Both topography and climate affected forest and woodland burn severity in two regions of the western US, 1984 to 2006

Abstract

Fire is a keystone process in many ecosystems of western North America. Severe fires kill and consume large amounts of above‐ and belowground biomass and affect soils, resulting in long‐lasting consequences for vegetation, aquatic ecosystem productivity and diversity, and other ecosystem properties. We analyzed the occurrence of, and trends in, satellite‐derived burn severity across six ecoregions in the Southwest and Northwest regions of the United States from 1984 to 2006 using data from the Monitoring Trends in Burn Severity project. Using 1,024 fires from the Northwest (4,311,871 ha) and 497 fires from the Southwest (1,434,670 ha), we examined the relative influence of fine‐scale topography and coarse‐scale weather and climate on burn severity (the degree of change from before the fire to one year after) using the Random Forest machine learning algorithm. Together, topography, climate, and weather explained severe fire occurrence with classification accuracies ranging from 68% to 84%. Topographic variables were relatively more important predictors of severe fire occurrence than either climate or weather variables. Predictability of severe fire was consistently lower during years with widespread fires, suggesting that local control exerted by topography may be overwhelmed by regional climatic controls when fires burn in dry conditions. Annually, area burned severely was strongly correlated with area burned in all ecoregions (Pearson's correlation 0.86–0.97; p < 0.001), while the proportion of area burned severely was significantly correlated with area burned only in two ecoregions (p ≤ 0.037). During our short time series, only ecoregions in the Southwest showed evidence of a significant increase (p ≤ 0.036) in annual area burned and area burned severely, and annual proportion burned severely increased in just one of the three Southwest ecoregions. We suggest that predictive mapping of the potential for severe fire is possible, and will be improved with climate data at the scale of the topographic and Landsat‐derived burn severity data. Although severity is a value‐laden term implying negative ecosystem effects, we stress that severity can be objectively measured and recognize that high severity fire is an important ecological process within the historical range of variability in some ecosystems.

Exploring the Relationship between Burn Severity Field Data and Very High Resolution GeoEye Images: The Case of the 2011 Evros Wildfire in Greece

“…Prior to the fire, topography influences the microclimate (temperature, precipitation, and direct solar radiation), plant productivity, and biomass accumulation that directly affects the amount of biomass available to burn during the outbreak of fire [18]. After the fire event, the topographic variations in slope, aspect, and elevation influences the microclimate at a local scale which, in turn, affects the post-fire regeneration rates [47].…”

“…To quantify the potential of VHR GeoEye satellite data to express the variations in the field-measured burn severity we used redundancy analysis (RDA) [47]. The RDA method was first developed by Rao [48,49].…”

A spatio-temporal Poisson hurdle point process to model wildfires

“…In fact, [15] point out that those topographic variables are relatively more important predictors of severe fire occurrence, than either climate or weather variables. The proximity to anthropic areas can be considered a factor explaining not only the incidence of fires in the intentional fires and arson category, but also why natural cause fires do not occur.…”

Integrating Satellite Imagery with Simulation Modeling to Improve Burn Severity Mapping

“…Some studies that have assessed the relationship between CBI and satellite-based burn severity indices have used CBI as the response variable (van Wagtendonk et al 2004;Cocke et al 2005;Holden et al 2009;Soverel et al 2010), while others have used CBI as the predictor variable (in that case, with the satellite index as the response) (Miller and Thode 2007;Miller et al 2009a, b;Dillon et al 2011a;Cansler and McKenzie 2012). Although Cansler and McKenzie (2012) make a strong case for why CBI should be used as the predictor, we used it as the response to facilitate the comparison of technologies, because it is the one common variable across the three approaches.…”

“…Studies conducted in a variety of landscapes have evaluated imagebased approaches to burn severity mapping in the US and internationally (see French et al 2008 for more detail). Other studies have employed the approach to investigate research questions requiring a spatial assessment of burn severity (Miller et al 2009b;Epting and Verbyla 2004;Collins et al 2007;Haire and McGarigal 2009;Dillon et al 2011a). Additionally, the Monitoring Trends in Burn Severity project is a multi-agency effort initiated to produce a national scale fire atlas based on satellite derived burn severity maps (Eidenshink et al 2007).…”