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Moose (Alces alces) damage in forest plantations have been at a high level in Finland in recent decades. Nowadays, moose is the most severe pest in Scots pine plantations also in Finnish Lapland. So far, despite the high level of damage and different bio-geographical conditions in Northern Finland, most of the moose-damage research has been carried out in Southern Finland. A number of research have also been performed to analyse factors affecting browsing but predictive models are rare. Data from 123 randomly selected and artificially regenerated pine plantations in Northern Finland were used in modelling the risk of moose browsing. The stands had been regenerated during 1984–1995. A total of 508 sample plots (range 2–8 plots per stand) were measured. Hierarchical logistic regression models with a random factor were constructed to predict the probability of leader-shoot browsing of pine on a plot. The number of planted pines and deciduous trees overtopping the pines were the most important predictors increasing the browsing probability. The results support earlier findings that deciduous trees overtopping or reaching the height of the pines should be cleaned from the immediate vicinity of the pines. Seedlings with a height ranging from 75 to 299 centimetres were more susceptible to browsing. Heavy soil scarification, such as ploughing or mounding, increased the browsing probability compared with lighter scarification methods. Soil type did not affect the browsing probability, but paludification decreased it. The within-stand variation in deciduous trees density and height should be taken into account in future moose browsing risk assessments. In Lapland, high moose damage risk areas are characterized by a low elevation and higher temperature sum.

Modelling the factors predisposing Scots pine to moose damage in artificially regenerated sapling stands in Finnish Lapland