Classifying elephant behaviour through seismic vibrations
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...
| Main Authors: | , , , |
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| Format: | Journal article |
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Elsevier
2018
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| _version_ | 1826301439776915456 |
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| author | Mortimer, B Rees, W Koelemeijer, P Nissen-Meyer, T |
| author_facet | Mortimer, B Rees, W Koelemeijer, P Nissen-Meyer, T |
| author_sort | Mortimer, B |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-03-07T05:32:28Z |
| format | Journal article |
| id | oxford-uuid:e2bb6fc9-ee4d-4ca7-9676-27858367df9b |
| institution | University of Oxford |
| last_indexed | 2024-03-07T05:32:28Z |
| publishDate | 2018 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oxford-uuid:e2bb6fc9-ee4d-4ca7-9676-27858367df9b2022-03-27T10:03:39ZClassifying elephant behaviour through seismic vibrationsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:e2bb6fc9-ee4d-4ca7-9676-27858367df9bSymplectic Elements at OxfordElsevier2018Mortimer, BRees, WKoelemeijer, PNissen-Meyer, TSeismic 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. |
| spellingShingle | Mortimer, B Rees, W Koelemeijer, P Nissen-Meyer, T Classifying elephant behaviour through seismic vibrations |
| title | Classifying elephant behaviour through seismic vibrations |
| title_full | Classifying elephant behaviour through seismic vibrations |
| title_fullStr | Classifying elephant behaviour through seismic vibrations |
| title_full_unstemmed | Classifying elephant behaviour through seismic vibrations |
| title_short | Classifying elephant behaviour through seismic vibrations |
| title_sort | classifying elephant behaviour through seismic vibrations |
| work_keys_str_mv | AT mortimerb classifyingelephantbehaviourthroughseismicvibrations AT reesw classifyingelephantbehaviourthroughseismicvibrations AT koelemeijerp classifyingelephantbehaviourthroughseismicvibrations AT nissenmeyert classifyingelephantbehaviourthroughseismicvibrations |