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High-order species interactions shape ecosystem diversity

Author

Listed:
  • Eyal Bairey

    (Technion—Israel Institute of Technology)

  • Eric D. Kelsic

    (Harvard Medical School
    Present address: Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA.)

  • Roy Kishony

    (Harvard Medical School
    Technion—Israel Institute of Technology)

Abstract

Classical theory shows that large communities are destabilized by random interactions among species pairs, creating an upper bound on ecosystem diversity. However, species interactions often occur in high-order combinations, whereby the interaction between two species is modulated by one or more other species. Here, by simulating the dynamics of communities with random interactions, we find that the classical relationship between diversity and stability is inverted for high-order interactions. More specifically, while a community becomes more sensitive to pairwise interactions as its number of species increases, its sensitivity to three-way interactions remains unchanged, and its sensitivity to four-way interactions actually decreases. Therefore, while pairwise interactions lead to sensitivity to the addition of species, four-way interactions lead to sensitivity to species removal, and their combination creates both a lower and an upper bound on the number of species. These findings highlight the importance of high-order species interactions in determining the diversity of natural ecosystems.

Suggested Citation

  • Eyal Bairey & Eric D. Kelsic & Roy Kishony, 2016. "High-order species interactions shape ecosystem diversity," Nature Communications, Nature, vol. 7(1), pages 1-7, November.
    • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms12285
    DOI: 10.1038/ncomms12285
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    Cited by:

    1. Chen, Shiliang & Liu, Xiang & He, Qiang & Zhou, Shurong, 2022. "Higher-order interactions on disease transmission can reverse the dilution effect or weaken the amplification effect to unimodal pattern," Ecological Modelling, Elsevier, vol. 474(C).
    2. González, Cecilia, 2023. "Evolution of the concept of ecological integrity and its study through networks," Ecological Modelling, Elsevier, vol. 476(C).
    3. Lin Wang & Xi Zhang & Chenwang Tang & Pengcheng Li & Runtao Zhu & Jing Sun & Yunfeng Zhang & Hua Cui & Jiajia Ma & Xinyu Song & Weiwen Zhang & Xiang Gao & Xiaozhou Luo & Lingchong You & Ye Chen & Zhuo, 2022. "Engineering consortia by polymeric microbial swarmbots," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    4. Gerrit Ansmann & Tobias Bollenbach, 2021. "Building clone-consistent ecosystem models," PLOS Computational Biology, Public Library of Science, vol. 17(2), pages 1-25, February.
    5. Papanikolaou, Nikos & Lambiotte, Renaud & Vaccario, Giacomo, 2023. "Fragmentation from group interactions: A higher-order adaptive voter model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    6. Ramasamy, Mohanasubha & Devarajan, Subhasri & Kumarasamy, Suresh & Rajagopal, Karthikeyan, 2022. "Effect of higher-order interactions on synchronization of neuron models with electromagnetic induction," Applied Mathematics and Computation, Elsevier, vol. 434(C).
    7. Alicia Sanchez-Gorostiaga & Djordje Bajić & Melisa L Osborne & Juan F Poyatos & Alvaro Sanchez, 2019. "High-order interactions distort the functional landscape of microbial consortia," PLOS Biology, Public Library of Science, vol. 17(12), pages 1-34, December.

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