Skip to page content
USDA Forest Service
  
Treesearch

Research & Development Treesearch

 
Treesearch Home
About Treesearch
Contact Us
Research & Development
Forest Products Lab
International Institute of Tropical Forestry
Northern
Pacific Northwest
Pacific Southwest
Rocky Mountain
Southern
Help
 

GeoTreesearch


Science.gov - We Participate


USA.gov  Government Made Easy


Global Forest Information Service

US Forest Service
P.O. Box 96090
Washington, D.C.
20090-6090

(202) 205-8333

You are here: Home / Search / Publication Information
Bookmark and Share

Publication Information

(540 KB)

Title: Probabilistic risk models for multiple disturbances: an example of forest insects and wildfires

Author: Preisler, Haiganoush K.; Ager, Alan A.; Hayes, Jane L.

Date: 2010

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)

   Note: This article is part of a larger document. View the larger document

Description: Building 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.

Keywords: Forest threats, multinomial regression, multiple stressors, nonparametric regression, spatial regression, spline functions

Publication Notes:

  • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
  • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
  • You may send email to pnw_pnwpubs@fs.fed.us to request a hard copy of this publication. (Please specify exactly which publication you are requesting and your mailing address.)

XML: View XML

Citation:


Preisler, 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.

 


 [ Get Acrobat ]  Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility

USDA logo which links to the department's national site. Forest Service logo which links to the agency's national site.