Assessing pest control treatments from phenology models and field data

Area of Science:

• Agricultural Entomology
• Pest Management Science
• Quantitative Ecology

Background:

• Insecticide efficacy is typically measured by yield loss, but pests can impact yields even with effective controls.
• Current pest monitoring often relies on adult counts, neglecting immature stages and population dynamics.
• Assessing control efficacy in non-experimental settings requires novel approaches beyond traditional yield loss measurements.

Purpose of the Study:

• To develop a framework for assessing insecticide treatment efficacy using adult pest counts in non-experimental agricultural settings.
• To analyze shifts in temporal adult emergence patterns caused by immature-stage treatments.
• To provide a robust method for optimizing pest control strategies and input selection.

Main Methods:

• Utilized phenology models scaled to field counts to track pest population stage structure.
• Generated reference population trajectories with and without control treatments.
• Employed a time-sequential probability ratio test to classify field-collected trajectories.
• Evaluated the framework using codling moth (Cydia pomonella) pheromone trap data from apple and pear orchards.

Main Results:

• Simulations indicated a 70% probability of >50% treatment effectiveness when trajectories are classified as treated.
• Classifying trajectories as untreated suggested <66% program effectiveness.
• The method's reliability was demonstrated with trajectories from at least 15 pheromone traps.

Conclusions:

• The developed framework offers a powerful, evidence-based tool for optimizing pest control inputs and application protocols.
• This approach is broadly applicable to various pests with regular sampling and degree-day-based phenology models.
• Enhances the ability to make informed decisions in integrated pest management programs.