Liniker Fernandes da Silva

Technical and economic analyses in semi-mechanized forest cutting are essential for planning forest harvesting activities. This study aimed to conduct a technical and economic analysis of semi-mechanized forest cutting in eucalyptus plantations located in the municipality of Itaporanga D’Ajuda, Sergipe State, Brazil. Technical analysis consisted of time and motion study of semi-mechanized cutting activities, including displacement, felling, delimbing, and processing operations. Most effective operational time was consumed during the delimbing stage. Effective productivity was 3.10 m3 h-1. The study results demonstrated good operational efficiency (83.24%) and mechanical availability (91.70%) of machinery. Economic analysis was based on operational semi-mechanized harvesting costs, production costs, and sensitivity analysis. Operating cost per effective working hour was US$ 16.62, with depreciation representing the main fixed cost and labor the main variable cost. Production cost was US$ 5.36 h-1. Labor cost was the variable that most strongly influenced production cost in sensitivity analysis, increasing this cost by an additional US$ 0.66 when labor expenses increased by 10%. Results demonstrated that technical and economic analyses are essential for planning sustainable forest harvesting operations.

Informações sobre o comportamento hidrológico em bacias hidrográficas são fundamentais para o diagnóstico ambiental, assim como para a otimização da utilização dos recursos hídricos ao longo do ano. Dessa forma, objetivou-se com este estudo, caracterizar a precipitação e a vazão em um trecho sudoeste da bacia hidrográfica do rio Paraguaçu, Bahia, Brasil. Foram obtidos dados pluviométricos e fluviométricos referente a série histórica das estações de João Amaro, Usina Mucugê, Andaraí e de Iaçu através do portal do Sistema Nacional de Informações sobre Recursos Hídricos da Agência Nacional das Águas (SNIRH/ANA). Para o processamento dos dados, foi utilizado o software Hidroweb, o qual possibilitou a gestão das bases de dados. E do software Action Stat 3.6 para as análises estatísticas. De acordo com os resultados obtidos, os totais médios mensais de precipitação mostram-se estacionários e sem sazonalidade determinística em toda série histórica. Dezembro mostrou-se mais chuvoso tanto para a área da Chapada quanto para a área de Iaçu. As probabilidades das vazões ocorrerem de forma permanentes ao longo do ano em Iaçu são fortemente significativas.

Modeling is an important tool to estimate forest production in planted areas. Although this issue has been studied worldwide, knowledge regarding volume measurement in specific locations such as Northeast Brazil is still scarce. The present study aimed to evaluated the effectiveness of artificial neural networks (ANNs) and regression analysis in estimating the timber volume of homogeneous stands of Anadantera macrocarpa, Genipa americana, and Mimosa casalpinifolia, in order to better predict the growth and production of these species. Both methods were suitable for estimating the individual volume in 7-year-old stands with different spacing. The Spurr regression model showed better statistical results and dispersion of unbiased errors for Anadantera macrocarpa and Genipa americana, whereas the Shumacher-Hall model provided more accurate volume estimates for Mimosa caesalpinifolia. The ANNs calibrated with two neurons in the middle layer exhibited the best fit for all three species. As such, artificial neural networks can be recommended to estimate the individual volumes of the species analyzed in the study area.

Forests in the southwestern Amazon are rich, diverse, and dense. The region is of high ecological importance, is crucial for conservation and management of natural resources, and contains substantial carbon and biodiversity stocks. Nevertheless, few studies have developed allometric equations for this part of the Amazon, which differs ecologically from the parts of Amazonia where most allometric studies have been done. To fill this gap, we developed allometric equations to estimate the volume, biomass, and carbon in commercial trees with diameter at breast height (DBH) ≥ 50 cm in an area under forest management in the southeastern portion of Brazil’s state of Acre. We applied the Smalian formula to data collected from 223 felled trees in 20 species, and compared multiple linear and nonlinear models. The models used diameter (DBH) measured at 1.30 m height (d), length of the commercial stem (l), basic wood density (p), and carbon content (t), as independent variables. For each dependent variable (volume, biomass, or carbon) we compared models using multiple measures of goodness-of-fit, as well as graphically analyzing residuals. The best fit for estimating aboveground volume of individual stems using diameter (d) and length (l) as variables was obtained with the Spurr model (1952; logarithmic) (root mean square error (RMSE) = 1.637, R² = 0.833, mean absolute deviation (MAD) = 1.059). The best-fit equation for biomass, considering d, l, and p as the explanatory variables, was the Loetsch et al. (1973; logarithmic) model (RMSE = 1.047, R² = 0.855, MAD = 0.609). The best fit equation for carbon was the Loetsch et al. (1973; modified) model, using the explanatory variables d, l, p, and t (RMSE = 0.530, R² = 0.85, MAD = 0.304). Existing allometric equations applied to our study trees performed poorly. We showed that the use of linear and nonlinear allometric equations for volume, biomass, and carbon can reduce the errors and improve the estimation of these metrics for the harvested stems of commercial species in the southwestern Amazon.

For a commercial reforestation success, it is necessary to know the species specific nutritional requirements used to overcome fertility limitations in a given site, allowing to fertility costs optimize in seedlings production. The objective of this study was to responses evaluate of Swietenia macrophylla King seedlings subject to nitrogen and phosphorus different dosages in corrected soil. The experiment was conducted between January and April 2015 in a greenhouse at the Universidade Federal do Recôncavo da Bahia, in Cruz das Almas (BA). The experimental design was a 5 x 2 factorial scheme (five different doses of phosphorus (Pn) in nitrogen absence and presence [N₀ and N₁]), making ten treatments, completely randomized. After 90 days of sowing, aerial part height (h) and stem based diameter of seedlings were measured. The data were submitted to variance analysis (ANOVA) at 5% error probability level. Treatments did not statically differ from each other, showing the same effect of P dosages with and without N on soil acidity correction with limestone (CaCO₃) condition on initial growth of Swietenia macrophylla seedlings.

