Fuels treatments and fire suppression operations during a fire are the two management influences on wildfire severity, yet their influence is rarely quantified in landscape-scale analyses. We leveraged a combination of datasets including custom canopy fuel layers and post-fire field data to analyse drivers of fire severity in a large wildfire in the southern Cascade Range, California, USA. We used a statistical model of tree basal area loss from the fire, factoring in weather, fuels and terrain to quantify the extent to which prescribed burning mitigated wildfire severity by simulating potential wildfire severity without prescribed fire and comparing that with modelled severity from areas burned with prescribed fire. Similarly, using a map of operations intensity, we calculated predicted fire severity under a scenario with no operations and used these predictions to quantify the influence of operations. We found that prescribed fires and operations reduced tree basal area loss from the wildfire by an average of 32% and 22% respectively, and that severity was reduced by 72% in areas with both prescribed fire and operations. Our approach could be applied to other wildfires and regions to better understand the effects of fuel treatments and fire suppression operations on wildfire severity.
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