Using stand-level optimization to reduce crown fire hazard

This study evaluated the ability to generate prescriptions for a wide variety of stands when the goal is to reduce crown fire potential. Forest managers charged with reducing crown fire potential while providing for commodity and ecological production have been hampered by the complexity of possible management options. A program called Stand-Level Optimization with Multiple Objectives (SLOMO) was developed that uses a dynamic programming based algorithm to find near-optimal solutions for a number of problem formulations. Sixty-four stand types from eastern Oregon were evaluated with SLOMO with the goal of reducing crown fire potential. Two attributes of stand canopies were manipulated, canopy base height (CBH) and canopy bulk density (CBD). Additionally, a baseline case of “grow only” was evaluated for each stand to help understand the potential effects of active management. Results illustrate the potential for optimization methods to provide useful management strategies to reduce crown fires. Relative to the grow only goal, treatments are derived that achieve and maintain target levels for CBH and CBD over a 100-year projection. Simulations show a substantive decrease in crown fires, especially active crown fires, with treatments derived from optimization procedures.