2020 journal article

Site index estimation for clonal eucalypt plantations in Brazil: A modeling approach refined by environmental variables


author keywords: Site index; Soil water deficit; Site-specific management
UN Sustainable Development Goal Categories
13. Climate Action (Web of Science)
15. Life on Land (Web of Science; OpenAlex)
Source: Web Of Science
Added: May 26, 2020

Growth models have been applied to assess the growth potential for areas without previous forest plantation records and to update forest inventory when commercial stands have been planted. However, there is a lack of growth models capable of incorporating environmental variables for updating forest inventories and recomputing site quality throughout Brazil. Consequently, this research aimed to deliver a compatible set of prediction and projection growth equations with parameters refined by environmental variables. The dataset used through this study is composed of remeasurement information of 16 research sites in Brazil. At each site, the same eleven eucalypt clones were planted in single block plots. Extra block plots were also installed in 14 sites to evaluate eucalyptus growth under drier climate scenarios. Four different competing model forms were tested. A common parameter of the best compatible set of growth equations was refined to test the magnitude of the environment effect on the prediction and projections of dominant height/site index in clonal eucalypt stands in Brazil. The compatible set of Chapman-Richards growth equations displayed the most accurate estimates of dominant height for clonal eucalypt plantations in Brazil. The common asymptote parameters between the growth models were refined as a function of annual soil water deficit (SWD), and a gain in accuracy of the projected and predicted dominant height estimates was observed. It is relevant to highlight that the developed set of growth equations possesses the ability to make short-, medium- and long-term predictions and projections with more assuredness about the biological behavior and its soundness. This feature ensures accurate estimation of site-specific growth curves.