title: Use of an individual-based simulation model to explore and evaluate potential insecticide resistance management strategies.
abstract: BACKGROUND
  Tools with the potential to predict risks of insecticide resistance and aid the evaluation and design of resistance management tactics are of value to all sectors of the pest management community. Here we describe use of a versatile individual-based model of resistance evolution to simulate how strategies employing single and multiple insecticides influence resistance development in the pollen beetle, Meligethes aeneus.
  
  
  RESULTS
  Under repeated exposure to a single insecticide, resistance evolved faster to a pyrethroid (lambda-cyhalothrin) than to a pyridine azomethane (pymetrozine), due to difference in initial efficacy. A mixture of these compounds delayed resistance compared to use of single products. The effectiveness of rotations depended on the sequence in which compounds were applied in response to pest density thresholds. Effectiveness of a mixture strategy declined with reductions in grower compliance. At least 50% compliance was needed to cause some delay in resistance development.
  
  
  CONCLUSIONS
  No single strategy meets all requirements for managing resistance. It is important to evaluate factors that prevail under particular pest management scenarios. The model used here provides operators with a valuable means for evaluating and extending sound resistance management advice, as well as understanding needs and opportunities offered by new control techniques. © 2016 Society of Chemical Industry.
authors.affiliation: Syngenta Crop Protection AG, Research Biology, Stein, Switzerland.
authors.forename: Russell
authors.initials: R
authors.lastname: Slater
authors.affiliation: Computational and Systems Biology Department, Rothamsted Research, Harpenden, UK.
authors.forename: Pierre
authors.initials: P
authors.lastname: Stratonovitch
authors.affiliation: Syngenta Crop Protection AG, Research Biology, Stein, Switzerland.
authors.forename: Jan
authors.initials: J
authors.lastname: Elias
authors.affiliation: Computational and Systems Biology Department, Rothamsted Research, Harpenden, UK.
authors.forename: Mikhail A
authors.initials: MA
authors.lastname: Semenov
authors.affiliation: Biological and Environmental Sciences Department, University of Hertfordshire, Hatfield, UK.
authors.forename: Ian
authors.identifier: http://orcid.org/0000-0001-9797-874X
authors.initials: I
authors.lastname: Denholm
mesh_terms: D000818:Animals; D001391:Azo Compounds; D029741:Brassica rapa / Q000469:parasitology; D001517:Coleoptera / Q000235:genetics* / Q000378:metabolism; D003198:Computer Simulation; D018556:Crops, Agricultural / Q000469:parasitology; D019143:Evolution, Molecular; D007300:Insect Control / Q000379:methods*; D007305:Insecticide Resistance / Q000235:genetics*; D007306:Insecticides; D009570:Nitriles; D011722:Pyrethrins
chemical_list: D001391:Azo Compounds; D007306:Insecticides; D009570:Nitriles; D011722:Pyrethrins; C001825:azomethane; C037304:cyhalothrin
keywords: Meligethes aeneus; computer simulation; individual-based modelling; insecticide mixtures; insecticide resistance; pollen beetle; resistance management