Individual Tree Volume Research Articles

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.

A Direct Measure of Stand Density Based on Stand Growth

Abstract Standardizing gross volume increment on periodic height increment of the dominant trees is a means of minimizing the effects of site quality and age in growth–growing-stock relations; however, volume increment per height increment contains more information than just a normalization method for fitting growth models. This study builds on previous work suggesting that the cumulative sum of the ratios between individual-tree volume increment and height increment may be a direct measure of stand density. We used data from several levels of growing-stock studies for Douglas-fir, ponderosa pine, and red pine to explore this hypothesis. Regression analysis indicated that the sum of the ratios is proportional to(Dqx⋅N), the underlying equation form of Reineke’s stand density index. Stem growth is a function of canopy dynamics, and additional analyses showed that volume added per unit of height growth was also related to canopy architecture, increasing with decreasing live-crown ratio and increasing foliage density. The linkages between growth, canopy architecture, intermediary canopy dynamics, and (Dqx⋅N) support the hypothesis that the sum of the tree ratios between volume increment and height increment is a direct measure of site occupancy due to its association between growth and corresponding resource use.

ALTERNATIVES TO ESTIMATE THE VOLUME OF INDIVIDUAL TREES IN FOREST FORMATIONS IN THE STATE OF MINAS GERAIS, BRAZIL

The objective of this study was to compare different alternatives to estimate the stem volume of individual trees in four different forest formations in the Minas Gerais state, Brazil. The data were obtained in a forest inventory procedure performed by the Minas Gerais Technological Center Foundation. The stem volumes were computed by the Smalian expression up to the outside bark diameter equal to 4 cm. The volume data of outside bark, diameters (DBH) and total heights were used to fit a Schumacher and Hall equation for each forest formation, considering the structures of the linear fixed and mixed models. Next, 100 Multilayer Perceptron artificial neural networks (ANN) were trained in a supervised manner. In addition, we evaluated eight support-vector machine regression (SVMR). The criteria to evaluate the performance of all the alternatives studied were: the correlation between the observed and estimated volumes, the square root of the mean square error and the frequency distribution by percentage relative error class. After the analyzes, all the alternatives were verified to estimate the volume of the individual trees in the different forest formations. Although the alternatives presented close statistics in the validation process, the graphical analysis of the error distribution showed greater precision of the estimates of the mixed linear models for the four formations. Given the results, it is concluded that there is no absolute superiority of one alternative over the others, and that all of them should be evaluated to find the one which best describes or explains the dataset.

Incorporating stand density effects in modeling the taper of red pine plantations

Taper models are used to estimate the diameter at any height along the bole of a tree. Individual tree volume can then be calculated based on these diameters and corresponding heights. As tree diameters are affected by stand density, inside- and outside-bark taper models that incorporate stand density information were developed for trees in red pine (Pinus resinosa Aiton) plantations. Data used in this study came from stem analysis on 150 red pine trees sampled from 30 even-aged, monospecific plantations across Ontario, Canada. A nonlinear mixed-effects approach was applied in fitting these taper models. Several forms of stand density were evaluated for both inside- and outside-bark diameters. A combination of stand densities expressed as [Formula: see text] (BA, basal area; TPH, trees per hectare) explained the most variation in stem taper of trees grown in red pine plantations in Ontario. This variable was highly significant in the regression and improved the predictive accuracies of both inside- and outside-bark taper models. The taper models presented here are dimensionally compatible. Therefore, these models are applicable for data using any system of units without adjusting parameter values.

