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Taper equations are indispensable tools for characterizing the stem profile of trees, providing valuable insights for forest management, timber inventory, and optimal assortments allocation. The recent progress in Terrestrial Laser Scanning (TLS) has revolutionized forest inventory practices by enabling non-destructive data collection. In this study, four taper models from three different model categories were established based on point cloud data of 219 Pinus nigra trees. The taper equations fitted with TLS data were used to predict the diameter at specific stem heights and the total stem volume. The results show that among fitted models, the Max and Burkhart segmented model calibrated by the means of a mixed-effects approach provided the best estimate of the diameter at different heights and the total stem volume evaluated for different diameter at breast height (DBH) classes. In numerical terms, this model estimated the diameter and the volume with a respective overall error of 0.781 cm and 0.021 m3. The predicted profile also shows that above a relative height of 0.7, the diameter error tends to increase due to the low reliability of data collected beyond the base of the crown primarily caused by interference from branches and leaves. Nevertheless, this study shows that TLS technology presents a compelling opportunity and a promising non-destructive alternative for generating taper profiles and estimating tree volume.

Quantifying nitrogen uptake rates across different forest types is critical for a range of ecological questions, including the parameterization of global climate change models. However, few measurements of forest nitrogen uptake rates are available due to the intensive labor required to collect in situ data. Here, we seek to optimize data collection efforts by identifying measurements that must be made in situ and those that can be omitted or approximated from databases. We estimated nitrogen uptake rates in 18 mature monodominant forest stands comprising 13 species of diverse taxonomy at the Morton Arboretum in Lisle, IL, USA. We measured all nitrogen concentrations, foliage allocation, and fine root biomass in situ. We estimated wood biomass increments by in situ stem diameter and stem core measurements combined with allometric equations. We estimated fine root turnover rates from database values. We analyzed similar published data from monodominant forest FACE sites. At least in monodominant forests, accurate estimates of forest nitrogen uptake rates appear to require in situ measurements of fine root productivity and are appreciably better paired with in situ measurements of foliage productivity. Generally, wood productivity and tissue nitrogen concentrations may be taken from trait databases at higher taxonomic levels. Careful sorting of foliage or fine roots to species is time consuming but has little effect on estimates of nitrogen uptake rate. By directing research efforts to critical in situ measurements only, future studies can maximize research effort to identify the drivers of varied nitrogen uptake patterns across gradients. [ABSTRACT FROM AUTHOR]

Trestima® is a computer vision-based smartphone application that utilises relascope theory to obtain estimates of forest attributes from smartphone photographs. The aim of this study was to investigate the accuracy of Trestima estimation and evaluate whether it is sufficiently accurate for operational use in forestry. Our data consisted of 37 forest stands, encompassing 73.5 ha in southeastern Finland, where Trestima estimates were obtained by forestry professionals during their work. The results were compared with harvester data obtained from clear-cut stands. The number of photographs taken per stand ranged between 1-29 (average: 7.3; standard deviation: 5.0). The total amount of industrial roundwood harvested from the stands was 21.531 m3 and the average harvest removal per hectare was 282 m3. The accuracy of Trestima estimation was relatively good when ≥ 10 photographs per stand were taken. In this case, the root mean square error percent (RMSE%) value associated with roundwood volume was 17.7%. When the number of photographs per stand was < 10, the accuracy of Trestima was much weaker (RMSE% 22.7-55.3%). On average, Trestima underestimated harvested volumes in Scots pine (Pinus sylvestris L.) stands (Bias% 11.4-89.2), although the bias was smaller (Bias% -12.7-12.4) with Norway spruce (Picea abies [L.] Karst.) stands. The Trestima smartphone application is a possible option for traditional field measurements in operational forestry, provided that its usage instructions are strictly followed, which is not always the case in practice.

Ecologically and economically sustainable planning of forest resources requires tools capable of providing estimates with adequate accuracy on volume, biomass and woody increments. Interest in these attributes has increased since the United Nations Framework Convention on Climate Change has been given a further boost by the birth of the carbon credit market in the early 2000s. However, the data collection necessary to formulate allometric models for estimating wood volume is challenging, both due to the considerable amount of data required and because the necessary destructive measurements are very laborious. Furthermore, given the great structural, managerial and environmental diversity that characterizes the Italian forests, the sample size for the development of allometric models must necessarily be large. Over the years, all these aspects have led to a progressive abandonment of measurements in the forests for the production of volume tables. Recent applications of the terrestrial laser scanner (TLS) for collecting dimensional information on trees have demonstrated their effectiveness. In this study we present the work carried out in the autumn/winter 2022-2023 for the creation of new volume tables for the black pine forests in Vallombrosa (FI - Central Italy), based on data collected with a TLS. The study involved the same pine forests studied in 1969 for the production of volume tables in Vallombrosa. After showing the methods and analysis needed to obtain the volume tables, the paper discusses the results in comparison with those produced in 1969.

Ecologically and economically sustainable planning of forest resources requires tools capable of providing estimates with adequate accuracy on volume, biomass and woody increments. Interest in these attributes has increased since the United Nations Framework Convention on Climate Change has been given a further boost by the birth of the carbon credit market in the early 2000s. However, the data collection necessary to formulate allometric models for estimating wood volume is challenging, both due to the considerable amount of data required and because the necessary destructive measurements are very laborious. Furthermore, given the great structural, managerial and environmental diversity that characterizes the Italian forests, the sample size for the development of allometric models must necessarily be large. Over the years, all these aspects have led to a progressive abandonment of measurements in the forests for the production of volume tables. Recent applications of the terrestrial laser scanner (TLS) for collecting dimensional information on trees have demonstrated their effectiveness. In this study we present the work carried out in the autumn/winter 2022-2023 for the creation of new volume tables for the black pine forests in Vallombrosa (FI -- Central Italy), based on data collected with a TLS. The study involved the same pine forests studied in 1969 for the production of volume tables in Vallombrosa. After showing the methods and analysis needed to obtain the volume tables, the paper discusses the results in comparison with those produced in 1969. [ABSTRACT FROM AUTHOR]

