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In order to do an effective analysis of the occur rence of damage by hoofed game on forest trees, we use the method of multivariate regression analysis and especially the logit model. We can estimate how the probability of damaged tree (browsing by fallow deer and red deer) depends on different explanatory variables such as tree species (Norway spruce or Scotch pine), time period (season: spring + summer or autumn + winter) and chemical structure of bark (amount of N, fat, ash, fibre, Ca, P, Mg, K, Na, NO 3 , Co, sugar in g per kg of bark). To get good estimates of parameters of the model, it is necessary to sample a sufficient number of observations for each variable. If it is possible to quantify damage to the tree in relation to the used explanatory variables, it is convenient to use an or dinary linear model of multiple regression. First we verify the validity of regression assumptions such as homoscedasticity, independence and normality of random term and lack of multicollinearity of explanatory variables.

Risk factors influencing the probability of browsing by hoofed game on forest trees