COMPARISON OF DIFFERENT METHODS OF MEASURING TREE VOLUMES IN THE MUNICIPALITY OF ANAPU, PARÁ, BRAZIL

The objective of this study was to compare three methods of measuring the volume of individual trees used extensively as a basis for adjusting volumetric functions in areas under forest management in the Brazilian Amazon, and verify the influence of species and diameter classes in obtaining the volume of individual trees. A total of 53 sample trees belonging to five species were analyzed and separated into three diametric classes. The real volume (VR) was obtained using Smalian’s method on fixed sections of 2 meters intervals along the stem; the geometric volume (VG) was also obtained by Smalian’s method, but with the lengths of the various sections along the stem. Volume loss (VP) was subtracted from the VR to obtain the usable volume (VA). An ANOVA in a factorial design (5 x 3 x 3) was performed to verify the effect of 5 species, 3 diameter classes, and 3 volume measurement methods (VR, VG, and VA) on the different volumes obtained. The 3 factors did affect the outcome of the analysis, but there were no interactions found between these variables. The volumes obtained by cubic scaling with different lengths (VG) presented a lower mean volume than VR. Although there was no difference between the means of VA and VR, wood loss was 6.5% of the total volume. There is a relationship between section length and volume loss, according to the presence of hollows, twists and cracks in the logs in the largest diameter classes.

K-NEAREST NEIGHBOR AND LINEAR REGRESSION IN THE PREDICTION OF THE ARTIFICIAL FORM FACTOR

k-nearest neighbor and linear regression in the prediction of the artificial form factor . T he proposal of this study was to test whether the performance of the non parametric approach k -Nearest Neighbor ( k -NN), would improve estimates of individual artificial form factor ( f 1.3 ) of trees of the hybrid Eucalyptus urophylla x Eucalyptus grandis compared to the O rdinary L east S quares method. A total of 149 sample-trees were selected , felled , and diameter was measured along the trunk at 10% (d 0. 1 ), 30% (d 0. 3 ), 50% (d 0. 5 ) and 70% (d 0. 7 ) of commercial height and posteriorly at 2m intervals . Mathematical models recognized in the literature for predicting the form factor were adjusted for comparison . The hyperparameter k of optimum adjust ment for the k -NN estimator was obtained by repeated cross-validation. The training data of the k -NN regression model were identical to those used in the adjustment of the linear regression models since m ost multiple linear regression models present problems of collinearity or multicollinearity. The use of the covaria te (d0.3.d0.7)/d1.32 and k = 15 made it possible to construct k -NN models with better generalization capacity. The potential of the k -NN estimator to predict the artificial form factor and thus to obtain less biased estimates of individual tree volumes was demonstrated and considered to be superior to the use of linear regression and average form factors. The k -NN approach can be considered more generic for predicti on of the tree form factor , and its use is recommended when classical linear regression models or other simpler methods do not yield good results.

Form Quotient in Estimating Caatinga Tree Volume

ABSTRACT The heterogeneity of Caatinga vegetation imposes the need for methodological adaptations to obtain reliable estimates of timber resources. Nevertheless, the number of volumetric studies related to biome trees is still restricted, especially in relation to obtaining form factors and quotients. This study proposes the use of a form quotient (FQ) based on the relationship between diameter at breast height and diameter at diameter at ground level and aimed to evaluate its accuracy in estimating individual tree volume in Caatinga forest. The study area is located in the municipality of Contendas do Sincorá, Bahia, Brazil. Precise scaling volume of 100 trees was performed. The obtained results were compared to the precise scaling volumes in order to evaluate how the form quotient behaved in the volume estimation. A comparative analysis of the FQ efficiency was also performed in relation to two conventionally used methods for volume estimation (form factor and adjusted equation). The mean value of the form quotient was very close to the value of the form factor (0.81 and 0.83, respectively). No significant differences were observed between the estimates and the actual values. The form quotient provided satisfactory results in estimating the total volume of Caatinga trees, and may be indicated for the tree physiognomies of the Caatinga biome.

Spatio-Temporal Modeling and Competition Dynamics in Forest Tillage Experiments on Early Growth of Eucalyptus grandis L.

