Experimental fuel treatment impacts on forest structure, potential fire behavior, and predicted tree mortality in a California mixed conifer forest

Abstract

Fuel treatments have been suggested as a means to limit the size and intensity of wildfires but few experiments are available to analyze the effectiveness of different treatments. This paper presents information from a replicated, stand level experiment from mixed conifer forests in the north-central Sierra Nevada that investigated how control, mechanical (crown thinning, thinning from below followed, rotary mastication), prescribed fire, and mechanical followed by prescribed fire treatments affected fuels, forest structure, potential fire behavior, and modeled tree mortality at 80th, 90th, and 97.5th percentile fire weather conditions. Fuels Management Analyst was used to model fire behavior and tree mortality. Thinning and mastication each reduced crown bulk density by approximately 19% in mechanical only and mechanical plus fire treatments. Prescribed burning significantly reduced the total combined fuel load of litter, duff, 1, 10, 100, and 1000 h fuels by as much as 90%. This reduction significantly altered modeled fire behavior in both mechanical plus fire and fire only treatments in terms of fireline intensity and predicted mortality. The prescribed fire only and mechanical followed by prescribed fire treatments resulted in the lowest average fireline intensities, rate of spread, and predicted mortality. The control treatment resulted in the most severe modeled fire behavior and tree mortality. Mechanical only treatments were an improvement over controls but still resulted in tree mortality at severe fire weather when compared with the treatments that included prescribed fire. Restoration of mixed conifer ecosystems must include an examination of how proposed treatments affect fire behavior and effects. Variation in existing stand structures will require solutions that are site specific but the principals outlined in this work should help managers make better decisions.