Effects of errors in basal area and mean diameter on the optimality of forest management prescriptions

Abstract

Abstract • Key message Errors in forest stand attributes can lead to sub-optimal management prescriptions concerning the set management objectives. When the objective is net present value, errors in mean diameter result in greater losses than similar errors in basal area, and underestimation greater losses than overestimation. • Context Errors in forest inventory data can cause inoptimality losses in the objectives set to forest management. Losses occur when the forest is treated with management prescriptions that are optimal for erroneous data but not for correct data. • Aims We evaluate the effect of varying levels of errors in basal area and mean diameter on the inoptimality losses. • Methods Errors from 20% of overestimation to 20% of underestimation were simulated in basal area and mean diameter. For each stand, the management prescription that maximized the net present value was selected with and without errors. The inoptimality losses were calculated for different error levels. • Results The tested error levels resulted in inoptimality losses of 0.11–3.01%. Errors in mean diameter increased inoptimality losses more than similar relative errors in basal area. Simultaneous underestimation of basal area and mean diameter led to greater inoptimality losses than simultaneous overestimation of these attributes. • Conclusion If the forest is considered as an investment, using inventory data where basal area and mean diameter are underestimated causes greater losses compared with data where these attributes are overestimated. Errors in mean diameter are more important than similar errors in the basal area. Large errors in basal area and mean diameter should be avoided especially in stands where the basal area is high.