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Dynamic Programming and Learning Models for Management of a Nonnative Species

Author

Listed:
  • Mark Eiswerth
  • G. Cornelis van Kooten
  • Jeff Lines
  • Alison Eagle

Abstract

Nonnative invasive species result in sizeable economic damages and expensive control costs. Because dynamic optimization models break down if controls depend in complex ways on past controls, non-uniform or scale-dependent spatial attributes, etc., decision support systems that allow learning may be preferred. We compare three models of an invasive weed in California’s grazing lands: (1) a stochastic dynamic programming model, (2) a reinforcement-based, experience-weighted attraction (EWA) learning model, and (3) an EWA model that also includes stochastic forage growth and penalties for repeated application of environmentally harmful control techniques. Results indicate that EWA learning models may be appropriate for invasive species management.

Suggested Citation

  • Mark Eiswerth & G. Cornelis van Kooten & Jeff Lines & Alison Eagle, 2005. "Dynamic Programming and Learning Models for Management of a Nonnative Species," Working Papers 2005-07, University of Victoria, Department of Economics, Resource Economics and Policy Analysis Research Group.
    • Handle: RePEc:rep:wpaper:2005-07
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    File URL: https://web.uvic.ca/~repa/publications/REPA%20working%20papers/WorkingPaper2005-07.pdf
    File Function: Final version, 2005
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    2. Kimberly Burnett & Sittidaj Pongkijvorasin & James Roumasset, 2012. "Species Invasion as Catastrophe: The Case of the Brown Tree Snake," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 51(2), pages 241-254, February.
    3. Morteza Chalak & David J. Pannell, 2015. "Optimal Integrated Strategies to Control an Invasive Weed," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 63(3), pages 381-407, September.
    4. Haider, Zulqarnain & Charkhgard, Hadi & Kwon, Changhyun, 2018. "A robust optimization approach for solving problems in conservation planning," Ecological Modelling, Elsevier, vol. 368(C), pages 288-297.
    5. James Nolan & Dawn Parker & G. Cornelis Van Kooten & Thomas Berger, 2009. "An Overview of Computational Modeling in Agricultural and Resource Economics," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 57(4), pages 417-429, December.
    6. Carrasco, L.R. & Mumford, J.D. & MacLeod, A. & Knight, J.D. & Baker, R.H.A., 2010. "Comprehensive bioeconomic modelling of multiple harmful non-indigenous species," Ecological Economics, Elsevier, vol. 69(6), pages 1303-1312, April.
    7. Eiswerth, Mark E. & Yen, Steven T. & van Kooten, G. Cornelis, 2011. "Factors determining awareness and knowledge of aquatic invasive species," Ecological Economics, Elsevier, vol. 70(9), pages 1672-1679, July.

    More about this item

    Keywords

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    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics

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