Uso de variáveis climáticas para classificação de sítios em povoamentos de eucalipto

Abstract

The site production capacity in forest modeling is represented by the site index or projection of dominant height at the reference age. The site rating is the key to the whole prognosis system. However, methods related with increase of accuracy and flexibility of equations are important to create productivity scenarios due to climate changes. The overall objective of this study was to relate forest development with climate variables. Firstly, we aimed to propose a flexible model seeking to represent the dominant height growth. Then, we sought to identify climatic variations that affect the site capacity in wood production, and how. The research was related with the development of eucalyptus stands under the tall trees and coppice management regimes in Midwest Region of the State of Espirito Santo and Southern Bahia. Data were obtained on 299 permanent plots of stands of Eucalyptus urograndis, from which 155 are related with the coppice management regime and 144 are related with high tree-trunk management regime. Climatic data were obtained from 31 meteorological stations distributed in the area under study. The polymorphic modified Von-Bertallanfy Richards model with common asymptote showed the best performance for both two management regimes. The mean monthly rainfall and distribution of rainy days were used to expand the model parameters. The climatic conditioning of coefficients brought gains in terms of accuracy of estimates. In addition, it allowed the generation of development scenarios from interannual climate variations. This survey also showed that the mean monthly rainfall and number of rainy days were the most related variables with the site productive capacity. These factors showed positive linear effect on the site capacity to produce wood. Therefore, this methodology allows managers to predict forest productivity scenarios on interannual climate changes, as well as the expectation of growth for sites without historical data of plantations.