Evidence map›Paper›PMID 29581390›Full record

ReviewPhilosophical transactions of the Royal Society of London. Series B, Biological sciences2018

Challenges and solutions for studying collective animal behaviour in the wild.

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

Open access · hybridAbstract readReview
In one paragraph

Review in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
61citing papers in PubMed, 5 pooled it
35.5field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

61 citing papers in PubMed, 5 syntheses or guidelines pooled it, 234 citations in OpenAlex.

  1. Pooled it
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  15. Individual and ecological heterogeneity promote complex communication in social vertebrate group decisions.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Review
  16. Article
  17. Article
  18. Article
  19. Beyond the horizon: immersive developments for animal ecology research.Visual computing for industry, biomedicine, and art · 2023
    Article
  20. Review

1 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 4 institutions in 4 countries.

Lacey F HugheyDepartment of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, CA 93106, USA lacey.hughey@lifesci.ucsb.edu.ORCID 0000-0001-8911-4001
Andrew M HeinSouthwest Fisheries Science Center, National Oceanographic and Atmospheric Administration, Santa Cruz, CA 95060, USA.
Ariana Strandburg-PeshkinDepartment of Migration and Immuno-Ecology, Max Planck Institute for Ornithology, Am Obstberg 1, 78315 Radolfzell, Germany.ORCID 0000-0003-2985-6788
Frants H JensenAarhus Institute of Advanced Studies, Aarhus University, Høegh-Guldbergs Gade 6B, 8000 Aarhus C, Denmark.
Aarhus University · DKUniversity of California, Santa Barbara · USUniversity of California, Santa Cruz · USUniversity of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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'.

Indexed as

Behavior, AnimalMovementAnimalsEcologyEthologySocial Behaviorbio-loggingcollective behaviourcollective motionreality miningremote sensing

Identifiers

PMID29581390
PMCPMC5882975
OpenAlexW2791198558

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.