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Combating Insecticide Resistance in Major UK Pests: Modelling Section

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Combating Insecticide Resistance in Major UK Pests: Modelling Section Rothamsted Research where knowledge grows Combating insecticide resistance in major UK pests: modelling section Joe Helps, Frank van den Bosch, Neil Paveley Start: 1/1/2013 End: 31/7/2016 Project aim • Key questions: Are mixtures beneficial? First need to understand what is the effect of dose on resistance? 1. Build a model of insecticide resistance 2. Explore various measures relating to both: Providing effective control of populations Delaying build up of resistance Insects in the UK Generations per year • Peach-potato aphid Multiple Single • Potato aphid • Grain aphid • Pea aphid • Rose-grain aphid • Currant-lettuce aphid Asexual • Glasshouse whitefly • Two-spotted spider mite • Western flower thrips • Diamondback moth • Leaf miner • Pollen beetle • Cabbage stem flea beetle Asexual / Sexual Asexual • Wheat bulb fly • Orange wheat blossom midge • Pea moth • Codling moth • Pea and bean weevil Sexual Model introduction Insecticide Overwintering insects Maturation Immigration (Susceptible adults) Larvae Adults SS SR RR SS SR RR Birth Damage: • Feeding • Virus transmission • Contamination Crop Model introduction Insecticide Maturation 2 0.99 SS SR 1 RR 0.9 Larvae Adults Logit mortality 0 0.5 Absolute mortality SS SR RR SS SR RR 0.1 -1 Birth -2 0.01 -3 -2 -1 0 1 2 3 Dose (log10) Crop Simulations Grain aphid Pollen beetle 30 50 Data Data Simulation Adults 25 Larvae 40 20 30 Insects per plant per Insects 15 Number of aphids per tille aphids per of Number 20 10 10 5 0 0 0 10 20 30 40 50 60 0 10 20 30 40 50 60 Time (days) Time (days) Data from Skirvin, D.J., Perry, J.N. & Harrington, R. Data from Sam Cook, Rothamsted Ecological Modelling, 96, 29-39 Model introduction 14 14 Total Larvae 10 10 Adults 8 8 InsectInsect density density 6 6 4 4 2 2 0 0 0 50 100 150 200 Time (days) Model introduction 14 Susceptible 12 Resistant 10 8 Insect density 6 4 2 0 0 1 2 3 4 5 6 Time (Years) High dose hypothesis Does a high dose lead to reduced or increased selection for resistance? High dose hypothesis • Applying a very high dose can lead to slower resistance frequency build up Scenario 1 Scenario 2 1e-03 1e-03 6e-04 Resistance frequencResistance 6e-04 R aft allele frequency 2e-04 2e-04 0.5 1.0 1.5 2.0 2.5 0.5 1.0 2.0 Multiple of single dose Multiple of single dose (log sca High dose hypothesis Scenario 1 1e-03 Resistance frequencResistance 6e-04 Scenario 1 2e-04 0.5 1.0 1.5 2.0 2.5 Multiple of single dose Dominance Scenario 2 1e-03 6e-04 Scenario 2 R aft allele frequency 2e-04 Insecticide Efficacy 0.5 1.0 2.0 Multiple of single dose (log sca (Mortality) High dose summary • One important mechanism allows high dose to reduce selection Immigration from external source • Under most parameter combinations tested, lowering the dose will lower the selection for resistance Resistance management & yield • Coupling control of the pest with resistance management • Effective life Number of years that the insecticide effectively controls the insect pest Following results: o Number of years until yield loss (reduction in HAD) exceeds 20% (an arbitrary value) Still to consider: o Contamination o Virus infection Exploring effective life Asexual; No immigration • Graphs show effective life • Graphs show difference in effective life between applying a full 1.0 dose and a half dose 0.8 5 3 4 0.6 SS Dominance SS 0.4 Dose (log10) Narrow 0.2 Broad Dose 6 9 10 7 8 (log10) effectiveness 6 5 effectiveness 0.0 7 Probit range range Probit mortality 0.80 0.85 0.90 0.95 mortality 1.0 1.0 1 Insecticide Efficacy 0 Mortality in first season -1 -3 (Mortality) 0.8 0.8 -1 0 -2 -2 0 0.6 0.6 5 Dominance Dominance 2 0.4 0.4 3 -4 6 4 -1 0.2 0.2 -4 0 7 -1 1 23 4 -1 9 -10 -8 -6 -2 -1 -2 0.0 0.0 -5-7 -11 0.80 0.85 0.90 0.95 0.80 0.85 0.90 0.95 InsecticideMortality Efficacy in first season InsecticideMortality Efficacy in first season (Mortality) (Mortality) Conclusions about half dose • Preliminary conclusion: When the insecticide dose can be reduced without incurring unacceptable yield losses, it will lead to reduced selection for resistance • Is there data available? • Possible to test in cage / field experiments? Two insecticides • Two insecticides • What is the consequence of mixing the two insecticides when: Resistance is developing to only one of the insecticides Resistance is developing to both insecticides Evolution against one insecticide in the mixture • Three key determinants: Emergence from an overwintering population Immigration from an untreated population If an insect stage (larvae / adults) is present but not affected by the insecticide • No emergence • With emergence • No emergence • No immigration • No immigration • With immigration • All stages susceptible • All stages susceptible • All stages susceptible 200% 200% 200% 0.3 0.25 0.6 0.2 0.15 0.1 100% 0.5 100% 0.5 100% 0.2 0.05 High-risk insecticide High-risk full do of Percentage High-risk insecticide High-risk full do of Percentage insecticide High-risk full do of Percentage 0.1 0.1 50% 50% 50% 10% 10% 10% 10% 50% 100% 200% 10% 50% 100% 200% 10% 50% 100% 200% Low-risk insecticide Low-risk insecticide Low-risk insecticide Percentage of full dos Percentage of full dos Percentage of full dos R allele frequency after 5 years Future work • High-risk mixtures • Exploration of the effective life of mixtures • Testing different strategies for two insecticides: Mixtures Alternation (within year) Rotation (between year) Sequential use • Validation Conclusions • We have developed a tool to test management strategies • With a single insecticide spray: Reduce dose as much as possible without compromising control • We are currently exploring additional management strategies • Determine critical characteristics of insects • Group insects by the optimal management strategy.
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