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Simulating crop rotation strategies with a spatiotemporal lattice model to improve legislation for the management of the maize pest Diabrotica virgifera virgifera

Author

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  • Szalai, Márk
  • Kiss, József
  • Kövér, Szilvia
  • Toepfer, Stefan

Abstract

Crop rotation is an effective control method against the root-feeding larvae of the maize pest Diabrotica virgifera virgifera (western corn rootworm; Coleoptera: Chrysomelidae). However, adults are mobile and can re-colonise previously rotated maize fields. A discrete, spatiotemporal, lattice-based and cellular automaton-like, interacting particles system model was developed to allow complex analyses for improving integrated pest management recommendations and legislations; and this through considering at one time legislation for pest control strategies such as crop rotation, characteristics of an agricultural region and the population dynamics of the pest. Sensitivity analyses identified only two of 20 varying input factors with high importance at influencing the model output, i.e. the percentage of maize fields reaching pest populations above an economic threshold. These were: the percentage of rotated maize among all maize fields and the generational growth rate of the pest in low populated fields. Increases in the percentage of rotated maize led to a decreasing logistic curve for the percentage of fields reaching pest populations above threshold. Only a small percentage of maize fields was above threshold when percentage of rotated maize exceeded 70% holding all other input factors at their most likely values. Legislation of mandatory rotation after 3 consecutive years of maize growing reduced the need for rotation of maize for D. v. virgifera management below 60%. In contrast, nearly all maize fields reached thresholds when less than 40% of maize fields were rotated. An increased growth rate resulted in more maize fields reaching populations above threshold. Astonishingly, the maize growing in an agricultural region had, in a range from 20% to 60%, little to no influence. In conclusion, legislations requiring 100% rotation for the control of this maize pest seem too strict. Metamodels are provided to easily estimate percentages of maize fields reaching pest populations above threshold, which can be used by regional or country-wide decision makers in agri-policy as well as for integrated pest management guidelines.

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  • 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.
    • Handle: RePEc:eee:agisys:v:124:y:2014:i:c:p:39-50
    DOI: 10.1016/j.agsy.2013.10.009
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    1. Maxime Dupin & Philippe Reynaud & Vojtěch Jarošík & Richard Baker & Sarah Brunel & Dominic Eyre & Jan Pergl & David Makowski, 2011. "Effects of the Training Dataset Characteristics on the Performance of Nine Species Distribution Models: Application to Diabrotica virgifera virgifera," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-11, June.
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    1. Feusthuber, Elisabeth & Mitter, Hermine & Schönhart, Martin & Schmid, Erwin, 2017. "Integrated modelling of efficient crop management strategies in response to economic damage potentials of the Western Corn Rootworm in Austria," Agricultural Systems, Elsevier, vol. 157(C), pages 93-106.
    2. 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.
    3. repec:zbw:inwedp:742019 is not listed on IDEAS
    4. Bernadette Kropf & Hermine Mitter & Martin Schönhart & Erwin Schmid, 2019. "Wahrnehmungen und Erfahrungen von Landwirtinnen und Landwirten in SüdostÖsterreich zu betrieblichen und regionalen Maßnahmen zur Regulierung des Westlichen Maiswurzelbohrers," Working Papers 742019, University of Natural Resources and Life Sciences, Vienna, Department of Economics and Social Sciences, Institute for Sustainable Economic Development.

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