Structural Equation Model for Burn Severity with Topographic Variables and Susceptible Forest Cover

Due to its significant roles in post-fire responses of forest ecosystem, numerous studies have been investigating factors affecting burn severity. In the broad sense, topography, fuels, and fire weather, known as the forest fire triangle, determine the degree of burn severity. Most previous studies have adopted ordinary least squares (OLS) methods to investigate these factors, which have proven effective for capturing the direct and linear effects of those variables on burn severity. However, they oversimplify the relationships among variables and have limitations in explaining the complex effects of the variables. One way to overcome this limitation is the structural equation model (SEM) method. SEM can decompose effects of a variable into direct effects and indirect (i.e., acting through other variables) effects. The goal of this study is to capture a systematic structure, explaining how topographic characteristics including slope, elevation, topographic wetness index (TWI), solar radiation index (SRI), and susceptible forest cover type (i.e., Japanese red pine) affect burn severity. We built a hypothetical SEM and estimated the model in AMOS. The results strongly suggest that the effects of topographic characteristics are far more complex than those suggested by the OLS analyses in previous studies. Specifically, elevation and TWI had direct and indirect negative effects on burn severity, while slope and SRI had only an indirect positive effect, which was not captured in the linear regression model. Nonetheless, the percentage of red pine showed the strongest positive effect on burn severity (i.e., increasing burn severity). The results of this study and those of previous studies reinforce the importance of controlling susceptible forest cover through forest management and silviculture.