César Augusto Guimarães Finger

Accurate modeling of stem taper is essential for forest management decisions, including the definition of cutting cycles, the feasibility of annual harvesting, assortment classification, size and volume estimation, and ensuring sustainable production continuity. This study modeled the stem taper of Araucaria angustifolia (Bertol.) Kuntze stands in southern Brazil using Kozak’s variable-exponent model fitted with nonlinear mixed-effects techniques. Both fixed- and mixed-effects models showed high predictive performance, regardless of calibration. An unstructured (UN) covariance structure was required to reduce autocorrelation. The mixed-effects model improved predictive accuracy by up to 22%, achieved R² values above 0.99 with RMSE < 0.74 cm, and significantly reduced residual autocorrelation in diameter estimates. The most effective calibration of random effects was achieved using diameter measurements taken at heights between 0.3 and 6.3 m above ground (approximately between 1.3% and 28.3% of the total height, considering the tallest tree as a reference). This research improves the accuracy of volume estimation and the definition of timber assortments for A. angustifolia, thereby supporting forest management decision-making in southern Brazil.

Precise estimates of dendrometric and morphometric variables are indispensable for effective forest resource conservation and sustainable utilization. This study focuses on modeling the relationships between shape (morphometric), dimension (dendrometric) and density (N) to assess the sustainability of forest resources. It sheds light on the current state of site characteristics, reproduction, and the structure of Araucaria angustifolia trees at selected forest remnants across multiple sites in Santa Catarina, Southern Brazil. Individual trees and their dendrometric variables, such as the diameter at breast height (d), height (h), crown base height (cbh), annual periodic increment (API) in growth rings, and morphometric variables, including four radii of the crown in cardinal directions, were evaluated. These measurements allowed us to calculate various morphometric indices and crown efficiency, enabling the assessment of both vertical and horizontal structural conditions. Statistical analysis confirmed a positive relationship of the crown volume (cv) and crown surface area (csa) with the crown length (cl). Conversely, the crown efficiency, density, increment rate, and reproductive structure production declined. These morphometric relationships emphasize the complex dynamics within these forest ecosystems, irrespective of the chosen site, indicating that horizontal and vertical forest structures have stagnated and have been characterized by limited change in the last ten years. Such results raise concerns about sustainability, highlighting the need for proper conservation measures and sustainable forest management practices. Our findings underscore the need for substantial adjustments in the structure and dynamics of the forest, particularly on selected rural properties where this tree species is abundant, to ensure long-term sustainability.

Vulgarmente conhecido como Açoita-cavalo, Luehea divaricata Mart. e Zucc., pertencente à família Malvaceae, possui importância econômica na indústria de cosméticos, medicinal e movelaria. O objetivo deste trabalho foi verificar a taxa de incremento de Luehea divaricata Mart. e Zucc em função do tempo, sob diferentes níveis de sombreamento. As plantas foram submetidas a quatro níveis de luz, sombreamentos: 0% (pleno sol), 30%, 50% e 70%. Para produzir o efeito de níveis de luz, utilizou-se sombrites de cor preta. As variáveis coletadas e quantificadas foram: altura da planta, diâmetro do caule, massas secas de folha, caule, raiz, e o volume de raíz. Os dados foram coletados por cinco meses, considerando cada mês como um bloco, foram organizados em planilha e submetidos ao programa estatístico. E analisados pela análise de variância ao nível de 95% de confiança. Havendo diferença entre os blocos, e/ou entre os tratamentos, aplicou-se o teste de Tukey. Houve efeito do tempo no incremento em altura e diâmetro, com maiores médias nos blocos de setembro e outubro. Nas massas secas de folha e caule, houve diferença entre os tratamentos, com maior média a 70% e menor no 50%. As menores médias em massa e volume de raiz estiveram no 50%, e as maiores no pleno sol. Para produção de L. divaricata em viveiro, recomenda-se o tratamento com 70% de sombreamento.

