IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v410y2019ic10.html
   My bibliography  Save this article

Modelling annual grass weed seed dispersal in winter wheat, when influenced by hedges and directional wind

Author

Listed:
  • Somerville, Gayle. J.
  • Melander, Bo
  • Kudsk, Per
  • Mathiassen, Solvejg K

Abstract

Accurate predictions of weed seed dispersal are important for spatial modelling of weed population dynamics. However there are few multi-year data sets available, and they are seldom analysed well. Here we gathered together and re-examined population growth and seed spread data from three grass weed species over 3 years. Using a new seed spread function in the simulation model SOMER it was possible to accurately parametrise population growth and seed spread to replicate the field data of Apera spica-venti (APESV) and Bromus sterilis (BROST). In contrast, the greatest increases in Alopecurus myosuroides (ALOMY) numbers occurred in the direction of machinery movement, which could not be predicted using this function. A probability-sum, exponential-type function gave an excellent fit to the field data for APESV and BROST, with changes in seed spread distances due to species differences, wind, and ‘shading’ from the hedge, accommodated by alterations in the scale, shape, and wind dispersal parameters. Here we describe a method of parametrising the probability function from within a stochastic simulation. Working within the simulation allowed empirical population size data sets to be successfully parameterised, without mathematical integration. This function is fully explained with stochastic simulated examples, and fitted to various two-dimensional longitudinal data sets. Enough detail to enable its parametrisation (including simplification) within a majority of spatial stochastic population models is included.

Suggested Citation

  • Somerville, Gayle. J. & Melander, Bo & Kudsk, Per & Mathiassen, Solvejg K, 2019. "Modelling annual grass weed seed dispersal in winter wheat, when influenced by hedges and directional wind," Ecological Modelling, Elsevier, vol. 410(C), pages 1-1.
    • Handle: RePEc:eee:ecomod:v:410:y:2019:i:c:10
    DOI: 10.1016/j.ecolmodel.2019.108729
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380019302297
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2019.108729?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. Sagnard, Fabrice & Pichot, Christian & Dreyfus, Philippe & Jordano, Pedro & Fady, Bruno, 2007. "Modelling seed dispersal to predict seedling recruitment: Recolonization dynamics in a plantation forest," Ecological Modelling, Elsevier, vol. 203(3), pages 464-474.
    2. Wang, Jihuai & Christensen, Svend & Hansen, Preben Klarskov, 2008. "A method for building spatial model of annual weed seed dispersal from experimental data and its application to simulating Bromus sterilis population dispersal," Ecological Modelling, Elsevier, vol. 210(4), pages 446-452.
    3. Somerville, Gayle J. & Powles, Stephen B. & Walsh, Michael J. & Renton, Michael, 2017. "How do spatial heterogeneity and dispersal in weed population models affect predictions of herbicide resistance evolution?," Ecological Modelling, Elsevier, vol. 362(C), pages 37-53.
    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. Goddard, K.A. & Craig, K.J. & Schoombie, J. & le Roux, P.C., 2022. "Investigation of ecologically relevant wind patterns on Marion Island using Computational Fluid Dynamics and measured data," Ecological Modelling, Elsevier, vol. 464(C).

    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. Maximilian Axer & Robert Schlicht & Rico Kronenberg & Sven Wagner, 2021. "The Potential for Future Shifts in Tree Species Distribution Provided by Dispersal and Ecological Niches: A Comparison between Beech and Oak in Europe," Sustainability, MDPI, vol. 13(23), pages 1-20, November.
    2. Manso, Rubén & Pardos, Marta & Keyes, Christopher R. & Calama, Rafael, 2012. "Modelling the spatio-temporal pattern of primary dispersal in stone pine (Pinus pinea L.) stands in the Northern Plateau (Spain)," Ecological Modelling, Elsevier, vol. 226(C), pages 11-21.
    3. Kolmanič, Simon & Guid, Nikola & Diaci, Jurij, 2014. "ForestMAS – A single tree based secondary succession model employing Ellenberg indicator values," Ecological Modelling, Elsevier, vol. 279(C), pages 100-113.
    4. Wallentin, Gudrun & Tappeiner, Ulrike & Strobl, Josef & Tasser, Erich, 2008. "Understanding alpine tree line dynamics: An individual-based model," Ecological Modelling, Elsevier, vol. 218(3), pages 235-246.
    5. Nanos, Nikos & Larson, Kajsa & Millerón, Matias & Sjöstedt-de Luna, Sara, 2010. "Inverse modeling for effective dispersal: Do we need tree size to estimate fecundity?," Ecological Modelling, Elsevier, vol. 221(20), pages 2415-2424.
    6. Wang, Wenhui & Xu, Feng & Huang, Yunxin & Feng, Hongqiang & Wan, Peng, 2022. "Modeling the evolution of resistance in cotton bollworm to concurrently planted Bt cotton and Bt maize in China," Ecological Modelling, Elsevier, vol. 467(C).
    7. Mateusz Malarczyk & Seiichiro Katsura & Marcin Kaminski & Krzysztof Szabat, 2024. "A Novel Meta-Heuristic Algorithm Based on Birch Succession in the Optimization of an Electric Drive with a Flexible Shaft," Energies, MDPI, vol. 17(16), pages 1-34, August.

    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:410:y:2019:i:c:10. 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.