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.

Amazon forest management plans have a variety of effects on carbon emissions, both positive and negative. All of these effects need to be quantified to assess the role of this land use in climate change. Here, we contribute to this effort by evaluating the carbon stocks in logs and timber products from an area under forest management in the southeastern portion of Acre State, Brazil. One hundred and thirty-six trees of 12 species had DBH ranging from 50.9 cm to 149.9 cm. Basic wood density ranged from 0.3 cm⁻³ to 0.8 g cm⁻³ with an average of 0.6 g cm⁻³. The logs had a total volume of 925.2 m³, biomass of 564 Mg, and carbon stock of 484.2 MgC. The average volumetric yield coefficient (VYC) was 52.3% and the carbon yield coefficient (CYC) was 53.2% for logs of the 12 species. The sawn-wood products had a total volume of 484.2 m³, biomass of 302.6 Mg, and carbon stock of 149.9 MgC. Contributions of the different species to the total carbon stored in sawn-wood products ranged from 2.2% to 21.0%. Means and standard deviations for carbon transferred to sawn-wood products per-species from the 1252.8-ha harvested area ranged from 0.4 ± 1.1 MgC to 2.9 ± 0.4 MgC, with the largest percentages of the total carbon stored in wood products being from Dipteryx odorata (21.0%), Apuleia leiocarpa (18.7%), and Eschweilera grandiflora (11.7%). A total of 44,783 pieces of sawn lumber (such as rafters, planks, boards, battens, beams, and small beams) was obtained from logs derived from these trees. Lumber production was highest for boards (54.6% of volume, 47.4% of carbon) and lowest for small beams (1.9% of volume, 2.3% of carbon). The conversion factor for transforming log volume into carbon stored in sawn-wood products was 16.2%. Our results also show that species that retain low amounts of carbon should be allowed to remain in the forest, thereby avoiding low sawmill yield (and consequent generation of waste) and allowing these trees to continue fulfilling environmental functions.

Tropical forest management has both positive and negative effects on climate change, and quantifying these effects is important both to avoid or minimize negative impacts and to reward net positive effects. This study contributes to this effort by estimating the aboveground volume and carbon present in commercial tree species in a managed forest in the forest harvest stage in Brazil’s state of Acre. A total of 12,794 trees of commercial species were measured. Trees were categorized and quantified as: “harvested trees” (“harvest or cut”), which were felled in the harvest stage, and “remaining trees” (“future cutting,” “trees in permanent protection areas or APPs,” “seed trees,” “rare trees” and “trees protected by law”) that remained standing in the forest post-harvest. Aboveground volume and carbon stocks of the 81 commercial species (diameter at breast height [DBH] ≥ 10 cm) totaled 79.19 m³ ha⁻¹ and 21.54 MgC ha⁻¹, respectively. The category “harvested trees” represents 44.48% and “remaining trees” 55.49% of the aboveground volume stocks. In the managed area, the category “harvested trees” is felled; this is composed of the commercial bole that is removed (19.25 m³ ha⁻¹ and 5.32 MgC ha⁻¹) and the stump and crown that remain in the forest as decomposing organic material (15.97 m³ ha⁻¹ and 4.41 MgC ha⁻¹). We can infer that the 21.54 MgC ha⁻¹ carbon stock of standing commercial trees (DBH ≥ 10 cm) represents 13.20% of the total aboveground carbon in the managed area. The commercial boles removed directly from the forest represent 3.26% of the total aboveground carbon, and the stumps and crowns of the harvested trees represent the loss of an additional 2.70%. For sustainability of the management system in terms of carbon balance, growth in the 35-year management cycle must be sufficient to replace not only these amounts (0.27 MgC ha⁻¹ year⁻¹) but also losses to collateral damage and to additional logging-related effects from increased vulnerability to forest fires. Financial viability of future management cycles will depend on replenishment of commercial trees of harvestable size (DBH ≥ 50 cm).

Selective logging activities are commonly observed in the Brazilian Amazon and are responsible for high forest impact. In this study, selective logging detection techniques and the spatiotemporal extension of forests impacted by logging activities between 2003 and 2014 in portions of the states of Mato Grosso, Pará, and Rondônia were assessed using remotely sensing data. Based on results obtained, it was estimated that the overall accuracies are greater than 91% for techniques applied to detect forests impacted by selective logging in the study areas. Forests impacted by selective logging increased in Western state of Mato Grosso and Northern state of Rondônia, which indicates a stage high forest activity in these regions. In contrast, in Eastern state of Pará, a decrease in forests impacted by logging activities was observed, which indicates collapsed stage of logging activities resulting from deforestation and predatory logging in that region.

The scarcity of hardwoods from tropical forests makes the search for alternative species necessary for commercialization. This study aimed to establish groups of timber species from the Amazon Forest with potential for logging purposes through the assessment of their physical-mechanical properties, aiming to identify alternative species that can meet the market demands. We utilized data from the Forest Products Laboratory (LPF) (containing information on basic density and other wood mechanical properties) and the Timberflow platform, as well. We applied a multivariate cluster analysis technique with the aim of grouping species based on the technological characteristics of their wood and evaluating similarity among them to obtain homogeneous groups in terms of economic potential and utilization. The results indicated four homogeneous groups: Cluster 1 (40.72% of species, basic density-db: 690 kg m⁻³), Cluster 2 (13.92%, db: 260 and 520 kg m⁻³), Cluster 3 (27.32%, db: 550 and 830 kg m⁻³), and Cluster 4 (18.04%, db: 830 kg m⁻³). Most of the 20 listed species are classified as more commercially viable (70%), with high wood density. Species identified as alternatives include Dialium guianense and Zollernia paraensis for Dipteryx odorata, Terminalia argentea for Dinizia excelsa, Terminalia amazonia and Buchenavia grandis for Goupia glabra, and Protium altissimum and Maclura tinctoria for Hymenaea courbaril. The analysis highlighted the overexploitation of a restricted group of species and the need to find alternatives to ensure the sustainability of forest management. This study contributed to identifying species that can serve as alternatives to commercial ones, promoting a more balanced and sustainable forest management.

The objective of this work was to build and apply environmental indicators to verify the environmental performance and diagnose the sustainability levels of the rural properties from Federal District, Brazil. Data analysis was performed based on the information required and declared to public administration. Exploratory sampling was applied, obtaining a sample population of 169 properties. It was decided to use the factor analysis methodology in order to verify the environmental performance and diagnose the sustainability levels of the rural properties. The results achieved allow us to state that most of the properties (91.49%) are in a state of severe unsustainability. The results also show that the remnants of native vegetation, when they exist, are not in sufficient proportion to the total size of the property according to what the legislation requires. The proposed model and the environmental indicators built from the environmental legislation proved to be an efficient, practical and low-cost tool for a satisfactory diagnosis about the measurement of the sustainability of Brazilian rural properties and in the identification of positive management situations in relation to the suitability for environmental laws.