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THE PHYSIOLOGICAL BASIS OF DIVING TO DEPTH: Birds and Mammals

Kooyman, G. L., Ponganis, P. J.·1998·Annual Review of Physiology

Abstract

▪ Abstract There is wide diversity in the animals that dive to depth and in the distribution of their body oxygen stores. A hallmark of animals diving to depth is a substantial elevation of muscle myoglobin concentration. In deep divers, more than 80% of the oxygen store is in the blood and muscles. How these oxygen stores are managed, particularly within muscle, is unclear. The aerobic endurance of four species has now been measured. These measurements provide a standard for other species in which the limits cannot be measured. Diving to depth requires several adaptations to the effects of pressure. In mammals, one adaptation is lung collapse at shallow depths, which limits absorption of nitrogen. Blood N 2 levels remain below the threshold for decompression sickness. No such adaptive model is known for birds. There appear to be two diving strategies used by animals that dive to depth. Seals, for example, seldom rely on anaerobic metabolism. Birds, on the other hand, frequently rely on anaerobic metabolism to exploit prey-rich depths otherwise unavailable to them.

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Metadata

Authors
Kooyman, G. L., & Ponganis, P. J.
Venue
Annual Review of Physiology
Published
1998-10
Volume
60
Issue
1
Pages
19-32
ISSN
  • 0066-4278 (ISSN-L)
  • 1545-1585
OpenAlex
W2101851266
Cited by
468
References
0
FWCI
2.04
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: THE PHYSIOLOGICAL BASIS OF DIVING TO DEPTH: Birds and Mammals. https://app.cochat.ai/papers/10.1146/annurev.physiol.60.1.19
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Kooyman, G. L., & Ponganis, P. J. (1998). THE PHYSIOLOGICAL BASIS OF DIVING TO DEPTH: Birds and Mammals. Annual Review of Physiology. https://doi.org/10.1146/annurev.physiol.60.1.19

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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.