations (tree height ranged up to 12.8 and 18.1 m, respectively) in the hemiboreal region of Europe (in Latvia). Individual trees’ CDs were measured using a drone orthophoto map. Afterwards, linear equations were developed to predict individual trees’ stem diameters at breast height (DBHs) and, consequently, tree AGB (which was then converted to C stock) from remote-sensed tree CD data. RMSEs of the prediction models of tree stem DBH were in the ranges of 1.87–2.12 cm for B. pendula and 2.50–3.12 cm for P. tremuloides × P. tremula. This demonstrated approach is applicable to carry out, for instance, a self-assessment and approximate C stock in the AGB of selected tree species by land owners, managers, and other implementers of climate change mitigation measures.

Individual tree detection from airborne laser scanning (ALS) point clouds is the basis for forestry inventory and further applications. In the past decade, many methods have been developed to localize tree instances in ALS point clouds. These methods rely on empirical rules and field measurements that may change from plot to plot. Besides, most existing methods cannot consider multiple clues (e.g., shape priors and neighboring trees) under the same framework, which makes them not flexible and extensible. In this letter, we devise a new point-based and model-driven framework named “crown guess and selection”. This framework first generates crown candidates automatically, and then the qualities of candidates and their neighboring information are both considered. Finally, expected crowns are selected from candidates simultaneously. The proposed framework is tested and evaluated in a benchmark dataset. We also compare the new framework with several existing methods, and it turns out that the proposed framework outperforms others in terms of model flexibility and detection accuracy.

Vascular epiphytes are an important component of many ecosystems and constitute a substantial part of global plant diversity. In this context, accidental epiphytism, that is, the opportunistic epiphytic growth of typically terrestrial species, deserves special attention because it provides crucial insights into the global distribution of vascular epiphytes and the initial evolution of epiphytic lineages. Even though accidental epiphytes have been mentioned in the literature for more than a century, they have been neglected in most epiphyte studies. Only recently has accidental epiphytism been investigated more thoroughly. Therefore, the aim of this article is to provide a comprehensive review of the ecological basis and evolutionary relevance of this common but largely neglected phenomenon and to highlight open questions and promising research directions. Our central statement—that any species has the potential to grow epiphytically given the availability of suitable microhabitats and successful dispersal—is backed up by a compilation of observations of accidental epiphytes from numerous ecosystems with diverse climates, even including semiarid Mediterranean ones. A variety of arboreal microhabitats and environmental conditions conform to the ecological niche of typical terrestrial species, with the availability of such microhabitats depending on the interaction of local climate conditions, host tree age, and host species identity. Whenever suitable microhabitats are available in tree crowns, accidental epiphytism is limited primarily by dispersal. In an evolutionary context, the conquest of forest canopy represents an ecological opportunity where accidental epiphytes act as links between terrestrial and epiphytic life forms. We discuss two fundamental scenarios with sympatric speciation, selective pressure, autopolyploidy, and allopatric speciation as underlying mechanisms in the transition from terrestrial to epiphytic growth. In conclusion, we argue that accidental epiphytism is a substrate and dispersal‐dependent phenomenon and that, both from an individual perspective and an evolutionary perspective, epiphytism reflects the occupation of suitable but previously unexploited arboreal microhabitats. Acknowledging the fundamental principles that plant growth is opportunistic and that dispersal is a stochastic process can decisively improve our understanding of species distributions and other ecological patterns, as in the case of accidental epiphytism. [ABSTRACT FROM AUTHOR]

Terrestrial laser scanning of conifer tree crowns is challenged by occlusion problems causing sparse point clouds for many trees. Automatic segmentation of conifer tree crowns from sparse point clouds is a task that has only recently been addressed and not solved in a way that all trees can be segmented automatically without assignment errors. We developed a new segmentation algorithm that is based on region growing from seeds in voxelized 3D laser point clouds. In our data, field measured tree positions and diameters were available as input data to estimate crown cores as seeds for the region growing. In other applications, these seeds can be derived from the laser point cloud. Segmentation success was judged visually in the 3D voxel clouds for 1294 tree crowns of Norway spruce and Scots pine on 24 plots in six mixed species stands. Only about half of the tree crowns had only minor or no segmentation errors allowing to fit concentric crown models. Segmentation errors were most often caused by unsegmented neighbors at the edge of the sample plots. Wrong assignments of crown parts were also more frequent in dense groups of trees and for understory trees. For some trees, point clouds were too sparse to describe the crown. Segmentation success rates were considerably higher for dominant trees in the plot center. Despite the incomplete automatic segmentation of tree crowns, metrics describing crown size and crown shape could be derived for a large number of sample trees. A description of the irregular shape of tree crowns was not possible for most trees due to the sparse point clouds in the upper crown of most trees. [ABSTRACT FROM AUTHOR]

