Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 109, Issue 3, Pages 775-780Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1117851109
Keywords
pesticide resistance; predictive evolutionary models; pest management; resistance management
Categories
Funding
- Monsanto and Dow AgroSciences
- Arizona Cotton Research and Protection Council
- US Department of Agriculture (USDA) National Research Initiative [2007-02227]
- USDA [0207436]
- Arizona Department of Agriculture [SCBGPFB0909, SCBGPFB1004]
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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.
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