Classifying elephant behaviour through seismic vibrations. / Mortimer, Beth; Rees, William Lake; Koelemeijer, Paula; Nissen-Meyer, Tarje.

In: Current Biology, Vol. 28, No. 9, 07.05.2018, p. R547-R548.

Research output: Contribution to journalLetter

Published

Standard

Classifying elephant behaviour through seismic vibrations. / Mortimer, Beth; Rees, William Lake; Koelemeijer, Paula; Nissen-Meyer, Tarje.

In: Current Biology, Vol. 28, No. 9, 07.05.2018, p. R547-R548.

Research output: Contribution to journalLetter

Harvard

Mortimer, B, Rees, WL, Koelemeijer, P & Nissen-Meyer, T 2018, 'Classifying elephant behaviour through seismic vibrations', Current Biology, vol. 28, no. 9, pp. R547-R548. https://doi.org/10.1016/j.cub.2018.03.062

APA

Mortimer, B., Rees, W. L., Koelemeijer, P., & Nissen-Meyer, T. (2018). Classifying elephant behaviour through seismic vibrations. Current Biology, 28(9), R547-R548. https://doi.org/10.1016/j.cub.2018.03.062

Vancouver

Mortimer B, Rees WL, Koelemeijer P, Nissen-Meyer T. Classifying elephant behaviour through seismic vibrations. Current Biology. 2018 May 7;28(9):R547-R548. https://doi.org/10.1016/j.cub.2018.03.062

Author

Mortimer, Beth ; Rees, William Lake ; Koelemeijer, Paula ; Nissen-Meyer, Tarje. / Classifying elephant behaviour through seismic vibrations. In: Current Biology. 2018 ; Vol. 28, No. 9. pp. R547-R548.

BibTeX

@article{897a7289ac4f44fabe73ad9b1b4de8db,
title = "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. Mortimer et al. explore elephant seismic vibrations. Combining computer modelling and field experiments, they show that behaviour, terrain and noise interact to affect the propagation of seismic information. Elephant behaviours generating high forces were predicted to travel farthest and could be used by researchers to remotely monitor wildlife.",
author = "Beth Mortimer and Rees, {William Lake} and Paula Koelemeijer and Tarje Nissen-Meyer",
year = "2018",
month = may
day = "7",
doi = "10.1016/j.cub.2018.03.062",
language = "English",
volume = "28",
pages = "R547--R548",
journal = "Current Biology ",
issn = "0960-9822",
publisher = "Cell Press",
number = "9",

}

RIS

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AU - Rees, William Lake

AU - Koelemeijer, Paula

AU - Nissen-Meyer, Tarje

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Y1 - 2018/5/7

N2 - 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. Mortimer et al. explore elephant seismic vibrations. Combining computer modelling and field experiments, they show that behaviour, terrain and noise interact to affect the propagation of seismic information. Elephant behaviours generating high forces were predicted to travel farthest and could be used by researchers to remotely monitor wildlife.

AB - 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. Mortimer et al. explore elephant seismic vibrations. Combining computer modelling and field experiments, they show that behaviour, terrain and noise interact to affect the propagation of seismic information. Elephant behaviours generating high forces were predicted to travel farthest and could be used by researchers to remotely monitor wildlife.

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