Tree Crown Volume Research Articles

Tree-size dimension inequality shapes aboveground carbon stock across temperate forest strata along environmental gradients

It is generally well-explored that overstorey stratum regulates understorey stratum through the dominant role over the available resources in forests. However, the relationships amongst topography, soil nutrients, species diversity, tree-size dimension inequality and aboveground carbon (AGC) stock across forest strata remain debated in forest ecosystems. Here, we assumed that soil nutrients, species diversity and tree-size dimension inequality promote AGC stock in overstorey stratum, which in turn regulate AGC stock in understorey stratum in natural temperate forests. To do so, using several structural equation models (SEMs) on the data from 104 temperate forest plots in Northern Iran, we assessed the effects of tree-size dimension inequality as well as the individual effects of either inequality in tree diameter, height, basal area, crown volume, or crown area, species diversity, soil nutrients and topographic factors on AGC in each forest stratum and at whole-community level as well as the effects of overstorey on understorey (i.e., joint SEMs). Results show that AGC stock in overstorey stratum was mainly determined by tree-size dimension inequality rather than by species diversity on nutrient-rich soils but controlled by topographic factors related to light availability. In understorey stratum, only basal area inequality was the strong driver of AGC stock, but overstorey overruled the effects of understorey drivers on understorey AGC stock. Specifically, overstorey tree-size dimension inequality increased but AGC stock decreased the AGC stock of understorey. The observed mechanism and effects at overstorey stratum were nearly similar to whole-community level. This study shows that overstorey stratum regulates understorey through dominant occupancy on the light availability and soil nutrients. We suggest that integrative modeling of overstorey and understorey strata based on tree height, diameter and crown inequality may better enhance our understanding and extend the existing debate based on multiple drivers of forest functioning, which may help to provide specific guidelines for forest management.

Spatially variable pesticide application in olive groves: Evaluation of potential pesticide-savings through stochastic spatial simulation algorithms.

Site-specific management using spatial crown volume characterization can greatly reduce the amount of pesticides applied in agricultural treatments performed with air-assisted sprayers, while helping farmers achieve the European legislation on safe use of pesticides. Nevertheless, variable rate treatments in olive groves have received little attention. Thus, field research was conducted in a 20.6-ha traditional olive grove. Two attributes of the trees - tree crown volume (V) and tree projected area - were determined, using 67 samples for V and all trees of the field (1433) for tree projected area. Spatial continuity of both attributes was modelled with exponential variograms. To gain a measure of local uncertainty, stochastic simulation algorithms were applied. One hundred simulated images were obtained for tree projected area using direct sequential simulation. Tree projected area simulations were used to improve spatial prediction of V, more difficult and more expensive to obtain, taking advantage of the high linear correlation between both variables (rxy=0.72,p<0.001). Thus, direct sequential cosimulation was employed to predict the spatial distribution of V, obtaining 100 geostatistical realizations of V. In order to estimate the potential reduction of pesticide use in the farm with variable rate treatments, two cut-off values of V were considered (50 and 100m3crown volume). Local uncertainty, understood as the probability of each tree belonging to a given crown volume interval was determined. Probability maps were further transformed to morphological maps and finally to variable prescription maps. Two scenarios with 2 and 3 management zones (MZs) were obtained. In comparison with a conventional phytosanitary application, the variable rate treatments could reduce the pesticide amounts by 21.3% with 2 MZs, and by 38% with 3 MZs. The joint use of V and tree projected area in stochastic sequential simulation algorithms has shown to be useful to determine MZs in olive groves.

