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

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.