Page Banner

United States Department of Agriculture

Agricultural Research Service

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

Authors
item Carriere, Yves -
item Ellers-Kirk, C -
item Harthfield, K -
item Degain, B -
item Barkley, Crowder -
item Dennehy, T -
item Ellsworth, P -
item Li, X -
item Fournier, A -
item March, S -
item Larocque, G -
item Dutilleul, P -
item Antilla, Larry -
item Naranjo, Steven
item Palumbo, J -
item Tabashnik, B -

Submitted to: Proceedings of the National Academy of Sciences
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: June 8, 2011
Publication Date: June 10, 2011
Citation: Carrière, Y., C.Ellers-Kirk, K. Hartfield, G. Larocque, B. Degain, P. Dutilleul, T. J. Dennehy, S. E. March, D. W. Crowder, X. Li, P. C. Ellsworth, S. E. Naranjo, J. C. Palumbo, A. Fournier, L. Antilla & B. E. Tabashnik. 2012. Large-scale, spatially explicit test of the refuge strategy for delaying insecticide resistance. Proc. Nat. Acad. Sci. (USA)109:775-780.

Interpretive Summary: The development of resistance in arthropod pests to pesticides is a major barrier to sustainable pest control in agricultural system. One strategy to slow or reverse resistance evolution is to provide crop areas for the pest where the pesticide in question is not used. This is called the refuge strategy, but there is little empirical data to show that such an approach actually works as theoretical models would predict. Here, we combined an eight-year, large-scale data set of resistance monitoring to the insect growth regulator pyriproxyfen in 84 populations of the sweetpotato whitefly sampled in cotton fields in Central AZ with spatial data on whitefly affected crops, to formulate an empirically-based statistical model linking the evolution of resistance to the distribution of refuges and evaluate the accuracy of predictions of this model. We found that the distribution of alfalfa and melon was not significantly associated with resistance, while treated and untreated cotton significantly influenced resistance. The model incorporating the distribution of treated and untreated cotton accounted for the highest proportion of variation in resistance at a scale of 2.75 km surrounding the sampled sites. This model predicted spatial variation in resistance, indicating that refuges of untreated cotton at < 2.75 km from treated fields will delay resistance. Our approach has the potential to improve refuge strategies for numerous pests and systems.

Technical Abstract: The refuge strategy used worldwide to delay the evolution of arthropod resistance to pesticides consists of leaving areas where a pesticide is not used near fields where the pesticide is used. Yet, empirical approaches are lacking to characterize effects of putative refuges on resistance evolution. Furthermore, predictive refuge strategy models have not been evaluated in the field, which is needed to improve credibility of this strategy for resistance management. Here, we combined an eight-year, large-scale data set of resistance to the insect growth regulator pyriproxyfen in 84 populations of the sweetpotato whitefly sampled in cotton fields in Central AZ with spatial data on whitefly affected crops, to formulate a statistical model linking the evolution of resistance to the distribution of refuges and treated fields and evaluate the accuracy of predictions of this model. We found that the distribution of alfalfa and melon was not significantly associated with resistance, while treated and untreated cotton significantly influenced resistance. The model incorporating the distribution of treated and untreated cotton accounted for the highest proportion of variation in resistance at a scale of 2.75 km surrounding the sampled sites. This model predicted spatial variation in resistance, indicating that refuges of untreated cotton at < 2.75 km from treated fields will delay resistance. Our approach has the potential to improve refuge strategies for numerous pests and systems

Last Modified: 12/22/2014
Footer Content Back to Top of Page