Influence of kaolin application on most important fruit and leaf characteristics of two apple cultivars under sustained deficit irrigation

BackgroundApple is one of the oldest and most valuable fruits. Water restriction is one of the major problems in the production of this fruit in some planting areas.MethodsEffects of kaolin spray treatments were studied on two early apple cultivars of Golab and Shafi-Abadi under sustained deficit irrigation (SDI) in Alborz province, Iran during 2017 and 2018. Irrigation treatments were 100%, 85%, and 70% ETc and kaolin application were concentrations of 0, 3 and 6% in 2017 and 0, 1.5 and 3% in 2018.ResultsResults showed that 85% ETc treatment compared to other irrigation treatments improved apple tree crown volume in 2017. Deficit irrigation treatments significantly reduced fruit weight in both years. Application with 6% kaolin resulted in 33.3% increase in apple fruit weight compared to non-kaolin treatment at 100% ETc irrigation in the first year. Severe deficit irrigation (70% ETc) significantly reduced apple fruit length in both years, but 6% kaolin increased fruit length in both apple cultivars in 2017. Severe deficit irrigation treatment increased the firmness of apple fruit compared to control and mild deficit irrigation (85% ETc) in the first year of experiment. There was no significant difference between irrigation treatments for apple fruit firmness in the second year of experiment. Kaolin treatments of 1.5% and 3% at full irrigation increased the soluble solids content of apple fruit by 36.6% and 44.1% in 2018, respectively. Deficit irrigation treatments significantly increased leaf proline content compared to control in both years. In the first year, kaolin treatments increased leaf proline but in the second year, leaf proline was not significant. Deficit irrigation treatment of 70% ETc and 6% kaolin had the highest amount of glycine betaine content, malondialdehyde and hydrogen peroxide in apple leaf in the first year of experiment.ConclusionsSevere deficit irrigation stress (70% ETc) increased the activity of nonenzymatic defense systems of apple trees. Kaolin as a drought stress reducing agent can be recommended in apple orchards of Golab and Shafi-Abadi cultivars as an effective and inexpensive method to improve tolerance to drought stress conditions.

Estimates of Tree Canopy Closure and Basal Area as Proxies for Tree Crown Volume at a Stand Scale

Research Highlights: Studies on tree canopy dwelling species often require simple proxies of tree canopy volume estimated at a stand level. These include allometrically related tree crown parameters such as crown area and basal area, and canopy cover. Background and Objectives: In monoculture Scot’s pine and mixed pine/Norway spruce forest, we aimed to test the relationships between tree diameter at breast height (DBH) and tree crown volume at a tree level and between densitometer canopy closure estimates and tree crown volume at a stand level. Materials and Methods: The study was carried out in eastern Latvia (hemiboreal zone) in monoculture pine and mixed coniferous stands. On a subset of trees in 22 forest stands (88 100 m2 plots), we determined the best regression model that described the relationship between tree DBH and crown volume for spruce and pine. Tree crown volume at a stand level was determined from the individual tree volume estimates calculated from these regression models. On a stand level, we also calculated regression models for densitometer closure estimates versus total crown volume for pine and mixed stands. Results: Linear mixed effects models showed significant relationships between DBH and crown volume for pine (R2 = 0.63) and spruce (R2 = 0.40), indicating that basal area could be used as a predictor of crown volume at a stand level. Variance explained by a regression model of canopy closure versus tree crown volume at a stand level was R2 = 0.52. Conclusions: Tree basal area and crown closure can be used as proxies of tree crown volume at a stand scale in monoculture stands. In mixed stands estimates of crown volume based on basal area need to be calculated separately for each tree species, while canopy closure will provide an estimate of total crown volume.

Assessing tree crown volume—a review

Abstract Tree crown volume is a fundamental tree characteristic. It correlates to forest biomass production and most relevant ecosystem and environmental functions, such as carbon sequestration and air pollution reduction. When researching these relationships, it is necessary to clearly define and then quantify tree crown variables in a both accurate and operational manner. In this paper, we review the reported literature on the assessment of tree crown volume. First, we compile the varying definitions of crown volume and other tree crown variables that may be used as inputs to quantify crown volume. Then, we examine the data sources for quantifying these variables, including field measurements, terrestrial photographs, aerial photographs and laser scanning. Furthermore, we compare the published approaches on translating these crown variable measurements into tree crown volume. These approaches include the approximation of simple geometric solids, approaches of computational geometry and voxelization. We also compare the reported accuracies and major challenges of these approaches. From this literature review, the reader may craft a suitable approach for the assessment of crown volume.

