IDEAS home Printed from https://ideas.repec.org/a/nat/nature/v426y2003i6964d10.1038_nature02115.html
   My bibliography  Save this article

Compartments revealed in food-web structure

Author

Listed:
  • Ann E. Krause

    (Educational Psychology, and Special Education, Michigan State University)

  • Kenneth A. Frank

    (Educational Psychology, and Special Education, Michigan State University
    Educational Psychology, and Special Education, Michigan State University)

  • Doran M. Mason

    (NOAA, Great Lakes Environmental Research Laboratory)

  • Robert E. Ulanowicz

    (University of Maryland)

  • William W. Taylor

    (Educational Psychology, and Special Education, Michigan State University)

Abstract

Compartments1 in food webs are subgroups of taxa in which many strong interactions occur within the subgroups and few weak interactions occur between the subgroups2. Theoretically, compartments increase the stability in networks1,2,3,4,5, such as food webs. Compartments have been difficult to detect in empirical food webs because of incompatible approaches6,7,8,9 or insufficient methodological rigour8,10,11. Here we show that a method for detecting compartments from the social networking science12,13,14 identified significant compartments in three of five complex, empirical food webs. Detection of compartments was influenced by food web resolution, such as interactions with weights. Because the method identifies compartmental boundaries in which interactions are concentrated, it is compatible with the definition of compartments. The method is rigorous because it maximizes an explicit function, identifies the number of non-overlapping compartments, assigns membership to compartments, and tests the statistical significance of the results12,13,14. A graphical presentation14 reveals systemic relationships and taxa-specific positions as structured by compartments. From this graphic, we explore two scenarios of disturbance to develop a hypothesis for testing how compartmentalized interactions increase stability in food webs15,16,17.

