A retrospective assessment of fuel break effectiveness for containing rangeland wildfires in the sagebrush biome

Variability in weather and site properties affect fuel and fire behavior following fuel treatments in semiarid sagebrush-steppe

Fuel-treatments targeting shrubs and fire-prone exotic annual grasses (EAGs) are increasingly used to mitigate increased wildfire risks in arid and semiarid environments, and understanding their response to natural factors is needed for effective landscape management. Using field-data collected over four years from fuel-break treatments in semiarid sagebrush-steppe, we asked 1) how the outcomes of EAG and sagebrush fuel treatments varied with site biophysical properties, climate, and weather, and 2) how predictions of fire behavior using the Fuel Characteristic Classification System fire model related to land-management objectives of maintaining fire behavior expected of low-load, dry-climate grasslands. Generalized linear mixed effect modeling with build-up model selection was used to determine best-fit models, and marginal effects plots to assess responses for each fuel type. EAG cover decreased as antecedent-fall precipitation increased and increased as antecedent-spring temperatures and surface soil clay contents increased. Herbicides targeting EAGs were less effective where pre-treatment EAG cover was >40 % and antecedent spring temperatures were >9.5 °C. Sagebrush cover was inversely related to soil clay content, especially where clay contents were >17 %. Predicted fire behavior exceeded management objectives under 1) average fire weather conditions when EAG or sagebrush cover was >50 % or >26 %, respectively, or 2) extreme fire weather conditions when EAG or sagebrush cover was >10 % or >8 %, respectively. Consideration of the strong effects of natural variability in site properties and antecedent weather can help in justifying, planning and implementing fuel-treatments.

Optimizing the implementation of a forest fuel break network

Methods and models to design, prioritize and evaluate fuel break networks have potential application in many fire-prone ecosystems where major increases in fuel management investments are planned in response to growing incidence of wildfires. A key question facing managers is how to scale treatments into manageable project areas that meet operational and administrative constraints, and then prioritize their implementation over time to maximize fire management outcomes. We developed and tested a spatial modeling system to optimize the implementation of a proposed 3,538 km fuel break network and explore tradeoffs between two implementation strategies on a 0.5 million ha national forest in the western US. We segmented the network into 2,766 treatment units and used a spatial optimization model to compare linear versus radial project implementation geometries. We hypothesized that linear projects were more efficient at intercepting individual fire events over larger spatial domains, whereas radial projects 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 developed in prior work. The results supported the hypothesis, with linear projects exhibiting substantially greater efficiency in terms of intercepting fires over larger areas, whereas radial projects had a higher interception length given a fire encountered a project. Adding economic objectives made it more difficult to obtain alternative project geometries, but substantially increased net revenue from harvested trees. We discuss how the model and results can be used to further understand decision tradeoffs and optimize the implementation of planned fuel break networks in conjunction with landscape conservation, protection, and restoration management in fire prone regions.