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Spatial Distribution and Hierarchical Behaviour of Cattle Using a Virtual Fence System.

Silje Marquardsen LundJohanne Holm JacobsenMaria Gytkjær NielsenMarie Ribergaard FriisNatalie Hvid NielsenNina Østerhaab MortensenRegitze Cushion SkibstedMagnus Fjord AaserSøren Krabbe StaahltoftDan BruhnChristian SonneAage Kristian Olsen AlstrupJohn FrikkeCino Pertoldi
Published in: Animals : an open access journal from MDPI (2024)
Interest in virtual fencing has increased due to its flexibility for agriculture and rewilding. However, systems like Nofence© require large financial investments, and the need for individual collars complicates large-scale use. If cattle herds maintain cohesive groups around leading individuals, fewer collars could be used, thereby enhancing cost efficiency. This study investigates the pattern in spatial distribution in a herd of 17 Angus cows on Fanø in Denmark with GPS locations, using a Nofence© system. The aim of this paper is to determine how individuals position themselves in a herd, spatially, and identify a pattern in ranks. The method used in this study examines the distances between an individual to the rest of the herdmates using nearest neighbour and descriptive statistics. Contrary to expectations, this study did not reveal a distinct pattern in herd distribution. While some tendencies in spatial distribution patterns were observed, only a low concordance could be found (W=0.15,p<0.001), indicating great variability in the cattle's ranks. A cumulative curve of the ranks estimated over the entire periods, however, allowed a rough estimation of the hierarchy and allowed identification of the highest-ranked cows, making the use of a cumulative curve a possible solution to finding the high-ranked cows. This research underscores the complexity of cattle social structures and highlights the need for extended observation periods and alternative methodologies to enhance the cost-effectiveness and scalability of virtual fencing in agricultural and rewilding contexts.
Keyphrases
  • healthcare
  • climate change
  • risk assessment
  • genome wide
  • single cell
  • cross sectional
  • human health