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

Tom Kompas, Long Chu and Hoa Nguyen ()

Ecological Economics, 2016, vol. 130, issue C, 156-165

Abstract: 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.

Keywords: Surveillance; Containment; Eradication; Invasive weeds; Hawkweed; Stochastic programming (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolec:v:130:y:2016:i:c:p:156-165

DOI: 10.1016/j.ecolecon.2016.07.003

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