Individual Tree Diameter Research Articles

Predicting individual tree growth using stand-level simulation, diameter distribution, and Bayesian calibration

We propose a methodology to develop a preliminary version of a growth model when tree-level growth data are unavailable. This modelling approach predicts individual tree growth using only one-time observations from temporary plots. A virtual dataset was generated by linking the whole stand and diameter distribution models. The individual tree model was parameterized using Bayesian calibration and a likelihood of diameter distributions. A key component of tree-level growth and yield prediction is the diameter increment model that requires at least two different points in time with individual tree measurements. In some cases, however, sufficient inventory data from remeasured permanent or semitemporary plots are unavailable or difficult to access. The purpose of this study was to propose a three-stage approach for modelling individual tree diameter growth based on temporary plots. The first stage is to predict stand dynamics at 5-year intervals based on stand-level resource inventory data. The second stage is to simulate diameter distribution at 5-year intervals using a Weibull function based on tree-level research inventory data. The final stage is to improve the reliability of individual tree diameter estimates by updating parameters with Bayesian calibration based on a likelihood of diameter distributions. The virtual-data-based diameter increment model provided logical patterns and reliable performances in both tree- and stand-level predictions. Although it underestimated the growth of suppressed trees compared with tree cores and remeasurements, this bias was negligible when aggregating tree-level simulations into stand-level growth predictions. Our virtual-data-based modelling approach only requires one-time observations from temporary plots, but provide reliable predictions of stand- and tree-level growth when validated with tree cores and whole-stand models. This preliminary model can be updated in a Bayesian framework when growth data from tree cores or remeasurements were obtained.

Modeling Early Responses of Loblolly Pine Growth to Thinning in the Western Gulf Coastal Plain Region

Abstract Growth response to thinning has long been a research topic of interest in forest science. This study presents the first 3–4 years of response of loblolly pine (Pinus taeda L.) growth to thinning at different intensities. Data were collected from the East Texas Pine Research Project’s region-wide loblolly pine thinning study, which covers a wide variety of stand conditions. Four treatments, light, moderate, and heavy thinning, respectively having 370, 555, and 740 residual trees per hectare after thinning, and an unthinned control, were included. Individual tree diameter at breast height (dbh) and total height were recorded annually for the first 3–4 years after thinning. Results indicate significant differences between treatments in dbh growth in each year after thinning, as well as for all years combined. Each thinning treatment had significantly greater dbh growth than the control in the first growing season with this positive response being more evident in the case of the heavier thinning or at the later years post-thinning. Conversely, the thinning effect on tree height growth was initially negligibly negative, then becoming positive after 2–4 years, with the heavier thinning becoming positive sooner. Tree size class, assigned based on prethinning dbh, had a significant effect on both dbh and height growth responses. Compared to the control, small trees had a greater response both in dbh and in height growth than the medium and large trees over the measurement period. At the stand level, the heavier thinning had significantly less stand basal area per hectare, but the difference in stand basal area per hectare between the thinned and the unthinned plots decreased with years post-thinning. Results from this study can improve our understanding in thinning effects and help forest managers make accurate decisions on silvicultural regimes.

Individual Tree Diameter and Height Growth Models for 30 Tree Species in Mixed-Species and Uneven-Aged Forests of Mexico

Lack of knowledge of individual tree growth in species-rich, mixed forest ecosystems impedes their sustainable management. In this study, species-specific models for predicting individual diameter at breast height (dbh) and total tree height (h) growth were developed for 30 tree species growing in mixed and uneven-aged forest stands in Durango, Mexico. Growth models were also developed for all pine, all oaks, and all other species of the genus Arbutus (strawberry trees). A database of 55,158 trees with remeasurements of dbh and h of a 5-year growth period was used to develop the models. The data were collected from 217 stem-mapped plots located in the Sierra Madre Occidental (Mexico). Weighted regression was used to remove heteroscedasticity from the species-specific dbh and h growth models using a power function of the tree size independent variables. The final models developed in the present study to predict dbh and total tree height growth included size variables, site factors, and competition variables in their formulation. The developed models fitted the data well and explained between 98 and 99% and of the observed variation of dbh, and between 77 and 98% of the observed variation of total tree height for the studied species and groups of species. The developed models can be used for estimating the individual dbh and h growth for the analyzed species and can be integrated in decision support tools for management planning in these mixed forest ecosystems.