This study investigated the initial growth, survival rate, and biomass content of Khaya senegalensis in a pure plantation system and under an agroforestry system (AFS) with banana and corn. The experiment was carried out in Northeast Brazil and measurements were made when trees were 30 months old. Spacing was 3 × 2 m and 3.5 × 3.5 m in pure plantation and in AFS, respectively. Banana and corn amounted to roughly 816 and 28.000 plants per ha for pure and AFS, respectively. The survival rate (99.7 × 96.1%) and wood density (595 × 551 kg dm−3) showed no difference between both systems. Individual growth was similar between both systems (0.0068 m3 tree−1). However, at the stand scale, yield was higher in pure plantation with a mean annual increase of 3.07 m3 ha−1 year−1, which means 129% higher than in AFS (1.34 m3 ha−1 year−1). Nevertheless, AFS added 20 and 8 t ha−1 of banana and green corn. Aboveground biomass accumulated at 30 months was 144% higher in the pure plantation (7.11 × 2.92 t ha−1), mainly leaf biomass, which was 228% higher in relation to AFS. In long rotation silvicultural systems like those used for African mahogany, only 100–400 trees per hectare will remain until the end of the rotation. As there was no difference in individual growth between the two systems, the AFS could be a very interesting alternative to mitigate establishment costs and optimizing land use with the production of agricultural crops specially to small farmers. [ABSTRACT FROM AUTHOR]

Studies that seek to identify potential techniques for obtaining diameter values at 1.30 m from the ground from tree height data are necessary, especially when considering the use of airborne Lidar in forest inventory activity. In this sense, this work aimed to evaluate two artificial intelligence tools for this purpose, namely the neurofuzzy inference systems and the artificial neural networks. Four models were tested to obtain estimates for the diameter variable, which were prepared by combining the independent variables useful area per plant, age and height. After processing, the statistics of bias, square root of the mean squared error in percentage, correlation and mean percentage error were calculated, in addition to the preparation of scatter plots and histogram of residues. It was observed that, for the estimation of the diameter in both techniques, the use of the model with all independent variables obtained the best values for the analysis statistics. It can be concluded that both tools can be used to estimate the diameter, with the neuro-fuzzy inference system being more suitable for its processing speed and small variability between the values obtained in different training sessions for the same database. [ABSTRACT FROM AUTHOR]

Forests provide a wide range of ecosystem services and information requirements on forests have grown considerably. Nevertheless, collecting information in the forest is expensive and for this reason assessment of forest resources strongly relies on statistical sampling. However, plot measurement remains essential even when remote-sensing data are used, and field assessments are still among the costliest components of forest inventories. Studies on the costs for plots survey are limited and usually based on expert evaluation rather than on data. This article analysed the relationship between the time needed for measuring forest plots and their site-related characteristics (slope, terrain roughness), stand features (number of trees, subsample trees, stumps, coarse woody debris, understorey vegetation) and protocol-related procedures, by means of univariate and multivariate analyses. Analyses showed that the time needed for measuring plots depends on the workload or the intensity of fieldwork. Especially, the number of variables surveyed matters, because the variables explained the measuring time variation by an additive effect, suggesting that within a complex field protocol the total number of measurements taken may not represent properly the overall intensity of work. Marking in an effective way permanent plots is recommendable because the retrieval success of the pins buried into the ground was the most important explanatory variable. Presence of understorey vegetation was more important than the number of individuals measured. The results obtained are consistent and logical, but the variance explained was limited, suggesting that predictability of the measuring time under complex field protocols might be intrinsically limited by the interactions among factors with opposite effects and especially by the adaptation of the surveyors to specific circumstances. For example, effects of physical tiredness were not detected in the days when two plots were measured; conversely, measuring a second plot reduced the measuring time of the first, an event most likely dependent on the surveyors’ behaviour. Under the conclusion that predictability is low by nature, the inference of studies based on simulation data and simplified protocols to practical applications was finally discussed. [ABSTRACT FROM AUTHOR]

Araucaria angustifolia (Bertol.) Kuntze, commonly known as Brazilian pine, is a significant tree species in the Brazilian flora that once covered an area of 200,000 km2 in the Southern region. During the 1970s, high-quality timber logs from this conifer became the primary export product of the country. However, the species is endangered due to uncontrolled exploitation and is subject to a harvesting ban. It is crucial, therefore, to explore sustainable cultivation methods for this species, which necessitates urgent research and scientific insights. In this study, we present a simulation of a management strategy for in situ conservation by manipulating growth space and crown size dynamics. Forest inventory data and mixed forest regression equations were employed to describe the horizontal dimensions of average and maximum potential crown growth, resulting in two management scenarios. The results presented in management diagrams show that both approaches required logging numerous trees to ensure adequate space for healthy tree growth and provide soil coverage and forest protection. Therefore, the absence of effective forest management initiatives for Araucaria forests may have further implications for the structure, production, conservation, and overall development. To address these challenges, we propose two hypotheses: firstly, that tree diameter depends on crown dimensions, which are in turn influenced by tree growth space, and, secondly, that crown dimensions serve as a reliable indicator of existing competition and can be utilized to simulate forest management practices. We urge that implementing sustainable forest management initiatives for Araucaria angustifolia at selected locations can contribute to expanding natural forest areas, mitigate deterioration caused by high competition, discourage illegal logging, and prevent overexploitation of their edible seeds, which hinders regeneration. Our results underscore the significant implications of the lack of forest management initiatives in rural properties, potentially resulting in irreversible deterioration. The exact consequences of this deterioration remain unclear, emphasizing the need for further studies to understand its eventual effects on the growth reaction of trees of different diameters, ages, and crown conditions after the liberation of their crowns. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Ciencias Agricolas is the property of University of Narino, Faculty of Agricultural Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The complexity in the management of field tools for recording dasometric information has led to the use of allometric equations that save time, work, and costs allowing the estimation of variables that are difficult to record, such as total height (TH). The objective of this research was to develop an allometric equation for the species Alnus acuminata in order to calculate TH from the diameter at breast height (DBH). At the Obonuco-AGROSAVIA Research Center in Pasto (Nariño), dasometric information was recorded for 75 months for 200 even-aged trees. Four models were evaluated: linear, polynomial, Mixed linear (random effect per tree age), and Mixed linear (random effect per tree). For the selection of the best model, the criteria were used with the lowest values ​​of Akaike (AIC) and Bayesian (BIC). The information was analyzed using the "Nonlinear Mixed-Effects Models" package, R software. The results revealed that A. acuminata had an 81% survival; the TH average was 7.4 ± 1.3 m; and the average DBH was 9.51 ± 2.23cm. The average annual increase of DBH was 1.5 cm year-1, and the TH was 1.18 m∙ per year-1. The mixed linear model confirmed the assumptions of normality, independence, and homogeneity of variances in addition of having good criteria in its predictive performance and efficiency through the equation TH=2.07+0.35*DBH+0.95*Age. This research contributes to the management of native species of the high tropics by designing an equation for the first vegetative growth phases of A. acuminata in high mountain agroecological zones.

