Present address: T. C. Cameron, Earth & Biosphere Institute, School of Biology, University of Leeds, Leeds LS2 9JT.
Population responses to perturbations: predictions and responses from laboratory mite populations
Article first published online: 18 AUG 2004
Journal of Animal Ecology
Volume 73, Issue 5, pages 983–995, September 2004
How to Cite
BENTON, T. G., CAMERON, T. C. and GRANT, A. (2004), Population responses to perturbations: predictions and responses from laboratory mite populations. Journal of Animal Ecology, 73: 983–995. doi: 10.1111/j.0021-8790.2004.00859.x
- Issue published online: 18 AUG 2004
- Article first published online: 18 AUG 2004
- Received 10 September 2003; accepted 5 January 2004
- density dependence;
- environmental stochasticity;
- population dynamics
- 1Mathematical models are frequently used to make predictions of the response of a population to management interventions or environmental perturbations, but it is rarely possible to make controlled or replicated tests of the accuracy of these predictions.
- 2We report results from replicated laboratory experiments on populations of a soil mite, Sancassania berlesei, living in ‘constant’ or ‘variable’ environments. We experimentally perturbed vital rates, via selective harvesting, and examined the population-level responses. The response depends on the stage manipulated and whether there is environmental variability. Increased mortality usually decreased population size and increased population variability. However, egg mortality in a variable environment increased total population size.
- 3We used time-series analysis to construct a stage-based population model of this system, incorporating the responses to both density and variation in food supply.
- 4The time-series model qualitatively captures the population dynamics, but does not predict well the way the populations will respond to the change in mortality. Elasticity analysis, conducted on the model's output, therefore did not lead to accurate predictions.
- 5The presence of indirect positive population effects of a negative perturbation, but only in a variable environment, suggests that predicting the population response will require the incorporation of density dependence and environmental stochasticity. That the considerable biological complexity of our time-series model did not allow accurate predictions suggests that accurate prediction requires modelling processes within a stage class rather than trying to make do with simple functions of total density.