Necromass has a relevant role to play in the carbon stock of forest ecosystems, especially with the increase of tree mortality due to climate change. Despite this importance, its quantification is often neglected in tropical forests. The objective of this study was to quantify the carbon storage in a secondary Atlantic Forest fragment in Viçosa, Minas Gerais, Brazil. Coarse Woody Debris (CWD), standing dead trees (snags), and litter were quantified in twenty 10 m x 50 m plots randomly positioned throughout the forest area (simple random sampling). Data were collected during 2015, from July to December. The CWD and snags volumes were determined by the Smalian method and by allometric equations, respectively. The necromass of these components was estimated by multiplying the volume by the apparent density at each decomposition classes. The litter necromass was estimated by the proportionality method and the average of the extrapolated estimates per hectare. The carbon stock of the three components was quantified by multiplying the necromass and the carbon wood content. The total volume of dead wood, including CWD and snag, was 23.6 ± 0.9 m³ ha⁻¹, being produced mainly by the competition for resources, senescence, and anthropic and climatic disturbances. The total necromass was 16.3 ± 0.4 Mg ha⁻¹. The total carbon stock in necromass was 7.3 ± 0.2 MgC ha⁻¹. The CWD, snag and litter stocked 3.0 ± 0.1, 1.8 ± 0.1, and 2.5 ± 0.1 MgC ha⁻¹, respectively. These results demonstrate that although necromass has a lower carbon stock compared to biomass, neglecting its quantification may lead to underestimation of the carbon balance of forest ecosystems and their potential to mitigate climate change.

The modeling of recruitment in tropical forests is important for studies of forest management sustainability, for giving adequate subsidies to the recovery of wood stock. The objective of the work was to estimate the recruitment after wood harvest, using a model of artificial neural network (ANN). The study area is located in the Tapajós National Forest (55° 00' W, 2° 45' S), Pará. In 64 ha of the study area, in 1979, an intensive harvest of 72.5 m3 ha-1 was carried out. In 1981, 36 permanent plots of 50 m x 50 m were randomly installed. These plots were measured in 1982, 1983, 1985, 1987, 1992, 1997, 2007, 2010 and 2012. To model the recruitment the variables of target subplot and its neighborhood were considered. The estimates obtained in the training and generalization of ANN were evaluated by statistics: correlation ( R) and root mean square error (RMSE) being obtained RMSE 35.6% and 0.89. It was possible to model the recruitment tendency over the time in tropical forests, after the wood harvest.

The secondary Atlantic forests play an important role in the context of climate change, acting as a carbon sink for the atmosphere. However, these forests can become a carbon source in case of increased tree mortality. Knowing this change is possible through continuous forest inventories that provide information on the dynamics of tree growth. Thus, the objective of this study was to evaluate the carbon growth dynamics of a Seasonal Semideciduous Forest fragment, with 44.11 ha, located in the Parque Tecnológico de Viçosa - MG. The forest inventories were carried out in twenty plots of 10 m x 50 m, in the years of 2010 and 2015, where all stems with dbh ≥ 5 cm were measured, botanically identified and classified in ecological groups. The stem volume was obtained through volumetric equation. Biomass and carbon stock were quantified for compartments located above the ground (stem, branches and leaves) and below ground (roots). The dynamics of carbon growth were evaluated by Gross Increment (GI) and Periodic Annual Increment in carbon of the species (PAI). The GI was 12.72 MgC ha-1, including the carbon from the stems that were recruited and died during the monitoring period. The carbon stock increased 10.01 MgC ha-1, resulting in an PAI of 2.00 MgC ha-1 year-1. Thus, it is concluded that the forest fragment present positive carbon stock growth due to successional progression, ratifying the importance of secondary forest of the Atlantic forest in the mitigation of greenhouse gases in the atmosphere.

The heterogeneous behavior of wood during drying is a process difficult to control. The objective of this study was to evaluate the accuracy of the neuro-fuzzy hybrid system for monitoring wood moisture during drying. Eucalyptus urophylla x Eucalyptus grandis samples (2 x 2 x 4 cm) were saturated and dried in climatic chamber for 15 days. Basic density was determined by the dry mass/saturated volume ratio. Two neuro-fuzzy systems were developed to monitor wood moisture, the first based on the genetic material and drying period and the second based on basic density and drying period. The drying rate of wood samples was higher at the initial period and all reached equilibrium moisture content after 15 days. Density showed relationship with wood moisture during the study period. Both systems have the potential to monitor moisture, however, neuro-fuzzy system based on basic density and drying period showed better results and is therefore more suitable.

In forest management, it is important to project diametric distribution along the cutting cycle to subsidize the most suitable silvicultural techniques to forest structure. The aim of this work was to project diametric distribution along the cutting cycle using Markov Transition Matrix. In 1979, selective harvest was performed with an intensity of 72.5 m (3) ha(-1), in a 64 ha area in `Floresta Nacional do Tapajos' - Para state (PA). In 1981, 36 permanent plots of 50m x 50m were randomly installed and measured successively in 1982, 1983, 1985, 1987, 1992, 1997, 2007, 2010 and 2012. For the projection, two transition matrices were used: one with time interval of one year (1981 to 1982) and another of two years (1981 to 1983). All projections showed diametric distribution in inverted "J" form, with small discontinuity last year (2012). There was adherence of diametric distribution at 5% significance between observed and estimated data, up to 11 years of projection. Transition matrix can be used to project diametric distribution after harvest in short periods of time after the forest harvest.