Degraded vegetation is the result of a process that affects structural and functional characteristics. Tree species from the Acacia genus are very important to the ecosystem in semi-arid lands due to their participation in the recovery of highly degraded areas. One of the most important species among this genus is A. schaffneri. The status of a forest stand is determined according to its structure, including height, stratum and density. Remote sensing is a valuable method for estimating volumetric stocks and associated changes in forest populations over established periods of time. The objective of this research was to estimate wood volume of A. schaffneri using remote sensing, and to complement that information with the results obtained from an estimation method based on forest measurements. The results obtained showed that the crown area was the dendrometric variable that can be used in a wood volume prediction model. In the exploratory analysis between dendrometric variables and remote sensing showed low and negative associations were observed in the four stations analyzed. There are conservation problems due to anthropogenic activities, among which stands out the intensive grazing that results in a decrease of the natural regeneration capacity of Acacia schaffneri.

Background: Urban tree inventories are fundamental to the monitoring and management of urban forests. Various handheld tools and methods exist to conduct tree mensuration, ranging from the simple stick method to laser rangefinders. This study examines the accuracy and precision of the stick method, clinometer, and laser rangefinder, and introduces tree type (i.e., conifer versus broadleaf) comparisons of accuracy and precision. Methods: Measurements were taken from 127 trees comprised of 85 (66.9%) broadleaf and 42 (33.1%) coniferous trees. Trees were distributed across 4 urban land use types: park, golf course, street, and trail system. A drone-mounted measurement tape was used to determine true height. Results: Measured heights ranged from 4.67 m to 25.71 m (x = 13.19 m). Measurements from the stick method yielded statistically similar results to both the rangefinder and clinometer methods. The methods had a Cronbach's Alpha of 0.991 (N = 3). Accuracy was highest for the rangefinder and lowest for the stick method. Precision was greatest between the rangefinder and the clinometer. Root-mean-square error (RMSE) and percent error were highest for the stick method and broadleaf trees for all 3 measurement methods. Conclusions: The findings indicate greater accuracy and precision across all tools when measuring conifers. The rangefinder was similar in accuracy to the clinometer, with notable changes in accuracy when using the stick method. [ABSTRACT FROM AUTHOR]

Unmanned aerial systems (UASs) and structure-from-motion (SfM) image processing are promising tools for sustainable forest management as they allow for the generation of photogrammetrically derived point clouds from UAS images that can be used to estimate forest structure, for a fraction of the cost of LiDAR. The SfM process and the quality of products produced, however, are sensitive to the chosen flight parameters. An understanding of the effect flight parameter choice has on accuracy will improve the operational feasibility of UASs in forestry. This study investigated the change in the plot-level accuracy of top-of-canopy height (TCH) across three levels of flying height (80 m, 100 m, and 120 m) and four levels of forward overlap (80%, 85%, 90%, and 95%). A SenseFly eBee X with an Aeria X DSLR camera was used to collect the UAS imagery which was then run through the SfM process to derive photogrammetric point clouds. Estimates of TCH were extracted for all combinations of flying height and forward overlap and compared to TCH estimated from ground data. A generalized linear model was used to statistically assess the effect of parameter choice on accuracy. The RMSE (root-mean-square error) of the TCH estimates (RMSETCH) ranged between 1.75 m (RMSETCH % = 5.94%) and 3.20m (RMSETCH % = 10.1%) across all missions. Flying height was found to have no significant effect on RMSETCH, while increasing forward overlap was found to significantly decrease the RMSETCH; however, the estimated decrease was minor at 4 mm per 1% increase in forward overlap. The results of this study suggest users can fly higher and with lower levels of overlap without sacrificing accuracy, which can have substantial time-saving benefits both in the field collecting the data and in the office processing the data. [ABSTRACT FROM AUTHOR]

Current study evaluates the vegetal development of Schizolobium parahyba var. amazonicum (Huber x Ducke) Barneby), commonly known as paricá, in pasturelands in the process of restoration in the Mosaic of Conservations Units of Carajás PA Brazil. The area comprises the connectivity program of forest fragments. They are degraded areas, previously occupied by pastures, which are at present being recuperated with native forest. Evaluation of the development of parica plants comprised plant height, diameter at breast height, cubing and canopy projection. Experimental data underwent regression analysis and Pearson's co-relation. As from strict cubing by Smalian method, a mean factor equal to 0.55 and a strong positive co-relationship with diameters and heights (r=0.83 and r=0.86) were determined. Cubing data helped in the adjustment of a mathematical model of double entry (diameter at breast height and height as independent variables) for estimating form factor in which regression adjustment statistics resulted in relatively high rates for the coefficient of determination (R² = 0.78) and low rates for standard estimation error (R² = 0.05). By applying the Schumacher-Hall's logarithm method for volume estimates, good statistical adjustments were obtained with a high coefficient of determination (R² = 0.99), low standard estimate error (R² = 0.07) and residual dispersion without biases. [ABSTRACT FROM AUTHOR]

Understanding the essential contribution of eucalyptus plantation for industry development and climate change mitigation requires the accurate quantification of aboveground biomass at the individual tree species level. However, the direct measurement of aboveground biomass by destructive method is high cost and time consuming. Therefore, developing allometric equations is necessary to facilitate this effort. This study was designed to construct the specific allometric models for estimating aboveground biomass of Eucalyptus urophylla in East Nusa Tenggara. Forty two sample trees were utilized to develop allometric equations using regression analysis. Several parameters were selected as predictor variables, i.e. diameter at breast height (D), quadrat diameter at breast height combined with tree height (D2H), as well as D and H separately. Results showed that the mean aboveground biomass of E. urophylla was 143.9 ± 19.44 kg tree-1. The highest biomass were noted in stem (80.06%), followed by bark (11.89%), branch (4.69%), and foliage (3.36%). The relative contribution of stem to total aboveground biomass improved with the increasing of diameter class while the opposite trend was recorded in bark, branch, and foliage. The equation lnŶ = lna + b lnD was best and reliable for estimating the aboveground biomass of E. urophylla since it provided the highest accurate estimation (91.3%) and more practical than other models. Referring to these findings, this study concluded the use of allometric equation was reliable to support more efficient forest mensuration in E. urophylla plantation.

