Developing a Framework for Assessing Wildfire Losses and Evaluating Economic-Environmental Trade-Offs in European Forests

Wildfires are escalating in frequency and intensity across the globe due to climate change and expanding human development, yet most existing studies still treat fire weather, exposure or economic impacts in isolation. Responding to that gap, this thesis develops an integrated approach to wildfire risk at the wildfire–forestry–climate interface, combining risk assessment, economic loss estimation, and forest-management trade-off analysis under future climate scenarios. The research is structured around three inter-linked studies that together form a complete decision workflow: (1) a novel framework that couples semi-probabilistic fire risk with economic–environmental decision support; (2) a supranational, machine-learning loss model that quantifies present and future damages in Europe using Average Annual Loss (AAL, € yr⁻¹) to buildings, infrastructure and forest assets; and (3) a trade-off analysis that feeds probabilistic loss estimates into multi-objective forestry planning to examine how wildfire risk reshapes the balance between timber production and carbon storage in European forests. All three studies draw on open-source and harmonized datasets, including EFFIS fire records, Copernicus land-cover maps, MERIT topography, climate simulations data, exposure layers from OSM and GEM, and employ climate-driven susceptibility modelling, geospatial hazard mapping, exposure-and-vulnerability assessment, and Pareto analysis. Key findings indicate that climate change could raise wildfire AAL by 40–130 % in Southern and Eastern Europe by mid-century under high-emission scenarios, underscoring the urgency of improved risk assessment and planning. Maximizing timber yields without accounting for fire risk can reduce forest carbon stocks by 40–50 %, whereas prioritizing carbon forfeits substantial timber revenue; yet the analysis also reveals win-win synergies, showing that moderate fuel reduction or extended rotations can simultaneously curb losses, retain carbon, and sustain timber yields. By evaluating timber–carbon trade-offs under realistic fire patterns, the thesis advances wildfire-risk science through a scalable, supranational modelling framework and demonstrates how integrated economic valuation and ecological objectives can guide risk-informed forest management. The results inform national risk assessments, forest-adaptation strategies, and incentive mechanisms such as carbon credits or insurance schemes, offering a timely toolkit for building fire-resilient landscapes that balance economic and environmental goals in a changing climate.