Challenges and solutions for studying collective animal behaviour in the wild

被引:103
|
作者
Hughey, Lacey F. [1 ]
Hein, Andrew M. [2 ,3 ]
Strandburg-Peshkin, Ariana [4 ,5 ]
Jensen, Frants H. [6 ,7 ]
机构
[1] Univ Calif Santa Barbara, Dept Ecol Evolut & Marine Biol, Santa Barbara, CA 93106 USA
[2] NOAA, Southwest Fisheries Sci Ctr, Santa Cruz, CA 95060 USA
[3] Univ Calif Santa Cruz, Inst Marine Sci, Santa Cruz, CA 95060 USA
[4] Max Planck Inst Ornithol, Dept Migrat & Immunoecol, Obstberg 1, D-78315 Radolfzell am Bodensee, Germany
[5] Univ Zurich, Dept Evolutionary Biol & Environm Studies, Winterthurstr 190, CH-8057 Zurich, Switzerland
[6] Aarhus Univ, Aarhus Inst Adv Studies, Hoegh Guldbergs Gade 6B, DK-8000 Aarhus C, Denmark
[7] Woods Hole Oceanog Inst, Woods Hole, MA 02543 USA
基金
美国国家科学基金会;
关键词
collective behaviour; collective motion; remote sensing; bio-logging; reality mining; FINNED PILOT WHALES; DECISION-MAKING; DYNAMICS; TRACKING; RULES; ACCELERATION; COORDINATION; DISTURBANCE; KINEMATICS; MIGRATION;
D O I
10.1098/rstb.2017.0005
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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'.
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页数:13
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