During the nineteenth century, the European field of forestry was transmitted through expanding colonial empires and networks that sought to inventory and monetize overseas woodlands. Encountering new environments and terrain, the nineteenth century British Empire discovered that existing surveying and enumeration methods were poorly suited for colonized territories. This was particularly true of British India, which spanned from modern-day Pakistan to Myanmar. Designed for European forests, forestry instruments in the nineteenth century performed poorly abroad. With the assistance of Syed Mir Mohsin Hussain, Dietrich Brandis—a German scientist and one of the first Inspectors General of Forests in British India—reconstituted a European hypsometer to address some of these challenges. The collaboration between the two men resulted in the Brandis hypsometer. For the subsequent half century, the hypsometer became a principal forestry device throughout the British Empire and the United States. Despite the widespread adoption of the device, critics challenged the operability and accuracy of the Brandis hypsometer. Using computer-aided design and modern fabrication techniques has allowed for a reexamination of this historic device. The authors' investigation supports critics' claims and suggests a degree of nuance for researchers relying on data produced by the device. [ABSTRACT FROM AUTHOR]

Background Laser scanning technology has opened new horizons for the research of forest dynamics, because it provides a largely automated and non-destructive method to rapidly capture the structure of individual trees and entire forest stands at multiple spatial scales. The structural data themselves or in combination with additional remotely sensed data also provide information on the local physiological state of structures within trees. The capacity of new methods is facilitated by the ongoing development of automated processing tools that are designed to capture information from the point cloud data provided by the remote measurements. Scope Terrestrial laser scanning (TLS), performed from the ground or from unmanned aerial vehicles, in particular, has potential to become a unifying measurement standard for forest research questions, because the equipment is flexible to use in the field and has the capacity to capture branch-level structural information at the forestplot or even forest scale. This issue of Annals of Botany includes selected papers that exemplify the current and potential uses of TLS, such as for examination of crown interactions between trees, growth dynamics of mixed stands, non-destructive characterization of urban trees, and enhancement of ecological and evolutionary models. The papers also present current challenges in the applicability of TLS methods and report recent developments in methods facilitating the use of TLS data for research purposes, including automatic processing chains and quantifying branch and above-ground biomass. In this article, we provide an overview of the current and anticipated future capacity of TLS and related methods in solving questions that utilize measurements and models of forests. Conclusions Due to its measurement speed, TLS provides a method to effortlessly capture large amounts of detailed structural forest information, and consequent proxy data for tree and forest processes, at a far wider spatial scale than is feasible with manual measurements. Issues with measurement precision and occlusion of laser beams before they reach their target structures continue to reduce the accuracy of TLS data, but the limitations are counterweighted by the measurement speed that enables large sample sizes. The currently high time-cost of analysing TLS data, in turn, is likely to decrease through progress in automated processing methods. The developments point towards TLS becoming a new and widely accessible standard tool in forest measurement and modelling. [ABSTRACT FROM AUTHOR]

Abstract Dendrochronological analyses were conducted across a gradient of productivity and soil drainage quality characterizing four vegetation types in a low‐productivity hypermaritime (perhumid) temperate rainforest on the Central Coast of British Columbia, Canada. We examined the structure, composition, and stand dynamics of trees growing in 400 m2 plots located in blanket bog, bog woodland, bog forest, and zonal forest vegetation types. We sampled over 2500 trees and 1500 seedlings and saplings and our dendrochronological reconstruction of six tree species revealed establishment ages extending to 660 A.D. (1350 yr). All forest plots contained numerous old trees (>250 yr) and the zonal forest and bog forest vegetation types contained significantly taller trees and also had the greatest amount of suppressed, shade‐tolerant tree species. The bog woodland vegetation type contained more seedlings and saplings than the other three vegetation types combined. The bog forest vegetation type had the highest density of dead standing trees (~530 per hectare). Blanket bogs contained an open structure with very few old trees (>250 yr). Significant differences in the ages of trees existed between forested vegetation types and the more open blanket bog vegetation type. Several trees exceeded 1000 yr in age and were situated in lower‐productivity bog forest and bog woodland sites. We found no evidence of widespread tree cohort establishment, indicating that small‐scale disturbances such as individual tree mortality and gap‐forming dynamics are likely the most frequent disturbance in the study area.

Dendrochronological analyses were conducted across a gradient of productivity and soil drainage quality characterizing four vegetation types in a low‐productivity hypermaritime (perhumid) temperate rainforest on the Central Coast of British Columbia, Canada. We examined the structure, composition, and stand dynamics of trees growing in 400 m2 plots located in blanket bog, bog woodland, bog forest, and zonal forest vegetation types. We sampled over 2500 trees and 1500 seedlings and saplings and our dendrochronological reconstruction of six tree species revealed establishment ages extending to 660 A.D. (1350 yr). All forest plots contained numerous old trees (>250 yr) and the zonal forest and bog forest vegetation types contained significantly taller trees and also had the greatest amount of suppressed, shade‐tolerant tree species. The bog woodland vegetation type contained more seedlings and saplings than the other three vegetation types combined. The bog forest vegetation type had the highest density of dead standing trees (~530 per hectare). Blanket bogs contained an open structure with very few old trees (>250 yr). Significant differences in the ages of trees existed between forested vegetation types and the more open blanket bog vegetation type. Several trees exceeded 1000 yr in age and were situated in lower‐productivity bog forest and bog woodland sites. We found no evidence of widespread tree cohort establishment, indicating that small‐scale disturbances such as individual tree mortality and gap‐forming dynamics are likely the most frequent disturbance in the study area. [ABSTRACT FROM AUTHOR]