Innovative deep learning artificial intelligence applications for predicting relationships between individual tree height and diameter at breast height

BackgroundDeep Learning Algorithms (DLA) have become prominent as an application of Artificial Intelligence (AI) Techniques since 2010. This paper introduces the DLA to predict the relationships between individual tree height (ITH) and the diameter at breast height (DBH).MethodsA set of 2024 pairs of individual height and diameter at breast height measurements, originating from 150 sample plots located in stands of even aged and pure Anatolian Crimean Pine (Pinus nigra J.F. Arnold ssp. pallasiana (Lamb.) Holmboe) in Konya Forest Enterprise. The present study primarily investigated the capability and usability of DLA models for predicting the relationships between the ITH and the DBH sampled from some stands with different growth structures. The 80 different DLA models, which involve different the alternatives for the numbers of hidden layers and neuron, have been trained and compared to determine optimum and best predictive DLAs network structure.ResultsIt was determined that the DLA model with 9 layers and 100 neurons has been the best predictive network model compared as those by other different DLA, Artificial Neural Network, Nonlinear Regression and Nonlinear Mixed Effect models. The alternative of 100 # neurons and 9 # hidden layers in deep learning algorithms resulted in best predictive ITH values with root mean squared error (RMSE, 0.5575), percent of the root mean squared error (RMSE%, 4.9504%), Akaike information criterion (AIC, − 998.9540), Bayesian information criterion (BIC, 884.6591), fit index (FI, 0.9436), average absolute error (AAE, 0.4077), maximum absolute error (max. AE, 2.5106), Bias (0.0057) and percent Bias (Bias%, 0.0502%). In addition, these predictive results with DLAs were further validated by the Equivalence tests that showed the DLA models successfully predicted the tree height in the independent dataset.ConclusionThis study has emphasized the capability of the DLA models, novel artificial intelligence technique, for predicting the relationships between individual tree height and the diameter at breast height that can be required information for the management of forests.

Measuring Individual Tree Diameter and Height Using GatorEye High-Density UAV-Lidar in an Integrated Crop-Livestock-Forest System

Accurate forest parameters are essential for forest inventory. Traditionally, parameters such as diameter at breast height (DBH) and total height are measured in the field by level gauges and hypsometers. However, field inventories are usually based on sample plots, which, despite providing valuable and necessary information, are laborious, expensive, and spatially limited. Most of the work developed for remote measurement of DBH has used terrestrial laser scanning (TLS), which has high density point clouds, being an advantage for the accurate forest inventory. However, TLS still has a spatial limitation to application because it needs to be manually carried to reach the area of interest, requires sometimes challenging field access, and often requires a field team. UAV-borne (unmanned aerial vehicle) lidar has great potential to measure DBH as it provides much higher density point cloud data as compared to aircraft-borne systems. Here, we explore the potential of a UAV-lidar system (GatorEye) to measure individual-tree DBH and total height using an automatic approach in an integrated crop-livestock-forest system with seminal forest plantations of Eucalyptus benthamii. A total of 63 trees were georeferenced and had their DBH and total height measured in the field. In the high-density (>1400 points per meter squared) UAV-lidar point cloud, we applied algorithms (usually used for TLS) for individual tree detection and direct measurement of tree height and DBH. The correlation coefficients (r) between the field-observed and UAV lidar-derived measurements were 0.77 and 0.91 for DBH and total tree height, respectively. The corresponding root mean square errors (RMSE) were 11.3% and 7.9%, respectively. UAV-lidar systems have the potential for measuring relatively broad-scale (thousands of hectares) forest plantations, reducing field effort, and providing an important tool to aid decision making for efficient forest management. We recommend that this potential be explored in other tree plantations and forest environments.

ForestFit: An R package for modeling plant size distributions

Modeling the diameter distribution of trees in forest stands is a frequent application in ecology that supports key biologically and economically relevant management decisions. The choice of model used to represent the diameter distribution and how to estimate its parameters has received much attention in the forestry literature; however, accessible software that facilitates comprehensive comparison of the myriad modeling approaches is not available. To this end, we developed an R package called ForestFit that simplifies estimation of common probability distributions used to model tree diameter distributions, including the two- and three-parameter Weibull distributions, Johnson’s SB distribution, Birnbaum–Saunders distribution, and finite mixture distributions. Frequentist and Bayesian techniques are provided for individual tree diameter data, as well as grouped data. Additional functionality facilitates fitting curves to height-diameter data. The package also provides a set of functions for computing probability distributions and simulating random realizations from common finite mixture models.

