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Optimal strategies for the surveillance and control of forest pathogens: A case study with oak wilt

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  • Horie, Tetsuya
  • Haight, Robert G.
  • Homans, Frances R.
  • Venette, Robert C.

Abstract

Cost-effective strategies are needed to find and remove diseased trees in forests damaged by pathogens. We develop a model of cost-minimizing surveillance and control of forest pathogens across multiple sites where there is uncertainty about the extent of the infestation in each site and when the goal is to minimize the expected number of new infections. We allow for a heterogeneous landscape, where grid cells may be differentiated by the number of trees, the expected number of infected trees, rates of infection growth, and costs of surveillance and control. In our application to oak wilt in Anoka County, Minnesota, USA, we develop a cost curve associated with saving healthy trees from infection. Assuming an annual infection growth rate of 8%, a $1 million budget would save an expected 185 trees from infection for an average of $5400 per tree.

Suggested Citation

  • Horie, Tetsuya & Haight, Robert G. & Homans, Frances R. & Venette, Robert C., 2013. "Optimal strategies for the surveillance and control of forest pathogens: A case study with oak wilt," Ecological Economics, Elsevier, vol. 86(C), pages 78-85.
  • Handle: RePEc:eee:ecolec:v:86:y:2013:i:c:p:78-85
    DOI: 10.1016/j.ecolecon.2012.09.017
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    References listed on IDEAS

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    1. Mehta, Shefali V. & Haight, Robert G. & Homans, Frances R. & Polasky, Stephen & Venette, Robert C., 2007. "Optimal detection and control strategies for invasive species management," Ecological Economics, Elsevier, vol. 61(2-3), pages 237-245, March.
    2. Haight, Robert G. & Polasky, Stephen, 2010. "Optimal control of an invasive species with imperfect information about the level of infestation," Resource and Energy Economics, Elsevier, vol. 32(4), pages 519-533, November.
    3. Homans, Frances & Horie, Tetsuya, 2011. "Optimal detection strategies for an established invasive pest," Ecological Economics, Elsevier, vol. 70(6), pages 1129-1138, April.
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    Cited by:

    1. Atallah, Shadi S. & Huang, Ju-Chin & Leahy, Jessica & Bennett, Karen, 2020. "Preference Heterogeneity and Neighborhood Effect in Invasive Species Control: The Case of Glossy Buckthorn in New Hampshire and Maine Forests," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304623, Agricultural and Applied Economics Association.
    2. Kıbış, Eyyüb Y. & Büyüktahtakın, İ. Esra, 2017. "Optimizing invasive species management: A mixed-integer linear programming approach," European Journal of Operational Research, Elsevier, vol. 259(1), pages 308-321.
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    5. Yemshanov, Denys & Haight, Robert G. & Koch, Frank H. & Lu, Bo & Venette, Robert & Fournier, Ronald E. & Turgeon, Jean J., 2017. "Robust Surveillance and Control of Invasive Species Using a Scenario Optimization Approach," Ecological Economics, Elsevier, vol. 133(C), pages 86-98.
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    7. İ. Esra Büyüktahtakın & Robert G. Haight, 2018. "A review of operations research models in invasive species management: state of the art, challenges, and future directions," Annals of Operations Research, Springer, vol. 271(2), pages 357-403, December.
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    9. Atallah, Shadi S., 2017. "The bio-economics of managing invasive plant externalities in forests with heterogeneous landowner preferences," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258540, Agricultural and Applied Economics Association.
    10. Bonneau, Mathieu & Martin, Julien & Peyrard, Nathalie & Rodgers, Leroy & Romagosa, Christina M. & Johnson, Fred A., 2019. "Optimal spatial allocation of control effort to manage invasives in the face of imperfect detection and misclassification," Ecological Modelling, Elsevier, vol. 392(C), pages 108-116.
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