scholarly journals Strategies to Maximize the Wood Production in Amazon Forest

2020 ◽  
Author(s):  
Aline Canetti ◽  
Evaldo Muñoz Braz ◽  
Patricia Mattos ◽  
Renato Olivir Basso ◽  
Afonso Figueiredo Filho

Abstract BackgroundThis study aimed to develop a procedure to determine which logging diameter would achieve optimal wood production by species, aiming to support sustainable management of the Amazon forest. Two main methodologies of analysis by species were combined: probability density function (PDF) and growth modeling. The growth models were used to derive the volume increment curves at the individual tree level. To detect the points of maximum annual increment in volume at the population tree level we used PDF with adjusted growth equations.ResultsThe population maximum annual volumetric increments occurred in smaller diameters compared to that of the individual-level. When combining shorter cutting cycles with the population biological rotation point considered as the minimum cutting diameter (MCD), we observed higher annual increments in volume than that achieved using the Brazilian law criteria (MCD = 50 cm) or other MCD tested.ConclusionThe procedure proposed may be used by forest managers and forest law-makers, aiming to maximize sustainable wood production in the Amazon forest.

ISRN Forestry ◽  
2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Edward Missanjo ◽  
Gift Kamanga-Thole ◽  
Vidah Manda

Genetic and phenotypic parameters for height, diameter at breast height (dbh), and volume were estimated for Pinus kesiya Royle ex Gordon clonal seed orchard in Malawi using an ASReml program, fitting an individual tree model. The data were from 88 clones assessed at 18, 23, 30, 35, and 40 years of age. Heritability estimates for height, dbh, and volume were moderate to high ranging from 0.19 to 0.54, from 0.14 to 0.53, and from 0.20 to 0.59, respectively, suggesting a strong genetic control of the traits at the individual level, among families, and within families. The genetic and phenotypic correlations between the growth traits were significantly high and ranged from 0.69 to 0.97 and from 0.60 to 0.95, respectively. This suggests the possibility of indirect selection in trait with direct selection in another trait. The predicted genetic gains showed that the optimal rotational age of the Pinus kesiya clonal seed orchard is 30 years; therefore, it is recommended to establish a new Pinus kesiya clonal seed orchard. However, selective harvest of clones with high breeding values in the old seed orchard should be considered so that the best parents in the old orchard can continue to contribute until the new orchard is well established.


2020 ◽  
Vol 28 ◽  
pp. 192-201
Author(s):  
Rodrigo Freitas Silva ◽  
Marcelo Otone Aguiar ◽  
Mayra Luiza Marques Da Silva ◽  
Gilson Fernandes Da Silva ◽  
Adriano Ribeiro De Mendonça

A continuously competitive forest market and tied to the demands for wood products promotes the study and development of applications that increase the revenue of the forest enterprises. At harvesting, the cutting pattern (forest assortment) in which the trees are traced is traditionally determined by the experience of the chainsaw operator without using any optimization technique, which may result in economic losses in relation to the commercialized products. In general, there are numerous distinct assortments that can be chosen and hardly processed by a brute-force algorithm. This is the forest assortment problem at the individual tree level with the objetice of maximizing the commercial values of the felled trees. stem-level bucking optimization problem. The aim is to maximize the sales value of harvested trees. Dynamic Programming (DP) is an efficient optimization technique to determine the optimum bucking tree as it significantly reduces the number of calculations to be made. Thus, the objective of this work was to develop a modern and intuitive computational system that is able to find the optimum tree stem bucking through DP to help companies over the bole tracing, therefore, characterizing itself as a tool that supports decision making. After the execution of the system, the optimum assortment is shown by sequentially detailing all products that should be removed from the analyzed bole as well as their respective volumes and revenue.


Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 871 ◽  
Author(s):  
Qiu ◽  
Wang ◽  
Zou ◽  
Yang ◽  
Xie ◽  
...  

To estimate mangrove biomass at finer resolution, such as at an individual tree or clump level, there is a crucial need for elaborate management of mangrove forest in a local area. However, there are few studies estimating mangrove biomass at finer resolution partly due to the limitation of remote sensing data. Using WorldView-2 imagery, unmanned aerial vehicle (UAV) light detection and ranging (LiDAR) data, and field survey datasets, we proposed a novel method for the estimation of mangrove aboveground biomass (AGB) at individual tree level, i.e., individual tree-based inference method. The performance of the individual tree-based inference method was compared with the grid-based random forest model method, which directly links the field samples with the UAV LiDAR metrics. We discussed the feasibility of the individual tree-based inference method and the influence of diameter at breast height (DBH) on individual segmentation accuracy. The results indicated that (1) The overall classification accuracy of six mangrove species at individual tree level was 86.08%. (2) The position and number matching accuracies of individual tree segmentation were 87.43% and 51.11%, respectively. The number matching accuracy of individual tree segmentation was relatively satisfying within 8 cm ≤ DBH ≤ 30 cm. (3) The individual tree-based inference method produced lower accuracy than the grid-based RF model method with R2 of 0.49 vs. 0.67 and RMSE of 48.42 Mg ha–1 vs. 38.95 Mg ha–1. However, the individual tree-based inference method can show more detail of spatial distribution of mangrove AGB. The resultant AGB maps of this method are more beneficial to the fine and differentiated management of mangrove forests.


