Abstract
Degradation of forest roads in Canada has strong negative effects on access to forestlands, together with economic (e.g., increased maintenance costs), environmental (e.g., erosion of materials and subsequent habitat contamination), and social (e.g., use risks) impacts. Maintaining sustainable and safe access to forestland requires a better understanding and knowledge of forest road degradation over time and space. Our study aimed to identify relevant spatiotemporal variables regarding the state of eastern Canadian forest road networks by (1) building predictive models of gravel forest road degradation and assessing effects of the slope, time, loss of the road surface, and road width (field approach), and (2) evaluating the potential of topography, roughness and vegetation indices obtained from Airborne Laser Scanning (ALS) data and Sentinel-2 optical images to estimate degradation rates (remote sensing approach). The field approach (n = 207 sample plots) confirmed that only four variables were efficient to estimate degradation rates (pseudo-R2 = 0.43 with ±8% error). Simulations that were conducted showed that after about five years without maintenance, the rate of degradation on a road, regardless of its width, increased exponentially, exacerbated by a high slope gradient and loss of road surface. The narrowest roads tended to degrade more rapidly over time. The remote sensing approach performed quite well (pseudo-R2 = 0.34 with ±9% error) in terms of predicting road degradation, giving us the valuable tools to spatialise the state of gravel forest road degradation in eastern Canadian forest. This study provided new knowledge and tools that are critical for maintaining and sustaining access to Canada’s boreal forest territory in both the short- and the long-term.
Highlights
Introduction iationsForest roads are anthropogenic disturbances that can considerably alter the connectivity and natural dynamics of the Canadian boreal forest
The objective of this study is to provide a better understanding and new spatiotemporal knowledge regarding the state of Canadian forest road networks
Percentage depression from Topographic Position Index (TPI), the standard deviation of TWI, the standard deviation of cross-sectional CSI, the mean value of TRI, the mean value of NDVI, and the percentage presence of vegetation that is derived from the Canopy Height Model (CHM) are the indices that were selected to construct the regression model for the remote sensing approach
Summary
Forest roads are anthropogenic disturbances that can considerably alter the connectivity and natural dynamics of the Canadian boreal forest. The continued densification, usage and attendant damage sustained by these networks raise several questions about their economic, environmental, and social impacts. Significant impacts on ecosystem processes and structure arising from the effects of their geometry, traffic volume, proximity and connectivity on biodiversity, biophysical processes and ecosystem functioning are well documented and studied around the world [1,2,3,4,5]. Roads disturb forest ecosystems during their construction, and in subsequent stages of degradation, rehabilitation, or decommissioning. A lack of road maintenance leads to road degradation, with several consequences, including contamination of watercourses and neighbouring habitats, increased collision, and predation risks for certain animals (e.g., caribou) and accident.
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