Stochastically generating tree diameter lists to populate forest stands based on the linkage variables forest type and stand age

Abstract

Forest inventory data were used to develop a standage-driven, stochastic predictor of unit-area, frequency weighted lists of breast high tree diameters (DBH). The average of mean statistics from 40 simulation prediction sets of an independent 78-plot validation dataset differed from the observed validation means by 0.5 cm for DBH, and by 12 trees/h for density. The 40- simulation average of standard deviation, quartile range, maximum value and minimum value differed from the validation dataset, respectively, by 0.3, 1.3, 0.6 and 1.5 cm for DBH, and 10, 42, 29, and 54 trees/h for density. In addition, test statistics were also computed individually for each of the 40 single simulations of the 78-plot validation dataset. In all cases, the test statistics supported the {} hypothesis of no difference between simulated and observed DBH lists. When power of these hypothesis test statistics was set to 80%, the calculated minimum detectable differences were still reasonably small at 2.7 cm for mean DBH and 90 trees/h for stocking. Also, the shape and dispersion of simulated mean-DBH/density scatter graphs were similar to the same scatter graph from the observed, validation dataset.

Citation

Parresol, Bernard R.; Lloyd, F. Thomas. 2003. Stochastically generating tree diameter lists to populate forest stands based on the linkage variables forest type and stand age. In: 2003 Join Statistical Meetings - Section on Statistics & the Environment: 3197-3202