Abstract
Pine flatwoods forests in the southeastern US have experienced severe wildfires over the past few decades, often attributed to fuel load build-up. These forest communities are fire dependent and require regular burning for ecosystem maintenance and health. Although prescribed fire has been used to reduce wildfire risk and maintain ecosystem integrity, managers are still working to reintroduce fire to long unburned areas. Common perception holds that reintroduction of fire in long unburned forests will produce severe fire effects, resulting in a reluctance to prescribe fire without first using expensive mechanical fuels reduction techniques. To inform prioritization and timing of future fire use, we apply remote sensing analysis to examine the set of conditions most likely to result in high burn severity effects, in relation to vegetation, years since the previous fire, and historical fire frequency. We analyze Landsat imagery-based differenced Normalized Burn Ratios (dNBR) to model the relationships between previous and future burn severity to better predict areas of potential high severity. Our results show that remote sensing techniques are useful for modeling the relationship between elevated risk of high burn severity and the amount of time between fires, the type of fire (wildfire or prescribed burn), and the historical frequency of fires in pine flatwoods forests.
Highlights
In forests characterized by a historically frequent fire return interval, prescribed fire is often used as a tool to mimic the effects of natural fire
Based on the differenced Normalized Burn Ratios (dNBR) analysis of fire events over time, severity level of the first fire, PDSI for the year of the first and second fire, fire type for the second fire, community type, and the time interval between the first fire and the second fire were all significant indicators of high burn severity occurring subsequently
Our analysis indicates that time since last fire and fire frequency are major factors affecting the risk of high burn severity
Summary
In forests characterized by a historically frequent fire return interval, prescribed fire is often used as a tool to mimic the effects of natural fire. The absence of fire in such forests would cause significant changes in vegetative species structure and composition, and could increase the threat of large-scale wildfires. In pine flatwoods forests of the southern US, prescribed burns reduce fuel accumulations to minimize damage from potential wildfires [1,2], improve wildlife habitat, and conserve biodiversity [3,4,5,6]. Implementing prescribed burns is increasingly difficult due to concerns related to the wildland urban interface (WUI). Fire management decision-making in Florida has been shown to be dictated by urban encroachment, forest fragmentation, and the challenges associated with smoke management [7]. Managers strive to implement burns where fuel and weather conditions will minimize the potential for the high-severity fires that create challenges for smoke management and post-fire ecosystem recovery
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