IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v16y2025i1d10.1038_s41467-025-61248-5.html
   My bibliography  Save this article

Bimodality in subaqueous dune height suggests flickering behavior at high flow

Author

Listed:
  • Sjoukje I. Lange

    (Wageningen University & Research
    HKV Lijn in Water)

  • Roeland C. Vijsel

    (Wageningen University & Research)

  • Paul J. J. F. Torfs

    (Independent researcher)

  • Nick P. Wallerstein

    (Wageningen University & Research)

  • Antonius J. F. Hoitink

    (Wageningen University & Research)

Abstract

River bedforms influence fluvial hydraulics by altering bed roughness. With increasing flow velocity, the sand-bedded river transitions from a flat bed to ripples, dunes, and an upper stage plane bed. Although prior research notes increased bedform height variation with flow strength and rapid shifts between bed configurations, the latter remains understudied. Here, we reveal flickering between low and high dune heights for transport stages exceeding 18, based on data from earlier experiments and a complementary experiment. Above this transport stage, the second mode in the dune height distributions becomes increasingly distinctive, suggesting a critical transition. The emergence of the second mode is potentially triggered by temporal changes in suspended sediment concentration impacting turbulence, or might result from dune kinematics enabling larger dunes to grow and persist longer. This flickering behavior challenges the adequacy of a single snapshot to capture the system’s bed geometry, impacting field measurements and experimental designs, and questions a classical equilibrium equation in geomorphology. Our study calls for further research to understand and quantify flickering behavior in sediment beds at high transport stages.

Suggested Citation

  • Sjoukje I. Lange & Roeland C. Vijsel & Paul J. J. F. Torfs & Nick P. Wallerstein & Antonius J. F. Hoitink, 2025. "Bimodality in subaqueous dune height suggests flickering behavior at high flow," Nature Communications, Nature, vol. 16(1), pages 1-9, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-61248-5
    DOI: 10.1038/s41467-025-61248-5
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-025-61248-5
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-025-61248-5?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
    ---><---

    References listed on IDEAS

    as
    1. Vasilis Dakos & Stephen R Carpenter & William A Brock & Aaron M Ellison & Vishwesha Guttal & Anthony R Ives & Sonia Kéfi & Valerie Livina & David A Seekell & Egbert H van Nes & Marten Scheffer, 2012. "Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-20, July.
    2. Marten Scheffer & Jordi Bascompte & William A. Brock & Victor Brovkin & Stephen R. Carpenter & Vasilis Dakos & Hermann Held & Egbert H. van Nes & Max Rietkerk & George Sugihara, 2009. "Early-warning signals for critical transitions," Nature, Nature, vol. 461(7260), pages 53-59, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. James J Elser & Timothy J Elser & Stephen R Carpenter & William A Brock, 2014. "Regime Shift in Fertilizer Commodities Indicates More Turbulence Ahead for Food Security," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-7, May.
    2. Katherine A Spielmann & Matthew A Peeples & Donna M Glowacki & Andrew Dugmore, 2016. "Early Warning Signals of Social Transformation: A Case Study from the US Southwest," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-18, October.
    3. Bian, Junhao & Huang, Tao & Zhang, Xu & Wang, Chunping & Zhang, Yongwen & Zeng, Chunhua, 2025. "Fluctuation-variable correlation as early warning signals of non-equilibrium critical transitions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 661(C).
    4. Alessandro Spelta, 2016. "Stock prices prediction via tensor decomposition and links forecast," DISCE - Working Papers del Dipartimento di Economia e Finanza def041, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    5. Yang, Anji & Wang, Hao & Yuan, Sanling, 2023. "Tipping time in a stochastic Leslie predator–prey model," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    6. Georg Jäger & Manfred Füllsack, 2019. "Systematically false positives in early warning signal analysis," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-14, February.
    7. Martin Heßler & Oliver Kamps, 2025. "Quantifying local stability and noise levels from time series in the US Western Interconnection blackout on 10th August 1996," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    8. Beatriz Arellano-Nava & Paul R. Halloran & Chris A. Boulton & James Scourse & Paul G. Butler & David J. Reynolds & Timothy M. Lenton, 2022. "Destabilisation of the Subpolar North Atlantic prior to the Little Ice Age," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    9. Mathias, Jean-Denis & Deffuant, Guillaume & Brias, Antoine, 2024. "From tipping point to tipping set: Extending the concept of regime shift to uncertain dynamics for real-world applications," Ecological Modelling, Elsevier, vol. 496(C).
    10. Navid Moghadam, Nastaran & Nazarimehr, Fahimeh & Jafari, Sajad & Sprott, Julien C., 2020. "Studying the performance of critical slowing down indicators in a biological system with a period-doubling route to chaos," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 544(C).
    11. repec:plo:pone00:0101014 is not listed on IDEAS
    12. Naoki Masuda & Kazuyuki Aihara & Neil G. MacLaren, 2024. "Anticipating regime shifts by mixing early warning signals from different nodes," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    13. Richter, Andries & Dakos, Vasilis, 2015. "Profit fluctuations signal eroding resilience of natural resources," Ecological Economics, Elsevier, vol. 117(C), pages 12-21.
    14. Karimi Rahjerdi, Bahareh & Ramamoorthy, Ramesh & Nazarimehr, Fahimeh & Rajagopal, Karthikeyan & Jafari, Sajad, 2022. "Indicating the synchronization bifurcation points using the early warning signals in two case studies: Continuous and explosive synchronization," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    15. Manfred Füllsack & Daniel Reisinger & Marie Kapeller & Georg Jäger, 2022. "Early warning signals from the periphery," Journal of Computational Social Science, Springer, vol. 5(1), pages 665-685, May.
    16. Andrew R. Tilman & Elisabeth H. Krueger & Lisa C. McManus & James R. Watson, 2023. "Maintaining human wellbeing as socio-environmental systems undergo regime shifts," Papers 2309.04578, arXiv.org.
    17. Haoyu Wen & Massimo Pica Ciamarra & Siew Ann Cheong, 2018. "How one might miss early warning signals of critical transitions in time series data: A systematic study of two major currency pairs," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-22, March.
    18. William A Brock & Stephen R Carpenter, 2012. "Early Warnings of Regime Shift When the Ecosystem Structure Is Unknown," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-10, September.
    19. Tatiana Baumuratova & Simona Dobre & Thierry Bastogne & Thomas Sauter, 2013. "Switch of Sensitivity Dynamics Revealed with DyGloSA Toolbox for Dynamical Global Sensitivity Analysis as an Early Warning for System's Critical Transition," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-12, December.
    20. Irina Alchinova & Mikhail Karganov, 2021. "Physiological Balance of the Body: Theory, Algorithms, and Results," Mathematics, MDPI, vol. 9(3), pages 1-8, January.
    21. Spelta, A. & Flori, A. & Pecora, N. & Pammolli, F., 2021. "Financial crises: Uncovering self-organized patterns and predicting stock markets instability," Journal of Business Research, Elsevier, vol. 129(C), pages 736-756.

    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:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-61248-5. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.