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Related Experiment Video

Updated: May 14, 2026

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

A new multicriteria risk mapping approach based on a multiattribute frontier concept.

Denys Yemshanov1, Frank H Koch, Yakov Ben-Haim

  • 1Natural Resources Canada, Canadian Forest Service, Great Lakes Forestry Centre, 1219 Queen Street East, Sault Ste. Marie, Ontario P6A 2E5, Canada.

Risk Analysis : an Official Publication of the Society for Risk Analysis
|January 24, 2013
PubMed
Summary

This study introduces a new method for creating invasive species risk maps by integrating multiple risk factors. This approach helps prioritize pest management by identifying key risk areas, even with limited prior knowledge.

Keywords:
Agrilus biguttatusmultiattribute efficient frontiermulticriteria aggregationnondominant setpest risk mappingrobustness to uncertainty

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Last Updated: May 14, 2026

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Published on: September 19, 2012

Area of Science:

  • Ecology
  • Invasive Species Management
  • Risk Assessment

Background:

  • Invasive species risk maps often treat risk components independently, limiting their utility for resource allocation.
  • Current multicriteria analysis techniques require prior knowledge of risk component importance, which is often unavailable for invasive pests.

Purpose of the Study:

  • To develop a novel approach for building integrated invasive species risk maps using multiattribute efficient frontiers.
  • To address the challenge of limited prior knowledge regarding the importance of individual risk components.

Main Methods:

  • Utilized the principle of multiattribute efficient frontiers to analyze risk components in multidimensional criteria space.
  • Estimated integrated risks as multiattribute frontiers across individual risk criteria dimensions.
  • Applied the method to Agrilus biguttatus (Fabricius) in North America, comparing it with linear weighted averaging under uncertainty using info-gap decision theory.

Main Results:

  • Identified significant geographic hotspots where integrating risk components alters risk rankings.
  • Both the proposed multiattribute frontier method and linear weighted averaging delineated similar high- and low-risk geographical regions.
  • The multiattribute frontier approach demonstrated robustness in the presence of uncertainties.

Conclusions:

  • The multiattribute efficient frontier method offers a robust tool for prioritizing risks of anticipated invasive pests, especially when prior knowledge is scarce.
  • This approach enhances the practical application of risk maps for pest monitoring and regulation by providing a more integrated risk assessment.
  • The study highlights the importance of considering tradeoffs between multiple risk components for accurate invasive species risk mapping.