Stem profile modeling is crucial in the forestry sector, particularly for commercially valuable species like teak (Tectona grandis Linn F.), whose value depends on its stem dimensions, heartwood proportion, and age. We proposed a nonlinear mixed-effect model to describe the evolution of the stem and heartwood profiles of clonal teak trees with ages between 4 and 12 years in the Brazilian Amazon. Tapering models were used to estimate the bark, bark-free, and heartwood diameters. Dummy variables were included in each tapering model to estimate each type of diameter and enable compatibility. We used mixed models with age as a random effect in order to improve the accuracy. The Demaerschalk model provided the most accurate and compatible estimates for all three types of stem diameter. Also, age as a random effect significantly improved the model’s accuracy by 7.2%. We observed a progressive increase in the heartwood proportion (14% to 34%) with advancing age, while the proportions of bark (23% to 20%) and sapwood (63% to 45%) showed inverse behavior. The growth rate of the heartwood differed from that of the bark volume, emphasizing the importance of considering the age of heartwood maximization when determining the cutting cycle of the species.

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.

We conducted a study on the dominant height growth of clonal teak (Tectona grandis Linn F.) plantations in the Brazilian Amazon to assess their potential and its agreement with volumetric production. We employed two approaches, ADA (algebraic difference) and GADA (generalized algebraic difference), and analyzed data from 58 permanent plots collected over a 10 year period. To classify the sites, we developed equations and evaluated their accuracy using various criteria, including correlation coefficient, mean square of residual, Akaike’s criterion, distribution of residuals, and validation through equivalence testing (TOST). We also assessed the biological realism of the constructed curves. We used cluster evaluation and dendrogram comparison to assess the agreement between site index and volumetric production for each approach. The Lundqvist–Korf baseline models (M1–ADA and M4–GADA) proved to be accurate and realistic in estimating dominant height in both approaches. Our findings indicate that the approaches utilizing dynamic equations and generating polymorphic curves effectively represent the sites and indicate the volumetric production of the plantations, with 98.3% of agreement rate. Based on our results, we recommend the use of ADA and GADA approaches for estimating the dominant height of clonal teak plantations in the Eastern Brazilian Amazon.

Tropical forests play an important role in mitigating global climate change, emphasizing the need for reliable estimates of forest carbon stocks at regional and global scales. This is essential for effective carbon management, which involves strategies like emission reduction and enhanced carbon sequestration through forest restoration and conservation. However, reliable sample-based estimations of forest carbon stocks require accurate allometric equations, which are lacking for the rainforests of the Atlantic Forest Domain (AFD). In this study, we fitted biomass equations for the three main AFD forest types and accurately estimated the amount of carbon stored in their above-ground biomass (AGB) in Rio de Janeiro state, Brazil. Using non-destructive methods, we measured the total wood volume and wood density of 172 trees from the most abundant species in the main remnants of rainforest, semideciduous forest, and restinga forest in the state. The biomass and carbon stocks were estimated with tree-level data from 185 plots obtained in the National Forest Inventory conducted in Rio de Janeiro. Our locally developed allometric equations estimated the state’s biomass stocks at 70.8 ± 5.4 Mg ha⁻¹ and carbon stocks at 35.4 ± 2.7 Mg ha⁻¹. Notably, our estimates were more accurate than those obtained using a widely applied pantropical allometric equation from the literature, which tended to overestimate biomass and carbon stocks. These findings can be used for establishing a baseline for monitoring carbon stocks in the Atlantic Forest, especially in the context of the growing voluntary carbon market, which demands more consistent and accurate carbon stock estimations.