Modeling Watershed-Scale Historic Change in the Alpine Treeline Ecotone Using Random Forest
David R. McCaffrey, Chris Hopkinson
Abstract
Historic changes in Alpine Treeline Ecotone were modeled using 21 topographic, climatic, geologic, and disturbance variables in a random forest model. Airborne LiDAR and oblique historic repeat photography were used to identify changes in canopy cover in the West Castle Watershed (WCW), Alberta, Canada (49.3° N, 114.4° W). A Random Forest model was trained on ∼30% of the watershed which was observable in oblique imagery, then used for a spatial extension to predict change classes in the unobserved regions of the watershed. Overall accuracy of the model was 77.3% and kappa showed moderate agreement at 0.56. The relative strength of each prediction variable was compared using permutation importance. Fire exposure, annual temperature, and annual solar radiation were the highest-ranking variables; canopy cover decreases on warm, fire-exposed aspects at high elevations, and increases on cool, non-fire-exposed aspects.