Nondestructive Tree Stem and Crown Volume Allometry in Hybrid Poplar Plantations Derived from Terrestrial Laser Scanning

Abstract Accurate and frequently updated tree volume estimates are required for poplar plantations, which are characterized by fast growth rate and short rotation. In this study, we tested the potential of terrestrial laser scanning (TLS) as a reliable method for developing nondestructive tree volume allometries in poplar plantations. The trial was conducted in Italy, where 4- to 10-year-old hybrid plantations were sampled to develop tree crown volume allometry in leaf-on conditions, tree stem volume, and height-diameter allometries in leaf-off conditions. We tested one-entry models based on diameter and two-entry models based on both diameter and height. Model performance was assessed by residual analysis. Results indicate that TLS can provide accurate models of tree stem and crown volume, with percentage of root-mean-square error of about 20 percent and 15 percent, respectively. The inclusion of height does not bring relevant improvement in the models, so that only diameter can be used to predict tree stem and crown volume. The TLS-measured stem volume estimates agreed with an available formula derived from harvesting. We concluded that TLS is a reliable method for developing nondestructive volume allometries in poplar plantations and holds great potential to enhance conventional tree inventory and monitoring. Study Implications: Terrestrial laser scanning (TLS) is a technique that allows nondestructive measurement of the three-dimensional structure of a tree with high precision and low cost. The ability of TLS to measure both tree crown volume and tree position can be effective to test optimal spacing requirements and also to test innovative schemes such as mixed or polycyclic poplar plantations. The spatially explicit nature of TLS measurements allows better integration with different remotely sensed sensors, which can be used in combination with TLS, enabling a multiscale assessment of poplar plantation structure with different levels of detail, enhancing conventional tree inventory and supporting effective management strategies.

Assessing the Orange Tree Crown Volumes Using Google Maps as a Low-Cost Photogrammetric Alternative

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.

How dynamic growth of avenue trees affects particulate matter dispersion: CFD simulations in street canyons

This study combined parameterized tree growth model, Reynolds Averaged Navier–Stokes model and revised generalized drift flux model to investigate the effect of dynamic growth of avenue trees on atmospheric particulate pollution dispersion in street canyons. We tested conditions with three street canyon aspect ratios (H/W = 0.45, 0.9 and 1.8) and five common avenue tree species (Gingko biloba, Aesculus chinensis, Acer buergerianum, Liriodendron chinense and Cedrus deodar). Results demonstrated that: 1) Avenue tree age was strongly correlated with their height and crown diameter (R2 ≥ 0.71). 2) PM reduction ratio increased significantly as tree age increased. G. biloba was the most effective at removing the pedestrian-level PM10, while L. chinenses has the greatest capacity to reduce pedestrian-level PM2.5. 3) Pedestrian-level PM on the windward street-side was positively related to H/W ratios. Maximum PM was measured on the leeward street-side at H/W = 0.9. 4) Tree height, crown diameter and crown volume in the street canyons were the primary factors affecting the pedestrian-level PM reduction ratio, while leaf area index and crown base height had less influence. Our results could provide guidelines for selecting avenue trees within street canyons and appropriate biometric characteristics during different plant stages to enhance urban sustainability.

