Hypsometric relations of clonal eucalyptus in south of Tocantins. This work was structured in two chapters, using 11 rectangular and permanent plots of 348 m² each, from a clonal plantation of Eucalyptus camaldulensis and Eucalyptus urophylla in the southern region of the state of Tocantins. The first chapter aimed at the best way of adjusting hypsometric models, analyzing the accuracy of the best model, and applying it in a different forest situation. The data were divided into one set of adjustment and another of application, with three classes of diameter and three classes of dominant height. The coefficient of determination adjusted in percentage (R²aj), standard error of the estimate in percentage (Syx%), and residual graphical analysis were determined initially. A model identity test was then performed, followed by a completely randomized design (DIC) in the subdivided plot scheme, along with the Dunnet test. At the end of the analysis, to evaluate the stability of the models in a validation test, the following criteria were used: prediction determination coefficient (R²), sum of squares of the residual residue (SQRR), square root mean error (RQEM) mean error (EMP). It was concluded that the best form of adjustment was to perform an adjustment by class, being the regional model the most appropriate to be used. The second chapter deals with the evaluation of hypsometric models applying the cross validation technique, and the comparison of the results with those obtained in chapter 1, aiming to obtain the best model to be used in the region under different aspects of selection. Initially the precision criteria were applied: adjusted coefficient of determination, standard error of the estimate and residual graphical analysis. Then, the stability criteria were applied by performing cross-validation between the two batches of data, which were: absolute mean error, mean square root, and mean square error sum. The selected models were submitted to a new analysis, using the data bundles of chapter 1, where the same criteria of precision and stability previously used were applied, resulting in the comparison between the chapters. It was concluded that the best local model was Chapman-Richards 14, the best regional model was parabolic 03, and in comparison with the models selected in chapter 01, the most suitable for planting was the regional parabolic model 3, of chapter 02.
|
