Using phenology models to estimate insecticide effects on population dynamics: examples from codling moth and obliquebanded leafroller. Issue 2 (24th October 2020) - Jones, Vincent P
Abstract: BACKGROUND: Phenology models based on degree‐days were modified to estimate the effects of insecticide applications on the codling moth, Cydia pomonell a (L.), and the obliquebanded leafroller, Choristoneura rosaceana (Harris) (Lepidoptera: Tortricidae). Because the models inherently track stage structure of the population over the course of the season, stage specific mortality can be applied for various durations and intensities allowing the user to simulate different types of pesticides (ovicides, larvicides, organic or conventional materials). The models presented incorporate reproduction, effects of an application on subsequent generations, and the effects of each insecticide by itself as well as the combination of all the treatments. By comparing the treated populations to an untreated control, an estimate of how much the population size is reduced by different treatment programs over the entire season provides a clear assessment of the effectiveness of the treatment program. Simulations for codling moth also allow the insecticide effects to be simulated in conjunction with mating disruption (or not) and simulations for obliquebanded leafroller include the effect of insecticides on both instars 1–3 and 4–6. RESULTS: The simulations show there are distinct windows of opportunity for management programs, with rather large windows where an insecticide application has only a minor effect on population growth and also shows that intergenerational effects greatly affect optimal timings in subsequent generations. CONCLUSION: The models are especially useful in assessing current management strategies, testing potential improvements in timings, and evaluating cost savings and reducing non‐target effects. Abstract : Models were developed to evaluate the effect of different treatment timings and residual activity periods on population density compared to untreated populations for specific locations and years. © 2020 Society of Chemical Industry