A Case Study Comparison of LANDFIRE Fuel Loading and Emissions Generation on a Mixed Conifer Forest in Northern Idaho, USA

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AbstractThe use of fire as a land management tool is well recognized for its ecological benefits in many natural systems. To continue to use fire while complying with air quality regulations, land managers are often tasked with modeling emissions from fire during the planning process. To populate such models, the Landscape Fire and Resource Management Planning Tools (LANDFIRE) program has developed raster layers representing vegetation and fuels throughout the United States; however, there are limited studies available comparing LANDFIRE spatially distributed fuel loading data with measured fuel loading data. This study helps address that knowledge gap by evaluating two LANDFIRE fuel loading raster options—Fuels Characteristic Classification System (LANDFIRE-FCCS) and Fuel Loading Model (LANDFIRE-FLM) layers—with measured fuel loadings for a 20 000 ha mixed conifer study area in northern Idaho, USA. Fuel loadings are compared, and then placed into two emissions models—the First Order Fire Effects Model (FOFEM) and Consume—for a subsequent comparison of consumption and emissions results. The LANDFIRE-FCCS layer showed 200%* higher duff loadings relative to measured loadings. These led to 23% higher total mean total fuel consumption and emissions when modeled in FOFEM. The LANDFIRE-FLM layer showed lower loadings for total surface fuels relative to measured data, especially in the case of coarse woody debris, which in turn led to 51% lower mean total consumption and emissions when modeled in FOFEM. When the comparison was repeated using Consume model outputs, LANDFIRE-FLM consumption was 59% lower relative to that on the measured plots, with 58% lower modeled emissions. Although both LANDFIRE and measured fuel loadings fell within the ranges observed by other researchers in US mixed conifer ecosystems, variation within the fuel loadings for all sources was high, and the differences in fuel loadings led to significant differences in consumption and emissions depending upon the data and model chosen. The results of this case study are consistent with those of other researchers, and indicate that supplementing LANDFIRE-represented data with locally measured data, especially for duff and coarse woody debris, will produce more accurate emissions results relative to using unaltered LANDFIRE-FCCS or LANDFIRE-FLM fuel loadings. Accurate emissions models will aid in representing emissions and complying with air quality regulations, thus ensuring the continued use of fire in wildland management.