AbstractForest tillage experiments regularly use long-term evaluations of large plots creating temporal and/or spatial correlations among observations. Not modeling these correlations could compromise treatment comparisons. The aim of this study was to evaluate the effect of modeling spatio-temporal (ST) variability in forest tillage experiments. We used different strategies that incorporate spatial and/or temporal correlations in the evaluation of tillage intensity effect in initial Eucalyptus growth as well as evaluate the effect of intraplot mortality and competition dynamics. Three tillage intensities in two contrasting soil conditions were compared for tree height and wood volume. Additionally, we compared the use of three individual growth curves for plant height to evaluate the time needed to reach 2 m in height (T2m). We modeled the spatial correlation of T2m using mixed models. In both sites, ST models were superior for plant height and wood volume per hectare, whereas for individual-tree wood volume, temporal models were superior. Pit planting always had a lower performance than disk harrowing and subsoiler, which behaved similarly. The competition dynamics within the plot because of tree mortality was affected by treatments and site. Modeling ST variability is key to improving treatment comparisons in forest experiments.

Adaptation and productivity of kaliandra for biomass energy source

The development of wood energy forest plantations is one of the government’s strategies to meet national energy needs. Kaliandra (Calliandra calothyrsus) is one tree/shrub species that is potential for biomass energy source due to its rapid growth and high calorific value. This study aims to analyze the level of adaptation and productivity of kaliandra planted in 3 spacing treatments in the Production Forest Management Unit (KPHP) Puncak Ngengas - Batulanteh, Sumbawa. The treatment of spacing applied is 4 m x 1 m or density of 2, 500 trees/ha (J1), 4 m x 2 m or density of 1, 250 trees/ha (J2), and 4 m x 2 m with stripe or density of 1, 850 trees/ha (J3). Measurements of adaptation and plant growth were carried out until 6 months after planting. The results of this study indicate that the J2 treatment showed the best level of adaptation with a survival rate of 89.3%, followed by treatments J3 and J1 with a survival rate of 85.9% and 84.4% respectively. The J3 treatment resulted in the best growth rate of Kaliandra plants with an average diameter of 18.1 mm, an average height of 244.9 cm and the volume of individual trees of 0.00085 m3/tree. The J3 treatment also produced the highest total volume, estimated biomass production and energy productivity compared to other treatments, which were 3.5 m3/ha, 2.7 tons/ha and 51.9 Gj/ha, respectively. Treatment of spacing indicates the influence on the level of tree adaptation and growth and estimation of biomass production and calorific value. However, the treatment of spacing does not show a clear pattern related to the effect of initial spacing on growth and productivity of Kaliandra at the beginning of the year.

Soil respiration negatively correlated with volume gains by a young Pinus radiata clone over five months

It is assumed that greater plant productivity enhances autotrophic respiration (Ra). In a glasshouse trial using a one year old Pinus radiata D. Don clone selected for rapid growth, we examined the relationship between soil respiration, its components and tree growth rates over approximately five months. Soil respiration and Ra were significantly influenced by temperature; the response of heterotrophic respiration (Rh) approached significance. Soil moisture content had no effect on respiration. The productivity of individual clones, measured as volume increment, was not consistently positively correlated with soil respiration across the measurement intervals. Indeed, over the life of the trial it was found that individual tree volume increments were significantly negatively correlated with soil respiration. These results indicate that the most productive trees were associated with lower rates of autotrophic respiration, contradicting past studies. Further work is recommended to determine if this relationship holds true for these, and other, P. radiata clones in forest settings.

