The AFM-ToolBox to Support Adaptive Forest Management Under Climate Change

Abstract

Climate change may strongly impact on forests and affect the provisioning of forest ecosystem services. The identification, design, selection and implementation of adaptive measures in forest management requires a sound knowledge base as well as tools to support the forest manager in decision making. Decision support systems (DSS) are considered as particularly useful to assist in dealing with ill structured decision making problems. Forest management planning and decision making deals with highly complex socio-ecological systems with multiple interacting spatial and temporal dimensions. Finding ways and means to communicate findings about such complex relationships in forest ecosystems and their management via information technology is a challenge in itself. This is amplified if decision problems include land use change and climate change issues as uncertainty in planning outcomes increases. The literature reports numerous attempts to develop DSS for forest management. However, recently several review papers conclude that there has been only limited uptake of DSS into practice because frequently user demands and the characteristics of decision problems are not considered properly. In this contribution we propose five design principles for forest management DSS: (1) modularity, (2) accessibility via the internet, (3) inclusion of different types of knowledge and information, (4) possibility to use different data sources, and (5) support of specific problem types. Based on these principles we promote a ToolBox approach attempting to meet context specificity as well as flexibility addressing different user and problem types simultaneously. The AFM (Adaptive Forest Management) ToolBox is introduced and the conceptual design and technical implementation of the ToolBox is presented. The combination of different decision support techniques (e.g. vulnerability assessment, multi-criteria analysis, optimization) allows to support all phases of the decision making process and provides the user with the flexibility to interpret the information in various forms. The results of a self-assessment of the ToolBox against eight evaluation criteria for DSS are combined with a feedback from a panel of expert users who had tested the usability and had evaluated the conceptual approach of the ToolBox. The feedback stimulates the further development and ultimately will increase the level of acceptance by potential users. It is concluded, that the ToolBox approach focusing on modularity while avoiding over-emphasis of technical integration provides the right frame to secure the flexibility to add new tools and improve the support of decision making processes which is mandatory if a DSS should be taken up by practice.