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 Research Station
Help
 

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

View PDF (307 KB)

Title: Identifying and assessing critical uncertainty thresholds in a forest pest risk model

Author: Koch, Frank H.; Yemshanov, Denys;

Date: 2015

Source: In:Venette, RC (ed.) Pest Risk Modelling and Mapping for Invasive Alien Species. CABI, Wallingford, UK, 189-205.

Publication Series: Book Chapter

Description: Pest risk maps can provide helpful decision support for invasive alien species management, but often fail to address adequately the uncertainty associated with their predicted risk values. Th is chapter explores how increased uncertainty in a risk model’s numeric assumptions (i.e. its principal parameters) might aff ect the resulting risk map. We used a spatial stochastic model, integrating components for entry, establishment and spread, to estimate the risks of invasion and their variation across a two-dimensional gridded landscape for Sirex noctilio, a non-native woodwasp detected in eastern North America in 2004. Historically, S. noctilio has been a major pest of pine (Pinus spp.) plantations in the southern hemisphere. We present a sensitivity analysis of the mapped risk estimates to variation in six key model parameters: (i) the annual probabilities of new S. noctilio entries at US and Canadian ports; (ii) the S. noctilio population-carrying capacity at a given location; (iii) the maximum annual spread distance; (iv) the probability of local dispersal (i.e. at a distance of 1 km); (v) the susceptibility of the host resource; and (vi) the growth rate of the host trees. We used Monte Carlo simulation to sample values from symmetric uniform distributions defi ned by a series of nested variability bounds around each parameter’s initial values (i.e. ±5%, …, ±50%). Th e results show that maximum annual spread distance, which governs longdistance dispersal, was the most sensitive of the tested parameters. At ±15% uncertainty in this parameter, mapped risk values shifted notably. No other parameter had a major eff ect, even at wider bounds of variation. Th e methods presented in this chapter are generic and can be used to assess the impact of uncertainties on the stability of pest risk maps or to identify any geographic areas for which management decisions can be made confi dently, regardless of uncertainty.

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 pubrequest@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:


Koch, Frank H; Yemshanov, Denys 2015. Identifying and assessing critical uncertainty thresholds in a forest pest risk model. In:Venette, RC (ed.) Pest Risk Modelling and Mapping for Invasive Alien Species. CABI, Wallingford, UK, 189-205. 17 p.

 


 [ 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.