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Analysis of time series data on agroecosystem vegetation using predictive clustering trees

Author

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  • Debeljak, Marko
  • Squire, Geoffrey R.
  • Kocev, Dragi
  • Hawes, Cathy
  • Young, Mark W.
  • Džeroski, Sašo

Abstract

We present an approach to modelling interdependent types of vegetation that support different functions in a managed ecosystem. For optimal management, plants that provide economic output (e.g., crops) and those that support ecological functions (e.g., wild plants or ‘weeds’) should coexist in an agroecosystem. To make progress with understanding how such plant communities interact over time, we analyse paired time series data about the cover of crop and weed vegetation in oilseed rape fields. The percentage crop and weed cover were measured every 7–14 days at 128 sites in the UK, covering a wide range of localities and management regimes.

Suggested Citation

  • Debeljak, Marko & Squire, Geoffrey R. & Kocev, Dragi & Hawes, Cathy & Young, Mark W. & Džeroski, Sašo, 2011. "Analysis of time series data on agroecosystem vegetation using predictive clustering trees," Ecological Modelling, Elsevier, vol. 222(14), pages 2524-2529.
    • Handle: RePEc:eee:ecomod:v:222:y:2011:i:14:p:2524-2529
    DOI: 10.1016/j.ecolmodel.2010.10.021
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    References listed on IDEAS

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    1. Debeljak, Marko & Squire, Geoff R. & Demšar, Damjan & Young, Mark W. & Džeroski, Sašo, 2008. "Relations between the oilseed rape volunteer seedbank, and soil factors, weed functional groups and geographical location in the UK," Ecological Modelling, Elsevier, vol. 212(1), pages 138-146.
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    Cited by:

    1. Coro, Gianpaolo & Webb, Thomas J. & Appeltans, Ward & Bailly, Nicolas & Cattrijsse, André & Pagano, Pasquale, 2015. "Classifying degrees of species commonness: North Sea fish as a case study," Ecological Modelling, Elsevier, vol. 312(C), pages 272-280.

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