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
], improve wildlife habitat, and conserve biodiversity [3
]. However, implementing prescribed burns is increasingly difficult due to concerns related to the wildland urban interface (WUI). In particular, 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
]. In WUI areas, fire behavior must be carefully controlled to prevent escapes. 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.
Fire severity is a measure of ecological and physical change attributable to fire [8
], and is dictated by the intersection of fuels and weather conditions. In addition to being associated with smoke production, severity is an important post-fire metric used to explain fire effects on exotic species establishment, soil responses, and forest recovery. To describe fire effects in the southeastern US, burn severity is classified in four categories: unburned, low, medium, and high severity [10
]. Low severity burns are characterized by lightly burned areas where only fine fuels are consumed with minor scorching of trees in the understory [14
]. Areas of moderate severity retain some fuels on the forest floor and have crown scorching in mid-large trees with mortality of small trees [14
]. High severity zones generally experience complete combustion of most of the litter layer, duff and small logs, mortality of small to medium trees, and consumption of large tree crowns [14
Assessing burn severity across a frequently burned landscape can provide important information about both the immediate and longer-term consequences of fire use and management, as the severity of one fire likely influences the severity of the subsequent fire. The timespan between fire events can also have a significant effect on subsequent fire behavior and fire effects [1
]. However, few studies have addressed the relationship between fire frequency, burn severity, and subsequent fire patterns in Florida’s fire-prone forests. Outcalt and Wade [2
] found a significant relationship between the amount of time since last fire and tree mortality following a wildfire in Florida pine flatwoods [2
]; as time increased to two or more years, mortality also increased [2
]. Also in pine flatwoods, Davis and Cooper [1
] showed that fuel accumulations of three years or less supported fewer fires, lower fire intensities, and lower burned acreage. These studies suggest that one fire affects the next, but do not address patterns across landscapes or among fires of differing severity, and are limited in temporal scope.
Combined with existing information about fire locations and perimeters, burn severity histories can be mapped to monitor trends in fire effects over time, in relation to frequency of fire, and as a function of time since last fire. Such data can then be used to make inferences about future fires. Remote sensing techniques are often utilized to monitor changes in fire regimes over time and to map burn severity [11
], but the technique has been under-utilized for burn severity analysis in southern forests [15
]. Normalized burn ratios (NBR) use the difference between Landsat Thematic Mapper (TM) near and mid-infrared band reflectance values to quantify the severity level of a burned area [14
]. The difference between bands 4 and 7 reflectance values can be attributed to fire induced changes in soil moisture, canopy cover, biomass, charring, and exposed soil. Difference normalized burn ratios (dNBR) capture fire effects by differencing pre- and post-fire NBRs from ETM/TM images directly before and soon after a fire. Changes in green reflectance values are captured by band 4; while increases in charred fuels, exposed soil, and decreases in vegetation density cause an increase in band 7. The dNBR technique is effective in representing burn severity because it captures relative changes in the pre- and post-fire normalized burn ratio. Employed as a radiometric index, dNBRs can be directly related to burn severity [14
] and, as long as the fire is within the resolution range of the satellite sensor (30 m), fires and their associated burn severity are often detectable [17
Previous studies in other regions have used dNBRs to calibrate severity levels to specific forest types [10
], compare severity levels between fire events [12
], interpret the effects of fuel management techniques on severity levels [20
], and to monitor changes in vegetation over time [17
] and across topography [11
]. The multi agency project, Monitoring Trends in Burn Severity (MTBS) is currently using dNBRs to map burn severity and the perimeters of wildfires greater than 405 ha in the western US and 202 ha in the eastern US [23
]. The MTBS does not, however, compare a given fire’s severity to the severity of subsequent fires, and given that most fires in southern states are less than 202 ha in size, many fires are overlooked.
Here, we analyze a decade of wildfire and prescribed burn severities in Florida flatwoods pine forests using dNBR, and examine whether landscape, vegetation, soils, and fire history, and fire frequency influence burn severity patterns. We then use these relationships to derive predictive models for high severity prescribed burns and wildfires. We hypothesize that time-since-fire will influence the probability of high burn severity in pine flatwoods only so long as the vegetation recovery does not result in altered species composition and structure. Severity should increase as time and fuel loads increase up to that threshold. We also hypothesize that mesic communities will have a higher probability of high burn severity than hydric communities during prescribed burns, while the opposite could be observed for wildfires. Prescribed burns are most frequently administered when hydric communities (e.g., cypress domes) are moist, as these communities are fire-sensitive. Because of this, prescribed burns only partially consume these understory fuels, with little consumption of the duff layer [2
] resulting in overall low severity. Consequently, hydric areas accumulate heavy fuel loads that can only support combustion during extended drought periods, and most often burn under weather conditions conducive to large, high-intensity wildfires [1
]. Research has shown that the number and size of wildfires in Florida are positively correlated with drought conditions [24
Optimally, prescribed burns in these forests are administered for minimal overstory mortality and partial consumption of understory surface fuels, with little consumption of the ground fuels including the duff layer. Predicting the probability of high severity wildfire risk would benefit land managers in their wildfire mitigation planning and tactics. There exist few locations worldwide where multiple prescribed burns and wildfires occur and overlap from one year to the next. The convergence of frequent prescribed fire and fast vegetation recovery rates sets the stage for this unique opportunity. Understanding how and why one fire affects a subsequent fire can lend insight into the complex relationships between fire behavior, fuels and vegetation recovery, and burn severity over time, and expand the utility of remotely sensed imagery for ecological research.
5. Conclusions and Recommendations
Remote sensing techniques were successfully used to model nearly a decade’s worth of fires to determine high burn severity risk and important time thresholds for pine flatwoods management. The models identified areas that require attention in order to reduce the risk of high burn severity effects, especially for prescribed burns that are commonly assumed to exhibit low burn severity [47
]. Our analysis indicates that time since last fire and fire frequency are major factors affecting the risk of high burn severity. A fire-free interval of less than five years is recommended to reduce the risk of high burn severity in pine flatwoods forests. Changes in vegetation and microclimate in response to less frequent fire may require more extreme weather conditions to burn [43
], increasing the probability of high severity fires.
Areas that burned more recently had an elevated risk of high burn severity for both prescribed burns and wildfires. This result may be attributable to a bias in the detection of high severity effects in relation to pre-fire biomass, if areas that were recently burned are burned under more extreme weather prescriptions, or if vegetation recovery corresponds to a shift in flammability and microclimate that reduces burn severity. Further research addressing the relationship between pre-fire biomass, vegetation type, and dNBRs is necessary to determine if there is a bias occurring in the low severity class due to species composition, or a bias in the high severity class that is associated with high pre-fire biomass in pine flatwoods forests. In areas with short fire return intervals, it may also be useful to look at the effects of delayed mortality to identify if this would cause further error in detecting high burn severity effects. Directly following a fire, delayed mortality may cause a bias in the low burn severity class and, burn severity in subsequent fire may exhibit a bias in the high burn severity class due to the detection of fire effects from the previous fire.
The models created here can effectively identify time thresholds that facilitate increased risks of high burn severity and areas with an increased risk based on the history of fire. Additionally, the models are able to capture the relationship between fire frequency and high severity, and time between fires and increased risks of high burn severity. As fire frequency has been identified as an important indicator of ecosystem condition in flatwoods forest [40
], these models can be used to inform prioritization and timing of fire use to maintain the pine flatwoods forests of the southern Coastal Plain.