Woodpecker cavity establishment in managed forests: relative rather than absolute tree size matters

What kind of tree should be preserved from logging for biodiversity conservation is a matter of debate. Large and old trees are potential candidates due to the structures they can bear, like cavities and other tree-related microhabitats (TreMs). One of the most studied TreM is woodpecker-made cavities, which, in addition to be breeding sites for primary cavity-nesters, are often the main breeding sites for secondary cavity-nesters, especially in managed forests. Therefore, understanding which trees woodpeckers select for cavities is relevant to forest management, especially in management regimes where individual trees are logged or spared, as in retention forestry. We used data from a forest inventory, TreM inventory and woodpecker counts in one-hectare plots in the Black Forest (southwest Germany) to investigate which features make a retention tree suitable for woodpeckers. By employing a resource selection probability function, we tested several variables for their influence on the probability of tree choice by woodpeckers including altitude, tree species, TreM richness and abundance, diameter at breast height (DBH) and deviation from the mean DBH per plot. The results show that the probability of selection by woodpeckers does not correlate with individual tree diameter. Instead, the probability is driven mainly by the deviation from the mean DBH per plot. We were able to identify a relative size for the selection of trees indicating that woodpeckers prefer trees that are about 15–20 cm larger than the mean DBH per plot. Thereby, we argue, that using absolute diameter thresholds to select retention might not be the best management solution in the short-term, as in managed forests woodpeckers might select sub-optimal trees. Apparently, more knowledge concerning relative thresholds, as detected in our study, is required to improve our understanding of the potential ecological value of retention trees.

Inter-tree competitive processes during early growth of an experimental plantation of Eucalyptus pilularis in sub-tropical Australia

Individual tree diameters, heights and crown dimensions were measured over four growth periods, from 2.5 to 6.6 years of age, in a plantation experiment with blackbutt (Eucalyptus pilularis Smith) on a highly productive site in sub-tropical, eastern Australia. The experiment compared several stocking densities at planting (ranging over 816–1667 stems ha−1) and rectangularities of tree espacement (ranging over 1–6). The effects of inter-tree competitive processes on individual tree diameter growth rates were examined using both a partial differential diffusion equation to describe the change with time of the frequency distribution of diameters and by examining which tree size classes were dominating growth. Over all four growth periods, it appeared that inter-tree competition for the light and soil resources necessary for growth was largely symmetric. That is, whilst larger trees would have been occupying more of the above- and below-ground space from which to obtain those resources than smaller trees, all trees would have been able to obtain quantities of each in amounts proportional to their sizes and grow at rates accordingly. However, even at these young ages, a tendency for larger trees to display growth rates disproportionately large relative to their sizes gave early evidence of asymmetric inter-tree competition developing; that involves taller trees denying light to shorter trees through shading, the reverse of which may not occur. These inter-tree competitive interactions became more pronounced both as tree sizes increased with age and when trees were planted more closely to each other. Asymmetric competition is expected to be a major determinant of individual tree size development for a large part of the subsequent growth of the forest. The results are consistent with the forest showing a transition from the first to the second phase of the Binkley et al. model of individual tree growth and development in forest stands.

Evaluation of the FVS-CR diameter growth model in structurally-heterogeneous ponderosa pine (Pinus ponderosa Douglas ex C. Lawson) stands in the Southern Rockies, and potential modifications

Forest managers are increasingly focused on promoting or maintaining forest structural complexity, including the heterogeneity of forest structures within stands. However, many of the forest growth models commonly used by forest managers assume that stands are structurally homogeneous. Therefore, using these forest models to project the development of structurally complex stands may provide inaccurate results. We investigated the accuracy and precision of individual tree growth estimates from an individual tree growth model commonly used by forest managers (Central Rockies Variant of the Forest Vegetation Simulator, FVS-CR) in six structurally heterogeneous ponderosa pine (Pinus ponderosa Douglas ex C. Lawson) stands. Furthermore, we examined whether the addition of non-spatial, semi-distance independent, or spatially explicit indices of local competition to the model improved the accuracy and precision of stand development projections over the 16-year study. We found that while the stand-scale estimates of growth were within the bounds of normal measurement precision, the estimates of individual tree diameter growth had a root mean square error (RMSE) that equated to 44% of the mean individual tree diameter growth. The addition of crown ratio to the model improved estimates more than the other investigated indices by halving the estimated bias and reducing the RMSE of the projected individual tree diameter growth by 4.8%.

