Pasture-use intensity and Vegetation: Insights from GPS Tracking and Remote Sensing from an alpine pasture

Understanding the relationship between grazing patterns and vegetation productivity is essential for the sustainable management of alpine pastures, their biodiversity and ecosystem services. This study integrates GPS tracking and remote sensing to assess the impact of dairy cow grazing on vegetation condition in alpine pastures. The study area is a summer farm pasture (171 ha) located in the eastern Italian Alps at an average elevation of 1900 m a.s.l. (SD: 90). The herd (150 Livestock units) was conducted to different pasture’s sub-areas each morning after the milking and returned to the barn for the evening milking. After that, it roamed freely during the night. We monitored 12 cows with GPS collars (one position every two minutes) from July 3 to September 5, 2023. We used NDVI (Normalized Difference Vegetation Index) from Copernicus SENTINEL-2 to index vegetation conditions at the beginning (June 22), during (July 17 and August 21) and after (September 25) the grazing seasons. We divided the pasture into a 25 m grid and associated with each cell the average NDVI (to index vegetation biomass) on each date and, on September 25, the NDVI difference from June 22 (“NDVI difference”, to index residual vegetation), the normalized positions count to index grazing intensity in the periods between each date, and slope, aspect, and prevalent vegetation type to consider permanent environmental features. Based on NDVI difference, we found a significant relationship between pasture use intensity and vegetation productivity, varying by vegetation type, with a general regrowth pattern in intensively used areas at the end of the season. A resource selection function approach revealed that the spatial selection patterns of farmer-animals varied between dates, with the preference for higher productivity areas at the beginning and end of the season and for lower ones in the middle, with a general avoidance of steep areas. These results indicate the potential for using vegetation indices to estimate the impact of grazing intensity on pasture conditions, highlighting the usefulness of remote sensing and GPS tracking for monitoring this agroecosystem and its productivity.