Challenges and lessons learned from integrated landscape management (ILM) projects

Most of the analyzed studies used the indicator set as a basis that feeds into the integrated model and creates a baseline for the future scenarios without presenting the indicators set and its analyses to the stakeholders. [...] This included commenting on the relevance of the scenarios for the local and regional community, but also it could address potential impacts of the future global development at the local scenarios if the applied integrated model doesn‘t account for changes at the global level. [...] Some of the analyzed projects supplemented the concluded recommendations for the policies with capacity building for the local and regional policy-makers on how to use the models and to develop scenarios. [...] The biggest challenge for many project teams was to help the stakeholders understand the ILM approach and the trade-off between being detail-oriented and using fewer data sets to try to understand the human-environment interactions that are often hard to express in measurements and data, and require modelling in much coarser scale (Robinson and Tansey, 2000; and Schoeter et al., 2004). [...] Rich local knowledge compensates in part for the fallibility of models, and participants in most of the 10 ILM projects became comfortable with the idea of working with ILM models in the development of the future scenarios (Bizikova et al., 2009).