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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 Västerbotten in the boreal zone of Sweden. The best model, using tree, stand, and site variables, correctly classified 81.1% of the undamaged and 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 Västerbotten, the model using tree, stand, and site variables showed the best overall predictability. When applied in southern Sweden, the models developed for Västerbotten showed poor predictability. The study shows possibilities for correctly classifying the overall susceptibility to damage from snow and wind if the models are used within their limits.
Fridman et al. (Thu,) studied this question.