Predicting Growing Stock Volume of Eucalyptus Plantations Using 3-D Point Clouds Derived from UAV Imagery and ALS Data

Estimating forest inventory variables is important in monitoring forest resources and mitigating climate change. In this respect, forest managers require flexible, non-destructive methods for estimating volume and biomass. High-resolution and low-cost remote sensing data are increasingly available to measure three-dimensional (3D) canopy structure and to model forest structural attributes. The main objective of this study was to evaluate and compare the individual tree volume estimates derived from high-density point clouds obtained from airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) in Eucalyptus spp. plantations. Object-based image analysis (OBIA) techniques were applied for individual tree crown (ITC) delineation. The ITC algorithm applied correctly detected and delineated 199 trees from ALS-derived data, while 192 trees were correctly identified using DAP-based point clouds acquired from Unmanned Aerial Vehicles (UAV), representing accuracy levels of respectively 62% and 60%. Addressing volume modelling, non-linear regression fit based on individual tree height and individual crown area derived from the ITC provided the following results: Model Efficiency (Mef) = 0.43 and 0.46, Root Mean Square Error (RMSE) = 0.030 m3 and 0.026 m3, rRMSE = 20.31% and 19.97%, and an approximately unbiased results (0.025 m3 and 0.0004 m3) using DAP and ALS-based estimations, respectively. No significant difference was found between the observed value (field data) and volume estimation from ALS and DAP (p-value from t-test statistic = 0.99 and 0.98, respectively). The proposed approaches could also be used to estimate basal area or biomass stocks in Eucalyptus spp. plantations.

Computational techniques applied to volume and biomass estimation of trees in Brazilian savanna

The Brazilian Savannah, known as Cerrado, has the richest flora in the world among the savannas, with a high degree of endemic species. Despite the global ecological importance of the Cerrado, there are few studies focused on the modeling of the volume and biomass of this forest formation. Volume and biomass estimation can be performed using allometric models, artificial intelligence (AI) techniques and mixed regression models. Thus, the aim of this work was to evaluate the use of AI techniques and mixed models to estimate the volume and biomass of individual trees in vegetation of Brazilian central savanna. Numerical variables (diameter at height of 1.30 m of ground, total height, volume and biomass) and categorical variables (species) were used for the training and fitting of AI techniques and mixed models, respectively. The statistical indicators used to evaluate the training and the adjustment were the correlation coefficient, bias and Root mean square error relative. In addition, graphs were elaborated as complementary analysis. The results obtained by the statistical indicators and the graphical analysis show the great potential of AI techniques and mixed models in the estimation of volume and biomass of individual trees in Brazilian savanna vegetation. In addition, the proposed methodologies can be adapted to other biomes, forest typologies and variables of interest.

The utility of terrestrial photogrammetry for assessment of tree volume and taper in boreal mixedwood forests

Key MessageThis study showed that digital terrestrial photogrammetry is able to produce accurate estimates of stem volume and diameter across a range of species and tree sizes that showed strong correspondence when compared with traditional inventory techniques. This paper demonstrates the utility of the technology for characterizing trees in complex habitats such as boreal mixedwood forests.ContextAccurate knowledge of tree stem taper and volume are key components of forest inventories to manage and study forest resources. Recent developments have seen the increasing use of ground-based point clouds, including from digital terrestrial photogrammetry (DTP), to provide accurate estimates of these key forest attributes.AimsIn this study, we evaluated the utility of DTP based on a small set of photos (12 per tree) for estimating stem volume and taper on a set of 15 trees from 6 different species (Populus tremuloides, Picea glauca, Pinus contorta latifolia, Betula papyrifera, Picea mariana, Abies balsamea) in a boreal mixedwood forest in Alberta, Canada.MethodsWe constructed accurate photogrammetric point clouds and derived taper and volume from three point cloud–based methods, which were then compared with estimates from conventional, field-based measurements. All methods were evaluated for their accuracy based on field-measured taper and volume of felled trees.ResultsOf the methods tested, we found that the point cloud–derived diameters in a taper curve matching approach performed the best at estimating diameters at the lowest parts of the stem (< 30% of total tree height), while using known DBH and height provided more accurate estimates for the upper parts of the stem (> 50% of total height). Using the field-measured DBH and height as inputs to calculate stem volume yielded the most accurate predictions; however, these were not significantly different from the best point cloud-based estimates.ConclusionThe methodology confirmed that using a small set of photographs provided accurate estimates of individual tree DBH, taper, and volume across a range of species and size gradients (10.8–40.4 cm DBH).

