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A dynamic similarity hypothesis for the gaits of quadrupedal mammals

Alexander, R. McN., Jayes, A. S.·1983·Journal of Zoology

Abstract

The dynamic similarity hypothesis postulates that different mammals move in a dynamically similar fashion whenever they travel at speeds that give them equal values of a dimensionless parameter, the Froude number. Thus, given information about one species, it could be possible to predict for others relationships between size, speed and features of gait such as stride length, duty factor, the phase relationships of the feet and the patterns of force exerted on the ground. Data for a diverse sample of mammals have been used to test the hypothesis. It is found to be tenable in many cases when comparisons are confined to quadrupedal mammals of the type described by Jenkins (1971) as “cursorial”. Most mammals of mass greater than 5 kg are of this type. Although the hypothesis applies less successfully to comparisons between cursorial and non‐cursorial mammals it is shown to be a reasonable approximation even for such comparisons and for comparisons between quadrupedal mammals and bipedal mammals and birds.

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Crossref · 10.1111/j.1469-7998.1983.tb04266.x

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Metadata

Authors
Alexander, R. M., & Jayes, A. S.
Venue
Journal of Zoology
Publisher
Wiley
Published
1983-09
Volume
201
Issue
1
Pages
135-152
ISSN
  • 0952-8369 (ISSN-L)
  • 1469-7998
OpenAlex
W2164932599
Cited by
637
References
0
FWCI
5.20
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A dynamic similarity hypothesis for the gaits of quadrupedal mammals. https://app.cochat.ai/papers/10.1111/j.1469-7998.1983.tb04266.x
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Alexander, R. M., & Jayes, A. S. (1983). A dynamic similarity hypothesis for the gaits of quadrupedal mammals. Journal of Zoology. https://doi.org/10.1111/j.1469-7998.1983.tb04266.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.