Management recommendations for short-lived weeds depend on model structure and explicit characterization of density dependence

Authors

  • Satu Ramula,

    Corresponding author
    1. The University of Queensland, School of Biological Sciences, Qld 4072, Australia
    2. Section of Ecology, Department of Biology, University of Turku, 20014 Turku, Finland
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  • Yvonne M. Buckley

    1. The University of Queensland, School of Biological Sciences, Qld 4072, Australia
    2. CSIRO Sustainable Ecosystems, 306 Carmody Rd, St Lucia, Qld 4067, Australia
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Correspondence author. E-mail: satu.ramula@utu.fi

Summary

1. Multiple modelling techniques are currently used to describe population dynamics of established invasions, where intraspecific competition is likely to reduce survival, growth and/or fecundity, suppressing population growth rate. To date, it remains unanswered whether these modelling techniques produce similar management recommendations for density-dependent weed populations and how to model density dependence to better inform management.

2. We constructed demographic models for a short-lived weed based on data on multiple manipulated densities in a glasshouse and data from the literature using three germination strategies. We compared management recommendations produced by two main modelling techniques for density-dependent weed populations and examined whether periodic matrix population models constructed from different densities without characterization of density-dependent processes (implicit models) produce management recommendations similar to that of the same models with density dependence explicitly characterized and simulated (explicit models). The use of a periodic matrix population model enabled us to target simulated management on either vital rates or entire life stages, and to examine the role of a weed’s germination strategy on model outcomes.

3. Management recommendations differed depending on how density dependence was included in demographic models. Explicit models showed that management conducted after the density-dependent process driving population dynamics best curbed density-regulated weed populations, with reductions in seed production having a negligible effect regardless of a germination strategy. By contrast, implicit models constructed from multiple densities produced similar management recommendations for sparse and dense populations, with reductions in survival to a flowering stage, juvenile establishment or seed production leading to the greatest predicted declines in weed density.

4. Our results emphasize the importance of model structure when modelling dynamics of density-dependent weed populations, suggesting that explicit characterization and inclusion of density dependence in population models is often necessary to inform management. As a weed’s germination strategy had a minor effect on model outcomes, our findings about explicit and implicit modelling techniques can be generalized across annual plants with non-overlapping generations.

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