IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v280y2014icp89-101.html
   My bibliography  Save this article

Using an individual-based model to select among alternative foraging strategies of woodpigeons: Data support a memory-based model with a flocking mechanism

Author

Listed:
  • Kułakowska, K.A.
  • Kułakowski, T.M.
  • Inglis, I.R.
  • Smith, G.C.
  • Haynes, P.J.
  • Prosser, P.
  • Thorbek, P.
  • Sibly, R.M.

Abstract

Population modelling is increasingly recognised as a useful tool for pesticide risk assessment. For vertebrates that may ingest pesticides with their food, such as woodpigeon (Columba palumbus), population models that simulate foraging behaviour explicitly can help predicting both exposure and population-level impact. Optimal foraging theory is often assumed to explain the individual-level decisions driving distributions of individuals in the field, but it may not adequately predict spatial and temporal characteristics of woodpigeon foraging because of the woodpigeons’ excellent memory, ability to fly long distances, and distinctive flocking behaviour. Here we present an individual-based model (IBM) of the woodpigeon. We used the model to predict distributions of foraging woodpigeons that use one of six alternative foraging strategies: optimal foraging, memory-based foraging and random foraging, each with or without flocking mechanisms. We used pattern-oriented modelling to determine which of the foraging strategies is best able to reproduce observed data patterns. Data used for model evaluation were gathered during a long-term woodpigeon study conducted between 1961 and 2004 and a radiotracking study conducted in 2003 and 2004, both in the UK, and are summarised here as three complex patterns: the distributions of foraging birds between vegetation types during the year, the number of fields visited daily by individuals, and the proportion of fields revisited by them on subsequent days. The model with a memory-based foraging strategy and a flocking mechanism was the only one to reproduce these three data patterns, and the optimal foraging model produced poor matches to all of them. The random foraging strategy reproduced two of the three patterns but was not able to guarantee population persistence. We conclude that with the memory-based foraging strategy including a flocking mechanism our model is realistic enough to estimate the potential exposure of woodpigeons to pesticides. We discuss how exposure can be linked to our model, and how the model could be used for risk assessment of pesticides, for example predicting exposure and effects in heterogeneous landscapes planted seasonally with a variety of crops, while accounting for differences in land use between landscapes.

Suggested Citation

  • Kułakowska, K.A. & Kułakowski, T.M. & Inglis, I.R. & Smith, G.C. & Haynes, P.J. & Prosser, P. & Thorbek, P. & Sibly, R.M., 2014. "Using an individual-based model to select among alternative foraging strategies of woodpigeons: Data support a memory-based model with a flocking mechanism," Ecological Modelling, Elsevier, vol. 280(C), pages 89-101.
  • Handle: RePEc:eee:ecomod:v:280:y:2014:i:c:p:89-101
    DOI: 10.1016/j.ecolmodel.2013.09.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380013004481
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2013.09.019?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.

    Citations

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


    Cited by:

    1. Malishev, Matthew & Kramer-Schadt, Stephanie, 2021. "Movement, models, and metabolism: Individual-based energy budget models as next-generation extensions for predicting animal movement outcomes across scales," Ecological Modelling, Elsevier, vol. 441(C).
    2. Chudzińska, Magda & Ayllón, Daniel & Madsen, Jesper & Nabe-Nielsen, Jacob, 2016. "Discriminating between possible foraging decisions using pattern-oriented modelling: The case of pink-footed geese in Mid-Norway during their spring migration," Ecological Modelling, Elsevier, vol. 320(C), pages 299-315.
    3. van der Vaart, Elske & Johnston, Alice S.A. & Sibly, Richard M., 2016. "Predicting how many animals will be where: How to build, calibrate and evaluate individual-based models," Ecological Modelling, Elsevier, vol. 326(C), pages 113-123.

    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:280:y:2014:i:c:p:89-101. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.