Improving phenological forecasting models for rape stem weevil,Ceutorhynchus napiGyll., based on long‐term multisite datasets

Abstract

AbstractNew threshold‐based models to predict the start of invasion by the stem‐boring pest, the rape stem weevil (Ceutorhynchus napiGyll.) of winter oilseed rape (Brassica napusL.), were developed and compared to published models using long‐term datasets on weather and weevil phenology from experimental locations in Germany and Luxembourg. Threshold values for daily records of maximum air temperature, mean soil temperature, sunshine duration and total precipitation were adjusted to local conditions on the date of first weevil migration in spring. Mean error and the root mean squared error were used to assess model quality, where the error is defined as the number of days between predicted and observed arrival of weevils on the crop (regardless of sign). Best model results predicted first crop invasion by rape stem weevil when the thresholds of daily maximum air temperature ≥7.8°C, mean soil temperature ≥6.6°C, daily total precipitation ≤1.0 mm and sunshine duration ≥1 h were matched. This model takes into account meteorological variables likely to influence conditions at the overwintering site of the weevils in the soil, as well as variables that may limit weevil flight. Adjusted air temperature threshold values were consistently lower for Luxembourg sites than for those optimized for Germany. A simple model relating the date of first weevil invasion to accumulated daily maximum air temperature above 0°C (from 1 January) was also evaluated. This proved less suitable for forecasting crop invasion byC. napi. We suggest that phenological models using locally adjusted meteorological‐based thresholds have the potential to offer sufficiently accurate forecasts of first immigration flights byC. napifor appropriate timing of insecticide application. In addition, the developed models are suitable tools to be used in climate change impact studies.