Spatial and temporal patterns of wildfire ignitions in Canada from 1980 to 2006
Nicholas J. Gralewicz A , Trisalyn A. Nelson A C and Michael A. Wulder BA Spatial Pattern Analysis and Research (SPAR) Laboratory, Department of Geography, University of Victoria, PO Box 3060, Victoria, BC, V8W 3R4, Canada.
B Canadian Forest Service, Natural Resources Canada, Pacific Forestry Centre, 506 West Burnside Road, Victoria, BC, V8Z 1M5, Canada.
C Corresponding author. Email: trisalyn@uvic.ca
International Journal of Wildland Fire 21(3) 230-242 https://doi.org/10.1071/WF10095
Submitted: 14 August 2010 Accepted: 7 June 2011 Published: 20 December 2011
Abstract
A spatially explicit baseline measure of historic, current and future wildfire ignition expectations is required to monitor and understand changes in fire occurrence, the distribution of which climate change is anticipated to modify. Using spatial–temporal patterns of fire in Canada, we present a method to identify baseline expectations and ignition trends between 1980 and 2006 across 1-km spatial units. Kernel density estimates of wildfire ignitions and temporal trajectory metrics were calculated to describe expected ignition density, variability from expected density, and increasing or decreasing density trends. Baseline ignition expectations and trends were used to create unique fire ignition regimes and assess anthropogenic influence on ignitions. Fire ignition densities decreased exponentially as distance to road or populated place increased, and largest ignition trends occurred closest to both variables. Fire ignition regime delineation was more dependent on human transportation networks than human settlement. These findings provide a unique approach to quantifying ignition expectations. This research highlights the potential of this baseline approach for monitoring efforts and fire–environment interaction research and offers a preliminary spatially explicit model of wildfire occurrence expectations in Canada.
Additional keywords: anthropogenic influence, fire regime, ignition trend, kernel density, monitoring, temporal trajectory.
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