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Journal article

Classifying elephant behaviour through seismic vibrations

Abstract:
Seismic waves — vibrations within and along the Earth’s surface — are ubiquitous sources of information. During propagation, physical factors can obscure information transfer via vibrations and influence propagation range [1]. Here, we explore how terrain type and background seismic noise influence the propagation of seismic vibrations generated by African elephants. In Kenya, we recorded the ground-based vibrations of different wild elephant behaviours, such as locomotion and infrasonic vocalisations [2], as well as natural and anthropogenic seismic noise. We employed techniques from seismology to transform the geophone recordings into source functions — the time-varying seismic signature generated at the source. We used computer modelling to constrain the propagation ranges of elephant seismic vibrations for different terrains and noise levels. Behaviours that generate a high force on a sandy terrain with low noise propagate the furthest, over the kilometre scale. Our modelling also predicts that specific elephant behaviours can be distinguished and monitored over a range of propagation distances and noise levels. We conclude that seismic cues have considerable potential for both behavioural classification and remote monitoring of wildlife. In particular, classifying the seismic signatures of specific behaviours of large mammals remotely in real time, such as elephant running, could inform on poaching threats.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.cub.2018.03.062

Authors

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Zoology
Oxford college:
Jesus College
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Earth Sciences
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Earth Sciences
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Earth Sciences
Role:
Author


More from this funder
Funding agency for:
Koelemeijer, P
Grant:
641943
More from this funder
Funding agency for:
Nissen-Meyer, T
More from this funder
Funding agency for:
Mortimer, B


Publisher:
Elsevier
Journal:
Current Biology More from this journal
Volume:
28
Issue:
9
Pages:
R547–R548
Publication date:
2018-05-07
Acceptance date:
2018-03-09
DOI:
EISSN:
1879-0445
ISSN:
0960-9822


Pubs id:
pubs:829522
UUID:
uuid:e2bb6fc9-ee4d-4ca7-9676-27858367df9b
Local pid:
pubs:829522
Source identifiers:
829522
Deposit date:
2018-03-14
ARK identifier:

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