Araucaria angustifolia (Bertol.) Kuntze, commonly known as Brazilian pine, is a significant tree species in the Brazilian flora that once covered an area of 200,000 km² in the Southern region. During the 1970s, high-quality timber logs from this conifer became the primary export product of the country. However, the species is endangered due to uncontrolled exploitation and is subject to a harvesting ban. It is crucial, therefore, to explore sustainable cultivation methods for this species, which necessitates urgent research and scientific insights. In this study, we present a simulation of a management strategy for in situ conservation by manipulating growth space and crown size dynamics. Forest inventory data and mixed forest regression equations were employed to describe the horizontal dimensions of average and maximum potential crown growth, resulting in two management scenarios. The results presented in management diagrams show that both approaches required logging numerous trees to ensure adequate space for healthy tree growth and provide soil coverage and forest protection. Therefore, the absence of effective forest management initiatives for Araucaria forests may have further implications for the structure, production, conservation, and overall development. To address these challenges, we propose two hypotheses: firstly, that tree diameter depends on crown dimensions, which are in turn influenced by tree growth space, and, secondly, that crown dimensions serve as a reliable indicator of existing competition and can be utilized to simulate forest management practices. We urge that implementing sustainable forest management initiatives for Araucaria angustifolia at selected locations can contribute to expanding natural forest areas, mitigate deterioration caused by high competition, discourage illegal logging, and prevent overexploitation of their edible seeds, which hinders regeneration. Our results underscore the significant implications of the lack of forest management initiatives in rural properties, potentially resulting in irreversible deterioration. The exact consequences of this deterioration remain unclear, emphasizing the need for further studies to understand its eventual effects on the growth reaction of trees of different diameters, ages, and crown conditions after the liberation of their crowns.

Knowledge of the formation and correlation of reproductive structures with dendro/morphometric variables of the Araucaria angustifolia tree species is a tool for its conservation and viability for sustainable forest management. We counted visually in araucaria trees the number of male strobili in RGB images acquired by Remotely Piloted Aircraft System (RPAs) over forest remnants. The diameter at the breast height (d), total height (h), crown radii (cr), crown base height (cbh), periodic annual increment in d based on increment rolls were measured, and the morphometric indices and crown efficiency were calculated with these variables. The relationships of these variables with male strobili production were analyzed by Pearson’s correlation and multivariate analysis techniques (cluster, factorial analysis, and main components). The morphometric variables correlated with the production of male strobili were d (r = 0.58, p-0.0002), crown diameter (r = 0.62, p < 0.0001), crown area (r = 0.62, p < 0.0001), coverage index (r = 0.51, p-0.001) and slenderness (r = −0.39, p-0.01). We argue that the production of male strobili is related to the vitality, dimension, density, growth space, and position in the stratum of the tree inside the forest, inferring a relationship between reproductive structures with the shape, size, growth space, and tree density. Such aspects shall be considered in future forest management initiatives in Southern Brazil.

The international market has recognized the high value of Tectona grandis L.f. plantations, requiring the development of reliable and accurate tools and techniques to quantify forest stocks accurately. In this study, we developed suitable equations to estimate the stem diameters and volume of Tectona grandis trees in the central-western region of Brazil, evaluating the stem form change points (FCPs) and testing the stratification of data as a measure to control their variation. The Schöepfer model was tested in the study of the FCPs of the stem, and single equation, segmented and variable-exponent taper functions were used to describe the stem profile. After the selection of the model for the taper, data stratification in the DBH classes, form parameter “r” and artificial form factor were proposed. The total volumes of each tree were calculated by integrating the Clark III et al. model. The FCPs of the Tectona grandis stems occurred at 28%, 57% and 73% of the total height, corresponding, on average, to the absolute positions of 6.4 m, 13.3 m and 16.5 m. The Clark III et al. equation, without stratification, was the most appropriate equation to estimate the diameters along the stem and the volume of Tectona grandis trees in the central-western region of Brazil.

The Brazilian Cerrado biome is a hotspot due to its ecological importance and high diversity of fauna and flora. We aimed to develop statistical models to predict the crown diameter of open-growing trees using several forest attributes. Potential crown diameter trends in the measured trees were determined by quantile regression. Crown diameter models were developed by regression analyses, artificial neural networks, support vector machine, and random forest techniques. We evaluated 200 trees characterized into 60 species belonging to 30 botanical families. Our equation for potential crown diameter predicts the derived basal area, number of trees, and the necessary growth space of crown diameter at breast height. Artificial neural networks (with the following validation statistics: R² = 0.90, RMSE = 1.21, MAE = 0.93, and MAPE = 16.25) predicted crown diameter more accurately than the other evaluated techniques. Modeling crown diameter via machine learning represents an important step toward the assessment of crown dynamics by species and can support the decision making of silvicultural practices and other related activities in several rural properties within the Cerrado biome.

