Landscape-Level Optimization of Silvicultural Treatments for Wildfire Risk Reduction: Comparative Applications in Portugal and Greece

Forest landscape configurations in Mediterranean regions often promote fuel continuity, low structural heterogeneity, and inefficient spatial allocation of fuel treatments, increasing wildfire intensity and spread. This study improves wildfire risk management by applying spatially explicit Integer Linear Programming (ILP) models to optimize fuel-treatment allocation under operational constraints in two Mediterranean case studies: Vale do Sousa, Portugal, and Lesvos Island, Greece. In Portugal, wildfire risk was represented using a stand-level wildfire resistance indicator that accounts for the spatial influence of neighboring stands, whereas in Greece, simulation-derived fire spread probabilities from the FSim fire behavior model were used to prioritize high-risk treatment zones. Despite differences in modelling complexity and data availability, both optimization frameworks generated spatially targeted treatment strategies under contrasting wildfire risk representations. Optimized treatment allocation increased landscape-level wildfire resistance in Portugal from 0.9907 to 0.9959 and reduced expected wildfire risk in Greece from 0.1751 to 0.1701 across increasing treatment-area scenarios. Although these improvements were modest in magnitude, they were consistent across all scenarios. The novelty of this study lies in demonstrating the transferability of an ILP-based optimization framework across contrasting Mediterranean contexts, providing a practical decision-support tool for prioritizing fuel treatments and supporting adaptive, risk-informed forest management.