Forest aboveground biomass (AGB) is an important indicator for characterizing forest ecosystem structures and functions. Therefore, how to effectively investigate forest AGB is a vital mission. Airborne laser scanning (ALS) has been demonstrated as an effective way to support investigation and operational applications among a wide range of applications in the forest inventory. Moreover, three-dimensional structure information relating to AGB can be acquired by airborne laser scanning. Many studies estimated AGB from variables that were extracted from point cloud data, but few of them took full advantage of variables related to tree crowns to estimate the AGB. In this study, the main objective was to evaluate and compare the capabilities of different metrics derived from point clouds obtained from ALS. Particularly, individual tree-based alpha-shape, along with other traditional and commonly used plot-level height and intensity metrics, have been used from airborne laser scanning data. We took the random forest and multiple stepwise linear regression to estimate the AGB. By comparing AGB estimates with field measurements, our results showed that the best approach is mixed metrics, and the best estimation model is random forest (R2 = 0.713, RMSE = 21.064 t/ha, MAE = 15.445 t/ha), which indicates that alpha-shape may be a good alternative method to improve AGB estimation accuracy. This method provides an effective solution for estimating aboveground biomass from airborne laser scanning. [ABSTRACT FROM AUTHOR]

Inter-tree competition can be assessed using relatively simple indices derived from tree diameters, heights and locations, but they have often been found to be deficient for predicting tree growth. To better understand these linkages, we measure dimensions of Scots pine and Norway spruce crowns, which are assumed to be affected by competition pressure. We extract these features from terrestrial laser scanning point clouds and model their dependencies on competition. Our results indicate that while competition is a major determinant for crown morphology, the characteristics and most applicable indices of the two species are contrasting. We interpret our results primarily by light competition: pines are seeking for light and invest their resources on widening the crown only in suitable conditions, while spruce may grow large despite of shortage of light. We conclude that shade tolerance affects strongly on the identification of actual competitors, which should be addressed when modelling competition.

The study of the leafmining moth of the chestnut miner (Cameraria ohridella Deschka & Dymić, 1986) was carried out through the planting of the common horse chestnut (Aesculus hippocastanum L.) in the Main Botanical Garden of the Russian Academy of Sciences. The effect of various degrees of insolation of horse chestnut plants on leaf morphology and the composition of secondary metabolites, as well as the relationship of these parameters with the number and density of C. ohridella populations during the growing season, was studied. The solar influence, it was noted, had a significant impact. Thus, the largest number of the pests was recorded on the leaves of the sunlit side of the tree crown, and the smallest on the leaves of the shady part of the crown. The low content of polyphenols in the pool of secondary metabolites in the tissues of the A. hippocastanum leaves did not deter C. ohridella and poorly protected the plants from this miner, while the significant content of carbohydrates in the leaves reduced the resistance of chestnut plants to damage by the Ohrid leaf miner.

This paper presents the results of a study carried out on new apple cultivars, namely 'Granny Smith', 'Gala Buckeye Simmons', 'Golden Delicious Reinders', 'Red Velox' and 'Fuji Kiku', grafted on 'M9' rootstock, which are intended to create high-density orchards in the central part of the Republic of Moldova. During the growth and fruiting periods of the trees, the number of fruit depends on the variety, the age of the trees and the distance from the ground which increases gradually year in year out. The distribution of fruits along the height of the tree depends on the number of branches and leaves on the tree and on the number of fruiting branches. During the periods of growth and fruiting, the trees of the studied cultivars gave an average yield of 10.9 kg/tree. [ABSTRACT FROM AUTHOR]

