Researchers have successfully used photographs and videos collected from camera traps to make welfare assessments of free-roaming wild horses.
The researchers were able to identify a majority of the horses captured by the cameras, having applied a previously developed protocol for scientifically assessing the welfare of each animal.
“Camera trapping was successful in detecting and identifying horses across a range of habitats, including woodlands where horses could not be directly observed,” Andrea Harvey and her fellow researchers reported in the journal Animals.
Twelve indicators of welfare were assessed with equal frequency using both still images and video, with an additional five indicators assessed on video.
The study team said the method they used could be adjusted and applied to other species, enabling significant advances to be made in the field of wild animal welfare.
The authors noted that many studies have evaluated wild horse behaviours – time budgets, home ranges, body condition scores and social organisation – but, until now, an extensive range of welfare indicators has apparently not been assessed.
“This,” they said, “is the first time such a methodology has been described for assessing a range of welfare indicators in free-roaming wild animals.
The research team had previously developed a 10-stage protocol, described in the table above, for scientifically assessing the welfare of individual free-roaming wild animals using the Five Domains Model – a science-based structure to help assess animal welfare. It covers nutrition, the environment, health, behaviour and mental well-being.
They selected measurable or observable welfare indicators that may be able to be captured in free-roaming horses using camera trap still images and/or videos, or by direct observation, described in the table below.
The cameras were installed and images recorded between December 2015 and March 2017 in the Kedumba Valley, an isolated section of about 130 square kilometres within the Warragamba Special Area of the Blue Mountains National Park, being part of the Greater Blue Mountains World Heritage Area in New South Wales.
The horse population there is known to be small and geographically constrained by natural physical boundaries.
The still images and videos were collected and analysed to assess whether horses could be detected and identified individually, which welfare indicators could be reliably evaluated, and whether behaviour could be quantitatively assessed.
Remote camera trapping was successful in detecting and identifying horses 75% of the horses on still images and 72% on video recordings, across a range of habitats, including woodlands where horses could not be directly observed.
The 12 indicators of welfare across the Five Domains were assessed with equal frequency on both still images and video events, with those most frequently assessable being body condition score (73% of still images and 79% of video recordings), body posture (76% for both), coat condition (42% for still images and 52% for video), and whether the horse was sweating excessively (42% on still images and 45% on video).
An additional five indicators could be assessed only on video, with those most frequently observable being the presence or absence of weakness (which could be assessed in 66% of cases), qualitative behavioural assessment (60%), the presence or absence of shivering (51%), and the gait at walk (50%).
The study team said specific behaviours were identified in 93% of still images and 84% of video events.
“Most social behaviours were rarely observed, but close spatial proximity to other horses, as an indicator of social bonds, was recorded in 36% of still images, and 29% of video observation events.”
Discussing their findings, the researchers said that precise and strategic camera placement was crucial to optimising image quality and detection of horses at appropriate angles and distances from the camera in order to both identify individual horses and assess a range of welfare indicators.
“Deploying cameras on tracks, grazing areas, and drinking locations within the same region assists in capturing the full range of listed welfare indicators, including a wider range of behaviours,” they said.
They said camera trap images and video provided valuable information about the horses, particularly those that could not be sighted regularly, sighted for a long enough duration, or approached closely enough to enable direct assessment of welfare indicators, as was the case in woodland habitats.
The next phases of the research will include applying the same method to larger populations across different geographical areas, in addition to incorporating these methods into a welfare assessment protocol to objectively evaluate how the welfare of wild free-roaming horses varies spatially and over time.
The study team comprised Harvey and Daniel Ramp, both with the Centre for Compassionate Conservation, part of the School of Life Sciences at the University of Technology Sydney; John Morton with Jemora Pty Ltd in Geelong, Victoria; David Mellor, with the Animal Welfare Science and Bioethics Centre at the School of Veterinary Science at Massey University in New Zealand; veterinary contractor Vibeke Russell; and Rosalie Chapple, with the Blue Mountains World Heritage Institute.
Harvey, A.M.; Morton, J.M.; Mellor, D.J.; Russell, V.; Chapple, R.S.; Ramp, D. Use of Remote Camera Traps to Evaluate Animal-Based Welfare Indicators in Individual Free-Roaming Wild Horses. Animals 2021, 11, 2101. https://doi.org/10.3390/ani11072101