The influence of forest data quality on planning processes in forestry

Forestry planning relies on decision support systems for predicting and evaluating the outcomes of different management options. The accuracy of data describing the initial state of the forest will inevitably affect the projections of forest development and, hence, the quality of management decisions. As data acquisition is expensive, there is a trade-off between improving management plans and the increasing cost of gathering more data. This review attempts, from a critical perspective, to summarize research on how the quality of forestry data affects the results of forestry planning and decision making. It is structured as follows: first, the attempts to evaluate forestry data for forestry planning purposes are described, including methodology and main conclusions; secondly, some generic questions concerning how important aspects of this research area can be handled are posed and discussed; and finally, some conclusions are drawn, including methodological recommendations. It is concluded that research in this area is scarce, which is in contrast to the fields of forestry planning and forest data acquisition. The inherent complexity of forestry planning is probably the reason why those who seek to evaluate forestry data often oversimplify the problems.