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Using body size to understand the structural design of animals: quadrupedal locomotion

McMahon, T. A.·1975·Journal of Applied Physiology

Abstract

Many parameters of gait and performance, including stride frequency, stride length, maximum speed, and rate of O2 uptake are experimentally found to be power-law functions of body weight in running quadrupeds. All of these parameters are reasonably easy to measure except maximum speed, where the question arises whether one means top sprinting speed or top speed for sustained running. Moreover, differences in training and motivation make comparisons of top speed difficult. The problem is circumvented by comparing animals running at the transition between trotting and galloping, a physiologically similar speed. Theoretical models are proposed which preserve either geometric similarity, elastic similarity, or static stress similarity between animals of large and small body weights. The model postulating elastic similarity provides the best correlation with published data on body and bone proportions, body surface area, resting metabolic rate, and basal heart and lung frequencies. It also makes the most successful prediction of stride frequency, stride length, limb excursion angles, and the metabolic power required for running at the trot-gallop transition in quadrupeds ranging in size from mice to horses.

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Metadata

Authors
McMahon, T. A.
Venue
Journal of Applied Physiology
Published
1975-10-01
Volume
39
Issue
4
Pages
619-627
ISSN
  • 0161-7567 (ISSN-L)
  • 8750-7587
  • 1522-1601
OpenAlex
W1806025462
Cited by
440
References
0
FWCI
6.26
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Using body size to understand the structural design of animals: quadrupedal locomotion. https://app.cochat.ai/papers/10.1152/jappl.1975.39.4.619
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McMahon, T. A. (1975). Using body size to understand the structural design of animals: quadrupedal locomotion. Journal of Applied Physiology. https://doi.org/10.1152/jappl.1975.39.4.619

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.