Abstract Quantitative data obtained from native forests is costly and time-consuming. Thus, alternative measurement methods need to be developed to provide reliable information, especially in Atlantic Rain Forests. In this study we evaluated the hypothesis that the combination of an Airborne Laser Scanner (ALS) and an Unmanned Aerial Vehicle (UAV) can provide accurate quantitative information on tree height, volume, and aboveground biomass of the Araucaria angustifolia species. The study was carried out in Atlantic Rain forest fragments in southern Brazil. We tested and evaluated 3 digital canopy height model (CHM) scenarios: 1) CHM derived from ALS models; 2) CHM derived from UAV models; and 3) CHM from a combined ALS digital terrain model and UAV digital surface model. The height value at each tree coordinate was extracted from the pixel in the three evaluated scenarios and compared with the field measured values. ALS and UAV+ALS obtained RMSE% of 6.38 and 12.82 for height estimates, while UAV was 49.91%. Volume and aboveground biomass predictions are more accurate by ALS and UAV+ALS, while the UAV produced biased estimates. Since the ALS is currently used, periodic monitoring can be carried out by a combination of active (ALS) and passive (UAV) sensors.

Abstract: Biomass is an important component of the Brazilian energy matrix, with a potential contribution of co-products from thinned forests. The aim of this work was to evaluate the energy balance and CO2 potential emission in mechanized biomass harvesting operations in Pinus taeda stands at 9 and 10 years-old and under thinning, searching to support the use of co-product biomass from thinning as a renewable energy source. Thinning was carried out through cut-to-length harvesting method, in which large logs for sawmill and small logs for energy were produced. In addition, tops, needles, barks, and branches were considered as co-products. The balance between consumed energy and emitted CO2 by machines for thinning in relationship to the energy and CO2 in thinned biomass was estimated. Thus, dry matter, energy potential, and CO2 potential emission were evaluated and compared considering thinning stand ages as treatments. Mechanized thinning consumes a large energy and produces CO2, however, the energy consumed by machines is lower than 1% of the estimated energy potential in thinned biomass, while the CO2 emission is lower than 0.5% of the biomass. Therefore, the use of co-product biomass of thinning is an important way to mitigate greenhouse gas emission.

Abstract: The lack of accurate models for estimating residual biomass in wood harvesting operations results in underutilization of this co-product by forestry companies. Due to the lack of this information, forestry operations planning, such as chipping and transport logistics, are influenced, with a consequent increase in costs. Thereby, the aim of this study was to propose and evaluate statistical models to estimate residual biomass of Eucalyptus sp. in wood harvesting operations by means of tree variables measured from harvester processing head. Generalized linear models were composed through stepwise procedure for estimating residual biomass by tree covariates: diameter at breast height, commercial height, commercial limit diameter, and stem commercial volume, considering also their transformations and combinations. Residual biomass distributions with positive skew support the application of generalized linear model and Gamma distribution in random component, since normality assumption in traditional linear regression was a requirement not satisfied in this study. By stepwise procedure, tree variables associated to forest biomass were selected, whose linear combinations resulted in models with high statistical efficiency and accuracy. Thus, models developed in this study are innovative tools to estimate residual biomass in mechanized wood harvesting, in which can be inserted into harvester’s hardware to provide real-time information.

Abstract Woody debris, defined as standing and downed deadwood, consists in an essential component of the forest carbon stock. However, few studies have been carried out to get an efficient and accurate sampling procedure for estimating it. This work proposes two methodologies to estimate the woody debris volume in a Brazilian mixed tropical forest: 1) two-stage systematic sampling, using a mixed methodology, in which the Strand’s method is applied to standing dead trees and stumps, and line intercept sampling is used to fallen trees and branches; and 2) ratio estimate of the sum of cross-sectional areas of deadwood pieces and forest basal area, aiming to obtain the total woody debris volume indirectly in the natural forest. Conversions for biomass and carbon stocks were made applying the mean basic density on the estimates of deadwood volumes. Both methodologies are accurate for woody debris volume estimates, with a sampling error equal to 16.1% (methodology 1) and 5.7% (methodology 2), at a 95% probability level. Thus, the methodology 2 has potential to be used in strategic forest inventories of woody debris, such as in National Forest Inventories, due to increasing importance of its quantification in all forest ecosystems.

