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Sustainable forest management is driving the development of forest decision support systems (DSSs) to include models and methods concerned with climate change, biodiversity and various ecosystem services (ESs). The future development of forest landscapes is very much dependent on how forest owners act and what goes on in the wider world; thus, models are needed that incorporate these aspects. The objective of this study is to assess how nine European state-of-the-art forest DSSs cope with these issues. The assessment focuses on the ability of these DSSs to generate landscape-level scenarios to explore the output of current and alternative forest management models (FMMs) in terms of a range of ESs and the robustness of these FMMs in the face of increased risks and uncertainty. Results show that all DSSs assessed in this study can be used to quantify the impacts of both stand- and landscape-level FMMs on the provision of a range of ESs over a typical planning horizon. DSSs can be used to assess how timber price trends may impact that provision over time. The inclusion of forest owner behavior as reflected by the adoption of specific FMMs seems to be also in the reach of all DSSs. Nevertheless, some DSSs need more data and development of models to estimate the impacts of climate change on biomass production and other ESs. Spatial analysis functionality needs to be further developed for a more accurate assessment of the landscape-level output of ESs from both current and alternative FMMs. European Commission Horizon 2020 Portuguese Science Foundation

Decision making in forest planning often involves situations, where the value of the stand is dependent on its location or the properties of the stands nearby. Often the most intuitive tool to describe spatial objectives and outcomes is a visual map. However, evaluating and comparing different maps may prove a considerable cognitive burden, especially over large areas and in long-term planning. In this study, we investigate the use of value functions for eliciting spatial preference information from maps. Our case study is part of a project investigating the possibilities of increasing broadleaf-tree-dominated habitats in a northern Swedish landscape. The experts involved in the project evaluated maps showing different fragmentation patterns. Different spatial indices were then calculated for the maps, and expert evaluations were used to sketch value functions describing the preferred fragmentation level. The approach was found to be a quick way of translating spatial preferences into numerical values and conceptualizing the relatively abstract concept of fragmentation in the landscape. Furthermore, the results show that the choice of a certain fragmentation index has a crucial effect on the value function.