Facing structural change, European rural areas still fulfil multiple social, economic and ecological functions. Because of scale interplays and sustainability trade-offs, their future dynamics are yet particularly difficult to ascertain. PRIMA aims to develop methods for scaling down the assessment of policy impacts on multifunctional land-use and economic activities. The project focuses on agriculture, forestry, tourism, and ecosystem services, with special attention to the structural effects of the policies. An analysis of the strategic and planning documents in the case study areas highlights that many measures are targeted to several pillars of sustainable development, even though multifunctionality (MF) concept is often unaddressed. Because of the bottom-up governance of the European cohesion policy, a large variety of priorities and measures has been observed, so we oriented the first stakeholders interviews towards their major objectives and the specific measures they activate from the cohesion policy to reach their own objectives. Two groups of stakeholders were identified: those who can assist in scenario and model development and in model validation (drawn from the institutions which implement policy), and the actors who may be affected by the policy and whose behaviour will be captured in the AB model. Two rounds of interviews have been performed, the first one to gain contextual information about the wider case study information. From cluster analysis and this information, sets of municipalities were selected, then a second round of interviews was conducted to identify relevant policy issues and appropriate policy measures. These interviews provide the main events which have occurred during the last 20 years, policy outcomes, the EU funding streams, proposals for new measures. A conceptual model has been developed from extensive literature review and information collected during the surveys. This model focuses on the population dynamics in rural municipalities and on the decision making behaviours observed in such areas, including indicators requirements to match with IA methods. A general method for generating households from different available data at municipality level has been designed: at this level, only average data are available and the method enables to generate relevant individual data to be included in the models. The model has been adapted to the case studies: at this stage, downscaling occurs to input data for the models. We developed a working regional economic model that interacts between global changes (GTAP-IMAGE interactions) and multi-agent based tool at local level. It covers activities agriculture, forestry, services and nature. A start has been made with a program for downscaling. We are working on a procedure to generate the basic regional data for the input. We have to start data generation and theoretical and empirical work to improve on the allocation procedures of national developments to regions. Considering backbone scenarios, first modelling at European level started, with the identification of key economic and demographic factors that drive land use patterns at regional and local levels. External drivers and policies have been distinguished. GTAP and IMAGES have been linked to provide a working modelling framework. Last, we progressed towards enhancing the scope of IA methods, with a review of literature and extensive work between all workpackages.