Generalized Nonlinear Mixed-Effects Individual Tree Diameter Increment Models for Beech Forests in Slovakia

Individual tree growth and yield models precisely describe tree growth irrespective of stand complexity and are capable of simulating various silvicultural alternatives in the stands with diverse structure, species composition, and management history. We developed both age dependent and age independent diameter increment models using long-term research sample plot data collected from both monospecific and mixed stands of European beech (Fagus sylvatica L.) in the Slovak Republic. We used diameter at breast height (DBH) as a main predictor and other characteristics describing site quality (site index), stand development stage (dominant height and stand age), stand density or competition (ratio of individual tree DBH to quadratic mean diameter), species mixture (basal area proportion of a species of interest), and dummy variable describing stand management regimes as covariate predictors to develop the models. We evaluated eight versatile growth functions in the first stage using DBH as a single predictor and selected the most suitable one, i.e., Chapman-Richards function for further analysis through the inclusion of covariate predictors. We introduced the random components describing sample plot-level random effects and stochastic variations on the diameter increment, into the models through the mixed-effects modelling. The autocorrelation caused by hierarchical data-structure, which is assumed to be partially reduced by mixed-effects modelling, was removed through the inclusion of the parameter accounting for the autoregressive error-structures. The models described about two-third parts of a total variation in the diameter increment without significant trends in the residuals. Compared to the age independent mixed-effects model (conditional coefficient of determination, R c 2 = 0.6566; root mean square error, RMSE = 0.1196), the age dependent model described a significantly larger proportion of the variations in diameter increment ( R c 2 = 0.6796, RMSE = 0.1141). Diameter increment was significantly influenced differently by covariate predictors included into the models. Diameter increment decreased with the advancement of stand development stage (increased dominant height and stand age), increasing intraspecific competition (increased basal area proportion of European beech per sample plot), and diameter increment increased with increasing site quality (increased site index) and decreased competition (increased ratio of DBH to quadratic mean diameter). Our mixed-effects models, which can be easily localized with the random effects estimated from prior measurement of diameter increments of four randomly selected trees per sample plot, will provide high prediction accuracies. Our models may be used for simulating growth of European beech irrespective of its stand structural complexity, as these models have included various covariate variables describing both tree-and stand-level characteristics, thinning regimes, except the climate characteristics. Together with other forest models, our models will be used as inputs to the growth simulator to be developed in the future, which is important for decision-making in forestry.

Short Rotation Eucalypts: Opportunities for Biochar

Eucalypts can be very productive when intensively grown as short rotation woody crops (SRWC) for bioproducts. In Florida, USA, a fertilized, herbicided, and irrigated cultivar planted at 2471 trees/ha could produce over 58 green mt/ha/year in 3.7 years, and at 2071 trees/ha, its net present value (NPV) exceeded $750/ha at a 6% discount rate and stumpage price of $11.02/green mt. The same cultivar grown less intensively at three planting densities had the highest stand basal area at the highest density through 41 months, although individual tree diameter at breast height (DBH) was the smallest. In combination with an organic fertilizer, biochar improved soil properties, tree leaf nutrients, and tree growth within 11 months of application. Biochar produced from Eucalyptus and other species is a useful soil amendment that, especially in combination with an organic fertilizer, could improve soil physical and chemical properties and increase nutrient availability to enhance Eucalyptus tree nutrition and growth on sandy soils. Eucalypts produce numerous naturally occurring bioproducts and are suitable feedstocks for many other biochemically or thermochemically derived bioproducts that could enhance the value of SRWCs.

Individual Tree Diameter Growth Models of Larch–Spruce–Fir Mixed Forests Based on Machine Learning Algorithms

Individual tree growth models are flexible and commonly used to represent growth dynamics for heterogeneous and structurally complex uneven-aged stands. Besides traditional statistical models, the rapid development of nonparametric and nonlinear machine learning methods, such as random forest (RF), boosted regression tree (BRT), cubist (Cubist) and multivariate adaptive regression splines (MARS), provides a new way for predicting individual tree growth. However, the application of these approaches to individual tree growth modelling is still limited and short of a comparison of their performance. The objectives of this study were to compare and evaluate the performance of the RF, BRT, Cubist and MARS models for modelling the individual tree diameter growth based on tree size, competition, site condition and climate factors for larch–spruce–fir mixed forests in northeast China. Totally, 16,619 observations from long-term sample plots were used. Based on tenfold cross-validation, we found that the RF, BRT and Cubist models had a distinct advantage over the MARS model in predicting individual tree diameter growth. The Cubist model ranked the highest in terms of model performance (RMSEcv [0.1351 cm], MAEcv [0.0972 cm] and R2cv [0.5734]), followed by BRT and RF models, whereas the MARS ranked the lowest (RMSEcv [0.1462 cm], MAEcv [0.1086 cm] and R2cv [0.4993]). Relative importance of predictors determined from the RF and BRT models demonstrated that the competition and tree size were the main drivers to diameter growth, and climate had limited capacity in explaining the variation in tree diameter growth at local scale. In general, the RF, BRT and Cubist models are effective and powerful modelling methods for predicting the individual tree diameter growth.

