Canadian Forest Service Publications

Modeling Wildfire Spread in Mountain Pine Beetle-Affected Forest Stands, British Columbia, Canada

Year: 2014

Issued by: Pacific Forestry Centre

Catalog ID: 40826

Language: English

Availability: PDF (request by e-mail)

Available from the Journal's Web site.
DOI: 10.4996/fireecology.1002010

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The mountain pine beetle (Dendroc- tonus ponderosae Hopkins; MPB) has killed lodgepole pines (Pinus contorta Dougl. ex Loud.) across 20 million hectares of central British Columbia, Canada, since the late 1990s, challenging land managers as well as fire management personnel. Although recent studies have used models to simulate how MPB might affect fire spread, very little fire behaviour has been documented in MPB-affected stands. We documented rate of spread (ROS) in experimental fires and wildfires in recent MPB-killed stands in British Columbia using interpretations of oblique photographs, airborne measurements of wildfire spread, and experimental burns. Fire spread observations were used to develop ROS models following the empirical approach of the Canadian Forest Fire Danger Rating System (CFFDRS). Sixteen fire runs were examined that occurred in mature MPB-affected pine stands from 1 to 5 years since peak attack. Observations of ROS were associated with corresponding weather measurements from nearby weather stations and non-linear regression curves were fit to paired ROS and Initial Spread Index (ISI) data according to CFFDRS convention. Although the dataset is less robust than a strictly experimental approach, fires had faster spread and more crown fire than predicted, with a linear average of 2.7 times higher ROS in best fit models than expected for unaffected pine. The most likely crown fire initiation threshold (P = 0.5) was ISI 5.5. Fire intensity is likely higher in early post-MPB stands due to increased ROS, lower crowning thresholds, and greater consumption of fine dead branches. Further studies on fire behaviour in MPB-affected stands are needed, but the present findings can help reduce uncertainty in fire and land management decisions in the interim.