An analysis of controls on fire activity in boreal Canada: comparing models built with different temporal resolutions. Issue 6 (1st September 2014)

• Record Type: Journal Article
• Authors: Parisien, Marc-André; Parks, Sean A.; Krawchuk, Meg A.; Little, John M.; Flannigan, Mike D.; Gowman, Lynn M.; Moritz, Max A.
• Is Part Of: Ecological applications. Volume 24:Issue 6(2014)
• Page Start: 1341
• Page End: 1356
• Publication Date: 2014-09-01
• Subjects: area burned -- Canadian boreal forest -- climate -- ignitions -- regression modeling -- temporal scale -- vegetation -- wildfire -- zero-inflated models; Ecology -- Periodicals; Environmental protection -- Periodicals; Biology, Economic -- Periodicals; 577.05
• DOI: 10.1890/13-1477.1
• Languages: English
• ISSNs: 1051-0761

Abstract

Abstract : Fire regimes of the Canadian boreal forest are driven by certain environmental factors that are highly variable from year to year (e.g., temperature, precipitation) and others that are relatively stable (e.g., land cover, topography). Studies examining the relative influence of these environmental drivers on fire activity suggest that models making explicit use of interannual variability appear to better capture years of climate extremes, whereas those using a temporal average of all available years highlight the importance of land‐cover variables. It has been suggested that fire models built at different temporal resolutions may provide a complementary understanding of controls on fire regimes, but this claim has not been tested explicitly with parallel data and modeling approaches. We addressed this issue by building two models of area burned for the period 1980–2010 using 14 explanatory variables to describe ignitions, vegetation, climate, and topography. We built one model at an annual resolution, with climate and some land‐cover variables being updated annually, and the other model using 31‐year fire "climatology" based on averaged variables. Despite substantial differences in the variables' contributions to the two models, their predictions were broadly similar, which suggests coherence between the spatial patterns of annually varying climate extremes and long‐term climate normals. Where the models' predictions diverged, discrepancies between the annual and averaged models could be attributed to specific explanatory variables. For instance, annually updating land cover allowed us to identify a possible negative feedback between flammable biomass and fire activity. These results show that building models at more than one temporal resolution affords a deeper understanding of controls on fire activity in boreal Canada than can be achieved by examining a single model. However, in terms of spatial predictions, the additional effort required to build annual models of fire activity may not always be warranted in this study area. From a management and policy standpoint, this key finding should boost confidence in models that incorporate climatic normals, thereby providing a stronger foundation on which to make decisions on adaptation and mitigation strategies for future fire activity.