Abstract:In mountain forests of Central Europe, storm and snow breakage as well as bark beetles are the prevailing major disturbances. The complex interrelatedness between climate, disturbance agents, and forest management increases the need for an integrative approach explicitly addressing the multiple interactions between environmental changes, forest management, and disturbance agents to support forest resource managers in adaptive management. Empirical data with a comprehensive coverage for modelling the susceptibility of forests and the impact of disturbance agents are rare, thus making probabilistic models, based on expert knowledge, one of the few modelling approaches that are able to handle uncertainties due to the available information. Bayesian belief networks (BBNs) are a kind of probabilistic graphical model that has become very popular to practitioners and scientists mainly due to considerations of risk and uncertainties. In this contribution, we present a development methodology to define and parameterize BBNs based on expert elicitation and approximation. We modelled storm and bark beetle disturbances agents, analyzed effects of the development methodology on model structure, and evaluated behavior with stand data from Norway spruce (Picea abies (L.) Karst.) forests in southern Austria. The high vulnerability of the case study area according to different disturbance agents makes it particularly suitable for testing the BBN model.
We introduce a Knowledge Transfer Portal (KTP) which supports knowledge transfer among researchers and forest managers. The KTP will be used for supporting transfer of knowledge generated in the FunDivEUROPE (FUNctional significance of forest bioDIVersity in EUROPE) after project life. It uses semantic web technologies to achieve a common understanding throughout a knowledge representation based on an expert elicitation process. Knowledge transfer tools (KTTs) take use of knowledge elements within the knowledge base and implement various knowledge transfer functionalities. The knowledge base shows interactions of biodiversity effects on the sustainable provision of ecosystem services. In this contribution we focus on the ongoing knowledge base engineering process and show first results that were based on a series of workshops with domain experts to generate a common understanding about terms, definitions and their relations. Relations were generated upon FunDivEUROPE project hypothesis with respect to project results and expert beliefs. We use a web-based, collaborative knowledge base engineering cycle and create a thesaurus which was initiated with terms from these expert workshops.
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