Abstract
Wind and bark beetle disturbances are the dominant natural disturbance agents across large parts of the European Alps. Spatial information products indicating the predisposition of forest stands to be subject of bark beetle infestations are still rare and the links between bark beetle infestation probabilities and environmental drivers not fully understood. In earlier studies, the share of salvage loggings related to bark beetles has been linked to abiotic disturbances, drought or forest management interventions such as salvage logging, thinning or promotion of tree species diversity. Nonetheless, there are very few studies addressing predictors predisposing forest stands to bark beetle infestations in the alpine region. This study suggests an approach to assess the predisposition status of forest stands to bark beetle infestations in complex terrain at the regional scale at a 30 m cell size by relying on satellite derived data. We identify drivers of bark beetle host selection related to topography using a high-resolution Digital Terrain Model-derived downslope index and to canopy water stress or canopy closure before attack by relying on the Normalized Difference Water Index calculated from Sentinel-2 data. Canopy openings were characterized by GEDI derived products and bark beetle infestation probability was found to be higher in open stands in the beginning of the epidemic phase. The testing of the inter-year variability of these bark beetle drivers of infestation revealed that the predictors generally remained stabled from one year to the next. The models showed consistent behavior in spatial patterns of predisposition of bark beetle infestation suggesting an overall suitability of using models with information extracted from one part of the region to predict the probability of disturbance over the entire region. The proposed methodology for the prediction of bark beetle attack predisposition at a broad scale can guide forest management in complex terrain and focus precision forestry intervention to specific areas.