Abstract Background The universal occurrence of randomly distributed dark holes (i.e., data pits appearing within the tree crown) in LiDAR-derived canopy height models (CHMs) negatively affects the accuracy of extracted forest inventory parameters. Methods We develop an algorithm based on cloth simulation for constructing a pit-free CHM. Results The proposed algorithm effectively fills data pits of various sizes whilst preserving canopy details. Our pit-free CHMs derived from point clouds at different proportions of data pits are remarkably better than those constructed using other algorithms, as evidenced by the lowest average root mean square error (0.4981 m) between the reference CHMs and the constructed pit-free CHMs. Moreover, our pit-free CHMs show the best performance overall in terms of maximum tree height estimation (average bias = 0.9674 m). Conclusion The proposed algorithm can be adopted when working with different quality LiDAR data and shows high potential in forestry applications.

The root system is important for supporting tree growth and stability. In this study, we analyzed the relationship between the main lateral root distribution pattern and vertical tree growth direction based on root detection and analysis of tree morphometry. Tree growth represented by morphometric data were measured directly, and the root distribution was identified using a sonic Root Detector. Sixteen targeted trees (eight Samanea saman and eight Delonix regia trees) in an urban area landscape were selected in this study. The Root Detector revealed that the average sonic velocity of lateral roots was 676.88 m∙s−1 for S. saman and 865.32 m∙s−1 for D. regia. For root distribution, Root Detector determined the average numbers of main lateral roots for S. saman and D. regia, which were 6 and 10, respectively. Based on correlation analysis, significant relationships were found between tree root sonic velocity and the degree of lean, height, and diameter of the tree; meanwhile the relationship between crown diameter and slenderness were not significant. Findings confirmed that, in relation to the root distribution and the growth direction of the trunk and crown, the lateral root is mainly distributed in the opposite direction of the tree lean rather than crown growth direction.

Testate amoebae (TA) are important components of soil ecosystems, where they play an essential role in belowground food webs. In this study, we examined species composition, diversity, and structure of TA assemblages in soils beneath tree crowns (microscale) at three slope positions (mesoscale) in subtropical urban parks in Shenzhen, China. Forty-two species of TA belonging to 18 genera were identified in 81 samples. TA assemblages were the most diverse and abundant in the center of the tree crown comparing with other under-tree habitats. Foot of the hills harbored higher TA abundance and diversity comparing with upper locations along the hillslopes. The distribution of TA was mostly driven by under-crown and hillside positions but not by elementary environmental conditions such as pH, moisture content and thickness of leaf litter layer. None of later factors were sufficient in shaping TA assemblage composition. The findings of our study suggest that in regional studies of soil microbial eukaryotes both micro- (i.e., under-crown) and mesoscale (i.e., the slope position) heterogeneity should be considered.

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Forest aboveground biomass (AGB) is an important indicator for characterizing forest ecosystem structures and functions. Therefore, how to effectively investigate forest AGB is a vital mission. Airborne laser scanning (ALS) has been demonstrated as an effective way to support investigation and operational applications among a wide range of applications in the forest inventory. Moreover, three-dimensional structure information relating to AGB can be acquired by airborne laser scanning. Many studies estimated AGB from variables that were extracted from point cloud data, but few of them took full advantage of variables related to tree crowns to estimate the AGB. In this study, the main objective was to evaluate and compare the capabilities of different metrics derived from point clouds obtained from ALS. Particularly, individual tree-based alpha-shape, along with other traditional and commonly used plot-level height and intensity metrics, have been used from airborne laser scanning data. We took the random forest and multiple stepwise linear regression to estimate the AGB. By comparing AGB estimates with field measurements, our results showed that the best approach is mixed metrics, and the best estimation model is random forest (R2 = 0.713, RMSE = 21.064 t/ha, MAE = 15.445 t/ha), which indicates that alpha-shape may be a good alternative method to improve AGB estimation accuracy. This method provides an effective solution for estimating aboveground biomass from airborne laser scanning.

