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Abstract
Fuel reduction treatments are often designed to achieve multiple resource management objectives in addition to reducing potential fire hazard. Many studies have documented reduced fire severity for a standard set of fuel treatments, but the range of variability in fuel treatment effectiveness for alternative treatment designs is poorly understood. We used nonlinear mixed-effects modeling to estimate the distance into the treated area at which fire severity decreases and randomization tests to compare forest structure. The range of variability in observed-distance high-severity fire effects persist into the treated area and, in conjunction with estimated relationships between posttreatment forest structure and severity, can inform the design of alternative fuel treatment prescriptions with various target prescriptions. Our study will inform decision makers on the size of treatments required to accomplish management objectives.