2020 ◽  
Author(s):  
Tom Locatelli ◽  
Sophie Hale ◽  
Bruce Nicoll ◽  
Barry Gardiner

<p>Wind disturbance to forests extends across spatial and temporal scales and encompasses direct and indirect wind effects on the dynamics of forest ecosystems. It is detrimental to the provision of ecosystem services and reduces forest resistance and resilience to future natural disturbances. Historically, in the ecological and land-use scientific communities, forecasting the extent and probability of wind disturbance to forests has represented a serious challenge, with most studies electing to adopt qualitative or statistical approaches. The low degree of portability of statistical assessments of vulnerability to wind has limited their applicability and use, but it is recognised that they have a role in building hypotheses of the processes involved in wind damage that can be subsequently tested under experimental conditions. Results from tree stability experiments have contributed, in the last two decades, to the development of a mechanistic model of wind damage - ForestGALES. This is a process-based wind risk model that was originally created to inform the management of commercial forest plantations in the UK. Built on principles of forest science, physics, and ecology, ForestGALES requires a simple set of inputs and it has now been expanded to cover more than 20 common conifer species from across three continents, and multiple broadleaved species (e.g. Oak, Beech, Birch, and Eucalypts). Two methods of assessing vulnerability to wind damage are available in ForestGALES, one designed for application at stand level, and a novel approach that estimates vulnerability to wind at the individual tree within a stand – the latter allowing for use in complex forest stands, and for the effect of competition between trees in a stand. Until recently, ForestGALES was only available as desktop software and as an online tool as part of forest decision support systems (only for selected countries and species). These formats can be limiting for research and academic projects that aim to model and understanding wind disturbance dynamics across diverse landscapes, and that require a bespoke approach with a high degree of flexibility. To accommodate these broader requirements, ForestGALES has recently been redeveloped and released as a FOSS R package (“<em>fgr</em>”) that is fully customisable and easily integrated in R and modelling workflows and FOSS GIS frameworks. With this poster we present two exemplar studies of assessing wind damage risk to forested landscapes, one for each ForestGALES method (stand- and individual trees level), to showcase the capabilities and flexibility of the model in working with e.g. climate projection data, with other process-based models (e.g. 3PG) within an R modelling framework, and with LiDAR data, at the individual tree level.</p>


Forests ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 187 ◽  
Author(s):  
Qiangxin Ou ◽  
Xiangdong Lei ◽  
Chenchen Shen

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.


2012 ◽  
Vol 144 (6) ◽  
pp. 733-744 ◽  
Author(s):  
Laurel J. Haavik ◽  
Tom W. Coleman ◽  
Mary Louise Flint ◽  
Robert C. Venette ◽  
Steven J. Seybold

AbstractIn recent decades, invasive phloem and wood borers have become important pests in North America. To aid tree sampling and survey efforts for the newly introduced goldspotted oak borer, Agrilus auroguttatus Schaeffer (Coleoptera: Buprestidae), we examined spatial patterns of exit holes on the boles (trunks) of 58 coast live oak, Quercus agrifolia Née (Fagaceae), trees at five sites in San Diego County, southern California, United States of America. Agrilus auroguttatus exit hole densities were greater at the root collar than at mid-boles (6.1 m above ground). Dispersion patterns of exit holes on lower boles (≤1.52 m) were random for trees with low exit hole densities and aggregated for trees with high exit hole densities. The mean exit hole density measured from three randomly chosen quadrats (0.09 m2) provided a statistically reliable estimate of the true mean exit hole density on the lower bole, with <25% error from the true mean. For future sampling and survey efforts in southern California oak forests and woodlands, exit hole counts within a 0.09 m2 quadrat could be made at any three locations on lower Q. agrifolia boles to accurately estimate A. auroguttatus exit hole densities at the individual tree level.


1979 ◽  
Vol 9 (2) ◽  
pp. 231-244 ◽  
Author(s):  
Alan R. Ek ◽  
Robert A. Monserud

A distance-dependent individual tree based growth model (FOREST) was compared with a diameter-class growth model (SHAF) for describing changes in stand density and structure. Projections of Lake States' northern hardwood stand development were made by each model for 5–26 years over a range of stand conditions and harvest treatments. Results from numerous performance tests and comparisons of actual and predicted diameter distributions, basal areas, and numbers of trees, indicate the individual tree model was considerably more sensitive to harvest treatments and reproduction response than the diameter-class model. Conversely, the latter was much less expensive to operate. Prediction of species and individual tree growth with the individual tree model appeared to provide sensitivity nearly equal to that observed for predictions of the stand as a whole. Long-term projections (120 years) for reserve (no cut) and clear-cut stand conditions further suggest the potential and limitations of the models for management analyses.


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