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Using phenology models to estimate insecticide effects on population dynamics: examples from codling moth and

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|October 3, 2020
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Summary

Modified phenology models help assess insecticide effectiveness for codling moth and leafroller control. Simulations reveal optimal management timings and highlight intergenerational impacts for pest control strategies.

Keywords:
Choristoneura rosaceana (Harris)Cydia pomonella (L.)insecticide effects modelsoptimal management programsphenology models

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Area of Science:

  • Agricultural Entomology
  • Pest Management Modeling

Background:

  • Degree-day phenology models were adapted to simulate insecticide impacts on codling moth (Cydia pomonella) and obliquebanded leafroller (Choristoneura rosaceana).
  • Models incorporate population stage structure, allowing simulation of stage-specific mortality from various pesticide types and application regimes.
  • Reproduction, intergenerational effects, and combined insecticide treatments are integrated for comprehensive analysis.

Purpose of the Study:

  • To develop and apply modified phenology models for estimating insecticide efficacy against key lepidopteran pests.
  • To simulate the effects of different insecticide applications, including ovicides and larvicides, on pest populations.
  • To assess the impact of insecticide treatments in conjunction with other management tactics like mating disruption.

Main Methods:

  • Utilized degree-day based phenology models to track pest development stages throughout the season.
  • Applied stage-specific mortality rates to simulate the effects of various insecticide applications (ovicides, larvicides, organic, conventional).
  • Compared simulated treated populations against untreated controls to evaluate overall treatment program effectiveness.

Main Results:

  • Identified distinct optimal windows for pest management interventions.
  • Demonstrated that insecticide applications can have minor effects on population growth during certain periods.
  • Highlighted the significant influence of intergenerational effects on optimal treatment timing for subsequent generations.

Conclusions:

  • The developed models are valuable tools for evaluating current pest management strategies.
  • Models facilitate testing improvements in treatment timings to enhance efficacy and cost-effectiveness.
  • Simulation results aid in reducing non-target effects by optimizing pesticide application strategies.