. Development and evaluation of an even- and uneven-aged ponderosa pine/Arizona fescue stand simulator. Ponderosa pine; Forest management. For large samples, Stage randomly picks a deviate from the normal distribution of the residuals about the log of basal area growth regression equation and adds it to the estimate of log of basal area growth. The underlying assumption is that, with a large sample, the effects of the individual random deviations will average out over the stand. For small samples, each sample tree record is divided into three sample tree records. The number of trees in each re
. Development and evaluation of an even- and uneven-aged ponderosa pine/Arizona fescue stand simulator. Ponderosa pine; Forest management. For large samples, Stage randomly picks a deviate from the normal distribution of the residuals about the log of basal area growth regression equation and adds it to the estimate of log of basal area growth. The underlying assumption is that, with a large sample, the effects of the individual random deviations will average out over the stand. For small samples, each sample tree record is divided into three sample tree records. The number of trees in each record is a fixed proportion of the original number of trees represented by the old sample tree record. The proportion breakdown Stage used was 15, 60, and 25 percent, based on previous findings that an average stand had 15 percent suppressed trees and 25 percent dominant trees.^ Each of the new sample tree records is assigned a growth rate computed by taking the average growth rate (as predicted by the log basal area growth equations) and adding a random component. For the 25 percent dominant trees, the random component is the expected residual value of the largest 25 percent of the normally distributed residuals about regression; for the 15 percent suppressed trees, it is the expected residual value of the lowest 15 percent of the normally distributed residuals, and similarly for the middle trees. As a result, the weighted log of basal area growth still sums to the average log of basal area growth, as predicted by the equation. At each simulation period, the sample tree records are split again until enough sample trees exist so that the first method can be used. Certain aspects of the second method seem applicable to this study. Within a diameter class, individual tree growth could be quite variable. By using only average diameter growth, all trees in the class will be assigned the same growth rate and, therefore, advancement to larger diameter classes will be identical. If, ho
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