Understanding the essential contribution of eucalyptus plantation for industry development and climate change mitigation requires the accurate quantification of aboveground biomass at the individual tree species level. However, the direct measurement of aboveground biomass by destructive method is high cost and time consuming. Therefore, developing allometric equations is necessary to facilitate this effort. This study was designed to construct the specific allometric models for estimating aboveground biomass of Eucalyptus urophylla in East Nusa Tenggara. Forty two sample trees were utilized to develop allometric equations using regression analysis. Several parameters were selected as predictor variables, i.e. diameter at breast height (D), quadrat diameter at breast height combined with tree height (D2H), as well as D and H separately. Results showed that the mean aboveground biomass of E. urophylla was 143.9 ± 19.44 kg tree-1. The highest biomass were noted in stem (80.06%), followed by bark (11.89%), branch (4.69%), and foliage (3.36%). The relative contribution of stem to total aboveground biomass improved with the increasing of diameter class while the opposite trend was recorded in bark, branch, and foliage. The equation lnŶ = lna + b lnD was best and reliable for estimating the aboveground biomass of E. urophylla since it provided the highest accurate estimation (91.3%) and more practical than other models. Referring to these findings, this study concluded the use of allometric equation was reliable to support more efficient forest mensuration in E. urophylla plantation. [ABSTRACT FROM AUTHOR]

Point sampling, which is also known as angle-count sampling (ACS), can be considered an efficient way of estimating the basal area and volume of forest stands. It is possible to use it in forest management: providing more accurate estimates (precision <10%) of site and stand characteristics needed for management planning. 20 black locust (Robinina pseudoacacia L.) stands were selected at final cutting age to determine the regeneration criteria based on their total volume. It was verified that at P=5% there was no difference between the main volume values of stands indicated in the relevant forest plans as well as calculated by the ACS method. [ABSTRACT FROM AUTHOR]

This work, prepared for the special issue of Journal Floresta, aimed to bring together the most significant contributions made by professors and collaborators in the area of Forest Management in the undergraduate and graduate courses in Forestry at the UFPR during the last 50 years. For its elaboration, it was decided by the sectorization of its content in themes, whose sequence included the evolution in the fields of forest mensuration, forest inventory, geotechnologies, statistics, planning and optimization of forest production, biomass and carbon in forests and their products, forest management, and their prospects. The reports clearly showed that during this period there were major evolutions and improvements in the training of forest engineers, as well as masters and doctors in this field of knowledge. The research was developed during this period, not only in the theoretical domain, but also in the technological and operational ground, due to the group's strong interaction with the productive forest sector and with the public institutions of the state of Paraná and the federal government. The training of masters and doctors was expressive, with the highest productivity in the Graduate Program in Forest Engineering at UFPR. In all the topics covered were presented the new directions for the evolution of scientific and technological knowledge in the field of Forest Management. [ABSTRACT FROM AUTHOR]

South Africa is new to the implementation of climate change policies, and the forestry sector in this country is taking ownership of estimating its greenhouse gas inventories. Improving the level of accuracy of carbon stock estimations calls for the population of a national biomass database on commercially planted species. The development of models to predict the biomass of Eucalyptus grandis × nitens aids in the goal of estimating aboveground carbon at Tier 2 and 3 levels as recommended by the Intergovernmental Panel on Climate Change (IPCC) guidelines for national greenhouse gas inventories. The recommended model set presented in this paper uses diameter at breast height (DBH) and total height as variables to model biomass and, ultimately, carbon. Model fitting followed a maximum likelihood approach, and model selection was based on overall fit, parsimony, ease of use and additivity. Pulpwood stands around clear-felling age (8–10 years) were used, which presented an average basic wood densities value of 498 kg m–3. The estimated average aboveground biomass per hectare of this hybrid was 137 ± 34 T·ha–1 with a biomass expansion factor (scaling from stem wood volume to total above ground biomass) value of 0.6108. [ABSTRACT FROM AUTHOR]

In the article are shown results of assessment of relationships between quantitative and qualitative characteristics of forests and morphometric characteristics of relief on an example model plot in Nanayskoe forest district of Khabarovsk Territory. The relevance of the investigation is connected with need for improvement of the system of forest evaluation operations in the Russian Federation, including with use of the landscape approach. The tasks of the investigation were assessment of relationships between characteristics of relief and characteristics of forest vegetation cover on different levels of forest management; evaluation of morphometric characteristics of relief are important for structure and productivity of forests; comparison of the results obtained through the use of digital terrain models ASTER and SRTM. Geoinformatic projects were formed for a model plot on the basis of digital terrain models and data of forest mensuration and State (National) Forest Inventory. On the basis of the developed method with use geoinformatic technologies were estimated morphometric characteristics of relief (average height, standard deviation of height, entropy, exposition and gradient of slopes, indexes of ruggedness and roughness), quantitative and qualitative characteristics of forests. The multifactor regression analysis, where characteristics of forests (as dependent variables) and morphometric characteristics of relief (as independent variables) were used, have been done. As a result of research, the set of morphometric characteristics of relief able to influence to variability of quantitative and qualitative characteristics of forests was identified. The set of linear regression equations able to explain 30–50 % of variability of dependent variables was obtained. The regression equations, obtained on base of digital terrain models ASTER and SRTM, comparable to each other in strength of relations (coefficients of determination), but includes the different sets of morphometric characteristics. The results of the study suggest the presence of relationships between characteristics of forests and morphometric characteristics of relief on different levels of forest management.

The median diameter of a longitudinal section of the stem may be used to determine the stem volume. However, to calculate stem volume, many measurements of diameter at different heights along the stem are required. Therefore, this approach is not generally applied because time-consuming and expensive. Here, we propose a novel, more rapid method to obtain median diameter using the area of the stem profile. A total of 218 height/diameter classes from more than 5000 spruce trees (Picea abies Karst.) were used to compute the median diameter using the classical method. In parallel, a regression model to assess the median diameter was developed. The strongest predictor of the median diameter for the stem profile was the diameter at breast height (R2 = 0.9985). Statistical analysis revealed that the height of the median diameter on the stem profile was 0.3 × H (tree height). The model was verified on standing and felled trees, revealing that differences between classical computations and the proposed model were less than 2% in most cases (86.24% of trees). The median diameter of the stem profile provides valuable information on stand architecture that could help in advancing our understanding on the mechanical stability of Norway spruce trees (i.e., delineating breakage point), growth model predictions, and competition among trees.

