IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v272y2014icp394-409.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380013004638
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2013.10.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vinatier, F. & Chauvet, M., 2017. "A neutral model for the simulation of linear networks in territories," Ecological Modelling, Elsevier, vol. 363(C), pages 8-16.
    2. Courtois, Pierre & Figuieres, Charles & Mulier, Chloe & Weill, Joakim, 2018. "A Cost–Benefit Approach for Prioritizing Invasive Species," Ecological Economics, Elsevier, vol. 146(C), pages 607-620.
    3. Dalmazzone, Silvana & Giaccaria, Sergio, 2014. "Economic drivers of biological invasions: A worldwide, bio-geographic analysis," Ecological Economics, Elsevier, vol. 105(C), pages 154-165.
    4. Langhammer, Maria & Thober, Jule & Lange, Martin & Frank, Karin & Grimm, Volker, 2019. "Agricultural landscape generators for simulation models: A review of existing solutions and an outline of future directions," Ecological Modelling, Elsevier, vol. 393(C), pages 135-151.
    5. Bourhis, Yoann & Poggi, Sylvain & Mammeri, Youcef & Cortesero, Anne-Marie & Le Ralec, Anne & Parisey, Nicolas, 2015. "Perception-based foraging for competing resources: Assessing pest population dynamics at the landscape scale from heterogeneous resource distribution," Ecological Modelling, Elsevier, vol. 312(C), pages 211-221.
    6. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:272:y:2014:i:c:p:394-409. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.