Using drones and sirens to elicit avoidance behaviour in white rhinoceros as an anti-poaching tactic

Abstract

Poaching fuelled by international trade in horn caused the deaths of over 1000 African rhinoceros ( Ceratotherium simum and Diceros bicornis ) per year between 2013 and 2017. Deterrents, which act to establish avoidance behaviours in animals, have the potential to aid anti-poaching efforts by moving at-risk rhinos away from areas of danger (e.g. near perimeter fences). To evaluate the efficacy of deterrents, we exposed a population of southern white rhinos ( C. simum simum ) to acoustic- (honeybee, siren, turtle dove), olfactory- (chilli, sunflower), and drone-based stimuli on a game reserve in South Africa. We exposed rhinos to each stimulus up to four times. Stimuli were considered effective deterrents if they repeatedly elicited avoidance behaviour (locomotion away from the deterrent). Rhinos travelled significantly further in response to the siren than to the honeybee or turtle dove stimulus, and to low-altitude drone flights than to higher altitude flights. We found the drone to be superior at manipulating rhino movement than the siren owing to its longer transmission range and capability of pursuit. By contrast, the scent stimuli were ineffective at inciting avoidance behaviour. Our findings indicate that deterrents are a prospective low-cost and in situ method to manage rhino movement in game reserves.

Negligible hormonal response following dehorning in free-ranging white rhinoceros (Ceratotherium simum)

“…A rise in demand for rhino horn in East Asia has resulted in the deaths of over 8000 African rhinos during the 2010s ( Vigne and Martin, 2018 ; Knight, 2020 ). Field responses include increases in security and law enforcement ( Haas and Ferreira, 2018 ), the strategic translocation or herding of rhinos from areas of high risk to areas of low risk ( Penny et al , 2019 ) and dehorning ( Knight, 2020 ). Faced with high security costs, private reserves and national parks in southern Africa are increasingly dehorning their rhinos as an attempt to reduce poaching ( Rubino and Pienaar, 2018 ; Knight, 2020 ).…”

An Evaluation of the Factors Affecting ‘Poacher’ Detection with Drones and the Efficacy of Machine-Learning for Detection

“…Automated detection software had a successful detection probability of greater than 0.5, but the full potential of the software could be reached through more training of the model, and this would also reduce the large number of false positives produced in detection results. All of the findings summarised in combination with findings from other studies about advancements in machine learning, poaching hotspots, and the success of drones in anti-poaching scenarios [3,[23][24][25]30,48,50,54,74] will be useful when incorporating drones into anti-poaching operations and will aid in increasing the efficiency of expenditure of anti-poaching resources. In future research, it would be beneficial to repeat this study with a focus on the efficiency of automated detection in real-time video on-board the drone under technological and environmental conditions recommended by this study to increase detection probability.…”

“…In the last few years, the proven success of drones in conservation and the increases in wildlife crime sparked research into the use of drones to detect and reduce illegal activity such as poaching and illegal hunting [22][23][24]. However, there is a lack of studies investigating the factors that influence detection, which are instrumental for understanding the environmental situations in which poachers may elude detection as well as the technical attributes that aid successful detection.…”

Unforeseen consequences of conservation management practices: case study on herding rhino as an anti‐poaching measure

“…Other anti‐poaching measures include the use of Remotely Piloted Aircraft Systems (i.e. drones when used by the military) (Mulero‐Pázmány et al ., 2014; Penny et al ., 2019), canine units, intelligent fence intrusion detection systems and real‐time anti‐poaching tags (O'Donoghue & Rutz, 2016).…”