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Abstract African mahogany (Khaya spp.) plantations are in expansion in Brazil and in the world. This fact justifies the need for studies related to its growth and yield. This paper aimed to evaluate the performance of single-entry and double-entry models for estimating merchantable and total volume for Khaya ivorensis plantations before the first thinning (7 years) and expected final cut (15 years). Volume data was from 100 and 46 trees in Minas Gerais and Pará states, respectively, by using an electronic dendrometer (Criterion RD 1000). Observed volumes were calculated by Smalian’s formula. To validate the optical dendrometer, 10 trees were felled and had their volume measured, and compared with the volumes measured indirectly. The results showed that observed and estimated volumes were statistically equal, and that double-entry models were more precise than single-entry models. Schumacher and Hall model was the best equation to estimate merchantable volume for first thinning and for final cut in Minas Gerais stands. Spurr logarithmized model was the best equation to estimate total volume for first thinning and Spurr model for final cut in Pará stands. All chosen equations can be used to quantify merchantable and total volumes of Khaya ivorensis grown under similar conditions.

As boreal forests rapidly warm due to anthropogenic climate change, long‐term baseline community data are needed to effectively characterize the corresponding ecological changes that are occurring in these forests. The combined seasonal dynamics (SEADYN) and annual dynamics (ANNDYN) data set, which documents the vegetative changes in boreal forests during the snow‐free period, is one such source of baseline community data. These data were collected by George H. La Roi and colleagues in Alberta, Canada from 1980 to 2015 within permanent sampling plots established in the Hondo‐Slave Lake area (eight stands; 1980–2015) in central Alberta and the Athabasca Oil Sands (AOS) region (17 stands; 1981–1984) near Fort McMurray in northeastern Alberta. Various data were collected, with temporal and spatial coverage differing by data set. These data sets include, but are not limited to, cover of each identified vascular plant and bryoid (moss, liverwort, and lichen) species; forest mensuration; forest litter production; and soil temperature and moisture. Notably, permanent sampling plots were set up as a grid, which will facilitate analyses of spatial relations. These data can be used to analyze long‐term changes in seasonal dynamics and succession within boreal forest communities and serve as a baseline for comparison with future forest conditions in unmanaged, managed, and reclaimed forests. Data are released under a CC‐BY license; please cite this data paper when using the data for analyses. [ABSTRACT FROM AUTHOR]

This paper examines the possible ecological controls on the diameter increment of oriental beech (Fagus orientalis Lipsky) in a high altitude forest in northern Iran. The main objectives of the study are computer-generated abiotic surfaces and associated plot estimates of (i) growing-season-cumulated potential solar radiation, (ii) seasonal air temperature, (iii) topographic wetness index in representing soil water distribution, and (iv) wind velocity generated from the simulation of fluid-flow dynamics in complex terrain. Plot estimates of the tree growth are based on averaged plot measurements of diameter at breast height increment during a growing period of nine years (2003−2012). Biotic variables related to the tree diameter increment involve averaged 2003 tree diameter and basal area measured in individual forest plots. In the modelling data (144 plots), the assemblage of modelled and observed site variables explained 75% of the variance in plot-level diameter increment. In the validation data (32 plots), the degree of explained variance was 77%. Mean tree diameter at breast height showed the strongest correlation with diameter increment, explaining 32% of the variation between-plot, followed by the configuration of topography and re-distribution of surface water (19.5%) and plot basal area (16.9%). On average, localised estimates of solar radiation and wind velocity potentially contribute to about 20% of the control on plot-level mean increment in oriental beech of the area. The results of the genetic programming showed that controlling the stand basal area and tree size by thinning and/or selective harvesting can have a favourable impact on the future distribution of mean diameter in oriental beech.

Biodiversity is commonly referred to as species diversity but in forest ecosystems variability in structural and functional characteristics can also be treated as measures of biodiversity. Small unmanned aerial vehicles (UAVs) provide a means for characterizing forest ecosystem with high spatial resolution, permitting measuring physical characteristics of a forest ecosystem from a viewpoint of biodiversity. The objective of this study is to examine the applicability of photogrammetric point clouds and hyperspectral imaging acquired with a small UAV helicopter in mapping biodiversity indicators, such as structural complexity as well as the amount of deciduous and dead trees at plot level in southern boreal forests. Standard deviation of tree heights within a sample plot, used as a proxy for structural complexity, was the most accurately derived biodiversity indicator resulting in a mean error of 0.5 m, with a standard deviation of 0.9 m. The volume predictions for deciduous and dead trees were underestimated by 32.4 m3/ha and 1.7 m3/ha, respectively, with standard deviation of 50.2 m3/ha for deciduous and 3.2 m3/ha for dead trees. The spectral features describing brightness (i.e. higher reflectance values) were prevailing in feature selection but several wavelengths were represented. Thus, it can be concluded that structural complexity can be predicted reliably but at the same time can be expected to be underestimated with photogrammetric point clouds obtained with a small UAV. Additionally, plot-level volume of dead trees can be predicted with small mean error whereas identifying deciduous species was more challenging at plot level. [ABSTRACT FROM AUTHOR]

The aim of this work was to assess the occurrence of Sclerocarya birrea in Chigubo district to provide information about its productive potential to promote the production of canhu oil by local communities. Diameter at breast height (DBH), total height and commercial height and species names were collected in 10 clusters of four plots with 0.2 ha each. The plots were randomly established in the area to determine horizontal forest structure, diameter distribution and timber volumes per unit area. Later on it was estimate de canhu nuts production in Chigubo district. We found diameter distribution in reverse J-shaped, 106 trees ha-1, with 50.59% from S. birrea, and total basal area of adult species of 34.26 m² ha-1, with 24.36 m² ha-1 (71.01%) represented by S. birrea. Sclerocarya birrea nuts production was estimate as 13,345 kg ha-1year-1. [ABSTRACT FROM AUTHOR]

The evolution of the stem form of trees in stands of Araucaria angustifolia (Bertol.) Kuntze was studied by means of taper functions and form factors. The data used were obtained by complete stem analysis and by rigorous scaling of standing trees in stands established in central-southern region of Paraná, with a sample of 45 trees. Four taper functions were adjusted for the total data set and for stratified data by classes of age. Tapering curves were constructed for different age classes. Model identity tests were performed to compare complete and reduced models. To assess the evolution of natural and artificial form factors, they were calculated for different ages, starting at 5 years old. Schöpfer's polynomial was the selected model. There were significant differences among complete and reduced models with a slight advantage in the use of equations adjusted by age classes, as well as a significant improvement in the stem taper with the increase in age, also verified by the stabilization of the values of form factor at 22 years. [ABSTRACT FROM AUTHOR]

