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Keywords:

  • biocontrol;
  • control;
  • integrated weed management;
  • simulation;
  • stochastic

Summary

  • 1
    Hypericum perforatum, St John's wort, is an invasive weed of natural and agro-ecosystems in south-eastern Australia. In previous work we used a long-term data set to determine which plant traits and environmental factors influence population growth and persistence in this species. These results were then used to parameterize an individual-based model of the population dynamics of H. perforatum, and this model was used to make predictions about what control strategies will be most effective for populations in open and shaded sites.
  • 2
    The model was constructed using multi-level, mixed-effects statistical models of growth, survival, fecundity and damage, incorporating intrinsic plant variables, environmental variables, herbivory and spatial and temporal stochasticity.
  • 3
    We found that populations in shaded and open sites had different dynamics and responses to control strategies. Shaded populations took longer to reach infestation densities and were less affected by herbivory and reductions in survival than open populations. Open populations increased faster in response to increases in rainfall, but this was not so for shaded populations.
  • 4
    We used sensitivity testing and management simulations to predict that the most successful control strategies will involve a reduction in vegetative size in both open and shaded sites. Reductions in flowering stem size and survival in shaded and open sites, respectively, are predicted to be the next most successful strategies. Dry conditions in the austral autumn/winter adversely affect populations in both open and shaded sites.
  • 5
    Synthesis and applications. These models have enabled us to rank management strategies based on quantitative analysis of their potential effects on population size. This is an important tool not only for ecologists concerned with control of invasive species but for conservation biologists trying to understand the factors limiting a rare or endangered species.