Landscape resilience knowledge alliance for agriculture and forestry in the Mediterranean basin

The objective of the ResAlliance is to facilitate information and knowledge flow and increase the awareness, understanding and capacity of farmers and foresters on landscape resilience in Mediterranean countries. More specifically, ResAlliance will gather and assess knowledge and practice needs, gaps, barriers, solutions and good practices to achieve resilient landscapes, with special emphasis on measures against hazards caused by climate change. It will also prepare and facilitate stakeholder engagement through interactive and innovative participation methods. It will finally transfer the knowledge and activate regional landscape resilience governance, with special emphasis in five Mediterranean regions.

ResAlliance will create and animate a Mediterranean thematic network on landscape resilience (“LandNet”) for forestry and agriculture. The LandNet will continuously identify, engage and grow new cooperation and networks to access, improve and increase the knowledge of solutions and good practices. The LandNet will prepare the context-specific knowledge and engage and train farmers, foresters and other key stakeholders for knowledge transfer of managerial, technological, financial or governance solutions.

The work programme will allow capturing and interpreting most urgent needs while identifying and coupling unknown best practices in research and practice with these needs; compiling a comprehensive description of the state of current farming and forestry practices on landscape resilience to summarise and explain the added-value, the relevance and the cost/benefit aspects of the practices collected, avoiding duplication; delivering an extensive range of useful, applicable, appealing and easy-to-access material in many formats, including EIP-AGRI, EU FarmBook and existing dissemination channels most consulted by farmers and foresters in the countries; and building synergies with OGs and innovation groups from EIP-AGRI, and implement multi-actor approach.