Characterizing grazing and terrain use patterns of Hispano-Breton mares in the Spanish Pyrenees using GPS devices and...

Geotechnologies, such as Global Navigation Satellite Systems (GNSS) and remote sensing, are essential for documenting topographic features and analyzing land use. Among them, the GPS (Global Position System)-based sensors have proven highly effective in monitoring livestock, providing high-resolution data on movement patterns. This study tracked two Hispano-Breton mares in the Spanish Pyrenees during summer 2023 using GPS collars. A°C (LiDAR) dataset provided the digital elevation model (DEM), while Sentinel-2 imagery assessed the grazing conditions. All data were integrated within a Geographic Information System (GIS). The study period ranged from 1 July to 28 August 2023. Until 7 August, the mares grazed in a valley area, while from that date on they traveled to high mountain pastures. The mares and their foals traveled a mean distance of 472.99 km, averaging 7.95 ± 2.58 km per day with a mean elevation gain of 561 m daily. Distance traveled increased with elevation gain, likely to mitigate steep slopes. Normalized Difference Vegetation Index (NDVI) analysis revealed that lower valley pastures maintained stable vegetation throughout the season, whereas high mountain pastures became significantly drier in August. These findings suggest that equine grazing patterns are shaped by forage availability, and possibly also by traditional herding practices. Although this study focuses on Hispano-Breton mares in the Spanish Pyrenees, the results provide insights applicable to horses managed in extensive grazing systems worldwide, including wild and feral populations in arid and semi-arid regions such as the Australian outback. Notably, the movement patterns observed in this study more closely resemble those of Australian domestic horses confined to large paddocks than those of feral horses, despite our mares being part of free-range grazing systems. This study highlights the joint value of GPS tracking and remote sensing in understanding equine behavior in mountainous environments, offering insights for sustainable husbandry practices in high-altitude regions.