Simulation of multi-platform LiDAR for assessing total leaf area in tree crowns

LiDAR (Light Detection and Ranging) technology has been increasingly implemented to assess the biophysical attributes of forest canopies. However, LiDAR-based estimation of tree biophysical attributes remains difficult mainly due to the occlusion of vegetative elements in multi-layered tree crowns. In this study, we developed a new algorithm along with a multiple-scan methodology to analyse the impact of occlusion on LiDAR-based estimates of tree leaf area. We reconstructed five virtual tree models using a computer graphic-based approach based on in situ measurements from multiple tree crowns, for which the position, size, orientation and area of all leaves were measured. Multi-platform LiDAR simulations were performed on these 3D tree models through a point-line intersection algorithm. An approach based on the Delaunay triangulation algorithm with automatic adaptive threshold selection was proposed to construct the scanned leaf surface from the simulated discrete LiDAR point clouds. In addition, the leaf area covered by laser beams in each layer was assessed in combination with the ratio and number of the scanned points. Quantitative comparisons of LiDAR scanning for the occlusion effects among various scanning approaches, including fixed-position scanning, multiple terrestrial LiDAR scanning and airborne-terrestrial LiDAR cross-scanning, were assessed on different target trees. The results showed that one simulated terrestrial LiDAR scan alongside the model tree captured only 25–38% of the leaf area of the tree crown. When scanned data were acquired from three simulated terrestrial LiDAR scans around one tree, the accuracy of the leaf area recovery rate reached 60–73% depending on the leaf area index, tree crown volume and leaf area density. When a supplementary airborne LiDAR scanning was included, occlusion was reduced and the leaf area recovery rate increased to 72–90%. Our study provides an approach for the measurement of total leaf area in tree crowns from simulated multi-platform LiDAR data and enables a quantitative assessment of occlusion metrics for various tree crown attributes under different scanning strategies.

Rubber Tree Crown Segmentation and Property Retrieval Using Ground-Based Mobile LiDAR after Natural Disturbances

Rubber trees in southern China are often impacted by natural disturbances, and accurate rubber tree crown segmentation and property retrieval are of great significance for forest cultivation treatments and silvicultural risk management. Here, three plots of different rubber tree clones, PR107, CATAS 7-20-59 and CATAS 8-7-9, that were recently impacted by hurricanes and chilling injury were taken as the study targets. Through data collection using ground-based mobile light detection and ranging (LiDAR) technology, a weighted Rayleigh entropy method based on the scanned branch data obtained from the region growing algorithm was proposed to calculate the trunk inclination angle and crown centre of each tree. A watershed algorithm based on the extracted crown centres was then adopted for tree crown segmentation, and a variety of tree properties were successfully extracted to evaluate the susceptibility of different rubber tree clones facing natural disturbances. The results show that the angles between the first-order branches and trunk ranged from 35.1–67.7° for rubber tree clone PR107, which is larger than the angles for clone CATAS 7-20-59, which ranged from 20.2–43.2°. Clone PR107 had the maximum number of scanned leaf points, lowest tree height and a crown volume that was larger than that of CATAS 7-20-59, which generates more frontal leaf area to oppose wind flow and reduces the gaps among tree crowns, inducing strong wind loading on the tree body. These factors result in more severe hurricane damage, resulting in trunk inclination angles that are larger for PR107 than CATAS 7-20-59. In addition, the rubber tree clone CATAS 8-7-9 had the minimal number of scanned leaf points and the smallest tree crown volume, reflecting its vulnerability to both hurricanes and chilling injury. The results are verified by field measurements. The work quantitatively assesses the susceptibility of different rubber tree clones under the impacts of natural disturbances using ground-based mobile LiDAR.

Identification of Potential Metabolic Markers for the Selection of a High-Yield Clone of Quercus acutissima in Clonal Seed Orchard

Quercus acutissima Carruth. is one of the most economically important deciduous tree species in Korea. The acorns of Q. acutissima are used for both food and medicinal purposes in Korea and China. In this study, we analyzed plant hormones and metabolite profiles to identify their correlation with the yield production of Q. acutissima. The contents of sucrose and inositol in the leaves of high-yield clones were significantly higher (p &lt; 0.05) than those of low-yield clones. In addition, high-yield clones have a higher content of phosphoric acid, succinic acid, malic acid, and butane-1,3-diol in stems compared with low-yield clones. Among the identified metabolites, zeatin-9-glucoside showed highly significant negative correlations with tree height, crown volume, and acorn production. It is considered that these metabolites could be useful metabolic markers for the selection of a high yield clone of Q. acutissima.

