Simulating the long-term dynamics of slug populations: a process-based modelling approach for pest control.
Abstract
An individual-based simulation model was developed to investigate the long-term dynamics of slug populations using the field slug Deroceras reticulatum as the test species. The model consisted of two components: a model to provide meteorological data and simulate crop growth; and a model to simulate slug life histories. The patterns of slug population dynamics produced by the model matched the characteristic bivoltine life cycle of D. reticulatum observed in field studies. A sensitivity analysis showed that the output of the model was significantly influenced by soil moisture, air temperature and leaf area index. These three environmental factors relate directly to important features in the biology of slugs. Of the life-history variables used as inputs to the model, growth rate, environmental mortality and the mortality of sexually mature slugs had a significant effect on the population dynamics predicted by the model. The model output was compared with the observed dynamics of slug populations collected in the field. Predicted slug dynamics and observed slug numbers showed a high degree of fidelity. The simulation model was used to investigate the effects of varying the timing of control methods used to combat slug damage to crops. This result suggested that there is a 'window of opportunity', immediately post-harvest, when slug control is likely to have a significant effect on both the current slug population and the slug numbers in the following spring. Modelling approaches that link crop growth and population dynamics of pests have potential in assessing their agricultural impacts and in evaluating alternative strategies for their management.