Artificial intelligence (AI) seeks to simulate the human ability to reason, make decisions, and solve problems. Several AI methodologies have been introduced in forestry to reduce costs and increase accuracy in estimates. We evaluate the performance of Artificial Neural Networks (ANN) in estimating the heights of Araucaria angustifolia (Bertol.) Kuntze (Brazilian pine) trees. The trees are growing in Uneven-aged Mixed Forests (UMF) in southern Brazil and are under different levels of competition. The dataset was divided into training and validation sets. Multi-layer Perceptron (MLP) networks were trained under different Data Normalization (DN) procedures, Neurons in the Hidden Layer (NHL), and Activation Functions (AF). The continuous input variables were diameter at breast height (DBH) and height at the base of the crown (HCB). As a categorical input variable, we consider the sociological position of the trees (dominant–SP1 = 1; codominant–SP2 = 2; and dominated–SP3 = 3), and the continuous output variable was the height (h). In the hidden layer, the number of neurons varied from 3 to 9. Results show that there is no influence of DN in the ANN accuracy. However, the increase in NHL above a certain level caused the model’s over-fitting. In this regard, around 6 neurons stood out, combined with logistic sigmoid AF in the intermediate layer and identity AF in the output layer. Considering the best selected network, the following values of statistical criteria were obtained for the training dataset (R² = 0.84; RMSE = 1.36 m, and MAPE = 6.29) and for the validation dataset (R² = 0.80; RMSE = 1.49 m, and MAPE = 6.53). The possibility of using categorical and numerical variables in the same modeling has been motivating the use of AI techniques in different forestry applications. The ANN presented generalization and consistency regarding biological realism. Therefore, we recommend caution when determining DN, amount of NHL, and using AF during modeling. We argue that such techniques show great potential for forest management procedures and are suggested in other similar environments.

This research aimed to develop statistical models to predict basal area increment (BAI) for Araucaria angustifolia using Artificial Neural Networks (ANNs). Tree species were measured for their biometric variables and identified at the species level. The data were subdivided into three groups: (1) intraspecific competition with A. angustifolia; (2) the first group of species that causes interspecific competition with A. angustifolia; and (3) the second group of species that causes interspecific competition with A. angustifolia. We calculated both the dependent and independent distance and the described competition indices, considering the impact of group stratification. Multi-layer Perceptron (MLP) ANN was structured for modeling. The main results were that: (i) the input variables size and competition were the most significant, allowing us to explain up to 77% of the A. angustifolia BAI variations; (ii) the spatialization of the competing trees contributed significantly to the representation of the competitive status; (iii) the separate variables for each competition group improved the performance of the models; and (iv) besides the intraspecific competition, the interspecific competition also proved to be important to consider. The ANN developed showed precision and generalization, suggesting it could describe the increment of a species common in native forests in Southern Brazil and with potential for upcoming forest management initiatives.

Pertencente à família Malvaceae, Luehea divaricata Mart. & Zucc, é importante para serviços ecológicos de recuperação de áreas alteradas e para extração de madeira. O objetivo deste trabalho foi entender o efeito de diferentes níveis de sombreamento no desenvolvimento de plantas de Luehea divaricata e qual ambiente de luz propicia melhores condições de crescimento e desenvolvimento para a espécie. Foram aplicados quatro tratamentos: 0% (pleno sol), 30%, 50% e 70% de sombreamento. Determinou-se: crescimento em altura (h), diâmetro (d), número de folhas (NF), brotos (NB, ramificações), área foliar (AF), área foliar específica (AFE), massa seca de folhas (MSF), de caule (MSC), raiz (MSR), massa seca total (MST), e volume da raiz (Volr). As avaliações deram-se por um período de 11 meses, determinando-se as massas e Volr, ao fim do experimento. O tratamento mais sombreado teve as maiores taxas de crescimento em h, enquanto o tratamento a pleno sol, o maior crescimento em d. Em NB os tratamentos à pleno sol e 30% se destacaram, enquanto os 50% e 70% de sombreamento apresentaram as menores médias. AF obteve melhor desempenho nos tratamentos extremos (à pleno sol e o mais sombreado). Para AFE, verificou-se que no tratamento a pleno sol, os valores foram menores que aqueles obtidos nos tratamentos sombreados. As plantas à pleno sol tiveram a MSF superior à dos tratamentos sombreados, enquanto MSC foi maior para os tratamentos a pleno sol e 70%. Ocorreu maior acúmulo de biomassa total em plantas expostas em ambientes com maior luminosidade, diferindo-se dos tratamentos sombreados que apresentaram as menores médias. Plantas de L. divaricata expostas a maior luminosidade tendem a apresentar mais ramificações, e o oposto ocorre em plantas que crescem em ambientes mais sombreados, que formam menos ramificações e investem seu crescimento em altura na haste principal. Assim, a recomendação do cultivo de plantas dessa espécie depende do objetivo a qual a espécie será destinada. Se para recuperação de áreas alteradas, pode-se fazer o cultivo delas em casa de vegetação em ambientes à pleno sol; e no campo, sugere-se o plantio direto, por suportar ambientes expostos a alta luminosidade. Se o objetivo for para fins de produção de madeira, recomenda-se o cultivo da espécie em casa de vegetação em ambientes com 70% de sombreamento, e quando transplantadas para o campo, sugere-se o plantio intercalados com espécies que propicie condições de sombreamento para o estabelecimento dela.