Incorporating rainfall data to better plan eucalyptus clones deployment in eastern Brazil

Abstract

The goals of this study were to identify and group three eucalyptus clones, each under coppice and clear-cut management regimes, into two or more groups based on similar growth rates; and fit a site index equation as a function of rainfall variables for each group to evaluate how different groups were impacted by climatic variation. The database came from the Continuous Forest Inventory (CFI) and weather stations. The CFI was conducted between 1994 and 2012, with climatic data also being gathered for the same period. The study area was managed by clear-cut and coppice regimes, with 126 and 72 CFI plots, respectively. The relationship between clones, management regimes and stand age with annual dominant height growth was assessed by linear mixed effects modeling. Ridge regression was applied for fitting each group as a function of the rainfall variables. Finally, ordinary Kriging was applied for each of the rainfall variables in the study area. Then, site index equations were applied to the generated maps enabling the observation of their pattern throughout the study area as well as their evaluation under a pessimistic climatic scenario. Three groups were defined, since each clone exhibited similar growth behavior under either management regimes; however, the 3 clones differ among each other. A significant reduction in the annual dominant height growth over time was observed for all 3 clones. Ridge regressions afforded good accuracy and equations with sound biological behavior. Applying the fitted site index equations to the maps of precipitation and rainy days enabled the definition of the most appropriate clone to be planted throughout the area. Site quality as a function of rainfall variables could be an important tool to better enable silvicultural planning, since it provides estimates of the site index and also enables the incorporation of short-term climate change.