Authors: P. Belavenutti, A. A. Ager, M. A. Day and W. Chung

Year: 2022

Journal: Fire

Abstract: We developed and applied a spatial optimization algorithm to prioritize forest and fuel management treatments within a proposed linear fuel break network on a 0.5 million hawestern US national forest. The large fuel break network combined with the logistics of conducting forest and fuel management requires that treatments bepartitioned into a sequence of discrete projects individually implemented over the next 10 – 20 years. The original plan for the network did not consider how linear segments would be packaged into projects and how projects would be prioritized for treatments through time as the network is constructed. Using our optimization algorithm, we analyzed 13 implementation scenarios where sized constrained projects were prioritized based on predicted wildfire encounter rate, treatment cost, and harvest revenue. We found that among the scenarios, predicted net revenue ranged from $-3,495 to $6,642 ha^-1 and that prioritizing wildfire encounter rate reduced net revenue and harvested timber. We demonstrate how the tradeoffs could be minimized using a multi-objective optimization approach. We found the most efficient implementation scale was a sequence of relatively small projects that treated 300 ha ±10% versus larger projects with the additional treated area. Our study provides a decision support model for multi-objective optimization to implement large fuel break networks being proposed or implemented in many fire prone regions on the globe.