Linking complex forest fuel structure and fire behaviour at fine scales
E. Louise Loudermilk A I , Joseph J. O’Brien B , Robert J. Mitchell C , Wendell P. Cropper
+ Author Affiliations
- Author Affiliations
A School of Natural Resources and Environment, University of Florida, PO Box 110410, Gainesville, FL 32611, USA.
B USDA Forest Service, Center for Forest Disturbance Science, Forestry Sciences Laboratory, 320 Green Street, Athens, GA 30602, USA.
C Joseph W. Jones Ecological Research Center at Ichauway, 3988 Jones Center Drive, Newton, GA 39870, USA.
D School of Forest Resources and Conservation, University of Florida, PO Box 110410, Gainesville, FL 32611, USA.
E Eglin Air Force Base, Natural Resource Branch, 107 Highway 85 North, Niceville, FL 32578, USA.
F Soil and Water Science Department, University of Florida, PO Box 110290, Gainesville, FL 32611, USA.
G Department of Statistics, University of South Carolina, 1523 Greene Street, Columbia, SC 29208, USA.
H Geosensing Engineering and Mapping Center, University of Florida, PO Box 116580, Gainesville, FL 32611, USA.
I Corresponding author. Present address: Department of Environmental Science and Management, Portland State University, PO Box 751, Portland, OR 97207, USA. Email: louise.loudermilk@gmail.com
International Journal of Wildland Fire 21(7) 882-893 https://doi.org/10.1071/WF10116
Submitted: 18 October 2010 Accepted: 21 February 2012 Published: 26 July 2012
Abstract
Improved fire management of savannas and open woodlands requires better understanding of the fundamental connection between fuel heterogeneity, variation in fire behaviour and the influence of fire variation on vegetation feedbacks. In this study, we introduce a novel approach to predicting fire behaviour at the submetre scale, including measurements of forest understorey fuels using ground-based LIDAR (light detection and ranging) coupled with infrared thermography for recording precise fire temperatures. We used ensemble classification and regression trees to examine the relationships between fuel characteristics and fire temperature dynamics. Fire behaviour was best predicted by characterising fuelbed heterogeneity and continuity across multiple plots of similar fire intensity, where impacts from plot-to-plot variation in fuel, fire and weather did not overwhelm the effects of fuels. The individual plot-level results revealed the significance of specific fuel types (e.g. bare soil, pine leaf litter) as well as the spatial configuration of fire. This was the first known study to link the importance of fuelbed continuity and the heterogeneity associated with fuel types to fire behaviour at metre to submetre scales and provides the next step in understanding the complex responses of vegetation to fire behaviour.
Additional keywords: fuel heterogeneity, IR imagery, LIDAR, longleaf pine, regression tree, savanna.
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