Title: Partitioning the Uncertainty in Estimates of Mean Basal Area Obtained from 10-year Diameter Growth Model Predictions

Author: McRoberts, Ronald E.

Year: 2005

Publication: In: McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C.; McWilliams, William H.; Cieszewski, Chris J., eds. Proceedings of the fourth annual forest inventory and analysis symposium; Gen. Tech. Rep. NC-252. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Research Station. 45-51

Abstract: Uncertainty in model-based predictions of individual tree diameter growth is attributed to three sources: measurement error for predictor variables, residual variability around model predictions, and uncertainty in model parameter estimates. Monte Carlo simulations are used to propagate the uncertainty from the three sources through a set of diameter growth models to estimate the total uncertainty in 10-year predictions of mean basal area per unit area for a sample of Forest Inventory and Analysis plots. Response surface methodology is used to partition the total uncertainty by source. Of the three sources, the uncertainty in parameter estimates contributes most to the variance of the estimate of mean basal area per unit area.