D3095: Rethinking biofix: Cold events and codling moth emergence in Michigan apple orchards

Phenology models have served as foundational tools for managing codling moth (Cydia pomonella, (Lepidoptera: Tortricidae) in Michigan apple orchards for more than 50 years. However, these models often rely on assumptions that may not hold under increasingly variable spring climate conditions. This project investigates whether cold temperature events following biofix, particularly low dusk temperatures, contribute to delays in emergence or reduced synchronization during the first flight of the season. Using long-term trap catch and weather data from Michigan orchards (2000 to 2024), we evaluated how well traditional growing degree-day (GDD) models capture observed codling moth activity across years. While colder conditions following biofix may appear to delay emergence, this pattern could instead reflect that earlier biofixes tend to occur during generally cooler periods, which naturally slow development. To disentangle these effects, we examined whether specific post-biofix cold events influence emergence timing beyond what GDD accumulation alone would predict. We compared the performance of traditional models, such as PETE, with alternative predictors, including dusk temperature, to identify weather-based indicators that may improve forecasting accuracy. This work lays the foundation for more adaptive modeling approaches under increasingly variable spring climate conditions. It also raises questions about whether biofix should be adjusted in years with significant cold periods after initial emergence. By integrating historical data with updated predictors, this study aims to support more responsive and climate-resilient pest management strategies.