An ecosystem-scale model for the spread of a host-specific forest pathogen in the Greater Yellowstone Ecosystem

Department of Environmental Science, Policy, and Management, University of California, Berkeley, California 94720, USA.
Ecological Applications (Impact Factor: 4.09). 06/2011; 21(4):1138-53. DOI: 10.2307/23022985
Source: PubMed


The introduction of nonnative pathogens is altering the scale, magnitude, and persistence of forest disturbance regimes in the western United States. In the high-altitude whitebark pine (Pinus albicaulis) forests of the Greater Yellowstone Ecosystem (GYE), white pine blister rust (Cronartium ribicola) is an introduced fungal pathogen that is now the principal cause of tree mortality in many locations. Although blister rust eradication has failed in the past, there is nonetheless substantial interest in monitoring the disease and its rate of progression in order to predict the future impact of forest disturbances within this critical ecosystem. This study integrates data from five different field-monitoring campaigns from 1968 to 2008 to create a blister rust infection model for sites located throughout the GYE. Our model parameterizes the past rates of blister rust spread in order to project its future impact on high-altitude whitebark pine forests. Because the process of blister rust infection and mortality of individuals occurs over the time frame of many years, the model in this paper operates on a yearly time step and defines a series of whitebark pine infection classes: susceptible, slightly infected, moderately infected, and dead. In our analysis, we evaluate four different infection models that compare local vs. global density dependence on the dynamics of blister rust infection. We compare models in which blister rust infection is: (1) independent of the density of infected trees, (2) locally density-dependent, (3) locally density-dependent with a static global infection rate among all sites, and (4) both locally and globally density-dependent. Model evaluation through the predictive loss criterion for Bayesian analysis supports the model that is both locally and globally density-dependent. Using this best-fit model, we predicted the average residence times for the four stages of blister rust infection in our model, and we found that, on average, whitebark pine trees within the GYE remain susceptible for 6.7 years, take 10.9 years to transition from slightly infected to moderately infected, and take 9.4 years to transition from moderately infected to dead. Using our best-fit model, we project the future levels of blister rust infestation in the GYE at critical sites over the next 20 years.

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Available from: Diana L Six, Oct 04, 2015
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    • "Most FIPs are associated with reductions in tree growth during and after an infection, which can result in mortality ranging in spatial scale from the patchy loss of individual trees to continental-scale die-offs (Hicke et al. 2012). A critical difference between disturbances caused by FIPs and those from clear-cuts and fires is that in many cases mortality due to FIPs is not instantaneous; it is often the cumulative result of ongoing stress that can sometimes persist for decades (Hatala et al. 2011). This variability in the scale and rate of mortality can have large impacts on land surface biophysics, such as changes in the surface energy budget, hydrology, canopy turbulence and snowpack. "
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