Unmanned Aerial Vehicles (UAVs) are increasingly used in forestry as they are economical and flexible. This study aims to present the advantages of the drone photogrammetry method in collecting individual tree crowns, as individual tree crown detection could deliver essential ecological and economic information. The referred accuracy for individual tree crown extraction is 79.2%. Only crowns that were clearly visible were selected and manually delineated on the image because the distribution of the true crown size is significantly different from the segmented crowns. The aim of this study is to investigate UAVs orthomosaics in individual tree crown detection. The objectives of this study are to produce the orthomosaic of tree crown extraction mapping using the Pix4D software and analyze the tree crowns using tree crown delineation and the OBIA algorithm. Data processing involves the processing of aerial images using Pix4Dmapper. Automatic tree crown detection involves a tree crown delineation algorithm and OBIA operations to process the tree crown extraction. The crown delineation algorithm and OBIA algorithm operation will be compared to the actual tree crown measurement in terms of diameter and area. The tree crown delineation method obtained a 0.347m mean diameter difference from the actual tree crown diameter, while the OBIA approach obtained 4.98m. The tree crown delineation method obtained 97.26% of the actual tree crown area, while OBIA obtained 91.74%. [ABSTRACT FROM AUTHOR]

Dwarf mistletoes (Arceuthobium species) are arboreal, hemiparasitic plants of conifers that can change the structure and function of the tree crown. Hemlock dwarf mistletoe (Arceuthobium tsugense subsp. tsugense) principally parasitizes western hemlock (Tsuga heterophylla) and effects 10.8% of all western hemlock trees in Oregon, USA. In this study, we climbed 16 western hemlock trees (age 97–321 years, height 33–54.7 m) across a gradient of infection (0%–100% of branches infected) and measured occurrence of all dwarf mistletoe infections, dwarf mistletoe caused deformities, foliage, branch and crown metrics, and sapwood area. We then modelled over 25 different response variables using linear and generalized linear models with three metrics of severity as explanatory variables: total infection incidence, proportion of all live branches infected, and proportion of all live, infected branches with 33 per cent or more foliage distal to infection. A strong effect of dwarf mistletoe intensification was the reduction of branch foliage and an increase in the proportional amount of foliage distal to infections, with severely infected trees having the majority of foliage distal to infections. Increasing severity led to an apparent crown compaction as crown volumes decreased and became increasingly comprised of deformities. Sapwood area was unrelated to infection severity. Branch length and diameters were unrelated to increasing infection severity despite severely infected branches supporting 1–70 infections. The most severely infected tree had 3,615 individual plants in the crown. Our results suggested that shifts in crown structure and branch deformation, foliage amount, and foliage distal to infection, reflected a likely reduction of capacity for tree growth that coincided with a hypothesized increase in resource demand by dwarf mistletoe plants as infection severity intensified. [ABSTRACT FROM AUTHOR]

The structural characteristics of the tree crowns of Cunninghamia lanceolata var. Luotian (herein, Luotian), a natural variety of C. lanceolata (Chinese-fir, herein Lanceolata) in China, were analyzed using trunk and branch measurements and biomass determinations. Samples from two typical cultivated varietal populations were collected, including twenty-six 15–23-year-old trees of Luotian from a plantation, and nine 16–23-year-old trees of Lanceolata. Our results show that Luotian and Lanceolata samples differed significantly in crown structure, morphological indices, and biomass: (1) the oldest live branches on Luotian trees were 5–6 years old and 8–11 years old on Lanceolata. The ages of the live branches were not affected by the ages of the Luotian trees, while live branch ages increased with ages of Lanceolata trees; (2) the maximum branching order of Luotian was level two. Compared to Lanceolata, the average number of first-order lateral branches (i.e., branches emerging from the trunk) and the number of first-order lateral branch whorls per sample tree were 12.9% and 32.2% lower, respectively, in Luotian. However, the average number of branches within a single whorl was 21.8% greater in Luotian; the average number of branch whorls at crown height was 51.1% greater. Thus, the Luotian variety has thicker branches; (3) the average lateral branch angles in Luotian and Lanceolata sample trees were 105.2° and 61.4°, respectively. The branch angles in 53.0% of lateral branches on Luotian ranged from 105° to 135°, but 30° to 90° in 96% of the lateral branches on Lanceolata. Within the same crown layer, the average branch angle was 1.6–2.2 times greater in Luotian, and the angle was directly proportional to crown thickness; (4) the average base diameter and branch length on Luotian were 1.3 cm and 75.8 cm, respectively, and 1.6 cm and 112.2 cm for Lanceolata. For individual trees, branch growth differed significantly (p < 0.01) between Luotian and Lanceolata. However, the lateral branches grew at a similar rate among Luotian trees of different ages; (5) the average height to the lowest live branch on Luotian was 128.3% greater than on Lanceolata, resulting in a significant difference (p < 0.01) in crown size. Compared to the crowns on Lanceolata, the Luotian crowns were 45.3% higher and 41.1% wider, and the surface area, volume, and growth of the crown were 27.0%, 11.4%, and 2.4 times greater than for Lanceolata, respectively; and, (6) the biomass of Luotian and Lanceolata sample trees also differed significantly. The mean crown, branch, and leaf biomass for Luotian was 40.0%, 25.2%, and 54.1% of those for Lanceolata, respectively. However, the leaf biomass in each layer of the Luotian crown was higher than that of Lanceolata, and leaf biomass increased with crown thickness. [ABSTRACT FROM AUTHOR]

