Controls on the spatial pattern of wildfire ignitions in Southern California
Nicolas Faivre A C , Yufang Jin B , Michael L. Goulden A and James T. Randerson AA Department of Earth System Science, University of California, 2101 E Croul Hall, Irvine, CA 92697-3100, USA.
B Department of Land, Air and Water Resources, University of California, Davis, CA 95616-8627, USA.
C Corresponding author. Email: nfaivre@uci.edu
International Journal of Wildland Fire 23(6) 799-811 https://doi.org/10.1071/WF13136
Submitted: 21 August 2013 Accepted: 7 May 2014 Published: 28 July 2014
Abstract
Wildfire ignition requires a combination of an open spark, and suitable weather and fuel conditions. Models of fire occurrence and burned area provide a good understanding of the physical and climatic factors that constrain and promote fire spread and recurrence, but information on how humans influence ignition patterns is still lacking at a scale compatible with integrated fire management. We investigated the relative importance of the physical, climatic and human factors regulating ignition probability across Southern California’s National Forests. A 30-year exploratory analysis of one-way relationships indicated that distance to a road, distance to housing and topographic slope were the major determinants of ignition frequency. We used logistic and Poisson regression analyses to model ignition occurrence and frequency as a function of the dominant covariates. The resulting models explained ~70% of the spatial variability in ignition likelihood and 45% of the variability in ignition frequency. In turn, predicted ignition probability contributed to some of the spatial variability in burned area, particularly for summer fires. These models may enable estimates of fire ignition risk for the broader domain of Southern California and how this risk may change with future population and housing development. Our spatially explicit predictions may also be useful for strategic fire management in the region.
Additional keywords: biophysical drivers, fire frequency, fire ignition, human influence, Mediterranean ecosystems, spatial regression model, wildland fire risk.
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