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Published VersionCC BY V4.0, Open Access
Journal article
Dynamic similarity and the peculiar allometry of maximum running speed
Nature Communications, Vol.15, pp.1-11
2024
PMID: 38467620
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Abstract
Animal performance fundamentally influences behaviour, ecology, and evolution. It typically varies monotonously with size. A notable exception is maximum running speed; the fastest animals are of intermediate size. Here we show that this peculiar allometry results from the competition between two musculoskeletal constraints: the kinetic energy capacity, which dominates in small animals, and the work capacity, which reigns supreme in large animals. The ratio of both capacities defines the physiological similarity index Γ, a dimensionless number akin to the Reynolds number in fluid mechanics. The scaling of Γ indicates a transition from a dominance of muscle forces to a dominance of inertial forces as animals grow in size; its magnitude defines conditions of "dynamic similarity" that enable comparison and estimates of locomotor performance across extant and extinct animals; and the physical parameters that define it highlight opportunities for adaptations in musculoskeletal "design" that depart from the eternal null hypothesis of geometric similarity. The physiological similarity index challenges the Froude number as prevailing dynamic similarity condition, reveals that the differential growth of muscle and weight forces central to classic scaling theory is of secondary importance for the majority of terrestrial animals, and suggests avenues for comparative analyses of locomotor systems.
Details
- Title
- Dynamic similarity and the peculiar allometry of maximum running speed
- Authors
- David Labonte (Corresponding Author) - Imperial College LondonPeter J Bishop - Harvard UniversityTaylor J M Dick - The University of QueenslandChristofer J Clemente - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
- Publication details
- Nature Communications, Vol.15, pp.1-11
- Publisher
- Nature Publishing Group
- Date published
- 2024
- DOI
- 10.1038/s41467-024-46269-w
- ISSN
- 2041-1723
- PMID
- 38467620
- Copyright note
- This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
- Data Availability
- All Source data are provided as a Source Data file. Source data are provided with this paper.
- Organisation Unit
- School of Science and Engineering - Legacy; School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991007470602621
- Output Type
- Journal article
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