Background: The universal occurrence of randomly distributed dark holes (i.e., data pits appearing within the tree crown) in LiDAR-derived canopy height models (CHMs) negatively affects the accuracy of extracted forest inventory parameters. Methods: We develop an algorithm based on cloth simulation for constructing a pit-free CHM. Results: The proposed algorithm effectively fills data pits of various sizes whilst preserving canopy details. Our pit-free CHMs derived from point clouds at different proportions of data pits are remarkably better than those constructed using other algorithms, as evidenced by the lowest average root mean square error (0.4981 m) between the reference CHMs and the constructed pit-free CHMs. Moreover, our pit-free CHMs show the best performance overall in terms of maximum tree height estimation (average bias = 0.9674 m). Conclusion: The proposed algorithm can be adopted when working with different quality LiDAR data and shows high potential in forestry applications. [ABSTRACT FROM AUTHOR]

The growth and production potential of a tree depends on its crown dimensions as these are closely related to a tree’s photosynthetic capacity. However, tree crowns have been studied less compared to their main stems because of their lower market value and because the measurement of crown dimensions, such as crown volume or surface area, is difficult. Frequently, an individual tree’s live crown ratio (LCR) is predicted by linear or nonlinear models that are a function of easy-to-measure dendrometric variables using ordinary least-squares techniques. Using the long-term data from established genetic and spacing trials, we developed and evaluated the predictive performance of three nonlinear models and introduced a new generalized linear model for predicting LCR. The nonlinear models were fit using exponential, Weibull, and Richards functions. The generalized linear model was based on beta regression. This resulted in a slightly smaller error than the other models in predicting the LCR of loblolly pine trees used in this study. Crown ratio is measured in percentage unit and should be modeled using generalized linear models that assume a beta distribution for error terms.

Tree species classification using hyperspectral imagery is a challenging task due to the high spectral similarity between species and large intra-species variability. This paper proposes a solution using the Multiple Instance Adaptive Cosine Estimator (MI-ACE) algorithm. MI-ACE estimates a discriminative target signature to differentiate between a pair of tree species while accounting for label uncertainty. Multi-class species classification is achieved by training a set of one-vs-one MI-ACE classifiers corresponding to the classification between each pair of tree species and a majority voting on the classification results from all classifiers. Additionally, the performance of MI-ACE does not rely on parameter settings that require tuning resulting in a method that is easy to use in application. Results presented are using training and testing data provided by a data analysis competition aimed at encouraging the development of methods for extracting ecological information through remote sensing obtained through participation in the competition. The experimental results using one-vs-one MI-ACE technique composed of a hierarchical classification, where a tree crown is first classified to one of the genus classes and one of the species classes. The species-level rank-1 classification accuracy is 86.4% and cross entropy is 0.9395 on the testing data, provided by the competition organizer, without the release of ground truth for testing data. Similarly, the same evaluation metrics are computed on the training data, where the rank-1 classification accuracy is 95.62% and the cross entropy is 0.2649. The results show that the presented approach can not only classify the majority species classes, but also classify the rare species classes.