Assessing Local Uncertainty of Soil Protection in an Olive Grove Area with Pruning Residues Cover: A Geostatistical Cosimulation Approach

AbstractThe spatial characterization of soil protection is important for preventing land degradation. Mulch covers of pruning residues are increasingly used by farmers, but little is known regarding their spatial variability. Thus, field research was conducted in a 14·7‐ha traditional olive grove located in Córdoba (Spain), to evaluate the variability of the initial density of pruning (Dpo), tree crown volume (V) and N content in residues (Np). Dry pruning weight and Np were characterized in 49 and 47 samples, respectively, covering approximately half of the area. V was measured in 178 locations covering all of the study area. The spatial continuity of these variables was described by spherical variograms. Geostatistical simulation algorithms were employed. One hundred realizations were made for Np through direct sequential simulation. Because the association with V was large (rxy = 0·72, p‐value &lt; 0·001), we ran a geostatistical cosimulation algorithm to obtain 100 maps of Dpo. The final density of pruning (FDp) was determined by applying a residue decomposition model for a 2‐year period to pairs of previously simulated maps of Np and Dpo. After setting soil protection cut‐off values for FDp, the soil protection probability was calculated for pruning strips of 2 and 4 m width. Finally, we converted the probability maps into binary maps and classified the farm into protected, unprotected and uncertain zones. V provided valuable input to evaluate soil protection. The application of stochastic simulations coupled with a decomposition model was useful to identify critical areas. This methodology can be easily applied to other crops. Copyright © 2017 John Wiley &amp; Sons, Ltd.

English

In this paper, four strategies were proposed for modeling tree crown volume using as independent variable stem variables, crown variables, combination of stem and crown variables, and stem volume. We used a dataset comprised of 170 trees from 12 temporary plots located in forest stands in southern Brazil. Models composed of stem variables presented weaker predictive ability. The best model contained crown variables, which explained 78.95% of observed variability. However, implementation of such model is bounded by its independent variables, which are not often measured in forest inventories. The model composed by diameter at breast height and crown length proved to be an adequate modeling approach. The predictive capability was kept by model which is composed by most easily measured variable in a forest - diameter at breast height, also by the most easily acquirable crown variable - crown length. In our suggested model, estimates of and are coefficients that convert volume of a regular geometric solid – RGS is dbh² times crown length) - into crown volume, whilst estimate of is an allometric constant. Key words: Crown modeling, diameter at breast height, crown length, crown volume.

Lidar detection of individual tree size in tropical forests

Abstract Characterization of tropical forest trees has been limited to field-based techniques focused on measurement of diameter of the cylindrical part of the bole, with large uncertainty in measuring large trees with irregular shapes, and other size attributes such as total tree height and the crown size. Here, we introduce a methodology to decompose lidar point cloud data into 3D clusters corresponding to individual tree crowns (ITC) that enables the estimation of many biophysical variables of tropical forests such as tree height, crown area, crown volume, and tree number density. The ITC-based approach was tested using airborne high-resolution lidar data collected over the 50-ha Center for Tropical Forest Science (CTFS) plot in the Barro Colorado Island, Panama. The lack of tree height and crown size measurements in the field prohibits the direct validation of the ITC metrics. We assess the reliability of our method by comparing the aboveground biomass (AGB) estimated using ground and lidar individual tree measurements at multiple spatial scales, namely 1 ha, 2.25 ha, 4 ha, and 6.25 ha. We examined four different lidar-derived AGB models, with three based on individual tree height, crown volume, and crown area, and one with mean top canopy height (TCH) calculated at the plot level using the lidar canopy height model. Results show that the predictive power of all models based on ITC size and TCH increases with decreasing spatial resolution from 16.9% at 1 ha for the worst model to 5.0% at 6.25 ha for the best model. The TCH-based model performed slightly better than ITC-based models except at higher spatial scales (~ 4 ha) and when errors due to edge effects associated with tree crowns were reduced. Unlike the TCH models that change regionally depending on forest type and structure allometry, the ITC-based models are derived as a function of individual tree allometry and can be extended globally to all tropical forests. The method for lidar detection of individual crown size overcome some limitations of ground-based inventories such as 1) it is able to access crowns of large trees and 2) it enables the assessment of directional changes in tree density, canopy architecture and forest dynamics over large and inaccessible areas to support robust tropical ecological studies.

