Abstract
Wildfires are the main cause of forest disturbance in the boreal forest of Canada. Climate change studies forecast important changes in fire cycles, such as increases in fire intensity, severity, and occurrence. The geographical information system (GIS) based cellular automata model, BorealFireSim, serves as a tool to identify future fire patterns in the boreal forest of Quebec, Canada. The model was calibrated using 1950–2010 climate data for the present baseline and forecasts of burning probability up to 2100 were calculated using two RCP scenarios of climate change. Results show that, with every scenario, the mean area burned will likely increase on a provincial scale, while some areas might expect decreases with a low emission scenario. Comparison with other models shows that areas forecasted to have an increase in fire likelihood, overlap with predicted areas of higher vegetation productivity. The results presented in this research aid identifying key areas for fire-dependent species in the near future.
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