Introduced to North America over a century ago, white pine blister rust (Cronartium ribicola J. C. Fisch. ex Rabenh.) has caused widespread mortality of five-needle pines along the eastern and western seaboards. The rust is continuing to spread into new areas, and now infects four species of pine in the Rocky Mountain region of the United States. We used maximum entropy distribution modeling to predict the potential probability distribution of the disease. Using calibration and test data, we verified that the maximum entropy model is an effective tool for predicting the current and potential spread of white pine blister rust.

Results/Conclusions

The quality and geographic range of the model results improved significantly as we were able to obtain more data. Growing degree days, elevation, and mean temperature of the driest quarter were among the top predictors of white pine blister rust’s potential distribution. The model results indicate that blister rust will continue its spread throughout the Rocky Mountains, infecting almost half of the available conifer hosts and may be affected by future climate change. The predictive distribution modeling that we created here is widely applicable to many types of invaders.