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Fluctuating interaction network and time-varying stability of a natural fish community

Author

Listed:
  • Masayuki Ushio

    (Faculty of Science and Technology, Ryukoku University
    Joint Research Center for Science and Technology, Ryukoku University
    Center for Ecological Research, Kyoto University
    PRESTO, Japan Science and Technology Agency)

  • Chih-hao Hsieh

    (Institute of Ecology and Evolutionary Biology, National Taiwan University
    Taiwan International Graduate Program (TIGP)–Earth System Science Program, Academia Sinica and National Central University
    National Center for Theoretical Science)

  • Reiji Masuda

    (Maizuru Fisheries Research Station, Field Science Education and Research Center, Kyoto University)

  • Ethan R Deyle

    (Scripps Institution of Oceanography, University of California at San Diego)

  • Hao Ye

    (Scripps Institution of Oceanography, University of California at San Diego
    University of Florida)

  • Chun-Wei Chang

    (Taiwan International Graduate Program (TIGP)–Earth System Science Program, Academia Sinica and National Central University)

  • George Sugihara

    (Scripps Institution of Oceanography, University of California at San Diego)

  • Michio Kondoh

    (Faculty of Science and Technology, Ryukoku University)

Abstract

A method for modelling time-varying dynamic stability in a natural marine fish community finds that seasonal patterns in community stability are driven by species diversity and interspecific interactions.

Suggested Citation

  • Masayuki Ushio & Chih-hao Hsieh & Reiji Masuda & Ethan R Deyle & Hao Ye & Chun-Wei Chang & George Sugihara & Michio Kondoh, 2018. "Fluctuating interaction network and time-varying stability of a natural fish community," Nature, Nature, vol. 554(7692), pages 360-363, February.
    • Handle: RePEc:nat:nature:v:554:y:2018:i:7692:d:10.1038_nature25504
    DOI: 10.1038/nature25504
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    Cited by:

    1. Duncan A. O’Brien & Smita Deb & Gideon Gal & Stephen J. Thackeray & Partha S. Dutta & Shin-ichiro S. Matsuzaki & Linda May & Christopher F. Clements, 2023. "Early warning signals have limited applicability to empirical lake data," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    2. Chao Liang & Yanran Hong & Luu Duc Toan Huynh & Feng Ma, 2023. "Asymmetric dynamic risk transmission between financial stress and monetary policy uncertainty: thinking in the post-covid-19 world," Review of Quantitative Finance and Accounting, Springer, vol. 60(4), pages 1543-1567, May.
    3. Fang Guo & Pei Zhang & Vivian Do & Jakob Runge & Kun Zhang & Zheshen Han & Shenxi Deng & Hongli Lin & Sheikh Taslim Ali & Ruchong Chen & Yuming Guo & Linwei Tian, 2024. "Ozone as an environmental driver of influenza," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    4. Qinghua Zhao & Paul J. Brink & Chi Xu & Shaopeng Wang & Adam T. Clark & Canan Karakoç & George Sugihara & Claire E. Widdicombe & Angus Atkinson & Shin-ichiro S. Matsuzaki & Ryuichiro Shinohara & Shuiq, 2023. "Relationships of temperature and biodiversity with stability of natural aquatic food webs," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    5. Samuel R Bray & Bo Wang, 2020. "Forecasting unprecedented ecological fluctuations," PLOS Computational Biology, Public Library of Science, vol. 16(6), pages 1-17, June.
    6. Johnson, Bethany & Munch, Stephan B., 2022. "An empirical dynamic modeling framework for missing or irregular samples," Ecological Modelling, Elsevier, vol. 468(C).

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