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Towards the integration of spread and economic impacts of biological invasions in a landscape of learning and imitating agents

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  • Carrasco, L. Roman
  • Cook, David
  • Baker, Richard
  • MacLeod, Alan
  • Knight, Jon D.
  • Mumford, John D.

Abstract

We develop an agent-based model integrated with a spatial stochastic simulation harmful non-indigenous species (NIS) spread model in which farmers have learning and imitation capabilities. The model is applied to the western corn rootworm (WCR) invasion in the UK. The invasion is never eradicated due to the high dispersal capacity of WCR, particularly under climate change conditions. The lowest expected welfare losses arise with a laissez faire policy against the invasion. The effectiveness of NIS control programmes that require participation by land managers is shown to depend greatly on their learning and imitation dynamics. Control programmes might fail completely if there is global knowledge of the burdens of compliance – e.g. through the media – and the land managers can foresee the future consequences of new actions. This is due to coordinated noncompliance occurring across the landscape. If the agents need to experience compliance to learn its consequences or communicate only locally, potential noncompliant behaviour spreads more slowly than the invasion front and trails behind it. In conclusion, negative opinions of land managers over NIS control programmes and their media coverage can strongly undermine programmes. Identification and management of these factors may increase the odds of success of the programmes.

Suggested Citation

  • Carrasco, L. Roman & Cook, David & Baker, Richard & MacLeod, Alan & Knight, Jon D. & Mumford, John D., 2012. "Towards the integration of spread and economic impacts of biological invasions in a landscape of learning and imitating agents," Ecological Economics, Elsevier, vol. 76(C), pages 95-103.
  • Handle: RePEc:eee:ecolec:v:76:y:2012:i:c:p:95-103 DOI: 10.1016/j.ecolecon.2012.02.009
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    Cited by:

    1. Martin Drechsler & Julia Touza & Piran C. L. White & Glyn Jones, 2016. "Agricultural landscape structure and invasive species: the cost-effective level of crop field clustering," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 8(1), pages 111-121, February.
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    3. Walker, Adam N. & Poos, Jan-Jaap & Groeneveld, Rolf A., 2015. "Invasive species control in a one-dimensional metapopulation network," Ecological Modelling, Elsevier, vol. 316(C), pages 176-184.
    4. Liu, Shuang & Aurambout, Jean-Philippe & Villalta, Oscar & Edwards, Jacqueline & De Barro, Paul & Kriticos, Darren J. & Cook, David C., 2015. "A structured war-gaming framework for managing extreme risks," Ecological Economics, Elsevier, vol. 116(C), pages 369-377.
    5. Feusthuber, E. & Schönhart, M. & Schmid, E., 2015. "Spatial analysis of maize cropping systems to relieve crop pest pressure in Austria," 150th Seminar, October 22-23, 2015, Edinburgh, Scotland 212661, European Association of Agricultural Economists.
    6. Schlüter, Maja & Baeza, Andres & Dressler, Gunnar & Frank, Karin & Groeneveld, Jürgen & Jager, Wander & Janssen, Marco A. & McAllister, Ryan R.J. & Müller, Birgit & Orach, Kirill & Schwarz, Nina & Wij, 2017. "A framework for mapping and comparing behavioural theories in models of social-ecological systems," Ecological Economics, Elsevier, vol. 131(C), pages 21-35.
    7. Szalai, Márk & Kiss, József & Kövér, Szilvia & Toepfer, Stefan, 2014. "Simulating crop rotation strategies with a spatiotemporal lattice model to improve legislation for the management of the maize pest Diabrotica virgifera virgifera," Agricultural Systems, Elsevier, vol. 124(C), pages 39-50.

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