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Cited by 467

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Dolphin societies: discoveries and puzzles

·1992·Choice Reviews Online

Abstract

Wild dolphins are an elusive subject for behavioral studies: How can you 'do a Jane Goodall' on animals usually visible only as a glimpse of rolling dorsal fins heading for the horizon? In this unusual book, two of the best-known scientists in the marine-mammal field have assembled an astonishing variety of discoveries about dolphins. The contributions range from a graduate student's first paper to senior scientists summarizing a lifetime of research. The dolphins they have studied range from tiny spinners to majestic pilot whales, from killer whales to the familiar bottle-nosed dolphin. The research tactics vary just as widely: the researchers have followed dolphins in boats, tracked them from shore, dived among hundreds of them (plus a few sharks) in tuna fishing nets. They have used computers and airplanes, genetic analysis and artificial language, and learned to read the life history of a dolphin from the cross-section of a single tooth. Pryor and Norris are successful writers as well as scientists; the book is peppered with entertaining essays, by one or both editors, on the intriguing history of dolphin research. Dolphin Societies not only surveys the most interesting recent research on dolphin behavior but also gives lay readers a fascinating look at the scientific mind at work.

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Metadata

Venue
Choice Reviews Online
Published
1992-03-01
Volume
29
Issue
07
Pages
29-3894-29-3894
ISSN
  • 0009-4978 (ISSN-L)
  • 1523-8253
OpenAlex
W1554834153
Cited by
467
References
0
Type
book review
Language
en
Open access
closed

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CoChat. (2026). Citation check: Dolphin societies: discoveries and puzzles. https://app.cochat.ai/papers/10.5860/choice.29-3894
The paper
Dolphin societies: discoveries and puzzles. (1992). Choice Reviews Online. https://doi.org/10.5860/choice.29-3894

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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.