Network node-based metrics.

Large wildfires, the dominant natural disturbance type in North American forests, can cause significant damage to human infrastructure. One well-known approach to reduce the threat of wildfires is the strategic removal of forest fuels in linear firebreaks that segment forest landscapes into distinct compartments. However, limited human and financial resources can make it difficult to plan compartmentalization effectively. In this study, we developed a simulation-optimization approach to assist with the planning of wildfire risk mitigation efforts in the Red Rock-Prairie Creek area of Alberta, Canada, a rugged, fire-prone landscape. First, we used a spatial fire growth model to calculate a matrix of fire spread likelihoods between all pairs of locations in the landscape and used this matrix to guide the allocation of firebreaks. Then, we formulated a firebreak compartmentalization problem to reduce the fire spread potential in the landscape. We depicted the landscape as a network of patches containing hazardous fuels and solved a critical edge removal linear programming problem (CERP) to partially fragment the landscape and minimize the potential of wildfires to spread to adjacent areas. We compared the CERP with other fuel treatment strategies intended to minimize fire-threat measures such as burn likelihood and fuel exposure. Compared to these strategies, the CERP solutions demonstrated better capacity to segment the landscape into evenly spaced compartments and effectively minimized fire spread along the prevailing wind paths. Our solutions provide several strategies for reducing the risk of wildfires to forest habitat and could assist strategic planning of wildfire mitigation activities in other regions.