Modelagem de crescimento em plantios de eucalipto em função da interação fertilização - clima - desbaste

Abstract

Intensive management of eucalyptus plantations requires an understanding of the factors that impact tree growth and system productivity. The thesis was structured based on two articles and, for this, a set of data from Eucalyptus grandis implanted in 1999 in the states of Bahia and Espírito Santo was used. Three experiments were conducted, each one with twelve thinning treatments, which differ from each other in number, age and intensity. Each thinning treatment had four identical plots, two fertilized and two unfertilized in the mid-rotation. In the first article, a two-step modeling was developed: a logistic regression model as a function of the interaction of the thinning index and the relative spacing to determine the probability of volume gain with fertilization in the mid-rotation rotation; and a volume prediction model as a function of thinning intensity, site and uniformity, to quantify the additional gain in stand productivity at the end of the rotation with the applied fertilization treatment. The results showed that the proposed approach was accurate to model the volume responses to fertilization in mid-rotation in eucalyptus clonal plantations conducted for solid wood production. In the second article, the set of growth equations in dominant height based on the Lundqvist formulation had its asymptote expanded as a function of the thinning index, the fertilization indicator and the minimum temperature, allowing more accurate estimates when predicting and projecting the dominant height of the eucalyptus plantations studied. The equations developed in the second article can be used to make predictions and projections in the short, medium and long term with higher precision and security on the biological behavior compared to traditional formulations, being recommended to update inventories and evaluate the growth potential of areas without previous record of forest plantations based on a combination of silvicultural factors and climate history.