Forest resource information has a hierarchical structure: individual tree attributes are summed at the plot level and then in turn, plot-level estimates are used to derive stand or large-area estimates of forest resources. Due to this hierarchy, it is imperative that individual tree attributes are measured with accuracy and precision. With the widespread use of different measurement tools, it is also important to understand the expected degree of precision associated with these measurements. The most prevalent tree attributes measured in the field are tree species, stem diameter-at-breast-height (dbh), and tree height. For dbh and height, the most commonly used measuring devices are calipers and clinometers, respectively. The aim of our study was to characterize the precision of individual tree dbh and height measurements in boreal forest conditions when using calipers and clinometers. The data consisted of 319 sample trees at a study area in Evo, southern Finland. The sample trees were measured independently by four trained mensurationists. The standard deviation in tree dbh and height measurements was 0.3 cm (1.5%) and 0.5 m (2.9%), respectively. Precision was also assessed by tree species and tree size classes; however, there were no statistically significant differences between the mensurationists for dbh or height measurements. Our study offers insights into the expected precision of tree dbh and height as measured with the most commonly used devices. These results are important when using sample plot data in forest inventory applications, especially now, at a time when new tree attribute measurement techniques based on remote sensing are being developed and compared to the conventional caliper and clinometer measurements. [ABSTRACT FROM AUTHOR]

Interest in measuring forest biomass and carbon stock has increased as a result of the United Nations Framework Convention on Climate Change, and sustainable planning of forest resources is therefore essential. Biomass and carbon stock estimates are based on the large area estimates of growing stock volume provided by national forest inventories (NFIs). The estimates for growing stock volume based on the NFIs depend on stem volume estimates of individual trees. Data collection for formulating stem volume and biomass models is challenging, because the amount of data required is considerable, and the fact that the detailed destructive measurements required to provide these data are laborious. Due to natural diversity, sample size for developing allometric models should be rather large. Terrestrial laser scanning (TLS) has proved to be an efficient tool for collecting information on tree stems. Therefore, we investigated how TLS data for deriving stem volume information from single trees should be collected. The broader context of the study was to determine the feasibility of replacing destructive and laborious field measurements, which have been needed for development of empirical stem volume models, with TLS. The aim of the study was to investigate the effect of the TLS data captured at various distance (i.e. corresponding 25%, 50%, 75% and 100% of tree height) on the accuracy of the stem volume derived. In addition, we examined how multiple TLS point cloud data acquired at various distances improved the results. Analysis was carried out with two ways when multiple point clouds were used: individual tree attributes were derived from separate point clouds and the volume was estimated based on these separate values (multiple-scan A), and point clouds were georeferenced as a combined point cloud from which the stem volume was estimated (multiple-scan B). This permitted us to deal with the practical aspects of TLS data collection and data processing for development of stem volume equations in boreal forests. The results indicated that a scanning distance of approximately 25% of tree height would be optimal for stem volume estimation with TLS if a single scan was utilized in boreal forest conditions studied here and scanning resolution employed. Larger distances increased the uncertainty, especially when the scanning distance was greater than approximately 50% of tree height, because the number of successfully measured diameters from the TLS point cloud was not sufficient for estimating the stem volume. When two TLS point clouds were utilized, the accuracy of stem volume estimates was improved: RMSE decreased from 12.4% to 6.8%. When two point clouds were processed separately (i.e. tree attributes were derived from separate point clouds and then combined) more accurate results were obtained; smaller RMSE and relative error were achieved compared to processing point clouds together (i.e. tree attributes were derived from a combined point cloud). TLS data collection and processing for the optimal setup in this study required only one sixth of time that was necessary to obtain the field reference. These results helped to further our knowledge on TLS in estimating stem volume in boreal forests studied here and brought us one step closer in providing best practices how a phase-shift TLS can be utilized in collecting data when developing stem volume models. [ABSTRACT FROM AUTHOR]

Height models based on high-altitude aerial images provide a low-cost means of generating detailed 3D models of the forest canopy. In this study, the performance of these height models in the detection of individual trees was evaluated in a commercially managed boreal forest. Airborne digital stereo imagery (DSI) was captured from a flight altitude of 5 km with a ground sample distance of 50 cm and corresponds to regular national topographic airborne data capture programs operated in many countries. Tree tops were detected from smoothed canopy height models (CHM) using watershed segmentation. The relative amount of detected trees varied between 26% and 140%, and the RMSE of plot-level arithmetic mean height between 2.2 m and 3.1 m. Both the dominant tree species and the filter used for smoothing affected the results. Even though the spatial resolution of DSI-based CHM was sufficient, detecting individual trees from the data proved to be demanding because of the shading effect of the dominant trees and the limited amount of data from lower canopy levels and near the ground. [ABSTRACT FROM AUTHOR]

Even if stand inventories based on growth tables have been widely discussed over the last years, this method of forest mensuration is still widely applied due to favourable ratio between costs and achievable precision of stand growing stock estimation. The aim of the study was to verify the potential of airborne laser scanning data (ALS) for direct estimation of mean stand height and mean stand density (stocking) as fundamental inputs for forest mensuration based on yield tables. The material from two reference plots with substantially different stand structure was processed by REFLEX software, and confronted with the results of the precise terrestrial inventory. The number of detected tree tops decreased from 100% in the case of super-dominant trees to 30% and 5% in the case of supressed trees at the homogeneous and heterogeneous plot, respectively. The correlation of ALS heights with terrestrially measured heights was R = 0.88 at the homogenous plot, and R = 0.77 at the heterogeneous plot. The tendency to underestimate dominant and to overestimate suppressed trees was revealed at both plots, but was more pronounced at the heterogeneous one. Nevertheless we justified that the mean ALS height calculated from the heights of the detected trees represented the biometric mean stand height linked to the stem with the mean basal area quite well. The stocking estimated by REFLEX software according to delineated crowns´ area was also closer to the real value of stocking than the one obtained by the routine mensuration procedure. The results indicate promising potential of the ALS data processed by REFLEX software to rationalise forest mensuration based on yield tables in even-aged forest structures. [ABSTRACT FROM AUTHOR]

