Risk of white pine blister rust to limber pine in Colorado and Wyoming,USA |
| |
| Authors: | H. S. J. Kearns W. R. Jacobi R. M. Reich R. L. Flynn K. S. Burns B. W. Geils |
| |
| Affiliation: | 1. Department of Bioagricultural Sciences and Pest Management, Colorado State University, , Fort Collins, CO, 80523‐1177 USA;2. USDA Forest Service, Forest Health Protection, , Sandy, OR, USA;3. Department of Forest, Rangeland and Watershed Stewardship, Colorado State University, , Fort Collins, CO, USA;4. Department of Soil and Crop Sciences, Colorado State University, , Fort Collins, CO, USA;5. USDA Forest Service, Forest Health Protection, , Golden, CO, USA;6. USDA Forest Service, Rocky Mountain Research Station, , Flagstaff, AZ, USA |
| |
| Abstract: | Cronartium ribicola, the introduced pathogen that causes white pine blister rust (WPBR), continues to spread to additional limber pine populations in the Southern Rocky Mountains of Colorado and Wyoming. Because WPBR can severely impact ecosystems, forecasts of its potential distribution and incidence would be useful to land managers. Site and climate data from long infested study areas in Wyoming were fit with two regression models [logistic and classification and regression trees (CART)] to determine the environmental conditions associated with the distribution of WPBR. These models were then used to map limber pine stands at risk of infestation by C. ribicola throughout Wyoming (where it has long occurred) and Colorado (where it is just becoming established). Although variables representing vegetation and landform could identify infested plots, 1‐km‐scale climate variables for monthly temperature and moisture were better predictors of current WPBR distribution and were available for mapping expected future distribution across the region. Of 280 485 ha where limber pine was projected to occur in Colorado, 41% was forecast by the logistic model to be at risk of infestation, and 53%, by the CART model. Of an estimated 782 229 ha in Wyoming with limber pine, the logistic model projected 61% to be at risk; CART projected 79%. Additional regression models were fit with site and climate data to predict WPBR incidence (per cent of trees infected) and intensification (incidence/age of the oldest canker). Nearly one half of the plot‐to‐plot variation in incidence was explained using environmental variables readily available to land managers. Although mean plot incidence increased over time, mean intensification decreased 50% per decade. This work provides managers with several tools to reduce uncertainty over the expected distribution and incidence of WPBR, but surveillance and monitoring remain prudent activities for supplementing forecasts of WPBR epidemics. |
| |
| Keywords: | |
|
|
