Abstract. Empirical ecological response surfaces were derived for eight dominant tree species in the boreal forest region of Canada. Stepwise logistic regression was used to model species dominance as a response to five climatic predictor variables. The predictor variables (annual snowfall, degree-days, absolute minimum temperature, annual soil moisture deficit, and actual evapotranspiration summed over the summer months) influence the response of plants more directly than the annual or monthly measures of temperature and precipitation commonly used in response surface modeling. The response surfaces provided estimates of the probability of species dominance across the spatial extent of North America with a high degree of success. Much of the variation in the probability of dominance is apparently related to the species' individualistic response to climatic constraints within different airmass regions.
A forest type classification for the Canadian boreal forest region was derived by a cluster analysis based on the probability estimates. Five major forest types were distinguished by the application of a stopping rule. The predicted forest types showed a high degree of geographic correspondence with the distribution of forest types in the actual vegetation mosaic. The distribution of the predicted types also bears a direct relationship to seasonal airmass dynamics in the boreal forest region.