Mdf. Shirley et al., Simulating the long-term dynamics of slug populations: a process-based modelling approach for pest control, J APPL ECOL, 38(2), 2001, pp. 401-411
1. An individual-based simulation model was developed to investigate the lo
ng-term dynamics of slug populations using the field slug Deroceras reticul
atum as the test species.
2. 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 th
e characteristic bivoltine life cycle of D. reticulatum observed in field s
tudies.
3. A sensitivity analysis showed that the output of the model was significa
ntly influenced by soil moisture, air temperature and leaf area index. Thes
e 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.
4. The model output was compared with the observed dynamics of slug populat
ions collected in the field. Predicted slug dynamics and observed slug numb
ers showed a high degree of fidelity.
5. 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 curr
ent slug population and the slug numbers in the following spring.
6. Modelling approaches that link crop growth and population dynamics of pe
sts have potential in assessing their agricultural impacts and in evaluatin
g alternative strategies for their management.