Predictive Model of Burn Severity (dNBR) in the Mojave Desert
Dates
Publication Date
2022-10-28
Start Date
1972
End Date
2010
Citation
Klinger, R.C., Underwood, E.C., McKinley, R., and Brooks, M.L., 2022, Fire regimes in the Mojave Desert (1972-2010): U.S. Geological Survey data release, https://doi.org/10.5066/P99YGHSJ.
Summary
This raster dataset represents spatially explicit predictions of burn severity (dNBRPredict.tif) in the Mojave Desert based on models developed from data on the difference normalized burn ratio (dNBR) within perimeters of fires greater than 405 hectares that burned between 1984 to 2010. Raster resolution equals 30 meters, projection equals UTM Zone 11N.
Summary
This raster dataset represents spatially explicit predictions of burn severity (dNBRPredict.tif) in the Mojave Desert based on models developed from data on the difference normalized burn ratio (dNBR) within perimeters of fires greater than 405 hectares that burned between 1984 to 2010. Raster resolution equals 30 meters, projection equals UTM Zone 11N.
Click on title to download individual files attached to this item.
dNBRMojaveMetadata.xml Original FGDC Metadata
View
27.84 KB
application/fgdc+xml
Extension:
dNBRPredictRF.zip
dNBRPredictRF.tif-ColorRamp.SLD
2.08 KB
dNBRPredictRF.tif
570.45 MB
Purpose
The extent and frequency of fire has increased in many arid systems over the last century, with a large proportion of area in some regions undergoing transitions to novel conditions. Portions of the Mojave Desert in southwestern North America have undergone such transitions, most often from woody to herbaceous-dominated systems. These transitions have often been attributed to the proliferation of invasive annual grasses that promote more frequent fire, but recent evidence indicates that transitions can also occur independent of fire frequency if burn severity is high. In addition, high probability of ignition (i.e. potentially high fire frequency) and high burn severity may not always be geographically related. Therefore, our goals were to: (1) map potential burn severity, fire frequency, and probability of ignition across the Mojave; and, (2) evaluate spatial association among predicted burn severity, fire frequency and probability of ignition. These data can be used in many ways, such as predicting vegetation states in sites that have the potential to burn at different frequencies and severities, examining fine scale spatial patterns in burn severity, and monitoring shifts in fire frequency across the Mojave ecoregion. But their most practical and useful application will be as planning tools for agencies responsible for fire management and postfire vegetation management in the Mojave.