Timely poacher detection and localization using sentinel animal movement

Abstract Wildlife crime is one of the most profitable illegal industries worldwide. Current actions to reduce it are far from effective and fail to prevent population declines of many endangered species, pressing the need for innovative anti-poaching solutions. Here, we propose and test a poacher ea...

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Autores principales:	Henrik J. de Knegt, Jasper A. J. Eikelboom, Frank van Langevelde, W. François Spruyt, Herbert H. T. Prins
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b3481e88bb6f43b99a9f90a50458a5f7
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spelling	oai:doaj.org-article:b3481e88bb6f43b99a9f90a50458a5f72021-12-02T13:20:23ZTimely poacher detection and localization using sentinel animal movement10.1038/s41598-021-83800-12045-2322https://doaj.org/article/b3481e88bb6f43b99a9f90a50458a5f72021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-83800-1https://doaj.org/toc/2045-2322Abstract Wildlife crime is one of the most profitable illegal industries worldwide. Current actions to reduce it are far from effective and fail to prevent population declines of many endangered species, pressing the need for innovative anti-poaching solutions. Here, we propose and test a poacher early warning system that is based on the movement responses of non-targeted sentinel animals, which naturally respond to threats by fleeing and changing herd topology. We analyzed human-evasive movement patterns of 135 mammalian savanna herbivores of four different species, using an internet-of-things architecture with wearable sensors, wireless data transmission and machine learning algorithms. We show that the presence of human intruders can be accurately detected (86.1% accuracy) and localized (less than 500 m error in 54.2% of the experimentally staged intrusions) by algorithmically identifying characteristic changes in sentinel movement. These behavioral signatures include, among others, an increase in movement speed, energy expenditure, body acceleration, directional persistence and herd coherence, and a decrease in suitability of selected habitat. The key to successful identification of these signatures lies in identifying systematic deviations from normal behavior under similar conditions, such as season, time of day and habitat. We also show that the indirect costs of predation are not limited to vigilance, but also include (1) long, high-speed flights; (2) energetically costly flight paths; and (3) suboptimal habitat selection during flights. The combination of wireless biologging, predictive analytics and sentinel animal behavior can benefit wildlife conservation via early poacher detection, but also solve challenges related to surveillance, safety and health.Henrik J. de KnegtJasper A. J. EikelboomFrank van LangeveldeW. François SpruytHerbert H. T. PrinsNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Henrik J. de Knegt Jasper A. J. Eikelboom Frank van Langevelde W. François Spruyt Herbert H. T. Prins Timely poacher detection and localization using sentinel animal movement
description	Abstract Wildlife crime is one of the most profitable illegal industries worldwide. Current actions to reduce it are far from effective and fail to prevent population declines of many endangered species, pressing the need for innovative anti-poaching solutions. Here, we propose and test a poacher early warning system that is based on the movement responses of non-targeted sentinel animals, which naturally respond to threats by fleeing and changing herd topology. We analyzed human-evasive movement patterns of 135 mammalian savanna herbivores of four different species, using an internet-of-things architecture with wearable sensors, wireless data transmission and machine learning algorithms. We show that the presence of human intruders can be accurately detected (86.1% accuracy) and localized (less than 500 m error in 54.2% of the experimentally staged intrusions) by algorithmically identifying characteristic changes in sentinel movement. These behavioral signatures include, among others, an increase in movement speed, energy expenditure, body acceleration, directional persistence and herd coherence, and a decrease in suitability of selected habitat. The key to successful identification of these signatures lies in identifying systematic deviations from normal behavior under similar conditions, such as season, time of day and habitat. We also show that the indirect costs of predation are not limited to vigilance, but also include (1) long, high-speed flights; (2) energetically costly flight paths; and (3) suboptimal habitat selection during flights. The combination of wireless biologging, predictive analytics and sentinel animal behavior can benefit wildlife conservation via early poacher detection, but also solve challenges related to surveillance, safety and health.
format	article
author	Henrik J. de Knegt Jasper A. J. Eikelboom Frank van Langevelde W. François Spruyt Herbert H. T. Prins
author_facet	Henrik J. de Knegt Jasper A. J. Eikelboom Frank van Langevelde W. François Spruyt Herbert H. T. Prins
author_sort	Henrik J. de Knegt
title	Timely poacher detection and localization using sentinel animal movement
title_short	Timely poacher detection and localization using sentinel animal movement
title_full	Timely poacher detection and localization using sentinel animal movement
title_fullStr	Timely poacher detection and localization using sentinel animal movement
title_full_unstemmed	Timely poacher detection and localization using sentinel animal movement
title_sort	timely poacher detection and localization using sentinel animal movement
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/b3481e88bb6f43b99a9f90a50458a5f7
work_keys_str_mv	AT henrikjdeknegt timelypoacherdetectionandlocalizationusingsentinelanimalmovement AT jasperajeikelboom timelypoacherdetectionandlocalizationusingsentinelanimalmovement AT frankvanlangevelde timelypoacherdetectionandlocalizationusingsentinelanimalmovement AT wfrancoisspruyt timelypoacherdetectionandlocalizationusingsentinelanimalmovement AT herberthtprins timelypoacherdetectionandlocalizationusingsentinelanimalmovement
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Timely poacher detection and localization using sentinel animal movement

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