Predicting the potential establishment of two insect species using the simulation environment INSIM (INsect SIMulation)

Abstract

Degree-day models have long been used to predict events in the life cycle of insects and therewith the timing of outbreaks of insect pests and their natural enemies. This approach assumes, however, that the effect of temperature is linear, whereas developmental rates of insects are non-linearly related to temperature. Therefore, we have developed the simulation tool INSIM (INsect SIMulation) that can easily handle non-linear temperature relationships, because the program interpolates between measured growth, mortality, and reproduction parameter values given at two subsequent ambient temperatures. We use the tool for predicting the establishment of two insect species. For the application of the biological control agent Podisus maculiventris (Say) (Hemiptera: Pentatomidae) in The Netherlands, we compare a linear and a non-linear function for the development. The number of adult females increases six-fold in the course of a year for the non-linear case, suggesting that the Dutch climate might be warm enough for this beneficial insect to settle. The implementation of a linear development rate shows approximately the same increase. For the invasive pest Drosophila suzukii (Matsumura) (Diptera: Drosophilidae) in The Netherlands, we assessed that it is probably well-adapted to the current Dutch climate: it is predicted to establish easily in most of the simulated scenarios. However, if it were only to attack blueberries (and not cherries), its invasion success is predicted to be limited, because the reproduction in blueberries is low. The implementation of a linear development rate gives rise to 50% fewer adult females (on cherry) or even 95% fewer (on blueberry) after a year. More data are needed for both systems, specifically on overwintering survival for P. maculiventris and for D. suzukii on lifetime reproduction at various temperatures and in different fruit hosts. From the implementation of the linear rate model we can see that, depending on how well the linear approximation is, the results may differ considerably. We have demonstrated that the INSIM program is a useful tool that can easily be adapted to predict the success and individual variation for different insect species.