Generalized linear models and extensions for analyzing height-diameter, taper, and biomass data in managed forest stands - Silva, Breno Gabriel da (2025)
The use of wood for various industrial sectors, such as furniture, steel, and pulp and paper, has been growing continuously. The species of the genera Eucalyptus, Pinusstand out as the most planted in Brazil, representing approximately 9.17 million hectares according to the report from the Brazilian Tree Industry. Therefore, its of utmost importance to estimate the volume of wood, which is generally done using equations that depend on variables such as height and diameter at breast height. Obtaining diameter at breast height values is relatively simple. However, quantifying the total heights of the inventoried trees using hypsometers becomes impractical, as this procedure is typically costly and prone to human error. Hypsometric equations are used to obtain essential information about a forest stand to estimate the total height of trees based on certain dendrometric variables, such as diameter at breast height, age, dominant height, etc. They are low-cost and have high explanatory power. On the other hand, taper equations are used to estimate the total volume or any specific part of interest in trees. The objective of this study is to provide contributions to the forestry field by proposing statistical models that best represent these variables based on commonly observed effects. Initially, a literature review was conducted on hypsometric models, highlighting historical facts about the formulation and purpose of the proposals in the scientific scenario. Next, the modeling of hypsometry and stem taper under the approach of mixed-effects models is proposed for the analysis of observational data from trees of the species Eucalyptus grandis × Eucalyptus urophylla and Pinus taeda , respectively. For the diagnostic analysis of the adopted models, the least confounded residuals, along with a simulation study to assess the adequacy of the models. It is expected that the results will show that mixed-effects models present an excellent alternative to the models commonly adopted in the forestry literature.