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Challenges and solutions for studying collective animal behaviour in the wild

Lacey F. Hughey, Andrew M. Hein, Ariana Strandburg-Peshkin, Frants H. Jensen
Published 26 March 2018.DOI: 10.1098/rstb.2017.0005
Lacey F. Hughey
Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, CA 93106, USA
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  • For correspondence: lacey.hughey@lifesci.ucsb.edu
Andrew M. Hein
Southwest Fisheries Science Center, National Oceanographic and Atmospheric Administration, Santa Cruz, CA 95060, USAInstitute of Marine Sciences, University of California Santa Cruz, Santa Cruz, CA 95060, USA
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Ariana Strandburg-Peshkin
Department of Migration and Immuno-Ecology, Max Planck Institute for Ornithology, Am Obstberg 1, 78315 Radolfzell, GermanyDepartment of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurstrasse 190, 8057 Zurich, Switzerland
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Frants H. Jensen
Aarhus Institute of Advanced Studies, Aarhus University, Høegh-Guldbergs Gade 6B, 8000 Aarhus C, DenmarkWoods Hole Oceanographic Institution, Woods Hole, MA 02543, USA
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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.

This article is part of the theme issue ‘Collective movement ecology’.

Footnotes

  • Electronic supplementary material is available online at https://dx.doi.org/10.6084/m9.figshare.c.4001157.

  • One contribution of 16 to a theme issue ‘Collective movement ecology’.

  • Accepted October 15, 2017.
  • © 2018 The Author(s)
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19 May 2018
Volume 373, issue 1746
Philosophical Transactions of the Royal Society B: Biological Sciences: 373 (1746)
  • Table of Contents
Theme issue ‘Collective movement ecology’ compiled and edited by Andrew M. Berdahl, Dora Biro, Peter A.H. Westley and Colin J. Torney

Keywords

collective behaviour
collective motion
remote sensing
bio-logging
reality mining
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Challenges and solutions for studying collective animal behaviour in the wild
Lacey F. Hughey, Andrew M. Hein, Ariana Strandburg-Peshkin, Frants H. Jensen
Phil. Trans. R. Soc. B 2018 373 20170005; DOI: 10.1098/rstb.2017.0005. Published 26 March 2018
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Review article:

Challenges and solutions for studying collective animal behaviour in the wild

Lacey F. Hughey, Andrew M. Hein, Ariana Strandburg-Peshkin, Frants H. Jensen
Phil. Trans. R. Soc. B 2018 373 20170005; DOI: 10.1098/rstb.2017.0005. Published 26 March 2018

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