Model testing by means of cost-plus-loss analyses

Tests of models on independent data as a part of the model development often end when the errors are calculated and evaluated, and compared with corresponding results from previously developed models. The error calculations, however, provide only limited information with respect to the application of a model. Valuable information may also be obtained if a link between the errors, the consequential incorrect treatment decisions and the corresponding economic losses can be established. A case study, based on models for prediction of basal area mean diameter and number of trees/ha in forest stands, where the economic losses related to incorrect timing of final harvests when decisions were based on erroneous predicted information, is presented. The case study demonstrates that calculation of the economic losses provides information that is useful as a supplement to considerations based on errors only when it comes to application of the models. The quantification of the economic losses, expressed in monetary terms, provides information that enables the modeller to relate effects of model errors directly to inventory costs. The variations in losses under different forest conditions also demonstrated a potential for reduced costs where there is a choice between use of the models when the economic losses are low and use of field measurements when the economic losses are high.