Human choices, slope and vegetation productivity determine patterns of traditional alpine summer grazing

• Published in: Italian journal of animal science 2022-12, Vol.21 (1), p.1126-1139
• Main Authors: Raniolo, Salvatore, Sturaro, Enrico, Ramanzin, Maurizio
• Format: Article
• Language: English
• Subjects: Cow's milk; Dairy cattle; GPS tracking; Grasslands; Grazing; Milk production; mountain pasture; NDVI; Pasture; Productivity; Remote sensing; Vegetation
• ISSN: 1828-051X; 1594-4077; 1828-051X
• DOI: 10.1080/1828051X.2022.2097453

Grazing behaviour influences animal productivity and the conservation of grassland ecosystem services. We used GPS tracking and remote sensing (NDVI index) to monitor the grazing patterns of lactating cows on the 'Malga Ombretta' summer farm (1,957 m asl) in the Dolomites, eastern Italian Alps, from 5th July to 5th August 2018. The pasture area (35 ha) was grazed by a mixed herd of Simmental and Alpine grey cows (stocking density = 0.6 LU/ha) under traditional management: each morning the farmer led the cows to graze in a selected sub-area of pasture, and during the afternoon he left them free to graze unrestricted until they returned to the barn for the night. GPS positions were collected every minute from 9 Simmental and 4 Alpine Grey cows with low milk production during the time they were outdoors. The farmer's choice of where to drive the herd to graze in the morning determined the distances the cows walked/day, which varied from 2.0 to 8.9 km, and favoured the use of higher and steeper areas that the cows tended otherwise to avoid. When free in the afternoon, the cows selected areas with higher NDVI values than those selected by the farmer in the morning, and Alpine Grey cows used slightly higher slopes and altitudes than Simmental cows, suggesting better adaptation to mountain pastures. The study revealed highly heterogenous grazing patterns dependent on multiple factors that can be assessed at fine temporal and spatial scales using GPS and remote sensing technologies to improve grazing management. HIGHLIGHTS Daily distances walked and grazing patterns were influenced differently by the farmer's decisions and the animals' choices in response to environmental features. The NDVI index of vegetation productivity suggested that cows grazed more productive areas when free than when driven by the farmer. GPS tracking and remote sensing shed light on how human and animal choices regarding grazing are influenced by environmental features.