Suggested Citation

  • Ann E. Krause & Kenneth A. Frank & Doran M. Mason & Robert E. Ulanowicz & William W. Taylor, 2003. "Compartments revealed in food-web structure," Nature, Nature, vol. 426(6964), pages 282-285, November.
    • Handle: RePEc:nat:nature:v:426:y:2003:i:6964:d:10.1038_nature02115
    DOI: 10.1038/nature02115
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/nature02115
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1038/nature02115?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Moujahid, Abdelmalik & d’Anjou, Alicia & Cases, Blanca, 2012. "Community structure in real-world networks from a non-parametrical synchronization-based dynamical approach," Chaos, Solitons & Fractals, Elsevier, vol. 45(9), pages 1171-1179.
    2. Piccardi, Carlo & Calatroni, Lisa & Bertoni, Fabio, 2010. "Communities in Italian corporate networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5247-5258.
    3. Krause, Ann E. & Frank, Ken A. & Jones, Michael L. & Nalepa, Thomas F. & Barbiero, Richard P. & Madenjian, Charles P. & Agy, Megan & Evans, Marlene S. & Taylor, William W. & Mason, Doran M. & Leonard,, 2009. "Adaptations in a hierarchical food web of southeastern Lake Michigan," Ecological Modelling, Elsevier, vol. 220(22), pages 3147-3162.
    4. Hines, David E. & Borrett, Stuart R., 2014. "A comparison of network, neighborhood, and node levels of analyses in two models of nitrogen cycling in the Cape Fear River Estuary," Ecological Modelling, Elsevier, vol. 293(C), pages 210-220.
    5. Franke, R., 2016. "CHIMERA: Top-down model for hierarchical, overlapping and directed cluster structures in directed and weighted complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 384-408.
    6. Chen, Qinghua & Chen, Shenghui, 2007. "A highly clustered scale-free network evolved by random walking," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(2), pages 773-781.
    7. Ali Kharrazi & Brian D. Fath & Harald Katzmair, 2016. "Advancing Empirical Approaches to the Concept of Resilience: A Critical Examination of Panarchy, Ecological Information, and Statistical Evidence," Sustainability, MDPI, vol. 8(9), pages 1-17, September.
    8. David William Shanafelt & Michel Loreau, 2018. "Stability trophic cascades in food chains," Post-Print hal-02097236, HAL.
    9. Selen Onel & Abe Zeid & Sagar Kamarthi, 2011. "The structure and analysis of nanotechnology co-author and citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 119-138, October.
    10. Jordán, Ferenc, 2022. "The network perspective: Vertical connections linking organizational levels," Ecological Modelling, Elsevier, vol. 473(C).
    11. Zetina-Rejón, Manuel J. & Cabrera-Neri, Erika & López-Ibarra, Gladis A. & Arcos-Huitrón, N. Enrique & Christensen, Villy, 2015. "Trophic modeling of the continental shelf ecosystem outside of Tabasco, Mexico: A network and modularity analysis," Ecological Modelling, Elsevier, vol. 313(C), pages 314-324.
    12. Andrea Lancichinetti & Filippo Radicchi & José J Ramasco & Santo Fortunato, 2011. "Finding Statistically Significant Communities in Networks," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-18, April.
    13. Feng, Qing Yi & Chai, Li He, 2008. "A new statistical dynamic analysis on vegetation patterns in land ecosystems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3583-3593.
    14. Chakraborty, Abhijit & Krichene, Hazem & Inoue, Hiroyasu & Fujiwara, Yoshi, 2019. "Characterization of the community structure in a large-scale production network in Japan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 210-221.
    15. Carlo Piccardi, 2011. "Finding and Testing Network Communities by Lumped Markov Chains," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-13, November.
    16. Bogoni, Juliano André & Navarro, Ana Beatriz & Graipel, Maurício Eduardo & Peroni, Nivaldo, 2019. "Modeling the frugivory of a plant with inconstant productivity and solid interaction with relictual vertebrate biota," Ecological Modelling, Elsevier, vol. 408(C), pages 1-1.
    17. Wilhelm, Thomas & Hollunder, Jens, 2007. "Information theoretic description of networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(1), pages 385-396.
    18. Lovato, Ilenia & Pini, Alessia & Stamm, Aymeric & Vantini, Simone, 2020. "Model-free two-sample test for network-valued data," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    19. Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2010. "Complex stock trading network among investors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4929-4941.
    20. González, Cecilia, 2023. "Evolution of the concept of ecological integrity and its study through networks," Ecological Modelling, Elsevier, vol. 476(C).
    21. Miehls, Andrea L. Jaeger & Mason, Doran M. & Frank, Kenneth A. & Krause, Ann E. & Peacor, Scott D. & Taylor, William W., 2009. "Invasive species impacts on ecosystem structure and function: A comparison of the Bay of Quinte, Canada, and Oneida Lake, USA, before and after zebra mussel invasion," Ecological Modelling, Elsevier, vol. 220(22), pages 3182-3193.
    22. Miehls, Andrea L. Jaeger & Mason, Doran M. & Frank, Kenneth A. & Krause, Ann E. & Peacor, Scott D. & Taylor, William W., 2009. "Invasive species impacts on ecosystem structure and function: A comparison of Oneida Lake, New York, USA, before and after zebra mussel invasion," Ecological Modelling, Elsevier, vol. 220(22), pages 3194-3209.
    23. Ying Song & Zhiwen Zheng & Yunmei Shi & Bo Wang, 2023. "GLOD: The Local Greedy Expansion Method for Overlapping Community Detection in Dynamic Provenance Networks," Mathematics, MDPI, vol. 11(15), pages 1-16, July.
    24. Federico Botta & Charo I del Genio, 2017. "Analysis of the communities of an urban mobile phone network," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-14, March.
    25. Wang, Tai-Chi & Phoa, Frederick Kin Hing, 2016. "A scanning method for detecting clustering pattern of both attribute and structure in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 295-309.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:nature:v:426:y:2003:i:6964:d:10.1038_nature02115. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.