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Aggregation of incomplete food web data may help to suggest sampling strategies

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  • Patonai, Katalin
  • Jordán, Ferenc

Abstract

Aggregation of data and incomplete sampling are two notoriuos problems of food web research. We suggest to look at them in parallel since their effects are interdependent. Different aggregation methods are not equally sensitive to missing data and they lead to different biases in describing food web structure. In this paper, we construct a low-quality food web of Lake Balaton (based only on high-quality literature), aggregate it in several ways, compare the different versions of the food web by network analysis and discuss how the results can help future sampling, field work and data management. We identify groups where resolution or aggregation should be increased.

Suggested Citation

  • Patonai, Katalin & Jordán, Ferenc, 2017. "Aggregation of incomplete food web data may help to suggest sampling strategies," Ecological Modelling, Elsevier, vol. 352(C), pages 77-89.
    • Handle: RePEc:eee:ecomod:v:352:y:2017:i:c:p:77-89
    DOI: 10.1016/j.ecolmodel.2017.02.024
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    References listed on IDEAS

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    1. Jordán, Ferenc & Liu, Wei-chung & Mike, Ágnes, 2009. "Trophic field overlap: A new approach to quantify keystone species," Ecological Modelling, Elsevier, vol. 220(21), pages 2899-2907.
    2. Everett, Martin G. & Borgatti, Steve, 1991. "Role colouring a graph," Mathematical Social Sciences, Elsevier, vol. 21(2), pages 183-188, April.
    3. Lai, Shu-mei & Liu, Wei-chung & Jordán, Ferenc, 2015. "A trophic overlap-based measure for species uniqueness in ecological networks," Ecological Modelling, Elsevier, vol. 299(C), pages 95-101.
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    1. Ferenc Jordán & Anett Endrédi & Wei-chung Liu & Domenico D’Alelio, 2018. "Aggregating a Plankton Food Web: Mathematical versus Biological Approaches," Mathematics, MDPI, vol. 6(12), pages 1-14, December.

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