Search

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]

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]

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]