Consistent predator-prey biomass scaling in complex food webs

Daniel M. Perkins (), Ian A. Hatton (), Benoit Gauzens, Andrew D. Barnes, David Ott, Benjamin Rosenbaum, Catarina Vinagre and Ulrich Brose
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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
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
Catarina Vinagre: Faculdade de Ciências da Universidade de Lisboa
Ulrich Brose: EcoNetLab, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig

Nature Communications, 2022, vol. 13, issue 1, 1-8

Abstract: 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.

Date: 2022
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DOI: 10.1038/s41467-022-32578-5

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