International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire

Predicting spatial patterns of fire on a southern California landscape

Alexandra D. Syphard A E , Volker C. Radeloff A , Nicholas S. Keuler B , Robert S. Taylor C , Todd J. Hawbaker A , Susan I. Stewart D and Murray K. Clayton B
+ Author Affiliations
- Author Affiliations

A Department of Forest and Wildlife Ecology, University of Wisconsin, Madison, WI 53706, USA.

B Department of Statistics, University of Wisconsin, Madison, WI 53706, USA.

C National Park Service, Santa Monica Mountains National Recreation Area, Thousand Oaks, CA 91360, USA.

D USDA Forest Service, Northern Research Station, Evanston, IL 60201, USA.

E Corresponding author. Email:

International Journal of Wildland Fire 17(5) 602-613
Submitted: 29 July 2007  Accepted: 19 November 2007   Published: 3 October 2008


Humans influence the frequency and spatial pattern of fire and contribute to altered fire regimes, but fuel loading is often the only factor considered when planning management activities to reduce fire hazard. Understanding both the human and biophysical landscape characteristics that explain how fire patterns vary should help to identify where fire is most likely to threaten values at risk. We used human and biophysical explanatory variables to model and map the spatial patterns of both fire ignitions and fire frequency in the Santa Monica Mountains, a human-dominated southern California landscape. Most fires in the study area are caused by humans, and our results showed that fire ignition patterns were strongly influenced by human variables. In particular, ignitions were most likely to occur close to roads, trails, and housing development but were also related to vegetation type. In contrast, biophysical variables related to climate and terrain (January temperature, transformed aspect, elevation, and slope) explained most of the variation in fire frequency. Although most ignitions occur close to human infrastructure, fires were more likely to spread when located farther from urban development. How far fires spread was ultimately related to biophysical variables, and the largest fires in southern California occurred as a function of wind speed, topography, and vegetation type. Overlaying predictive maps of fire ignitions and fire frequency may be useful for identifying high-risk areas that can be targeted for fire management actions.

Additional keywords: fire frequency, fire ignitions, generalised linear model, predictive mapping, wildland–urban interface.


We are grateful to the USDA Forest Service Northern Research Station and the Pacific Northwest Research Station for their support. We also thank the editor, the associate editor, and our anonymous reviewers for their insightful comments and recommendations that greatly improved the manuscript. Thanks also to Janet Franklin for her statistical advice.


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