Developing a decision support tool to forecast the abundance of the cabbage stem weevil in winter oilseed rape

Abstract

Reducing the use of pesticides in agricultural systems is a prerequisite for sustainable agriculture and, the-refore, knowledge on the factors that influence the regional insect pest densities is necessary. Based on multi-site and multi-annual observations of the cabbage stem weevil [Ceutorhynchus pallidactylus (Marsham, 1802)] in winter oilse-ed rape (Brassica napus Linnaeus) and the corresponding meteorological measurements, a statistical relationship for forecasting the abundance was derived. The model explains 84% of the variation of the data set. The remaining 16% might be explained by the landscape effects and agricultural practices, such as crop protection. Based on the statistical relationship between the mean winter air temperature and the abundance of the cabbage stem weevil in the winter oilseed rape, risk maps were derived as a forecast tool for practical farming.