OPTIMAL STAND LEVEL FOREST INVENTORY INTENSITIES UNDER DETERMINISTIC AND STOCHASTIC STUMPAGE VALUE ASSUMPTIONS

The basis for this study was that forest inventories, as well as other forestry activities, should be performed in such a way that a maximum present net value is attained. Consequently, both the inventory cost and the expected loss from erroneous decisions, caused by data errors, should be considered in the decision about which inventory designs should be used. Investigations of the optimal sampling intensities in stand level sample plot inventories were made under the assumptions of stumpage values being deterministic as well as stochastic. The methodology involved sampling simulation and simulation of stumpage value fluctuations. It was found that the optimal inventory intensities should be slightly lower in the stochastic case, the reason being that harvest decisions were largely influenced by the current stumpage values. The study, however, only addressed the problem of deciding the optimal point of time for clearcutting in cases when no harvest level restrictions over time were present.