Separating effects of crown structure and competition for light on trunk growth of Sequoia sempervirens

Tree-level productivity is largely determined by crown size and aboveground vigor, but light availability ultimately controls growth. Competition indices are typically used in modeling instead of actual measurements of light. Our goals were to determine which measure of light best predicts trunk growth increments of Sequoia sempervirens, to quantify the amount of growth variation explained by light after accounting for effects of tree structure, and to compare model fitness of various competition indices. Twenty-four trees spanning a wide range of light environments were randomly selected from stands of different ages, including trees 23–72m tall and 20–560years old. Tree structure and trunk growth increments were quantified via direct measurements of all branches and coring main trunks at multiple heights. Light availability was quantified via hemispherical photography throughout tree crowns. Competition indices were computed by measuring the size and distribution of neighboring trees. The largest tree had 69m3 of wood and bark, 3208m2 of leaf area, and produced 1.04m3yr−1 of wood in the main trunk, whereas the smallest tree had less than 1m3 of wood and bark, 134m2 of leaf area, and produced 0.04m3yr−1 of wood in the main trunk. After accounting for tree structure, light availability explained an additional 10% of variation in trunk wood volume increment. Light availability alone explained 49% of the variation in wood volume increment, while tree size alone explained 41%. The growth model with average mid-crown openness as the measure of light availability was 19 times more likely than the model without a term for light. A distance-dependent competition index computing neighboring tree crown volume (DDCV) was >1200 times more likely than any other competition index in the best growth model. Together with tree size and aboveground vigor, DDCV explained 91% of variation in trunk wood volume increment.

Estimation of acorn production capacity using growth characteristics of Quercus acutissima in a clonal seed orchard

Acorn production varies considerably among individual trees, years, and locations, which directly affect oak regeneration and populations of wildlife species. This study was conducted to estimate the acorn production capacities of trees in a clonal seed orchard (CSO) of Quercus acutissima by analyzing the relationship among morphological characteristics of acorns, growth characteristics of trees, and the number of acorns per tree in 9-year-old and 15-year-old trees, respectively. The age of the tree did not affect individual acorn morphological characteristics (weight, length, and width), but increased the mean acorn yield per tree from 1.26 kg at 9-year-old to 2.71 kg at 15-year-old. The number of acorns per tree showed strong positive correlations (P < 0.0001) with both crown width and crown volume of the tree. According to our equation, it was estimated that the management of tree density (to 180 trees per ha) and crown volume (to 78 m3) may have the maximum acorn production per ha. Therefore, our results suggested that optimal management of tree density and crown volume may be very effective in increasing the acorn production in CSO of Q. acutissima, which further provides an important initial step in establishing a governmental policy for seedling supply plans.

Individual Tree Measurement in Tropical Environment using Terrestrial Laser Scanning

Detailed forest inventory and mensuration of individual trees have drawn attention of research society mainly to support sustainable forest management. This study aims at estimating individual tree attributes from high density point cloud obtained by terrestrial laser scanner (TLS). The point clouds were obtained over single reference tree and group of trees in forest area. The reference tree is treated as benchmark since detailed measurements of branch diameter were made on selected branches with different sizes and locations. Diameter at breast height (DBH) was measured for trees in forest. Furthermore tree height, height to crown base, crown volume and tree branch volume were also estimated for each tree. Branch diameter is estimated directly from the point clouds based on semi-automatic approach of model fitting i.e. sphere, ellipse and cylinder. Tree branch volume is estimated based on the volume of the fitted models. Tree height and height to crown base are computed using histogram analysis of the point clouds elevation. Tree crown volume is estimated by fitting a convex-hull on the tree crown. The results show that the Root Mean Squared Error (RMSE) of the estimated tree branch diameter does not have a specific trend with branch sizes and number of points used for fitting process. This explains complicated distribution of point clouds over the branches. Overall cylinder model produces good results with most branch sizes and number of point clouds for fitting. The cylinder fitting approach shows significantly better estimation results compared to sphere and ellipse fitting models.

