Regression tree model and linear regression model approaches were employed to quantify the relationship between site index and soil parameters. The final linear regression model performed better than the optimal regression tree model. These resulting predictive models are particularly well-suited for areas where forest stands are not currently established.
Learning Objectives:
Provide non-industrial private forest landowners (NIPLs) and practicing foresters with updated Natural Resources Conservation Service (NRCS) estimates of site index (SI) and mean annual increment (MAI) for loblolly pine plantations in the Coastal Plain.
Demonstrate how to use regression tree model and linear regression model approaches to quantify the relationship between site index and soil parameters.
