The vulnerability matrices developed for the 23 MRLs are the most comprehensive analysis of the vulnerability of land use systems in Europe's mountains to date. This work captures the perceptions of a large number of farmers, managers, extension agents and researchers on the importance of the drivers of change that determine the vulnerability of the systems, indicating that the drivers of change that most affect and will affect in the near future, as well as the resource base for the selected value chains, are specific to each MRL. However, it has been observed that the spatial information provided, as well as the indicators produced, are sometimes difficult to understand and interpret with the actors involved, which highlighted the importance of an adequate knowledge transfer adapted to the variability of the stakeholders. However, the methodology used has proven to provide more comprehensive, substantial, and contextualised knowledge, as well as fostering interaction and increased knowledge exchange between the actors involved. The information processed and produced in this work provides a solid basis for assessing the challenges faced by the selected value chains in the near future in their respective MRLs, as well as assessing how changes in the value chain can affect, reinforce or minimise the effects of the identified drivers of change. As a follow-up to these results, and with the aim of improving the transfer of the knowledge generated, work is currently underway to develop and provide interactive visual tools - especially maps and indicators - that offer real information on assets, sustainability, and resilience, and that can contribute to the awareness of AKIS (Agricultural Knowledge and Information Systems), the VC actors, the civil society and the political actors in mountain areas. The main document includes the vulnerability matrix of the 23 MRLs and those vulnerability maps that could be calculated. In addition, a more detailed vulnerability analysis report has been included as Appendix for each MRL including information on the context, drivers and its components and the participatory analysis of the driver ranking, trends, sensitivity, and adaptive mechanisms.