Terrestrial mammalian wildlife responses to Unmanned Aerial Systems approaches

Bennitt, Emily; Bartlam‐Brooks, Hattie L. A.; Hubel, Tatjana Y.; Wilson, Alan M.

doi:10.1038/s41598-019-38610-x

Cited by 60 publications

(60 citation statements)

References 44 publications

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“…Obviously, at lower altitudes the drone is more likely to be heard and seen by the kangaroos and perceived as a potential threat. This result is supported by other studies where drones flown at altitudes of less than 40 m induced evasive behaviour on African herbivore species [4] crocodiles (Crocodylus porosus) [13] and bird species [9][10][11]13]. Repeated drone monitoring of kangaroos may create a lasting stress response in target animals and reduce the reliability of any ecological interpretations.…”

Section: Discussionsupporting

confidence: 79%

“…There is growing interest in the use of drones as a tool in wildlife ecology as the technology has become more available and less expensive in recent years [1]. While many are utilising drones to monitor and count [2] terrestrial [3] and marine wildlife, few studies have assessed the impact of this type of monitoring on the behaviour of terrestrial mammals [4]. To date, most studies assessing behavioural responses of wildlife to drones have focused on marine vertebrates [5][6][7][8] and birds [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

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Fright or Flight? Behavioural Responses of Kangaroos to Drone-Based Monitoring

Brunton

Bolin

Leon

et al. 2019

Drones

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: Drones are often considered an unobtrusive method of monitoring terrestrial wildlife; however research into whether drones disturb wildlife is in its early stages. This research investigated the potential impacts of drone monitoring on a large terrestrial mammal, the eastern grey kangaroo (Macropus giganteus), in urban and peri-urban environments. We assessed the response of kangaroos to drone monitoring by analysing kangaroo behaviour prior to and during drone deployments using a linear modelling approach. We also explored factors that influenced kangaroo responses including drone altitude, site characteristics and kangaroo population dynamics and demographics. We showed that drones elicit a vigilance response, but that kangaroos rarely fled from the drone. However, kangaroos were most likely to flee from a drone flown at an altitude of 30 m. This study suggests that drone altitude is a key consideration for minimising disturbance of large terrestrial mammals and that drone flights at an altitude of 60–100 m above ground level will minimise behavioural impacts. It also highlights the need for more research to assess the level of intrusion and other impacts that drone surveys have on the behaviour of wildlife and the accuracy of the data produced.

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Section: Discussionsupporting

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Fright or Flight? Behavioural Responses of Kangaroos to Drone-Based Monitoring

Brunton

Bolin

Leon

et al. 2019

Drones

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“…The area is unfenced, with the exclusion of a few veterinary cordon fences that do not represent any barrier to African wild dog movements (Cozzi et al 2013). All major large carnivores and herbivores typical of African savannas are common throughout the large study area (Cozzi et al 2013, Bennitt et al 2019). Human populations and activities are concentrated along the major roads at the southern and western distal ends of the Okavango Delta (Mendelson et al 2010; Fig.…”

Section: Study Areamentioning

confidence: 64%

African Wild Dog Dispersal and Implications for Management

et al. 2020

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Successful conservation of species that roam and disperse over large areas requires detailed understanding of their movement patterns and connectivity between subpopulations. But empirical information on movement, space use, and connectivity is lacking for many species, and data acquisition is often hindered when study animals cross international borders. The African wild dog (Lycaon pictus) exemplifies such species that require vast undisturbed areas to support viable, self-sustaining populations.To study wild dog dispersal and investigate potential barriers to movements and causes of mortality during dispersal, between 2016 and 2019 we followed the fate of 16 dispersing coalitions (i.e., same-sex group of ≥1 dispersing African wild dogs) in northern Botswana through global positioning system (GPS)-satellite telemetry. Dispersing wild dogs covered ≤54 km in 24 hours and traveled 150 km to Namibia and 360 km to Zimbabwe within 10 days. Wild dogs were little hindered in their movements by natural landscape features, whereas medium to densely human-populated landscapes represented obstacles to dispersal. Human-caused mortality was responsible for >90% of the recorded deaths. Our results suggest that a holistic approach to the management and conservation of highly mobile species is necessary to develop effective research and evidence-based conservation programs across transfrontier protected areas, including the need for coordinated research efforts through collaboration between national and international conservation authorities.

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“…Drones are also relatively cheap, safe and less disturbing, improving traditional wildlife surveys [3,18,20,21]. They can, however, disturb some animal populations, requiring careful consideration of appropriateness when surveying [22]. As a result of such time and cost savings, drones are increasingly used to monitor bird communities [23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Counting Mixed Breeding Aggregations of Animal Species Using Drones: Lessons from Waterbirds on Semi-Automation

et al. 2020

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Using drones to count wildlife saves time and resources and allows access to difficult or dangerous areas. We collected drone imagery of breeding waterbirds at colonies in the Okavango Delta (Botswana) and Lowbidgee floodplain (Australia). We developed a semi-automated counting method, using machine learning, and compared effectiveness of freeware and payware in identifying and counting waterbird species (targets) in the Okavango Delta. We tested transferability to the Australian breeding colony. Our detection accuracy (targets), between the training and test data, was 91% for the Okavango Delta colony and 98% for the Lowbidgee floodplain colony. These estimates were within 1-5%, whether using freeware or payware for the different colonies. Our semi-automated method was 26% quicker, including development, and 500% quicker without development, than manual counting. Drone data of waterbird colonies can be collected quickly, allowing later counting with minimal disturbance. Our semi-automated methods efficiently provided accurate estimates of nesting species of waterbirds, even with complex backgrounds. This could be used to track breeding waterbird populations around the world, indicators of river and wetland health, with general applicability for monitoring other taxa.Remote Sens. 2020, 12, 1185 2 of 17 semi-automated methods. The former can be extremely labour-intensive and consequently expensive, particularly for large aggregations of wildlife [26], further complicated when more than one species is counted. Semi-automated methods, including the counting of animals from photographs (e.g., camera traps) and drone imagery, are increasingly being developed around the world [27]. These methods reduce the time required to count and process drone images [28], accelerating the data entry stage and encouraging the use of drones as scientific tools for management. Such benefits allow for real-time monitoring and management decisions and could, for example, assist in the targeted delivery of environmental flows for waterbird breeding events [29].Generally, semi-automated counting methods are most effective for species where there are strong contrasts against the backgrounds, particularly when background colours and shapes are consistent [28]. They can distinguish large single species aggregations on relatively simple backgrounds [30][31][32], up to sixteen avian species (numbering in the hundreds) on simple single colour backgrounds, such as oceans [33,34], or single species aggregations of hundreds of thousands on complex backgrounds [3].Development of flexible, repeatable and efficient methods, using open source software, is important in ensuring methods are applicable across a range of datasets [35,36]. Further, there are potential cost implications of processing data, given that some processing software can be expensive (i.e., compulsory licence fees, called 'payware' in this paper) and so are often only accessible to large organisations in high-income countries [37]. Open source software, or software with optional lic...

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Terrestrial mammalian wildlife responses to Unmanned Aerial Systems approaches

Cited by 60 publications

References 44 publications

Fright or Flight? Behavioural Responses of Kangaroos to Drone-Based Monitoring

Fright or Flight? Behavioural Responses of Kangaroos to Drone-Based Monitoring

African Wild Dog Dispersal and Implications for Management

Counting Mixed Breeding Aggregations of Animal Species Using Drones: Lessons from Waterbirds on Semi-Automation

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