Biomass quantification of Pinus taeda L. from remote optical sensor data

This research aimed to estimate the biomass of the trunk area of a Pinus taeda L. stand from vegetation indices from Landsat-8/OLI and Sentinel-2/MSI optical remote sensors. In order to obtain the biomass, a forest inventory was carried out with the installation of 33 circular plots of 400 m², in which all the individuals had the diameter at breast height (cm) and the total height (m) measured. Then, 30 trees were scaled by the Smalian method. The individual tree volume was estimated by the Meyer regression volumetric equation. The biomass was obtained through the product of the individual tree volume by the wood basic density. Subsequently, aerial biomass was obtained per plot. The processed orbital images were gathered from the Landsat-8/OLI and Sentinel-2/MSI sensors. We derived 19 vegetation indices for both images, which were correlated with the biomass per plot. The indexes with the best correlation with the biomass were considered as regression variables to develop models by the Stepwise technique (Backward and Forward). The correlation was significant among the variables and the best model was derived from the Landsat-8 data, which estimated the biomass per plot with an error of 8.75% and an adjusted coefficient of determination of 0.8173. Nevertheless, the statistical analysis revealed that there was no significant difference between the biomass estimated by the inventory and by the remotely located data.

Intra-annual Ips typographus outbreak monitoring using a multi-temporal GIS analysis based on hyperspectral and ALS data in the Białowieża Forests

Disturbances caused by biotic and abiotic agents are inherent processes of forest ecosystems and often play a key role in forming the ecosystems themselves. However, they also may negatively affect wood production and alter ecosystem services. Thus, precise and up-to-date spatial information on invasion presence and dynamic is essential when planning protective and sanitary actions. Gathering such data is still challenging if large areas, with limited access, are affected.This study addresses this issue by suggesting a GIS-workflow based on high-resolution multi-temporal remote sensing data to describe the spread of a bark beetle outbreak by mapping dead trees on a single tree level and estimating timber losses associated with the infestations in the Polish part of the Białowieża Forest (BF) in 2015.Along with field inventories, airborne hyperspectral data were collected in 2015 at three acquisition dates: 2–4 July, between August 24th and 27th and between 1st and 2nd October with a HySpex VNIR-1800 camera. Airborne laser scanning data were collected during 2–5 July 2015 using a Riegl LMS-Q680i scanner. The analysis consisted of three steps: (i) hyperspectral images were used to stratify the area into living vegetation and all other classes (including dead trees); (ii) a single tree delineation was performed and individual tree volumes were calculated based on a volume ∼ height allometry; (iii) the delineated trees were assigned as either living trees or dead trees (snags). Based on these data bark beetle dynamics between the three time steps were analysed.The results show that the Ips typographus outbreak in BF in 2015 was very dynamic. The volume of dead standing spruce detected in subsequent dates was as follows: July – 503 410 m3; August – 640 692 m3; October – 737 978 m3 New groups of dead trees in the flat landscape of Białowieża forest appeared preferably but not only in the immediate vicinity of trees classified as dead in the previous period. New infestations were also identified over 100 m away from earlier infested trees. On the other hand, we could not identify any tendencies in terms of the spread direction which makes the prediction of the spread-dynamics challenging in our study area.

