Quantifying the Dynamics of Livestock Distribution by Unmanned Aerial Vehicles (UAVs): A Case Study of Yak Grazing at the Household Scale

Abstract

Managed grazing is the most extensive land use worldwide. Information about the spatio-temporal distribution of livestock is critical for grassland ecosystem management. However, no direct and cost-effective method exists to monitor livestock distribution under natural conditions. We proposed a practical method that uses unmanned aerial vehicles (UAVs), and tested it at a typical household pasture on the Qinghai-Tibetan Plateau. We monitored and analyzed the hourly spatial distribution of each yak (Bos mutus). We found that (1) yak information extracted by our independently developed software was sufficiently accurate (P > 0.05); (2) yak density (frequency/area/period) decreased with increasing distance from campsites in the early growing season, while the pattern reversed in the late growing season; (3) dispersion index (DI, m2/yak) of the yak herd exhibited a tendency to decrease in the morning and then to increase in the afternoon within a day; from June to September DI decreased in both the morning and afternoon, but was similar at noon. The monitoring method we developed in this study characterized the spatial distribution of the whole yak herd dynamically with high frequency, resolution, and efficiency. We conclude that this method is suitable for long-term monitoring of animal behavior, and for studying relationship between the distribution of pastoral livestock and resource availability, which will be beneficial for grassland sustainable management.