Towards an optimized method of olive tree crown volume measurement.

Accurate crown characterization of large isolated olive trees is vital for adjusting spray doses in three-dimensional crop agriculture. Among the many methodologies available, laser sensors have proved to be the most reliable and accurate. However, their operation is time consuming and requires specialist knowledge and so a simpler crown characterization method is required. To this end, three methods were evaluated and compared with LiDAR measurements to determine their accuracy: Vertical Crown Projected Area method (VCPA), Ellipsoid Volume method (VE) and Tree Silhouette Volume method (VTS). Trials were performed in three different kinds of olive tree plantations: intensive, adapted one-trunked traditional and traditional. In total, 55 trees were characterized. Results show that all three methods are appropriate to estimate the crown volume, reaching high coefficients of determination: R2 = 0.783, 0.843 and 0.824 for VCPA, VE and VTS, respectively. However, discrepancies arise when evaluating tree plantations separately, especially for traditional trees. Here, correlations between LiDAR volume and other parameters showed that the Mean Vector calculated for VCPA method showed the highest correlation for traditional trees, thus its use in traditional plantations is highly recommended.

Cattle browsing impacts on stunted Avicennia marina mangrove trees

Mangroves in South Africa are threatened by over-utilization through harvesting for firewood and building materials as well as excessive browsing and trampling by livestock. At Nxaxo Estuary (32°S; 28°E) the response of Avicennia marina to cattle browsing and trampling was investigated by using exclusion plots. These were established by fencing in five 25m2 quadrats and adjacent to each experimental quadrat a browsed quadrat. Trees were tagged and measured annually from 2010 to 2012. Sediment salinity, pH, moisture, organic content, compaction as well as sediment particle size did not differ between browsed and non-browsed quadrats. Significant increases in mean tree height (5.41±0.53cm), crown volume (0.54±0.01m3) and crown diameter (7.09±0.60cm) from 2010 to 2012 were recorded for the non-browsed plots. Trees in the browsed plots had significantly lower growth (p<0.05). The browsed trees were stunted with horizontal spreading of branches while the trees in the non-browsed plots showed an increase in vertical growth and expansion. There was a greater percentage of flowering (54%) and fruiting (19%) for trees in non-browsed plots compared to the browsed sites where 34% of the trees were flowering and 6% of the trees carried immature propagules. The study concluded that browsing changes the morphological structure of mangrove trees and reduces growth and seedling establishment. This is the first study to document the impact of browsing on mangroves.

Comparison of conventional measurement and LiDAR-based measurement for crown structures

Tree crown projection area and crown volume are the important parameters for the estimation of biomass and other forestry science applications. However, it is difficult to validate their accuracy. In this research, measurement errors were quantified based on the 3D virtual LiDAR dataset of 22 common tree species in Beijing, China, which were derived from high-resolution terrestrial laser scanner. The hypotheses include that: (1) primary sources of height measurement are the violations of Total station based on the triangulation theory; (2) approximation of tree crown projections with 4-point fixed angles are not precise enough for irregular crown silhouettes; and (3) tree crown volumes obtained by conventional method with a taper’s formula (VC) are not corresponding to the need of accurate measurement. The relative accuracies derived from total station measurements between crown base height (BT) and tree height (HT) were compared. Meanwhile, different methods for tree crown projections and crown volumes were researched. The results show that the measurement errors of HT (RMSE=4.56m) is higher than that of BT (RMSE=3.35m), VC (RMSE=45.0243m3) is 8.03% on average smaller than VVC (RMSE=48.56094m3), A4 is 25.5% on average larger than AV. The deviations between filed investigation method and virtual 3D LiDAR data could be attributed to irregularity of the crowns’ silhouettes. Based on the results, we propose that: (1) the use of 8-point or 16-point projection with fixed angles to estimate crown projections and (2) different regular volume formula to simulate crown volume according to the tree crown shapes.