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Information content in pollination network reveals missing interactions

Author

Listed:
  • Stock, Michiel
  • Piot, Niels
  • Vanbesien, Sarah
  • Vaissière, Bernard
  • Coiffait-Gombault, Clémentine
  • Smagghe, Guy
  • De Baets, Bernard

Abstract

Network analysis is an indispensable part of ecological studies. Specifically, networks have played a pivotal role in studying the diversity, dynamics and functionality of pollination systems. Recording plant-pollinator interaction networks is a laborious task, prone to missing or false negative interactions. Several methods enable the assessment of sampling completeness of the network with the use of species accumulation curves or Chao estimators. However, these methods do not provide a way to identify which interactions might be missed in the field. Methods that enable a more directed and focused field sampling are needed. Such methods would greatly benefit plant-pollinator studies and network studies in general.

Suggested Citation

  • Stock, Michiel & Piot, Niels & Vanbesien, Sarah & Vaissière, Bernard & Coiffait-Gombault, Clémentine & Smagghe, Guy & De Baets, Bernard, 2020. "Information content in pollination network reveals missing interactions," Ecological Modelling, Elsevier, vol. 431(C).
    • Handle: RePEc:eee:ecomod:v:431:y:2020:i:c:s0304380020302325
    DOI: 10.1016/j.ecolmodel.2020.109161
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    References listed on IDEAS

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    1. Kallimanis, A.S. & Petanidou, T. & Tzanopoulos, J. & Pantis, J.D. & Sgardelis, S.P., 2009. "Do plant–pollinator interaction networks result from stochastic processes?," Ecological Modelling, Elsevier, vol. 220(5), pages 684-693.
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    Cited by:

    1. Stock, Michiel & Piot, Niels & Vanbesien, Sarah & Meys, Joris & Smagghe, Guy & De Baets, Bernard, 2021. "Pairwise learning for predicting pollination interactions based on traits and phylogeny," Ecological Modelling, Elsevier, vol. 451(C).

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