Large-scale, spatially-explicit test of the refuge strategy for delaying insecticide resistance

Yves Carrière, Christa Ellers-Kirk, Kyle Hartfield, Guillaume Larocque, Ben Degain, Pierre Dutilleul, Timothy J. Dennehy, Stuart E. Marsh, David W. Crowder, Xianchun Li, Peter C. Ellsworth, Steven E. Naranjo, John C. Palumbo, Al Fournier, Larry Antilla, Bruce E. Tabashnik

Research output: Contribution to journalArticle

53 Scopus citations

Abstract

The refuge strategy is used worldwide to delay the evolution of pest resistance to insecticides that are either sprayed or produced by transgenic Bacillus thuringiensis (Bt) crops. This strategy is based on the idea that refuges of host plants where pests are not exposed to an insecticide promote survival of susceptible pests. Despite widespread adoption of this approach, large-scale tests of the refuge strategy have been problematic. Here we tested the refuge strategy with 8 y of data on refuges and resistance to the insecticide pyriproxyfen in 84 populations of the sweetpotato whitefly (Bemisia tabaci) from cotton fields in central Arizona. We found that spatial variation in resistance to pyriproxyfen within each year was not affected by refuges of melons or alfalfa near cotton fields. However, resistance was negatively associated with the area of cotton refuges and positively associated with the area of cotton treated with pyriproxyfen. A statistical model based on the first 4 y of data, incorporating the spatial distribution of cotton treated and not treated with pyriproxyfen, adequately predicted the spatial variation in resistance observed in the last 4 y of the study, confirming that cotton refuges delayed resistance and treated cotton fields accelerated resistance. By providing a systematic assessment of the effectiveness of refuges and the scale of their effects, the spatially explicit approach applied here could be useful for testing and improving the refuge strategy in other crop-pest systems.

Original languageEnglish (US)
Pages (from-to)775-780
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume109
Issue number3
DOIs
StatePublished - Jan 17 2012

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Keywords

  • Pest management
  • Pesticide resistance
  • Predictive evolutionary models
  • Resistance management

ASJC Scopus subject areas

  • General

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