Natural disturbances such as wind are known to cause threats to ecosystem services as well as sustainable forest ecosystem management. The objective of this research was to better understand and quantify drivers of predisposition to wind disturbance, and to model and map the probability of wind-induced forest disturbances (PDIS) in order to support forest management planning. To accomplish this, we used open-access airborne light detection and ranging (LiDAR) data as well as multi-source National Forest Inventory (NFI) data to modelPDISin southern Finland. A strong winter storm occurred in the study area in December 2011. High spatial resolution aerial images, acquired after the disturbance event, were used as reference data. Potential drivers associated withPDISwere examined using a multivariate logistic regression model. The model based on LiDAR provided good agreement with detected areas susceptible to wind disturbance (73%); however, when LiDAR was combined with multi-source NFI data, the results were more promising: prediction accuracy increased to 81%. The strongest predictors in the model were mean canopy height, mean elevation, and stem volume of the main tree species (Norway spruce and Scots pine). Our results indicate that open-access LiDAR data can be used to model and map the probability of predisposition to wind disturbance, providing spatially detailed, valuable information for planning and mitigation purposes. [ABSTRACT FROM AUTHOR]

Dendrometrical study of Acacia auriculiformis A. Cunn. in mixed stands on claysoils in Benin. Acacia auriculiformis is a fast growing species planted on vertisols in Benin. An inventory of 11 mixed stands of Acacia, which are 7 to 9 years old, has been realized to estimate growth parameters of the stands. The present study shows that, for the dendrometrical parameters, there is no difference between species associations at a 0.05 significance level. Nevertheless, the largest values of quadratic mean diameter of the stems foot are observed in the species associations including Leucaena leucocephala. Moreover, the branch volume decreases with the increasing of the number of stems per tree. The most appropriate volume function for Acacia auriculiformis is the one that takes into account the diameter of the stems foot and the total height. Otherwise, the species associations do not influence the profile of Acacia trees, which is constant within the associations. The predicted conversion and cutting coefficients show that the stacked wood volume represents about 144% of the real stand volume.

Airborne LiDAR data has been used operationally for more than ten years to model, characterize and map forest resource has been known in Northern countries of America and Europe. However, in France, where topography is more complex and forests more heterogeneous compared to the boreal and large pine forests of Northern Europe, only few examples of LiDAR applications over large areas can be found. In this study, an "area based" approach, that establishes empirical models relating forest measurements collected in the field to plot level LiDAR metrics, was used in three contrasted forest sites. Models were established using the usual metrics derived from the LiDAR point cloud, as well as metrics calculated from dominant tree crowns individualized by applying a CHM segmentation algorithm. At stand level, an independent model validation was used to evaluate predictions accuracy on areas of around one hectare, which are relevant to forest managers. Results showed that it is possible to estimate forest resource in contrasted stands, ranging from beech or pine even-aged plain stands, to mixed fir-spruce mountain stands. The cross-validation residual error (RMSE) at the plot level was 14 to 22% (R² from 0.75 to 0.90) for basal area, 7 to 8% (R² from 0.76 to 0.96) for dominant diameter, and 17 to 32% (R² from 0.50 to 0.88) for stem density. Independent validation at the stand level showed a good reliability of the models for all studied parameters, as far as they were used within their validity domain. The differences between the averaged predictions and the field reference measurements were about 10 to 15% for basal area, 6 to 8% for dominant diameter and 10 to 33% for stem density. These results showed that, on area of around one hectare, airborne LiDAR inventories can reach an accuracy equivalent to that of traditional field methods, even in complex forests. [ABSTRACT FROM AUTHOR]

Generating accurate and unbiased wall-to-wall canopy height maps from airborne lidar data for large regions is useful to forest scientists and natural resource managers. However, mapping large areas often involves using lidar data from different projects, with varying acquisition parameters. In this work, we address the important question of whether one can accurately model canopy heights over large areas of the Southeastern US using a very heterogeneous dataset of small-footprint, discrete-return airborne lidar data (with 76 separate lidar projects). A unique aspect of this effort is the use of nationally uniform and extensive field data (∼1800 forested plots) from the Forest Inventory and Analysis (FIA) program of the US Forest Service. Preliminary results are quite promising: Over all lidar projects, we observe a good correlation between the 85th percentile of lidar heights and field-measured height (r = 0.85). We construct a linear regression model to predict subplot-level dominant tree heights from distributional lidar metrics (R2 = 0.74, RMSE = 3.0 m, n = 1755). We also identify and quantify the importance of several factors (like heterogeneity of vegetation, point density, the predominance of hardwoods or softwoods, the average height of the forest stand, slope of the plot, and average scan angle of lidar acquisition) that influence the efficacy of predicting canopy heights from lidar data. For example, a subset of plots (coefficient of variation of vegetation heights <0.2) significantly reduces the RMSE of our model from 3.0-2.4 m (∼20% reduction). We conclude that when all these elements are factored into consideration, combining data from disparate lidar projects does not preclude robust estimation of canopy heights. [ABSTRACT FROM AUTHOR]

We evaluated a smartphone app (TRESTIMATM) for forest sample plot measurements. The app interprets imagery collected from the sample plots using the camera in the smartphone and then estimates forest inventory attributes, including species-specific basal areas (G) as well as the diameter (DgM) and height (HgM) of basal area median trees. The estimates from the smartphone app were compared to forest inventory attributes derived from tree-wise measurements using calipers and a Vertex height measurement device. The data consist of 2169 measured trees from 25 sample plots (32 m x 32 m), dominated by Scots pine and Norway spruce from southern Finland. The root-mean-square errors (RMSEs) in the basal area varied from 19.7% to 29.3% and the biases from 11.4% to 18.4% depending on the number of images per sample plot and image shooting location. DgM measurement bias varied from -1.4% to 3.1% and RMSE from 5.2% to 11.6% depending on the tree species. Respectively, HgM bias varied from 5.0% to 8.3% and RMSE 10.0% to 13.6%. In general, four images captured toward the center of the plot provided more accurate results than four images captured away from the plot center. Increasing the number of captured images per plot to the analyses yielded only marginal improvement to the results. [ABSTRACT FROM AUTHOR]