Equações volumétricas para clones de eucalipto em três densidades populacionais

Abstract

This study was conducted in the context of searching for sustainable and efficient practices in the management of forest plantations and the adjustment of volumetric equations for eucalyptus clones based on population density. These are essential to meet the growing industrial demands for forest-based products, such as paper, pulp, and biomass for energy. The objective of this work was to adjust volumetric equations for eucalyptus clones based on population density and the age of the plantation. To achieve this goal, the study focused on analyzing variables such as tree height, trunk section diameters, and tree volume across different population densities. The adopted methodology involved collecting data on these variables in eucalyptus plantations, where specific clones were monitored over time. Statistical analysis of the collected data enabled the development and adjustment of predictive models capable of estimating the growth of the clones based on population density. For the VE41 clone, the Schumacher-Hall model proved very accurate for 26-month-old trees, with an adjusted R2 of 97.27%, while the Prodan model was highlighted for 40-month-old trees, with an adjusted R2 of 98.23%. The I144 clone had better results with the Modified Naslund model at 26 months and with the Logarithmic Spurr model at 40 months. Models such as Kopezki-Gehrardt and Husch showed inferior performance in various contexts, indicating their inadequacy for certain growth conditions and population densities. Rigorous cubing models, which directly involve the cut woods, generally exhibit higher adjusted R2s and lower Syx(m3) errors compared to standing tree cubing models, which, although less precise, offer advantages in terms of sustainability and lesser environmental impact. A comprehensive analysis provides valuable insights for the selection of suitable models in different forest management settings, aiming at the sustainable optimization of wood production.