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Data and scripts underlying the publication: Timely poacher detection and localization using sentinel animal movement

dataset
posted on 16.02.2021, 11:42 by J.A.J. (Jasper) Eikelboom, Henrik J. de Knegt
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 500m 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.

Funding

NWO program “Advanced Instrumentation for Wildlife Protection”

History

Publisher

4TU.ResearchData

Time coverage

Sep. 2017 - Mar. 2018

Geolocation

Welgevonden Game Reserve, South Africa

Geolocation Longitude

27.89

Geolocation Latitude

-24.22

Format

R scripts, R data structures and CSV files

Organizations

Wageningen University and Research, Wildlife Ecology and Conservation Group

Licence

Exports