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Identifying important species: Linking structure and function in ecological networks

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  • Jordán, Ferenc
  • Okey, Thomas A.
  • Bauer, Barbara
  • Libralato, Simone

Abstract

At least two different approaches have been used to quantitatively assess the importance of species in communities. One approach is to derive relatively simple, structural importance indices from network analysis. This assumes that well-connected species are more important. Another approach is to derive functional importance indices using dynamical simulations. We performed both kinds of analysis, and we ranked the species of the Prince William Sound food web based on 13 structural and 5 functional importance indices. We then compared the rank correlation between structural and functional indices. Our results show that different approaches to quantifying importance give different results; unweighted structural indices never correlate significantly with functional ones, but certain weighted structural indices correlate reasonably well with simulated function. This line of research could help in improving our understanding of the usefulness of structural approaches in quantifying the importance of species and understanding biological communities in general. The results strongly indicate the fundamental importance of indirect effects in governing ecosystem dynamics and the need to account for them in structural approaches. Conversely, it generally verifies the usefulness of functional approaches to the investigation of biological communities that account for indirect effects, whether they are modelling or direct empirical studies.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ecomod:v:216:y:2008:i:1:p:75-80
    DOI: 10.1016/j.ecolmodel.2008.04.009
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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.
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    3. Schramski, J.R. & Gattie, D.K. & Patten, B.C. & Borrett, S.R. & Fath, B.D. & Whipple, S.J., 2007. "Indirect effects and distributed control in ecosystems: Distributed control in the environ networks of a seven-compartment model of nitrogen flow in the Neuse River Estuary, USA—Time series analysis," Ecological Modelling, Elsevier, vol. 206(1), pages 18-30.
    4. Whipple, Stuart J. & Borrett, Stuart R. & Patten, Bernard C. & Gattie, David K. & Schramski, John R. & Bata, Seth A., 2007. "Indirect effects and distributed control in ecosystems: Comparative network environ analysis of a seven-compartment model of nitrogen flow in the Neuse River estuary, USA—Time series analysis," Ecological Modelling, Elsevier, vol. 206(1), pages 1-17.
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    1. Almpanidou, Vasiliki & Mazaris, Antonios D. & Mertzanis, Yorgos & Avraam, Ioannis & Antoniou, Ioannis & Pantis, John D. & Sgardelis, Stefanos P., 2014. "Providing insights on habitat connectivity for male brown bears: A combination of habitat suitability and landscape graph-based models," Ecological Modelling, Elsevier, vol. 286(C), pages 37-44.
    2. Navia, Andrés F. & Cortés, Enric & Mejía-Falla, Paola A., 2010. "Topological analysis of the ecological importance of elasmobranch fishes: A food web study on the Gulf of Tortugas, Colombia," Ecological Modelling, Elsevier, vol. 221(24), pages 2918-2926.
    3. Móréh, Ágnes & Endrédi, Anett & Piross, Sándor Imre & Jordán, Ferenc, 2021. "Topology of additive pairwise effects in food webs," Ecological Modelling, Elsevier, vol. 440(C).
    4. 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.
    5. Endrédi, Anett & Senánszky, Vera & Libralato, Simone & Jordán, Ferenc, 2018. "Food web dynamics in trophic hierarchies," Ecological Modelling, Elsevier, vol. 368(C), pages 94-103.
    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. Yang, Xu-Hua & Wang, Bo & Chen, Sheng-Yong & Wang, Wan-Liang, 2012. "Epidemic dynamics behavior in some bus transport networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 917-924.
    8. Losapio, Gianalberto & Jordán, Ferenc & Caccianiga, Marco & Gobbi, Mauro, 2015. "Structure-dynamic relationship of plant–insect networks along a primary succession gradient on a glacier foreland," Ecological Modelling, Elsevier, vol. 314(C), pages 73-79.
    9. Supratim Laha & Soumik Chatterjee & Amlan Das & Barbara Smith & Parthiba Basu, 2022. "Selection of Non-Crop Plant Mixes Informed by Arthropod-Plant Network Analyses for Multiple Ecosystem Services Delivery Towards Ecological Intensification of Agriculture," Sustainability, MDPI, vol. 14(3), pages 1-13, February.
    10. Zhu, Xueting & Mu, Xianzhong & Hu, Guangwen, 2019. "Ecological network analysis of urban energy metabolic system—A case study of Beijing," Ecological Modelling, Elsevier, vol. 404(C), pages 36-45.

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