A surface fuel classification for estimating fire effects

Abstract

We present a classification of duff, litter, fine woody debris, and logs that can be used to stratify a project area into sites with fuel loading that yield significantly different emissions and maximum soil surface temperature. Total particulate matter smaller than 2.5 μm in diameter and maximum soil surface temperature were simulated using the First Order Fire Effects Model. Simulation results were clustered into 10 Effects Groups using an agglomerative routine where each Effects Group defined a unique range of soil temperature and emissions. Classification tree analysis was used to estimate the critical duff, litter, fine woody debris, and log loadings associated with the soil temperature and emissions of each Effects Group. The resulting 21 fuel classes are called Fuel Loading Models and classified the study dataset with an ~34% misclassification rate. The classification can be used to describe fuel loadings for a plot or stand, or as map units for mapping fuel loadings across large regions. The classification process can be used to develop finer-scale fuel classifications for specific regions or ecosystems.