Abstract Floristic surveys and diversity indices are often applied to measure tree species diversity in mixed tropical forest remnants. However, these analyses are frequently limited to the overall results and do not allow to evaluate the spatial variability distributions of tree diversity, leading to develop additional tools. This study aimed to estimate the spatial variability of tree diversity and map their spatial patterns in a Brazilian mixed tropical forest conservation area. We used indices to measure the tree species diversity (dbh ≥ 10 cm) in 400 sampling units (25 m x 25 m) from a continuous forest inventory. Semivariograms were fitted to estimate spatial dependences and punctual kriging was applied to compose maps. Mean diversity values were constant in the continuous inventories, indicating a forest remnant in an advanced stage of ecological succession. On the other hand, tree diversity presented spatial patterns identified by geostatistics, in which the dynamics were composed of heterogeneous mosaics spatially influenced by tree species with different ecological features and densities, gap dynamics, advancement of forest succession, mortality, and Araucaria angustilofia’s cohorts.

ABSTRACT The spatial distribution of tropical tree species can affect the consistency of the estimators in commercial forest inventories, therefore, appropriate sampling procedures are required to survey species with different spatial patterns in the Amazon Forest. For this, the present study aims to evaluate the conventional sampling procedures and introduce the adaptive cluster sampling for volumetric inventories of Amazonian tree species, considering the hypotheses that the density, the spatial distribution and the zero-plots affect the consistency of the estimators, and that the adaptive cluster sampling allows to obtain more accurate volumetric estimation. We use data from a census carried out in Jamari National Forest, Brazil, where trees with diameters equal to or higher than 40 cm were measured in 1,355 plots. Species with different spatial patterns were selected and sampled with simple random sampling, systematic sampling, linear cluster sampling and adaptive cluster sampling, whereby the accuracy of the volumetric estimation and presence of zero-plots were evaluated. The sampling procedures applied to species were affected by the low density of trees and the large number of zero-plots, wherein the adaptive clusters allowed concentrating the sampling effort in plots with trees and, thus, agglutinating more representative samples to estimate the commercial volume.

Geralmente as empresas florestais usam a área total de um ano de plantio como estrato mínimo do total da população e, consequentemente, o processamento do inventário florestal tem sido realizado pela aplicação da amostragem aleatória estratificada. Este estudo foi realizado na Floresta Nacional de Três Barras, Brasil, e teve como objetivo classificar e mapear os locais onde Pinus elliottii se destaca. A amostragem sistemática foi estruturada em grupos e aplicada de forma independente por compartimentos. Os conglomerados em cruz maltesa, foram compostos por quatro subunidades de amostragem, utilizando o método de amostragem Prodan com um número fixo de seis árvores. Pela análise da metodologia, foi possível confirmar as hipóteses: a) o afinamento seletivo causa expressivo aumento de variabilidade volumétrica dentro dos compartimentos; b) a variação de locais no interior dos compartimentos provoca a expansão volumétrica de variância e esta cresce proporcionalmente à qualidade dos sítios; c) a estratificação em locais resulta em menor variância dentro deles; d) a estratificação em locais resultou em redução de até 91% das variâncias dentro deles.

Generally, the forest companies use the total one year planting area as a minimum stratum of the total population and, consequently, the forest inventory processing has been conducted by applying the stratified random sampling to it. This study was carried out in the National Forest of Tres Barras, Brazil, and it aimed to classify and map the sites of Pinus elliottii stands. A systematic sampling was structured into clusters and applied independently by compartments. The clusters, in maltese cross, were composed of four sampling subunits, using Prodan sampling method with a fixed number of six trees. By analysis of the methodology it was possible to confirm the hypothesis: a) the selective thinning cause expressive increase of volumetric variability within compartments; b) the variation of sites within the compartments causes volumetric expansion of variance and this grows proportionally to the quality of the sites; c) the stratification in sites results in minimum variance within them; d) the stratification in sites resulted in until to 91% reduction of variances within them.