EFFECT OF INDIVIDUAL TREE VOLUME ON OPERATIONAL PERFORMANCE OF HARVESTER PROCESSOR

The need to obtain multi-products from the forest makes the wood processing an important step in the timber harvest, being necessary, then, to understand the influence of the stand characteristics on the operational performance of the machines. The aim of this study was to evaluate the effect of the individual tree volume on the operational performance of the harvester forest processor in Pinus taeda L. stands, in order to assist in planning operations and reducing production costs. The analyzes were carried out by means of a time and motion study, determining the time consumed in the phases of the operational cycle, mechanical availability, operational efficiency, productivity, and production costs in three stands with different individual mean volumes (IMV): I (1.21 m3 tree-1); II (1.34 m3 tree-1) and III (1.61 m3 tree-1). In a completely randomized design, the averages of the variables were compared, as well as models for estimating productivity and production costs were fitted according to individual tree volume. The results showed that the processing element consumed a significant part of the total operational cycle time, with 46, 53 and 64% in treatments I, II and III, respectively, with an average operational efficiency of 56% in all treatments. Productivity increase and reduction of production costs were observed in the order of 43 and 30%, respectively, with the increase in IMV from 1.21 to 1.61 m3 tree-1. Such behavior can be represented by the third degree polynomial, which demonstrated the operational limit of 1.5 m3 tree-1 for the harvester forest processor.

The growth and production modeling of individual trees of Eucalyptus urophylla plantations

Individual tree models (ITMs) are classified as growth and production models for projecting current and future forest stands. ITMs are more complex than other growth and production models, show a higher level of detail and, consequently, produce a better modeling resolution. However, the accuracy and efficiency of ITMs have not been properly assessed to date. In this study, we estimated the growth in height, diameter, and individual tree volume of a Eucalyptus urophylla plantation by applying an ITM. We used a continuing forest inventory dataset in which 1554 individual trees within 29 permanent plots were measured in the field over a 6-year period (24 to 72 months). Each individual tree volume was estimated for future tree age. To achieve this, we adjusted the model to predict the height and diameter growth, and the probability of mortality as a function of the competition index. The ITM accuracy was assessed based on the analysis of variance results and, subsequently, the multiple mean comparison test at the 5% significance level. The tree volumes predicted by the ITM for the forest stand aged 72 months, beginning at ages 24, 36, 48, and 60 months, were compared to the field measured tree volume acquired from the 72-month forest inventory that was used as the reference age. Estimated and observed tree volumes were similar when the estimation was based on the 48-month forest plots. These results might help to reduce financial costs of forest inventory because the ITM produces accurate future predictions of forest stand stocks. Our estimated ITM for Eucalyptus plantations using measurement intervals up to 2 years is recommended because it significantly reduced the projected volume discrepancy compared to the field measurements.

A Concave Hull Methodology for Calculating the Crown Volume of Individual Trees Based on Vehicle-Borne LiDAR Data

Crown volume is an important tree factor used in forest surveys as a prerequisite for estimating biomass and carbon stocks. This study developed a method for accurately calculating the crown volume of individual trees from vehicle-borne laser scanning (VLS) data using a concave hull by slices method. CloudCompare, an open-source three-dimensional (3D) point cloud and mesh processing software package, was used with VLS data to segment individual trees from which single tree crowns were extracted by identifying the first branch point of the tree. The slice thickness and number to be fitted to the canopy point cloud were adaptively determined based on the change rate in area with height, with the area of each slice calculated using the concave hull algorithm with portions of the crown regarded as truncated cones. The overall volume was then calculated as the sum of all sub-volumes. The proposed method was experimentally validated on 30 urban trees by comparing the crown volumes calculated using the proposed method with those calculated using five existing methods (manual measurement, 3D convex hull, 3D alpha shape, convex hull by slices, and voxel-based). The proposed method produced the smallest average crown volume. Gaps and holes in the point cloud were regarded as part of the crown by the manual measurement, 3D convex hull, and convex hull by slices method, resulting in the calculated volume being higher than the true value; the proposed method reduced this effect. These results indicate that the concave hull by slices method can more effectively calculate the crown volume of a single tree from VLS data.

