Challenges and solutions for studying collective animal behaviour in the wild

Lacey F. Hughey, Andrew M. Hein, Ariana Strandburg-Peshkin, Frants H. Jensen

Research output: Contribution to journalReview articlepeer-review

106 Scopus citations

Abstract

Mobile animal groups provide some of the most compelling examples of self-organization in the natural world. While field observations of songbird flocks wheeling in the sky or anchovy schools fleeing from predators have inspired considerable interest in the mechanics of collective motion, the challenge of simultaneously monitoring multiple animals in the field has historically limited our capacity to study collective behaviour of wild animal groups with precision. However, recent technological advancements now present exciting opportunities to overcome many of these limitations. Here we review existing methods used to collect data on the movements and interactions of multiple animals in a natural setting. We then survey emerging technologies that are poised to revolutionize the study of collective animal behaviour by extending the spatial and temporal scales of inquiry, increasing data volume and quality, and expediting the post-processing of raw data.

Original languageEnglish (US)
Article number20170005
JournalPhilosophical Transactions of the Royal Society B: Biological Sciences
Volume373
Issue number1746
DOIs
StatePublished - May 19 2018
Externally publishedYes

Keywords

  • Bio-logging
  • Collective behaviour
  • Collective motion
  • Reality mining
  • Remote sensing

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology
  • General Agricultural and Biological Sciences

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