Modelling probability of snow and wind damage using tree, stand, and site characteristics from Pinus sylvestris sample plots

The risk of damage on trees from snow and wind was modelled using tree, stand, and site characteristics from 286 permanent Scots pine (Pinus sylvestris L.) sample plots within the Swedish National Forest inventory. Three logistic risk assessment models were developed for the county of Vasterbotten in the boreal zone of Sweden. The best model, using tree, stand, and site variables, correctly classified 81.1% of the undamaged an 81.8% of the damaged plots. The model over-predicted the proportion of damaged plots (21.3%), compared to the observed proportion of 3.8%,. When evaluating the models using temporary plots from Vasterbotten, the model using tree, stand, and site variables showed the best overall predictability. When applied in southern Sweden, the models developed for Vasterbotten showed poor predictability. The study shows possibilities for correctly classifying the overall susceptibility to damage from snow and mind if the models are used within their limits.