Estimating Tree Volume Distributions in Subtropical Forests Using Airborne LiDAR Data

Accurate and reliable information on tree volume distributions, which describe tree frequencies in volume classes, plays a key role in guiding timber harvest, managing carbon budgets, and supplying ecosystem services. Airborne Light Detection and Ranging (LiDAR) has the capability of offering reliable estimates of the distributions of structure attributes in forests. In this study, we predicted individual tree volume distributions over a subtropical forest of southeast China using airborne LiDAR data and field measurements. We first estimated the plot-level total volume by LiDAR-derived standard and canopy metrics. Then the performances of three Weibull parameter prediction methods, i.e., parameter prediction method (PPM), percentile-based parameter recover method (PPRM), and moment-based parameter recover method (MPRM) were assessed to estimate the Weibull scale and shape parameters. Stem density for each plot was calculated by dividing the estimated plot total volume using mean tree volume (i.e., mean value of distributions) derived from the LiDAR-estimated Weibull parameters. Finally, the individual tree volume distributions were generated by the predicted scale and shape parameters, and then scaled by the predicted stem density. The results demonstrated that, compared with the general models, the forest type-specific (i.e., coniferous forests, broadleaved forests, and mixed forests) models had relatively higher accuracies for estimating total volume and stem density, as well as predicting Weibull parameters, percentiles, and raw moments. The relationship between the predicted and reference volume distributions showed a relatively high agreement when the predicted frequencies were scaled to the LiDAR-predicted stem density (mean Reynolds error index eR = 31.47–54.07, mean Packalén error index eP = 0.14–0.21). In addition, the predicted individual tree volume distributions predicted by PPRM of (average mean eR = 37.75) performed the best, followed by MPRM (average mean eR = 40.43) and PPM (average mean eR = 41.22). This study demonstrated that the LiDAR can potentially offer improved estimates of the distributions of tree volume in subtropical forests.

Initial spacing of teak (Tectona grandis) in northern Lao PDR: Impacts on the growth of teak and companion crops

Teak (Tectona grandis) has been planted extensively by smallholder farmers in Luang Prabang province of northern Laos, primarily in small woodlots established at high initial stocking rates with little/no management until the largest trees are harvested selectively, commencing at 15–20 years after planting. This study used a Nelder wheel experiment planted in 2008, and measured annually after the end of the first 10 growing seasons, to evaluate the effects of the initial planting density on the growth of teak. The potential for intercropping established teak was also evaluated using this Nelder wheel, when the trees were 5–6 years of age, to emulate what might be achievable from companion cropping under an agroforestry system with teak. Individual tree diameter was maximised at the lowest initial stocking, but tree height showed optimum development between 637 and 1020 trees ha−1. While standing volume (m3 ha−1) was maximised at the highest initial stocking (2424 trees ha−1), merchantable volume maximised at initial stocking rates between 423 and 637 trees ha−1. Companion cropping demonstrated that modest yields of maize, cassava and pigeon pea are possible under established teak, where the spacing between trees exceeds 8 m. Both maize and cassava achieved yields of over 2 t ha−1 with a spacing of 8 m between trees, while pigeon pea achieved 3 t ha−1 at 10 m spacing between trees. These results demonstrate that the adoption of reduced initial stocking rates for teak (i.e. below 1000 trees ha−1) can significantly increase the growth rates of teak, improving individual tree volumes, and potentially reducing time to commercial harvest. Further, where row spacing is at least 8–10 m, these results suggest that extended periods of companion cropping (2–6 years after planting) may be possible. Finally, given that Lao farmers are reluctant to adopt pre-commercial thinning, serious consideration should be given to the promotion of simple, regimes for teak woodlots using an initial stocking rate of around 600 trees ha−1. Alleys widths of 10 m are recommended for farmers wishing to establish grow teak in an agroforestry system and extend the period for companion cropping. Nevertheless, revision of Government of Lao policy frameworks are required to support the adoption of more appropriate initial spacing in teak woodlots and agroforestry systems by smallholders.