A dynamic population model of Ixodes scapularis, the vector of a number of tick-borne zoonoses in North America, was developed to simulate effects of temperature on tick survival and seasonality. Tick development rates were modelled as temperature-dependent time delays, calculated using mean monthly normal temperature data from specific meteorological stations. Temperature also influenced host-finding success in the model. Using data from stations near endemic populations of I. scapularis, the model reached repeatable, stable, cyclical equilibria with seasonal activity of different instars being very close to that observed in the field. In simulations run using data from meteorological stations in central and eastern Canada, the maximum equilibrium numbers of ticks declined the further north was the station location, and simulated populations died out at more northerly stations. Tick die-out at northern latitudes was due to a steady increase in mortality of all life stages with decreasing temperature rather than a specific threshold event in phenology of one life stage. By linear regression we investigated mean annual numbers of degree-days >0 degrees C (DD>0 degrees C) as a readily mapped index of the temperature conditions at the meteorological stations providing temperature data for the model. Maximum numbers of ticks at equilibrium were strongly associated with the mean DD>0 degrees C (r2>0.96, P<0.001), when the Province of origin of the meteorological station was accounted for (Quebec>Ontario, beta=103, P<0.001). The intercepts of the regression models provided theoretical limits for the establishment of I. scapularis in Canada. Maps of these limits suggested that the range of southeast Canada where temperature conditions are currently suitable for the tick, is much wider than the existing distribution of I. scapularis, implying that there is potential for spread. Future applications of the model in investigating climate change effects on I. scapularis are discussed.