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Probabilistic risk models for multiple disturbances: an example of forest insects and wildfiresAuthor(s): Haiganoush K. Preisler; Alan A. Ager; Jane L. Hayes
Source: In: Pye, John M.; Rauscher, H. Michael; Sands, Yasmeen; Lee, Danny C.; Beatty, Jerome S., tech. eds. Advances in threat assessment and their application to forest and rangeland management. Gen. Tech. Rep. PNW-GTR-802. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest and Southern Research Stations: 371-379
Publication Series: General Technical Report (GTR)
Station: Pacific Northwest Research Station
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DescriptionBuilding probabilistic risk models for highly random forest disturbances like wildfire and forest insect outbreaks is a challenging. Modeling the interactions among natural disturbances is even more difficult. In the case of wildfire and forest insects, we looked at the probability of a large fire given an insect outbreak and also the incidence of insect outbreaks following wildfire. We developed and used a probabilistic model framework for estimating (1) the probability that a wildfire, at a given location and time, reaches a given size class under the conditions at the site—including history of insect outbreaks; and (2) the probability of an insect infestation at a given location and year under the conditions at the site—including history of fire occurrence and size. The study used historical data (1980 through 2004) on fire occurrence and forest insect outbreaks collected in Oregon and Washington. Spatial data on insect activity was obtained from aerial sketch maps created by the Forest Service Forest Health Protection program. Federal wildfire data obtained from the Desert Research Institute included information on the date, location, and size of the fire. Average monthly temperature and Palmer Drought Severity Indices were obtained from the National Climatic Data Center’s climate division data set Web page. The methods employed provide an objective tool for modeling complex hybrid processes and estimating associated probability maps.
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CitationPreisler, Haiganoush K.; Ager, Alan A.; Hayes, Jane L. 2010. Probabilistic risk models for multiple disturbances: an example of forest insects and wildfires. In: Pye, John M.; Rauscher, H. Michael; Sands, Yasmeen; Lee, Danny C.; Beatty, Jerome S., tech. eds. Advances in threat assessment and their application to forest and rangeland management. Gen. Tech. Rep. PNW-GTR-802. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest and Southern Research Stations: 371-379.
KeywordsForest threats, multinomial regression, multiple stressors, nonparametric regression, spatial regression, spline functions
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