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    Author(s): Denys Yemshanov; Frank H. Koch; Bo Lu; D. Barry Lyons; Jeffrey P. Prestemon; Taylor Scarr; Klaus Koehler
    Date: 2014
    Source: Ecological Economics 104:61-72
    Publication Series: Scientific Journal (JRNL)
    Station: Southern Research Station
    PDF: Download Publication  (4.19 MB)


    In this study we demonstrate how the notion of diversification can be used in broad-scale resource allocation for surveillance of invasive species. We consider the problem of short-term surveillance for an invasive species in a geographical environment.Wefind the optimal allocation of surveillance resourcesamongmultiple geographical subdivisions via application of a classical portfolio framework, which allocates investments among multiple financial asset types with uncertain returns in a portfolio that maximizes the performance and, by meeting the desired diversification targets, protects against errors in estimating the portfolio's performance. Weillustrate the approach with a case study that applies a spatial transmission model to assess the risk of spread of the emerald ash borer (EAB), a significant pest in NorthAmerica, with infested firewood that may be carried by visitors to campground facilities in central Canada. Adding the diversification objective yields an expected survey performance that is comparable with undiversified optimal allocation, but more importantly, makes the geographical distribution of survey priorities less subject to possible errors in the spread rate estimates. Overall, diversification of pest surveillance can be viewed as a viable short-term strategy for hedging against uncertainty in expert- and model-based assessments of pest invasion risk.

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    Yemshanov, Denys; Koch, Frank H.; Lu, Bo; Lyons, D. Barry; Prestemon, Jeffrey P.; Scarr, Taylor; Koehler, Klaus. 2014. There is no silver bullet: the value of diversification in planning invasive species surveillance. Ecological Economics 104:61-72.


    Emerald ash borer, Surveillance, Diversification, Equal risk sharing, Portfolio variance, Portfolio theory

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