Abstract

Pest risk maps are important decision support tools when devising strategies to minimize introductions of invasive organisms and mitigate their impacts. When possible management responses to an invader include costly or socially sensitive activities, decision-makers tend to follow a more certain (i.e., risk-averse) course of action. We presented a new mapping technique that assesses pest invasion risk from the perspective of a risk-averse decision maker.We demonstrated the method by evaluating the likelihood that an invasive forest pest will be transported to one of the U.S. states or Canadian provinces in infested firewood by visitors to U.S. federal campgrounds. We tested the impact of the risk aversion assumption using distributions of plausible pest arrival scenarios generated with a geographically explicit model developed from data documenting camper travel across the study area. Next, we prioritized regions of high and low pest arrival risk via application of two stochastic ordering techniques that employed, respectively, first- and second-degree stochastic dominance rules, the latter of which incorporated the notion of risk aversion. We then identified regions in the study area where the pest risk value changed considerably after incorporating risk aversion.While both methods identified similar areas of highest and lowest risk, they differed in how they demarcated moderate-risk areas. In general, the second-order stochastic dominance method assigned lower risk rankings to moderate-risk areas. Overall, this new method offers a better strategy to deal with the uncertainty typically associated with risk assessments and provides a tractable way to incorporate decision-making preferences into final risk estimates, and thus helps to better align these estimates with particular decision-making scenarios about a pest organism of concern. Incorporation of risk aversion also helps prioritize the set of locations to target for inspections and outreach activities, which can be costly. Our results are especially important and useful given the huge number of camping trips that occur each year in the United States and Canada.

Highlights

  • Management of invasive species populations often requires making decisions about allocating scarce resources for surveillance or eradication of newly detected incursions

  • Our goal with this paper is to present the method of prioritizing uncertain outcomes of ecological invasions that would agree with a risk-averse decision-making strategy, and to explore how the notion of riskaversion changes the delineation of pest risk in a geographical domain

  • Adding the risk aversion assumption adds the condition that the decision-maker’s expected utility function (EUF) is concave (Fig.1; a more detailed discussion about riskaversion and the concavity of the EUF can be found in Arrow 1971 and Levy 1998)

Read more

Summary

Introduction

Management of invasive species populations often requires making decisions about allocating scarce resources for surveillance or eradication of newly detected incursions. To aid in the decision-making process, agencies responsible for monitoring and controlling invasive species, such as the USDA Animal and Plant Health Inspection Service (APHIS) in the U.S (APHIS 1999; Lance 2003) or the Canadian Food Inspection Agency (CFIA) in Canada (CFIA 2001), routinely assess the projected risk impacts of alien organisms on biological resources, trade and other economic activities (Simberloff 2005, Venette et al 2010, Magarey et al 2011). Government agencies tasked with monitoring and regulating the incursion and spread of unwanted

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.