D1.13 brief 2: Recommendations and novel adaptive management scenarios to create resilient landscapes to Extreme Wildfire Events

Extreme Wildfire Events (EWEs) challenge conventional fire management approaches and call for integrated strategies that reduce vulnerability and foster resilient landscapes. This deliverable provides a set of recommendations to increase resilience, with a focus on stand-level interventions that can be applied across the wildfire cycle: before, during, and after fire. Three management scenarios are considered in detail: low-productivity forests, often not managed and prone to fire; high-productivity forests, where intensive management interacts with fire risk; and the wildland–urban interface, where protecting people and infrastructure is the priority. 
The recommendations emphasize the importance of spatially planning stand-level treatments to reduce vulnerability to EWEs and adapting management to changing fire regimes. They highlight the need to tailor treatments to vegetation structure and composition, with defined thresholds for fuel structure, composition, and load to prevent EWEs.  The specific management actions provided are structured around the wildfire cycle. In the prevention phase, the focus is on reducing fuel loads and designing vegetation structures less vulnerable to EWEs, using mechanical treatments (thinning, understory clearing, and slash management), fire use (prescribed burns and traditional fire use), and grazing. In the suppression phase, the focus is on the opportunities that unplanned ignitions burning under controlled conditions offer to achieve management goals and harness fire’s ecological benefits. In the recovery phase, recommendations include supporting natural regeneration when possible, applying active restoration when necessary, and promoting vegetation and landscape structures adapted to future fire regimes.
Overall, this deliverable provides practical recommendations for creating resilient landscapes across Europe. While the strategies can be applied widely, they should be adapted to local ecological and socio-economic conditions to improve efficiency.