The effects of climate change in the Arctic are particularly pronounced since temperatures have risen nearly three to four times as fast as in the rest of the planet. Shifts in climatic patterns enable the expansion of temperature-limited vegetation at a global scale to higher latitudes and elevations. The purpose of this study is to predict the distribution of pine trees (Pinus sylvestris) across Fennoscandia by drawing from three distinctive datasets. I ask (i) How will the distribution of pine trees will respond to climate change in the next 50 years? (ii) Which method used to collect data is better at predicting the distribution of pine? Three datasets on pine presence together with environmental data were used to model pine distribution with Generalized Linear Models. The first dataset belongs to the Swedish National Forest Inventory and the second is from a Swedish online portal where citizens report their observations of species. The third was compiled by setting up a network of vegetation plots along an elevation gradient in Sweden and Norway. Current and future environmental data was sourced from the Coupled Model Intercomparison Project. The probability of pine presence in general increased with temperature and decreased with precipitation. Therefore, the model forecasts that pine will expand in distribution to areas of higher elevation. The citizen science dataset was superior in predicting pine distribution due to the large number and the wide spatial distribution of observations. The conservation of the tundra and the unique ecosystem process taking place in this area will be threatened by the encroachment of the evergreen treeline which is driven by climate, and citizen science holds unique importance for wide spatial and temporal ecological research.