DEVELOPMENT OF MODELS TO AID DECISION-MAKING IN THE MANAGEMENT OF Araucaria angustifolia (Bertol.) Kuntze

et al. 2023

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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.

Section: Field Inventorymentioning

confidence: 99%

Simulating Sustainable Forest Management Practices Using Crown Attributes: Insights for Araucaria angustifolia Trees in Southern Brazil

Finger

Costa

et al. 2023

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Enhancing Height Predictions of Brazilian Pine for Mixed, Uneven-Aged Forests Using Artificial Neural Networks

Costa

Finger

et al. 2022

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.

Can We Predict Male Strobili Production in Araucaria angustifolia Trees with Dendrometric and Morphometric Attributes?

Demétrio

Sousa

et al. 2022

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.