Proposals to build new and expand existing linear fuel breaks networks (FBN) have emerged as part of several national initiatives in the US and elsewhere. Fuel break networks are typically built on a core of existing roads and right-of-ways to minimize cost and maximize ingress, egress and safety. Natural barriers are also used including low-flammability vegetation, and non-vegetated features such as lakes and rivers. A key question facing managers is how to organize treatments into manageable project areas that meet operational and administrative constraints and prioritize investments over time to maximize fire management outcomes.

We expanded the application of both the ForSysX and ForSysR applications to prioritize linear fuel breaks (versus scattered treatment blocks in a landscape) with modifications to both the input data structure and source code and conducted two studies, both on the Umatilla National Forest. The proposed network extended over 3,538 km, both on the forest and on adjacent lands, and will require extensive forest and fuel management treatments to implement with current budgets and workforce. The long length of the fuel break network combined with the logistics of conducting forest and fuel management requires that treatments be partitioned into a sequence of discrete projects individually implemented over the next 10 – 20 years.

In the first study we analyzed 13 implementation scenarios where optimized projects were built with ForSysR and 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 per hectare, and that prioritizing wildfire hazard significantly reduced net revenue and harvested timber. We demonstrate how the tradeoffs could be minimized using a multi-objective optimization approach. The multi-objective scenario resulted in the highest treatment of hazard, highest timber volume and revenue except when compared to the scenarios that prioritized each of those objectives individually. We found the most efficient implementation scale was a sequence of relatively small projects that treated 300 ha ±10%, versus larger projects with additional treated area. The study demonstrated a decision support model for multi-objective optimization to implement large fuel break networks and provided initial high-priority fuel breaks for the forest.

We then segmented the network into 2,766 treatment units (1000 m long x 300 m wide segments) and modified the ForSysX spatial optimization model to maximize linear distance of treated projects to examine alternative project implementation geometries, linear versus radial. We hypothesized that linear projects (long stretches of fuel break) were more efficient at intercepting a large number of individual fire events over larger spatial domains, whereas radial projects (semi-circular web of treatments that radiate from the project centroid) conferred a higher level of network redundancy in terms of the length of the fuel break exposed to fires. We simulated implementation of the alternative project geometries and then examined fuel break-wildfire spatial interactions using a library of simulated fires. The results supported the hypothesis, with linear projects exhibiting substantially greater efficiency in terms of intercepting fires (providing potential control locations) over larger areas, whereas radial projects had a higher interception length given a fire encountered a project providing multiple opportunities to control the same fire. Adding economic objectives made it more difficult to find long stretches of linear fuel break, but substantially increased net revenue from harvested trees.

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