Informations et ressources scientifiques
sur le développement des zones arides et semi-arides

Titre : Sentinel animals : enriching artificial intelligence with wildlife ecology to guard rhinos

Auteur : Eikelboom, Jasper A.J.

Université de soutenance : Wageningen University

Grade : Doctor 2021

Résumé partiel
The survival of both African rhinoceros species is under threat due to large-scale poaching. The pressure that poaching currently exerts on rhino populations is too large to solely wait for long-term conservation strategies, e.g., demand and corruption reduction campaigns, to take effect. Consequently, protection efforts aimed at the short-term survival of the rhino species seem to be urgently needed. Unfortunately, current rhino protection efforts fail to prevent large rhino population declines as conservation officers often fail to localize poachers before they can kill a rhino. Therefore I aimed to develop a poacher early warning system that provides conservation officers with more situational awareness, which can therefore decrease the risk of shootouts between poachers and conservation officers.

For this task I focused on developing a ’’sentinel-based poacher early warning system’’, for which I envision nature reserves where abundant prey animals are tracked and where the movement responses of these animals are automatically used to detect the presence and infer the location of poachers. Hence the term : ’’sentinel’’, as the animals themselves will take the role of game wardens. The benefit of such a system is that it could be working at all times and is not limited solely to rhino poachers. Apart from the obvious wildlife conservation challenge this thesis poses, it also tackles a major scientific challenge : to be able to detect abrupt changes in an environmental variable based on animal movement. In order to solve this challenge, a myriad of environmental and animal movement variables needed to be considered in interaction in a single model. This premise lead me to the use of a non-traditional statistical approach for wildlife ecologists : artificial intelligence.

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