A practical optimal surveillance policy for invasive weeds: An application to Hawkweed in Australia

We propose a practical analytical framework which can help government agencies determine an optimal surveillance strategy for invasive weeds, including cases of slow-growing or ‘sleeper weeds', and for all weeds at early stages of invasion where quantitative information is scant or rough. The f...

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Published inEcological economics Vol. 130; pp. 156 - 165
Main Authors Kompas, Tom, Chu, Long, Nguyen, Hoa Thi Minh
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.10.2016
Subjects
Containment
Eradication
Hawkweed
Invasive weeds
Stochastic programming
Surveillance
Australia
Surveillance
Eradication
Invasive weeds
Hawkweed
Containment
Stochastic programming
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Summary:We propose a practical analytical framework which can help government agencies determine an optimal surveillance strategy for invasive weeds, including cases of slow-growing or ‘sleeper weeds', and for all weeds at early stages of invasion where quantitative information is scant or rough. The framework consists of three key components: (a) a simple rule that can determine weed surveillance zones or where early detection is desirable, (b) a function that maps surveillance effort to early detection probability, and (c) a schedule to determine an optimal surveillance budget. A calibration to Hawkweed in Australia provides an example of the framework and shows that the optimal annual surveillance budget for this sleeper weed is substantial.
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ISSN:0921-8009
1873-6106
DOI:10.1016/j.ecolecon.2016.07.003