Analyzing the impacts of forest disturbance on individual tree diameter increment across the US Lake States.

Disturbances play a critical role in forest ecosystem dynamics. Disturbances cause changes in forest structure which in turn influence the species composition of the site and alter landscape patterns over time. The impacts of disturbance are seen over a broad spectrum of spatial scales and varying intensities, ranging from biotic agents such as insect and leaf disease outbreaks to abiotic agents such as a windstorm (a stand-replacing disturbance). This study utilized Forest Inventory and Analysis (FIA) data collected between 1999 and 2014 in the US Lake States (Michigan, Minnesota, and Wisconsin) to examine the impacts that disturbances have on the growth of residual trees using species-specific diameter increment equations. Results showed that animal and weather damage were the most common disturbance agents and fires were the least common in the region. Results also indicated that while the diameter increment equations performed well on average (overprediction of 0.08 ± 1.98cm/10years in non-disturbed stands), when the data were analyzed by species and disturbance agent, the model equation was rarely validated using equivalence tests (underprediction of 0.30 ± 2.24cm/10years in non-disturbed stands). This study highlights the importance of monitoring forest disturbances for their impacts on forest growth and yield.

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.

Comparing performance of contrasting distance-independent and distance-dependent competition metrics in predicting individual tree diameter increment and survival within structurally-heterogeneous, mixed-species forests of Northeastern United States

Most studies comparing the predictive performance of distance-independent and -dependent competition metrics have been conducted in even-aged, single species stands. In addition, past studies have generally not considered more sophisticated distance-dependent competition metrics such as open sky-view or light interception indices. Using data from fully stem mapped inventory plots (n = 260) established in structurally complex, mixed-species experimental forests (n = 5) in the Northeastern US, we evaluated prediction performance of one- and two-sided distance-dependent as well as more conventional distance-independent competition metrics in both annualized diameter increment (n = 1735) and probability of survival models (n = 1953) developed across 26 contrasting softwood and hardwood species. Prediction accuracy of non-spatial and spatial models was further assessed by classifying observations by species shade-tolerance, relative tree height, time since harvest, and tree clumping. Our analyses revealed no general superiority of distance-dependent competition metrics over their distance-independent counterparts for either diameter increment or survival, which was particularly true for the latter variable. Distance-dependent metrics tended to outperform distance-independent ones for observations from shade-tolerant species, trees of lower crown classes, and immediately after harvest. However, results on the comparative analysis of the predictive power of the different types of competition metrics under varying stand conditions and situations were often inconsistent and not always conclusive. In addition, model complexity, i.e. number of non-spatial explanatory variables in the base model, strongly affected the performance of distance-dependent competition metrics. Our findings thus appear to support the critical assumption that distance-independent competition metrics are sufficient for most operational growth and yield applications, even in managed, naturally-regenerated and species rich forests.

A novel approach to selecting a competition index: the effect of competition on individual-tree diameter growth of Calabrian pine

In this study, we evaluated the performance of 18 competition indices composed of nine distance-dependent and nine distance-independent indices in explaining the variation in individual-tree diameter growth of Calabrian pine (Pinus brutia Ten.) in the central Mediterranean region of Turkey. The data were obtained from 432 sample plots with varying stand age, site index, and stand density. To evaluate the performance of each competition index, the mean square error reduction approach was used relative to the noncompetition. Also, this study compared fixed and mixed effects models to analyze diameter growth. Statistical analyses showed that the best distance-independent competition indices performed as well as the best distance-dependent competition indices. The distance-independent competition index of Schröder and Gadow (1999; Can. J. For. Res. 29(2): 280–283, doi: 10.1139/x98-199) performed best and is recommended for use in future growth and yield models to be used in the central Mediterranean region of Turkey. Also, the best selection of competitive neighbors was achieved using the area of influence overlap method, whereas the fixed-radius and angle count sampling methods had no significant improvement in quantifying the competition effects. On the other hand, all mixed effects models provided much better fits than their fixed model counterparts.

