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Requirements, design and implementation of a general model of biological invasion

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  • Savage, David
  • Renton, Michael

Abstract

The speed at which a response to a novel biological invasion can be developed and implemented plays a crucial role in the ability of biosecurity practitioners to successfully contain or eradicate the invading organism. In developing a response to a novel invasion, computational models of biological spread can play a key role, allowing practitioners to rapidly evaluate a range of invasion scenarios and the likely distribution of the invading population over time. This in turn can allow practitioners to compare different response plans and select those that will be most cost-effective and most likely to succeed. Unfortunately, the development of models that are capable of providing a realistic description of invasive spread is a costly and time consuming exercise and developing models specifically tailored to each of the vast array of potentially invasive organisms is infeasible. Therefore, we have developed a general model of biological invasion (GMBI) that is capable of simulating the invasive spread of a diverse range of organisms across heterogeneous landscapes, and can be used to represent particular invasion scenarios. The GMBI includes a small, highly biologically meaningful parameter set that can be relatively easily estimated using expert knowledge, and can therefore be quickly setup to simulate the spread of organisms which have not previously been well characterised. In this paper we discuss the desirability of a GMBI and elucidate the characteristics that are required. We then describe the formulation of a model that meets these requirements and demonstrate how it meets these requirements by parameterising the model to simulate the spread of two very different types of invasive organisms, namely a fungal pathogen and a pest beetle. These simulations demonstrate the flexibility of our GMBI, and the ease with which the model can be parameterised using parameter values found in the literature or obtained through expert elicitation.

Suggested Citation

  • Savage, David & Renton, Michael, 2014. "Requirements, design and implementation of a general model of biological invasion," Ecological Modelling, Elsevier, vol. 272(C), pages 394-409.
    • Handle: RePEc:eee:ecomod:v:272:y:2014:i:c:p:394-409
    DOI: 10.1016/j.ecolmodel.2013.10.001
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    References listed on IDEAS

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    1. Liu, Shuang & Hurley, Michael & Lowell, Kim E. & Siddique, Abu-Baker M. & Diggle, Art & Cook, David C., 2011. "An integrated decision-support approach in prioritizing risks of non-indigenous species in the face of high uncertainty," Ecological Economics, Elsevier, vol. 70(11), pages 1924-1930, September.
    2. Le Ber, F. & Lavigne, C. & Adamczyk, K. & Angevin, F. & Colbach, N. & Mari, J.-F. & Monod, H., 2009. "Neutral modelling of agricultural landscapes by tessellation methods—Application for gene flow simulation," Ecological Modelling, Elsevier, vol. 220(24), pages 3536-3545.
    3. Savage, David & Barbetti, Martin J. & MacLeod, William J. & Salam, Moin U. & Renton, Michael, 2011. "Can mechanistically parameterised, anisotropic dispersal kernels provide a reliable estimate of wind-assisted dispersal?," Ecological Modelling, Elsevier, vol. 222(10), pages 1673-1682.
    4. Pitt, Joel P.W. & Kriticos, Darren J. & Dodd, Michael B., 2011. "Temporal limits to simulating the future spread pattern of invasive species: Buddleja davidii in Europe and New Zealand," Ecological Modelling, Elsevier, vol. 222(11), pages 1880-1887.
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    Cited by:

    1. Bellot, Benoit & Poggi, Sylvain & Baudry, Jacques & Bourhis, Yoann & Parisey, Nicolas, 2018. "Inferring ecological processes from population signatures: A simulation-based heuristic for the selection of sampling strategies," Ecological Modelling, Elsevier, vol. 385(C), pages 12-25.
    2. Walker, Adam N. & Poos, Jan-Jaap & Groeneveld, Rolf A., 2015. "Invasive species control in a one-dimensional metapopulation network," Ecological Modelling, Elsevier, vol. 316(C), pages 176-184.

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