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Trophic field overlap: A new approach to quantify keystone species

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  • Jordán, Ferenc
  • Liu, Wei-chung
  • Mike, Ágnes

Abstract

It is a current challenge to better understand the relative importance of species in ecosystems, and the network perspective is able to offer quantitative tools for this. It is plausible to assume, in general, that well-linked species, being key interactors, are also more important for the community. Recently a number of methods have been suggested for quantifying the network position of species in ecological networks (like the topological importance metric, TI). Most of them are based on node centrality indices and it may happen that the two most important species in a food web have very similar interaction structure and they can essentially replace each other if one becomes extinct. For conservation considerations it is a challenge to identify species that are richly connected and, at the same time, have a relatively unique and irreplaceable interaction pattern. We present a new method and illustrate our approach by using the Kuosheng Bay trophic network in Taiwan. The new method is based on the interaction matrix, where the strength of the interaction between nodes i and j depends only on topology. By defining a threshold separating weak and strong interactors, we define the effective range of interactions for each graph node. If the overlaps between pairs of these ranges are quantified, we gain a metric expressing how unique is the interaction pattern of a focal node (TO). The combination of centrality (TI) and uniqueness (TO) is called topological functionality (TF). We compare the nodal importance rank provided by this metric to others based on a variety of centrality measures. The main conclusion is that shrimps seem to have the most unique interaction pattern despite that their structural importance has been underestimated by all conventional centrality indices. Also, our network analysis suggests that fisheries disturb the ecosystem in a more critical network position than the impingement by the local power plant.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ecomod:v:220:y:2009:i:21:p:2899-2907
    DOI: 10.1016/j.ecolmodel.2008.12.003
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    References listed on IDEAS

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    1. Jordán, Ferenc & Benedek, Zsófia & Podani, János, 2007. "Quantifying positional importance in food webs: A comparison of centrality indices," Ecological Modelling, Elsevier, vol. 205(1), pages 270-275.
    2. Jordán, Ferenc & Okey, Thomas A. & Bauer, Barbara & Libralato, Simone, 2008. "Identifying important species: Linking structure and function in ecological networks," Ecological Modelling, Elsevier, vol. 216(1), pages 75-80.
    3. Stephen P. Borgatti, 2006. "Identifying sets of key players in a social network," Computational and Mathematical Organization Theory, Springer, vol. 12(1), pages 21-34, April.
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    Cited by:

    1. Liu, Wei-Chung & Chen, Hsuan-Wien & Tsai, Tsung-Hsi & Hwang, Hsien-Kuei, 2012. "A fish tank model for assembling food webs," Ecological Modelling, Elsevier, vol. 245(C), pages 166-175.
    2. 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.
    3. Jordán, Ferenc, 2022. "The network perspective: Vertical connections linking organizational levels," Ecological Modelling, Elsevier, vol. 473(C).
    4. Pier Francesco Moretti & Domenico D’Alelio & Aldo Drago & Jaime Pitarch & Patrick Roose & Isa Schön & Mario Sprovieri & Federico Falcini, 2024. "A Process-Based Approach to Guide the Observational Strategies for the Assessment of the Marine Environment," Sustainability, MDPI, vol. 16(19), pages 1-18, September.
    5. Móréh, Ágnes & Endrédi, Anett & Piross, Sándor Imre & Jordán, Ferenc, 2021. "Topology of additive pairwise effects in food webs," Ecological Modelling, Elsevier, vol. 440(C).
    6. Torres-Alruiz, Maria Daniela & Rodríguez, Diego J., 2013. "A topo-dynamical perspective to evaluate indirect interactions in trophic webs: New indexes," Ecological Modelling, Elsevier, vol. 250(C), pages 363-369.
    7. 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.
    8. Navia, Andrés Felipe & Cruz-Escalona, Víctor Hugo & Giraldo, Alan & Barausse, Alberto, 2016. "The structure of a marine tropical food web, and its implications for ecosystem-based fisheries management," Ecological Modelling, Elsevier, vol. 328(C), pages 23-33.
    9. 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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