Diameter increment is an important variable in modeling tree growth. Most facets of predicted tree development are dependent in part on diameter or diameter increment, the most commonly measured stand variable. The behavior of the Forest Vegetation Simulator (FVS) largely relies on the performance of the diameter increment model and the subsequent use of predicted dbh in forecasting tree attributes.
Previous research has shown the efficacy of localized inventory data in calibrating model parameters when better predictions of individual and stand growth in focal geographic areas are sought. A sample-based sensitivity analysis (SA) is proposed as a preliminary step to model calibration, in order to identify which variables are most influential in determining predicted outcomes. SIMLab software was used for SA of the default dbh increment submodel in FVS-SN; samples were obtained from a recent inventory of longleaf pine stands in Fort Bragg, NC. Preliminary results show that dbh is by far the most important variable, followed by site index and competition-related predictors. Topographical and other site variables were largely non-influential. Before calibration and re-engineering of the submodel, variables conveying redundant or non-influential information may be considered for elimination.