Graphical abstract Highlights • We conceptualized the approach for measuring three-dimensional crown asymmetry. • Our novel approach separates the effects of crown shift and local crown plasticity. • Smaller trees exhibited higher ability to shift and re-shape their crowns. • Crown models neglecting tree asymmetry were poor predictors of direct competitors. • Light availability computed by geometric crown models were significantly biased. Abstract There are many indications that for a true understanding of aboveground canopy competition, the concept of symmetric trees is oversimplified and unsatisfactory; in spite of that, this concept is still commonly used in forest ecology research. In this study we analyzed and quantified the effect of tree/crown asymmetry on crown-to-crown interactions and canopy light availability with respect to tree size and species. Geometric crown models were used to represent the concept of symmetric trees, while data from terrestrial laser scanning were employed to constitute real crown shapes, positions and mutual crown-to-crown interactions. We developed an original approach for measuring three-dimensional crown asymmetry, separating the effect of positional crown shift and local crown plasticity, and analyzed their effect in aboveground competition for space and light. In comparison with reality, the models neglecting tree asymmetry were only poor predictors of trees mutually competing for space. Geometric models taking the positional crown shift into account were good predictors of 'space competitors' for Norway spruce, but were still insufficient for European beech. This is because for spruce crown shifting seems to be the major neighbor avoidance strategy, while beech in addition exhibited high local crown shape plasticity. Additionally, of the two species beech showed overall greater crown plasticity, which (in contrast to spruce) decreased only slowly with increasing tree size. Importantly, the concept of symmetric trees significantly underestimates the potential canopy light availability (and thus overestimates canopy competition for light), because asymmetric and the plastic 'puzzle-like' arrangement of real tree crowns is more effective than assumed symmetric organization. This most likely inserts a systematic bias into stand growth simulators that are based on the concept of symmetric trees. [ABSTRACT FROM AUTHOR]

Estimation of newly grown needle area, as the most active part of assimilation appa-ratus, is important for better understanding of biochemical processes of trees. This paper investigates the relationship between the projected area of newly grown need-les and other biometric tree parameters (tree height HTREE, diameter at breast height DBH, projected crown area and crown length) of Norway spruce trees. The total pro-jected area of newly grown needles of seven sampled trees was estimated using a detailed inventory of the number and length of shoots. The relationship between this value and other readily measurable biometric tree characteristics was tested to find the best model for estimating total area of newly grown needles. The model using HTREE*DBH with a coefficient of determination of 0.96 had the best performance. The DBH and HTREE inventory of all trees in the studied plot was used to estimate the total projected area of newly grown needles of the entire forest stand (4506.7 m2 per hec-tare). We also investigated specific leaf area (SLA) of newly grown needles in vertical profile of tree crown. SLA increased constantly from the tree top (28.7 cm2.g2) to the crown base (80.3 cm2.g2). [ABSTRACT FROM AUTHOR]

The accurate assessment of tree crowns is important for agriculture, for example, to adjust spraying rates, to adjust irrigation rates or even to estimate biomass. Among the available methodologies, there are the traditional methods that estimate with a three-dimensional approximation figure, the HDS (High Definition Survey), or TLS (Terrestrial Laser Scanning) based on LiDAR technology, the aerial photogrammetry that has re-emerged with unmanned aerial vehicles (UAVs), as they are considered low cost. There are situations where either the cost or location does not allow for modern methods and prices such as HDS or the use of UAVs. This study proposes, as an alternative methodology, the evaluation of images extracted from Google Maps (GM) for the calculation of tree crown volume. For this purpose, measurements were taken on orange trees in the south of Spain using the four methods mentioned above to evaluate the suitability, accuracy, and limitations of GM. Using the HDS method as a reference, the photogrammetric method with UAV images has shown an average error of 10%, GM has obtained approximately 50%, while the traditional methods, in our case considering ellipsoids, have obtained 100% error. Therefore, the results with GM are encouraging and open new perspectives for the estimation of tree crown volumes at low cost compared to HDS, and without geographical flight restrictions like those of UAVs.