Abstract
ContextWildfires play a crucial role in maintaining ecological and societal functions of North American boreal forests. Because of their contagious way of spreading, using statistical methods dealing with spatial autocorrelation has become a major challenge in fire studies analyzing how environmental factors affect their spatial variability.ObjectivesWe aimed to demonstrate the performance of a spatially explicit method accounting for spatial autocorrelation in burn rates modelling, and to use this method to determine the relative contribution of climate, physical environment and vegetation to the spatial variability of burn rates between 1972 and 2015.MethodsUsing a 482,000 km2 territory located in the coniferous boreal forest of eastern Canada, we built and compared burn rates models with and without accounting for spatial autocorrelation. The relative contribution of climate, physical environment and vegetation to the burn rates variability was identified with variance partitioning.ResultsAccounting for spatial autocorrelation improved the models’ performance by a factor of 1.5. Our method allowed the unadulterated extraction of the contribution of climate, physical environment and vegetation to the spatial variability of burn rates. This contribution was similar for the three groups of factors. The spatial autocorrelation extent was linked to the fire size distribution.ConclusionsAccounting for spatial autocorrelation can highly improve models and avoids biased results and misinterpretation. Considering climate, physical environment and vegetation altogether is essential, especially when attempting to predict future area burned. In addition to the direct effect of climate, changes in vegetation could have important impacts on future burn rates.
Highlights
Wildfires have been shaping boreal forests for millennia by creating mosaics of landscapes of different age structure, size, and composition (Stocks et al 2003; Gauthier et al 2015a)
Our method allowed the unadulterated extraction of the contribution of climate, physical environment and vegetation to the spatial variability of burn rates
The goal of our study was (i) to implement a spatially explicit method involving residuals autocovariate (RAC) models (Crase et al 2012) in burn rates analyses, and to test its performance against more standard models not accounting for spatial autocorrelation; and (ii) to use this method to determine the relative contribution of climate, vegetation and physical environment to the spatial variability of burn rates in the coniferous boreal forest of eastern Canada
Summary
Wildfires have been shaping boreal forests for millennia by creating mosaics of landscapes of different age structure, size, and composition (Stocks et al 2003; Gauthier et al 2015a). In the north American coniferous boreal forest, the spatial variability of fire regimes has been demonstrated at scales of millennia (Hu et al 2006; Senici et al 2015), centuries (Girardin and Mudelsee 2008) and decades (Kasischke and Turetsky 2006). This spatiotemporal variability is decisive for many ecological attributes such as biodiversity (Gauthier et al 2015a), and societal attributes such as forest management (Johnson et al 1998). Spatial autocorrelation is often disregarded by fire studies, but this omission can lead to type I error and to incorrect estimation of parameters and important misinterpretation (Reed et al 1998; Dormann et al 2007; Mishra et al 2016)
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