IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-32578-5.html
   My bibliography  Save this article

Consistent predator-prey biomass scaling in complex food webs

Author

Listed:
  • Daniel M. Perkins

    (University of Roehampton)

  • Ian A. Hatton

    (Max Planck Institute for Mathematics in the Sciences)

  • Benoit Gauzens

    (EcoNetLab, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig
    Friedrich Schiller University Jena)

  • Andrew D. Barnes

    (University of Waikato)

  • David Ott

    (Zoological Research Museum Alexander Koenig)

  • Benjamin Rosenbaum

    (EcoNetLab, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig
    Friedrich Schiller University Jena)

  • Catarina Vinagre

    (Faculdade de Ciências da Universidade de Lisboa
    University of Algarve)

  • Ulrich Brose

    (EcoNetLab, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig
    Friedrich Schiller University Jena)

Abstract

The ratio of predator-to-prey biomass is a key element of trophic structure that is typically investigated from a food chain perspective, ignoring channels of energy transfer (e.g. omnivory) that may govern community structure. Here, we address this shortcoming by characterising the biomass structure of 141 freshwater, marine and terrestrial food webs, spanning a broad gradient in community biomass. We test whether sub-linear scaling between predator and prey biomass (a potential signal of density-dependent processes) emerges within ecosystem types and across levels of biological organisation. We find a consistent, sub-linear scaling pattern whereby predator biomass scales with the total biomass of their prey with a near ¾-power exponent within food webs - i.e. more prey biomass supports proportionally less predator biomass. Across food webs, a similar sub-linear scaling pattern emerges between total predator biomass and the combined biomass of all prey within a food web. These general patterns in trophic structure are compatible with a systematic form of density dependence that holds among complex feeding interactions across levels of organization, irrespective of ecosystem type.

Suggested Citation

  • Daniel M. Perkins & Ian A. Hatton & Benoit Gauzens & Andrew D. Barnes & David Ott & Benjamin Rosenbaum & Catarina Vinagre & Ulrich Brose, 2022. "Consistent predator-prey biomass scaling in complex food webs," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-32578-5
    DOI: 10.1038/s41467-022-32578-5
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-32578-5
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-32578-5?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. C. Brock Woodson & John R. Schramski & Samantha B. Joye, 2018. "A unifying theory for top-heavy ecosystem structure in the ocean," Nature Communications, Nature, vol. 9(1), pages 1-8, December.
    2. Benoit Gauzens & Björn C. Rall & Vanessa Mendonça & Catarina Vinagre & Ulrich Brose, 2020. "Biodiversity of intertidal food webs in response to warming across latitudes," Nature Climate Change, Nature, vol. 10(3), pages 264-269, March.
    3. Richard J. Williams & Neo D. Martinez, 2000. "Simple rules yield complex food webs," Nature, Nature, vol. 404(6774), pages 180-183, March.
    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. He, He & Yang, Bo & Hu, Xiaoming, 2016. "Exploring community structure in networks by consensus dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 342-353.
    2. Fath, Brian D. & Halnes, Geir, 2007. "Cyclic energy pathways in ecological food webs," Ecological Modelling, Elsevier, vol. 208(1), pages 17-24.
    3. Jihui Han & Wei Li & Longfeng Zhao & Zhu Su & Yijiang Zou & Weibing Deng, 2017. "Community detection in dynamic networks via adaptive label propagation," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-16, November.
    4. Nonaka, Etsuko & Kuparinen, Anna, 2023. "Limited effects of size-selective harvesting and harvesting-induced life-history changes on the temporal variability of biomass dynamics in complex food webs," Ecological Modelling, Elsevier, vol. 476(C).
    5. Sabine Dritz & Rebecca A. Nelson & Fernanda S. Valdovinos, 2023. "The role of intra-guild indirect interactions in assembling plant-pollinator networks," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    6. Johnson, Jeffrey C. & Luczkovich, Joseph J. & Borgatti, Stephen P. & Snijders, Tom A.B., 2009. "Using social network analysis tools in ecology: Markov process transition models applied to the seasonal trophic network dynamics of the Chesapeake Bay," Ecological Modelling, Elsevier, vol. 220(22), pages 3133-3140.
    7. Giacomini, Henrique Corrêa & De Marco, Paulo & Petrere, Miguel, 2009. "Exploring community assembly through an individual-based model for trophic interactions," Ecological Modelling, Elsevier, vol. 220(1), pages 23-39.
    8. Li, Xiaojia & Li, Menghui & Hu, Yanqing & Di, Zengru & Fan, Ying, 2010. "Detecting community structure from coherent oscillation of excitable systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(1), pages 164-170.
    9. Yoshida, Katsuhiko, 2008. "Evolutionary cause of the vulnerability of insular communities," Ecological Modelling, Elsevier, vol. 210(4), pages 403-413.
    10. Fath, Brian D. & Killian, Megan C., 2007. "The relevance of ecological pyramids in community assemblages," Ecological Modelling, Elsevier, vol. 208(2), pages 286-294.
    11. Sakiyama, Tomoko, 2021. "A power law network in an evolutionary hawk–dove game," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    12. Weiwei Zhang & Jinde Cao & Dingyuan Chen & Ahmed Alsaedi, 2019. "Out Lag Synchronization of Fractional Order Delayed Complex Networks with Coupling Delay via Pinning Control," Complexity, Hindawi, vol. 2019, pages 1-7, August.
    13. Chengyi Tu & Joel Carr & Samir Suweis, 2016. "A data driven network approach to rank countries production diversity and food specialization," Papers 1606.01270, arXiv.org.
    14. Carscallen, W. Mather A. & Romanuk, Tamara N., 2012. "Structure and robustness to species loss in Arctic and Antarctic ice-shelf meta-ecosystem webs," Ecological Modelling, Elsevier, vol. 245(C), pages 208-218.
    15. Fath, Brian D., 2007. "Structural food web regimes," Ecological Modelling, Elsevier, vol. 208(2), pages 391-394.
    16. De Roos, André M. & Schellekens, Tim & Van Kooten, Tobias & Van De Wolfshaar, Karen & Claessen, David & Persson, Lennart, 2008. "Simplifying a physiologically structured population model to a stage-structured biomass model," Theoretical Population Biology, Elsevier, vol. 73(1), pages 47-62.
    17. Richard J. Williams & Neo D. Martinez, 2001. "Stabilization of Chaotic and Non-Permanent Food Web Dynamics," Working Papers 01-07-037, Santa Fe Institute.
    18. Yang, Lixin & Jiang, Jun & Liu, Xiaojun, 2016. "Cluster synchronization in community network with hybrid coupling," Chaos, Solitons & Fractals, Elsevier, vol. 86(C), pages 82-91.
    19. Tiziano Squartini & Guido Caldarelli & Giulio Cimini & Andrea Gabrielli & Diego Garlaschelli, 2018. "Reconstruction methods for networks: the case of economic and financial systems," Papers 1806.06941, arXiv.org.
    20. Alexandridis, Nikolaos & Dambacher, Jeffrey M. & Jean, Fred & Desroy, Nicolas & Bacher, Cédric, 2017. "Qualitative modelling of functional relationships in marine benthic communities," Ecological Modelling, Elsevier, vol. 360(C), pages 300-312.

    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:13:y:2022:i:1:d:10.1038_s41467-022-32578-5. 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.