Use of Remote Camera Traps to Evaluate Animal-Based Welfare Indicators in Individual Free-Roaming Wild Horses.
Authors: Harvey Andrea M, Morton John M, Mellor David J, Russell Vibeke, Chapple Rosalie S, Ramp Daniel
Journal: Animals : an open access journal from MDPI
Summary
# Editorial Summary Harvey and colleagues have developed and tested a practical methodology for assessing welfare in individual free-roaming wild horses using remote camera traps, applying their previously developed Ten-Stage Protocol against the Five Domains Model framework. The researchers deployed remote cameras across varied habitats to determine whether individual horses could be reliably detected and identified, which welfare indicators could be assessed from still images versus video footage, and whether quantitative behavioural data could be extracted. Detection and identification success rates reached 75% on still images and 72% on video, with body condition score (73–79% assessable), body posture (76%), and coat condition (42–52%) proving consistently evaluable across both media types; video footage additionally enabled assessment of gait, weakness, shivering, and qualitative behavioural assessment in 50–66% of observations, whilst specific behaviours were identifiable in the majority of events (93% still images, 84% video). For equine practitioners working with wild or semi-feral populations, this methodology offers a non-invasive framework for monitoring individual welfare status, with particular value in detecting early signs of systemic disease (weakness, shivering, excessive sweating) or social integration; the authors' detailed protocols can inform welfare surveillance programmes and research applications across other species as well.
Read the full abstract on PubMed
Practical Takeaways
- •Remote camera traps provide a non-invasive method for detecting individual horses and assessing key welfare indicators like body condition and coat quality in wild or free-roaming populations
- •Video recording captures more welfare information than still images alone, particularly for dynamic indicators such as gait, weakness, and shivering assessment
- •This methodology can be applied to other species and represents a practical tool for wild animal welfare monitoring where direct observation is difficult or impossible
Key Findings
- •Remote camera traps successfully detected and identified individual wild horses in 75% of still images and 72% of video events, including in woodlands where direct observation was impossible
- •Body condition score was the most frequently assessable welfare indicator (73-79% of observation events), followed by body posture (76%) and coat condition (42-52%)
- •Twelve welfare indicators across the Five Domains could be assessed via remote camera traps, with an additional five indicators assessable only on video
- •Specific behaviors were identified in 93% of still images and 84% of video events, with social proximity to other horses recorded in 29-36% of observation events