Abstract
• Key messageErrors 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.• ContextErrors 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.• AimsWe evaluate the effect of varying levels of errors in basal area and mean diameter on the inoptimality losses.• MethodsErrors 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.• ResultsThe 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.• ConclusionIf 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.
Highlights
Forest management planning aims to find the combination of management prescriptions for different stands that maximizes the utility of the decision-maker (Pukkala 2002)
When the management prescriptions were selected for the datasets that were based on random information, the mean of inoptimality losses ± standard error was 8.85 ± 0.09% for the 10-year period
The greatest inoptimality loss and the smallest based on random information (BRI) value were obtained when the basal area was overestimated by 20% and the mean diameter was underestimated by 20%
Summary
Forest management planning aims to find the combination of management prescriptions for different stands that maximizes the utility of the decision-maker (Pukkala 2002). Plans are developed using forest planning systems where the current stand attributes are used as the starting point for the simulation of Handling Editor: John M Lhotka. PP and TP supervised the research, commented, and revised the manuscript. Extended author information available on the last page of the article alternative treatment schedules for the stands or some other calculation units. The optimal combination of the simulated treatment schedules is searched for. If the decisionmaker considers the forest as an investment, the optimal management prescriptions are commonly selected based on the net present value (NPV)
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