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Economics of controlling invasive species: a stochastic optimisation model for a spatial-dynamic process

Author

Listed:
  • Chalak, Morteza
  • Pannell, David J.
  • Polyakov, Maksym

Abstract

Invasive species are significant threats to biodiversity, natural ecosystems and agriculture leading to large worldwide economic and environmental damage. Spread and control of invasive species are stochastic processes with important spatial dimensions. Most economic studies of invasive species control ignore spatial and stochastic aspects. This paper covers this gap in the previous studies by analysing a spatially explicit dynamic process of controlling invasive species in a stochastic setting. We show how stochasticity, spatial location of infestation and control can influence the spread, control efficiency and optimal control strategies. The main aim of this paper is to analyse the relationship between economic parameters and stochastic spatial characteristics of infestation and control. In the model used, there are two ways to control infestation: border control, under which the spread of invasive species from any of its infested neighbouring cell is prevented, and cell control, which removes the infestation from the existing cell. An integer optimisation model is applied to find the optimal strategies to deal with invasive species. Results show that it is optimal to eradicate or contain for a larger range of border control and cell control costs when the invasion is in the corner or on the edge as compared to the case where the initial infestation is in the middle of the landscape. Decrease in the probability of successful border control makes containment an unfavourable control option even for low border control costs. We show that decrease in the rate of spread can result in switching optimal strategies from containment to abandonment of control, or from eradication to containment. We also showed when the probability of successful cell control decreases, a lower eradication cost is required for eradication to remain the optimal strategy. In summary, this paper shows that in order to avoid providing misleading recommendations to environmental managers, it is important to include uncertainty in the spatial dynamic analysis of invasive species control.

Suggested Citation

  • Chalak, Morteza & Pannell, David J. & Polyakov, Maksym, 2011. "Economics of controlling invasive species: a stochastic optimisation model for a spatial-dynamic process," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103325, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea11:103325
    DOI: 10.22004/ag.econ.103325
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    References listed on IDEAS

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    1. James E. Wilen, 2007. "Economics of Spatial-Dynamic Processes," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(5), pages 1134-1144.
    2. Olson, Lars J. & Roy, Santanu, 2010. "Dynamic sanitary and phytosanitary trade policy," Journal of Environmental Economics and Management, Elsevier, vol. 60(1), pages 21-30, July.
    3. Epanchin-Niell, Rebecca S. & Wilen, James E., 2010. "Optimal control of spatial-dynamic processes: The case of biological invasions," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61375, Agricultural and Applied Economics Association.
    4. Odom, Doreen I. S. & Cacho, Oscar J. & Sinden, J. A. & Griffith, Garry R., 2003. "Policies for the management of weeds in natural ecosystems: the case of scotch broom (Cytisus scoparius, L.) in an Australian national park," Ecological Economics, Elsevier, vol. 44(1), pages 119-135, February.
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    6. Burnett, Kimberly M. & Kaiser, Brooks A. & Roumasset, James A., 2007. "Invasive Species Control over Space and Time: Miconia calvescens on Oahu, Hawaii," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 39(s1), pages 125-132, October.
    7. Costello, Christopher & Springborn, Michael & McAusland, Carol & Solow, Andrew, 2007. "Unintended biological invasions: Does risk vary by trading partner?," Journal of Environmental Economics and Management, Elsevier, vol. 54(3), pages 262-276, November.
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    Cited by:

    1. Courtois, Pierre & Figuieres, Charles & Mulier, Chloe & Weill, Joakim, 2018. "A Cost–Benefit Approach for Prioritizing Invasive Species," Ecological Economics, Elsevier, vol. 146(C), pages 607-620.
    2. Billionnet, Alain, 2013. "Mathematical optimization ideas for biodiversity conservation," European Journal of Operational Research, Elsevier, vol. 231(3), pages 514-534.
    3. Atallah, Shady S. & Gómez, Miguel I. & Jaramillo, Juliana, 2018. "A Bioeconomic Model of Ecosystem Services Provision: Coffee Berry Borer and Shade-grown Coffee in Colombia," Ecological Economics, Elsevier, vol. 144(C), pages 129-138.
    4. Tom Kompas & Pham Van Ha & Hoa-Thi-Minh Nguyen & Graeme Garner & Sharon Roche & Iain East, 2020. "Optimal surveillance against foot-and-mouth disease: A sample average approximation approach," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-21, July.
    5. Sean F. Ellis & Mark Masters & Kent D. Messer & Collin Weigel & Paul J. Ferraro, 2021. "The Problem of Feral Hogs and the Challenges of Providing a Weak‐Link Public Good," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(3), pages 985-1002, September.

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    Keywords

    Environmental Economics and Policy;

    JEL classification:

    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics

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