Validation of two parameter function height diameter models

Eleven nonlinear height diameter models were fitted and developed for Pinus trees based on individual tree height and diameter at breast height data (n=300) collected from block Langate of Kashmir province in India. Fitting of height diameter models using non-linear least square regression showed that all the parameters across all models were significant. In order to test the predictive performance of the models 10- folded cross-validation technique was used in this study. Comparison of AIC, RMSE, ME and Ad-R 2 values for the training and validation data showed that most of the non-linear HD models capture the height diameter relationships for Pinus trees. Validation results suggest that Naslund -2 HD model provide the best height predictions in case of Pinus tree.

Evaluating the influence of stem form and damage on individual-tree diameter increment and survival in the Acadian Region: implications for predicting future value of northern commercial hardwood stands

Northern hardwood species display a variety of forms and defects that can reduce stem quality and complicate their timber management. However, for the most part, growth and yield models do not account for the influence of stem form and damage. This study determined the influence of stem form and damage on growth, survival, and projected future sawlog value among several northern commercial hardwood species. To accomplish this, hardwood trees on 112 permanent plots across three long-term research sites in Maine were assigned stem form and risk classes using a tree classification system developed in New Brunswick. A highly significant influence of stem form and risk on annualized individual-tree diameter increment and survival was found. Inclusion of these equations into a regional growth and yield model highlighted the importance of stem form and defects on long-term simulations as projected stand-level future value was significantly reduced by over 17%, on average (range of 13% to 28%), when compared with projections that did not include that tree-level information. The results highlight the importance of stem form and defects, as well as the need to account for them, in growth and yield applications that assess the forecasted value of commercially important hardwood stands.

Estimating Individual Tree Height and Diameter at Breast Height (DBH) from Terrestrial Laser Scanning (TLS) Data at Plot Level

Abundant and refined structural information under forest canopy can be obtained by using terrestrial laser scanning (TLS) technology. This study explores the methods of using TLS to obtain point cloud data and estimate individual tree height and diameter at breast height (DBH) at plot level in regions with complex terrain. Octree segmentation, connected component labeling and random Hough transform (RHT) are comprehensively used to identify trunks and extract DBH of trees in sample plots, and tree height is extracted based on the growth direction of the trees. The results show that the topography, undergrowth shrubs, and forest density influence the scanning range of the plots and the accuracy of feature extraction. There are differences in the accuracy of the results for different morphological forest species. The extraction accuracy of Yunnan pine forest is the highest (DBH: Root Mean Square Error (RMSE) = 1.17 cm, Tree Height: RMSE = 0.54 m), and that of Quercus semecarpifolia Sm. forest is the lowest (DBH: RMSE = 1.22 cm, Tree Height: RMSE = 1.23 m). At plot scale, with the increase of the mean DBH or tree height in plots, the estimation errors show slight increases, and both DBH and height tend to be underestimated.

A comparison of two methods of data collection for modelling productivity of harvesters: manual time study and follow-up study using on-board-computer stem records

Productivity of a mechanized P. patula cut-to-length harvesting operation was estimated and modelled using two methods of data collection: manual time study and follow-up study using StanForD stem files. The objective of the study was to compare the productivity models derived using these two methods to test for equivalence. Manual time studies were completed on four different machines and their operators. Two Ponsse Bear harvesters fitted with H8 heads, and two Ponsse Beaver harvesters, fitted with H6 heads, were included. All machines were equipped with Ponsse Opti2 information system. All four operators had approximately 1 year of experience working with their respective machines. The four machines worked in separate four-tree-wide harvesting corridors, and they each harvested 200 trees. Individual tree diameter at breast height (DBH), and height measurements were made manually. Subsequently, data on the trees in each study were extracted from the StanForD stem reports from each of the harvesters. Cycle times in the stem reports were determined based on the difference between consecutive harvest timestamps. The two methods were compared in terms of their abilities to estimate equivalent measures for tree DBH, volume, and productivity. In all four cases, significant differences were found between the DBH and volume measures derived using the two methods. Subsequently, the volume measures from the manual methods were used as the basis for productivity calculations. Results of the productivity comparisons found no significant differences between the models developed from the two methods. These results suggest that equivalent productivity models can be developed in terms of time using either method, however volume discrepancies indicate a need to reconcile bark and volume functions with the high variability experienced in the country.