ARANGE · Advanced multifunctional forest management in European mountain ranges

The sustainable provision of ecosystem services (ES) in and from mountain regions is of crucial importance to an array of stakeholders and society in general, going much beyond the interests of particular landowners in the mountain regions themselves. Mountain ecosystems can only continue to provide all these services in a rapidly changing world if a wide array of ES is considered in forest management at local, landscape and regional scales (multi-functionality). The project builds on seven case study regions in major mountain ranges throughout Europe covering a wide range of forest types, socio-economic conditions and cultural contexts and seeks to develop and evaluate strategies for their multifunctional management considering risks and uncertainty due to changing climatic and socio-economic conditions. The project addresses four main ES: timber production, protection against gravitational natural hazards, the role of forests in climate change mitigation via carbon sequestration as well as bioenergy production, and nature conservation and the maintenance of biodiversity. Non-timber forest products, recreation as well as use of forested landscapes by game and livestock species will be dealt with as well. To analyse conflicts and comple¬mentarities among ES from stand to landscape scales, improved models for the assessment and projection of ecosystem services as well as novel planning and decision support tools will be developed together with SMEs and applied in the case study regions. Stakeholder panels in all study regions will inform research activities and contribute to the development of improved mountain forest management approaches. SME partners play a key role in the development of new planning tools. Ultimately, ARANGE will translate project findings on the efficient provision of multiple ES from mountain forests into decision support for policy makers and forest practitioners, so as to improve the robustness of planning tools in real-world decision making.