Climatic Change

, Volume 130, Issue 4, pp 587–601 | Cite as

Mitigating risks of future wildfires by management of the forest composition: an analysis of the offsetting potential through boreal Canada

  • Martin P. GirardinEmail author
  • Aurélie Terrier


Wildfire activity is projected to increase through upcoming decades in boreal Canada due to climatic changes. Amongst the proposed strategies to offset the climate-driven fire risk is the introduction of broadleaf species into dense-coniferous landscapes so as to decrease the intensity and rate of spread of future wildfires. Here we examine this offsetting potential through boreal Canada by searching for optimal conifer to broadleaf conversion rates that would stabilize the burn rate metric, and an upper bound for the maximum potential effect. We developed an empirical model relating regional burn rates to mean annual fire weather conditions and tree genus proportions, and applied it to regional climate and forest composition change scenarios covering the interval from 1971 to 2100. Results suggested that many areas in the southern and northern boreal regions will record either a constant or a decreasing burn rate and, therefore, will not require a change of forest composition. Besides, a conversion rate of 0.1 to 0.2 % year−1 starting in year 2020 was sufficient to maintain burn rates constant across much of the southern boreal forest. In northern forests, however, higher conversion rates were required to meet the fire objectives (0.3 to 0.4 % year−1). This mitigation option will be difficult to implement over northern forests given the size of areas involved. Nonetheless the estimated conversion rate for much of the southern boreal forest is attainable, considering that harvesting and industrialization during recent decades have already contributed to similar changes of the proportion of broadleaf species in boreal landscapes.


Boreal Forest Multivariate Adaptative Regression Spline Forest Composition Fire Season Fire Weather 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This project was financially supported by the Canadian Forest Service (Natural Resources Canada) and the Natural Sciences and Engineering Research Council of Canada (NSERC; Discovery Grant allocated to M.P. Girardin). We thank Rémi Saint-Amant (Natural Resources Canada) for providing the climate data generated by BioSIM. The CanRCM4 data were supplied by the Canadian Centre for Climate Modelling and Analysis. We extend our thanks to Pierre Grondin, Luc Guindon, Dan McKenney and four anonymous reviewers for helpful comments and to Pamela Cheers for technical editing.

Supplementary material

10584_2015_1373_MOESM1_ESM.docx (2 mb)
ESM 1 (DOCX 2044 kb)


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Copyright information

© Her Majesty the Queen in Right of Canada 2015

Authors and Affiliations

  1. 1.Centre d’étude de la forêtUniversité du Québec à MontréalMontréalCanada
  2. 2.Natural Resources Canada, Canadian Forest ServiceLaurentian Forestry CentreStn. Sainte-Foy, QuebecCanada

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