Predicting Potential Fire Severity Using Vegetation, Topography and Surface Moisture Availability in a Eurasian Boreal Forest Landscape

Abstract

Severity of wildfires is a critical component of the fire regime and plays an important role in determining forest ecosystem response to fire disturbance. Predicting spatial distribution of potential fire severity can be valuable in guiding fire and fuel management planning. Spatial controls on fire severity patterns have attracted growing interest, but few studies have attempted to predict potential fire severity in fire-prone Eurasian boreal forests. Furthermore, the influences of fire weather variation on spatial heterogeneity of fire severity remain poorly understood at fine scales. We assessed the relative importance and influence of pre-fire vegetation, topography, and surface moisture availability (SMA) on fire severity in 21 lightning-ignited fires occurring in two different fire years (3 fires in 2000, 18 fires in 2010) of the Great Xing'an Mountains with an ensemble modeling approach of boosted regression tree (BRT). SMA was derived from 8-day moderate resolution imaging spectroradiometer (MODIS) evapotranspiration products. We predicted the potential distribution of fire severity in two fire years and evaluated the prediction accuracies. BRT modeling revealed that vegetation, topography, and SMA explained more than 70% of variations in fire severity (mean 83.0% for 2000, mean 73.8% for 2010). Our analysis showed that evergreen coniferous forests were more likely to experience higher severity fires than the dominant deciduous larch forests of this region, and deciduous broadleaf forests and shrublands usually burned at a significantly lower fire severity. High-severity fires tended to occur in gentle and well-drained slopes at high altitudes, especially those with north-facing aspects. SMA exhibited notable and consistent negative association with severity. Predicted fire severity from our model exhibited strong agreement with the observed fire severity (mean r 2 = 0.795 for 2000, 0.618 for 2010). Our results verified that spatial variation of fire severity within a burned patch is predictable at the landscape scale, and the prediction of potential fire severity could be improved by incorporating remotely sensed biophysical variables related to weather conditions.

Mean Composite Fire Severity Metrics Computed with Google Earth Engine Offer Improved Accuracy and Expanded Mapping Potential

“…The degree of fire-induced ecological change, or fire severity, has been the focus of countless studies across the globe [1][2][3][4][5]. These studies often rely on gridded metrics that use pre-and post-fire imagery to estimate the amount of fire-induced change; the most common metrics are the delta normalized burn ratio (dNBR) [6], the relativized delta normalized burn ratio (RdNBR) [7], and the relativized burn ratio (RBR) [8].…”

“…The fire severity datasets produced by the MTBS program have clearly advanced wildland fire research in the US. Although some studies involving the trends, drivers, and distribution of satellite-inferred fire severity are evident outside of the US [4,5,15,29,30], the number and breadth of such studies are relatively scarce and restricted compared to those conducted in the US. We suggest that, if spatially and temporally comprehensive satellite-inferred severity metrics were more widely available in other countries or regions, opportunities for fire severity monitoring and research would increase substantially.…”

Competition and Burn Severity Determine Post-Fire Sapling Recovery in a Nationally Protected Boreal Forest of China: An Analysis from Very High-Resolution Satellite Imagery

“…) we studied was ignited by lightning on 17 June 2000 and lasted for seven days [45]. It burned an area approximately 7735 ha, most of which was moderate-high severity with high tree mortality rates [26,39].…”

“…A strict ban on logging of natural forests has been enforced across the Great Xing'an Mountains since April 2014, thus historical fires in the nature reserve will provide valuable insight for understanding how resilient this forest is in responding to wildfire and for refining post-fire management practices. The particular fire (Lat/Lon: 122°50′E, 51°53′N) we studied was ignited by lightning on 17 June 2000 and lasted for seven days [45]. It burned an area approximately 7735 ha, most of which was moderate-high severity with high tree mortality rates [26,39].…”

Wildfire Alters Spatial Patterns of Available Soil Nitrogen and Understory Environments in a Valley Boreal Larch Forest

“…However, recent studies have found that these interactions and the potential heterogeneity across landscapes could be modified by disturbances [9][10][11]. Wildfire is one of the most important natural ecological disturbance agents in forest ecosystems, is characterized by variations in fire severity and frequency [12,13], and therefore produces spatial and temporal variations in ecological systems. Fire frequency and severity have been predicted to increase under a warming climate [14]; thus, understanding changes in patterns of post-fire soil resources and plants across space is necessary to better understand the ecological effects of fires in fire-prone ecosystems.…”