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Using triaxial accelerometry to detect hunts and kills by African wild dogs

James Redcliffe, Scott Creel, Ben Goodheart, Johnathan Reyes de Merkle, Stephani S. Matsushima, Michelo Mungolo, Ruth Kabwe, Emmanuel Kaseketi, Will Donald, Adrian Kaluka, Clive Chifunte, Matthew S. Becker, Rory Wilson Orcid Logo

Frontiers in Ecology and Evolution, Volume: 12, Start page: 1465094

Swansea University Authors: James Redcliffe, Rory Wilson Orcid Logo

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DOI (Published version): 10.3389/fevo.2024.1465094

Abstract

Most large carnivores feed on prey infrequently and may expend large amounts of energy to locate, capture and kill their prey. This makes them probabilistically vulnerable to fluctuating rates of energy acquisition over time, especially within the increasingly human-altered landscapes that dominate...

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Published in: Frontiers in Ecology and Evolution
ISSN: 2296-701X
Published: Frontiers Media SA 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa67606
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spelling 2025-01-31T12:12:41.4689499 v2 67606 2024-09-06 Using triaxial accelerometry to detect hunts and kills by African wild dogs 4046e46611e52bf1ee798d17411df8e9 James Redcliffe James Redcliffe true false 017bc6dd155098860945dc6249c4e9bc 0000-0003-3177-0177 Rory Wilson Rory Wilson true false 2024-09-06 BGPS Most large carnivores feed on prey infrequently and may expend large amounts of energy to locate, capture and kill their prey. This makes them probabilistically vulnerable to fluctuating rates of energy acquisition over time, especially within the increasingly human-altered landscapes that dominate their remaining range. Consequently, quantifying their hunting behaviors and success rates is critical, yet direct observation of these events is rarely feasible. We theorized that we could determine prey pursuit and capture in African wild dogs (Lycaon pictus) using a mechanistic approach by constructing Boolean algorithms applied to accelerometer data derived from collar-mounted tags. Here, we used this method and then iteratively improved algorithms by testing them on observed hunts and kills of collared packs. Using this approach on 47 days of acceleration from three wild dogs in three packs, we identified 29 hunts with 10 kills, all of which were confirmed by direct observation except for a single kill. Our results demonstrate that hunting effort and success can largely be determined from acceleration data using a mechanistic approach. This is particularly valuable when such behaviors are rarely quantified and offers a template for research on foraging in canid species, while also contributing to the expanding body of literature that employs similar methods to quantify hunting in large carnivores. Journal Article Frontiers in Ecology and Evolution 12 1465094 Frontiers Media SA 2296-701X African wild dogs, accelerometry, hunts, kills, VeDBA, movement, pitch angle 9 12 2024 2024-12-09 10.3389/fevo.2024.1465094 COLLEGE NANME Biosciences Geography and Physics School COLLEGE CODE BGPS Swansea University Other The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The work was funded by NERC (NE/X015491/1) and by the National Science Foundation (IOS-1145749, DEB-2032131 and DEB-2221826), National Geographic Society Predator Research Grant, Dazzle Africa, World Wildlife Fund-Netherlands & Zambia, Tusk Trust, Painted Dog Conservation Inc., Gemfields Inc., Green Safaris. 2025-01-31T12:12:41.4689499 2024-09-06T21:48:56.9085430 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Biosciences James Redcliffe 1 Scott Creel 2 Ben Goodheart 3 Johnathan Reyes de Merkle 4 Stephani S. Matsushima 5 Michelo Mungolo 6 Ruth Kabwe 7 Emmanuel Kaseketi 8 Will Donald 9 Adrian Kaluka 10 Clive Chifunte 11 Matthew S. Becker 12 Rory Wilson 0000-0003-3177-0177 13 67606__33458__08a9f2d3955940359896fab67bda4822.pdf 67606.VOR.pdf 2025-01-31T12:09:41.2543074 Output 1635359 application/pdf Version of Record true © 2024 Redcliffe, Creel, Goodheart, Reyes de Merkle, Matsushima, Mungolo, Kabwe, Kaseketi, Donald, Kaluka, Chifunte, Becker and Wilson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). true eng http://creativecommons.org/licenses/by/4.0/
title Using triaxial accelerometry to detect hunts and kills by African wild dogs
spellingShingle Using triaxial accelerometry to detect hunts and kills by African wild dogs
James Redcliffe
Rory Wilson
title_short Using triaxial accelerometry to detect hunts and kills by African wild dogs
title_full Using triaxial accelerometry to detect hunts and kills by African wild dogs
title_fullStr Using triaxial accelerometry to detect hunts and kills by African wild dogs
title_full_unstemmed Using triaxial accelerometry to detect hunts and kills by African wild dogs
title_sort Using triaxial accelerometry to detect hunts and kills by African wild dogs
author_id_str_mv 4046e46611e52bf1ee798d17411df8e9
017bc6dd155098860945dc6249c4e9bc
author_id_fullname_str_mv 4046e46611e52bf1ee798d17411df8e9_***_James Redcliffe
017bc6dd155098860945dc6249c4e9bc_***_Rory Wilson
author James Redcliffe
Rory Wilson
author2 James Redcliffe
Scott Creel
Ben Goodheart
Johnathan Reyes de Merkle
Stephani S. Matsushima
Michelo Mungolo
Ruth Kabwe
Emmanuel Kaseketi
Will Donald
Adrian Kaluka
Clive Chifunte
Matthew S. Becker
Rory Wilson
format Journal article
container_title Frontiers in Ecology and Evolution
container_volume 12
container_start_page 1465094
publishDate 2024
institution Swansea University
issn 2296-701X
doi_str_mv 10.3389/fevo.2024.1465094
publisher Frontiers Media SA
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Biosciences, Geography and Physics - Biosciences{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Biosciences
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description Most large carnivores feed on prey infrequently and may expend large amounts of energy to locate, capture and kill their prey. This makes them probabilistically vulnerable to fluctuating rates of energy acquisition over time, especially within the increasingly human-altered landscapes that dominate their remaining range. Consequently, quantifying their hunting behaviors and success rates is critical, yet direct observation of these events is rarely feasible. We theorized that we could determine prey pursuit and capture in African wild dogs (Lycaon pictus) using a mechanistic approach by constructing Boolean algorithms applied to accelerometer data derived from collar-mounted tags. Here, we used this method and then iteratively improved algorithms by testing them on observed hunts and kills of collared packs. Using this approach on 47 days of acceleration from three wild dogs in three packs, we identified 29 hunts with 10 kills, all of which were confirmed by direct observation except for a single kill. Our results demonstrate that hunting effort and success can largely be determined from acceleration data using a mechanistic approach. This is particularly valuable when such behaviors are rarely quantified and offers a template for research on foraging in canid species, while also contributing to the expanding body of literature that employs similar methods to quantify hunting in large carnivores.
published_date 2024-12-09T08:15:55Z
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