Version 1
: Received: 2 April 2024 / Approved: 2 April 2024 / Online: 3 April 2024 (05:51:07 CEST)
How to cite:
Aaser, M.F.; Staahltoft, S.K.; Andersen, M.; Alstrup, A.K.O.; Sonne, C.; Bruhn, D.; Frikke, J.; Pertoldi, C. Using Activity Measures and GPS Data from a Virtual Fencing System to Assess Habitat Preference and Habitat Utilisation Patterns in Cattle. Preprints2024, 2024040189. https://doi.org/10.20944/preprints202404.0189.v1
Aaser, M.F.; Staahltoft, S.K.; Andersen, M.; Alstrup, A.K.O.; Sonne, C.; Bruhn, D.; Frikke, J.; Pertoldi, C. Using Activity Measures and GPS Data from a Virtual Fencing System to Assess Habitat Preference and Habitat Utilisation Patterns in Cattle. Preprints 2024, 2024040189. https://doi.org/10.20944/preprints202404.0189.v1
Aaser, M.F.; Staahltoft, S.K.; Andersen, M.; Alstrup, A.K.O.; Sonne, C.; Bruhn, D.; Frikke, J.; Pertoldi, C. Using Activity Measures and GPS Data from a Virtual Fencing System to Assess Habitat Preference and Habitat Utilisation Patterns in Cattle. Preprints2024, 2024040189. https://doi.org/10.20944/preprints202404.0189.v1
APA Style
Aaser, M.F., Staahltoft, S.K., Andersen, M., Alstrup, A.K.O., Sonne, C., Bruhn, D., Frikke, J., & Pertoldi, C. (2024). Using Activity Measures and GPS Data from a Virtual Fencing System to Assess Habitat Preference and Habitat Utilisation Patterns in Cattle. Preprints. https://doi.org/10.20944/preprints202404.0189.v1
Chicago/Turabian Style
Aaser, M.F., John Frikke and Cino Pertoldi. 2024 "Using Activity Measures and GPS Data from a Virtual Fencing System to Assess Habitat Preference and Habitat Utilisation Patterns in Cattle" Preprints. https://doi.org/10.20944/preprints202404.0189.v1
Abstract
There has been an increased focus on new technologies to monitor habitat use and behaviour of cattle, to develop a more sustainable livestock grazing system, without compromising animal welfare. The currently most used method for monitoring cattle behaviour is tri-axial accelerometer data from systems such as virtual fencing technology or bespoke monitoring technology. This method requires high frequency data, and as such, quickly drains contemporary systems of power making it unsuitable for long-term monitoring. In this paper, we explore the possibility of determining habitat preference and habitat utilisation patterns in cattle, using low frequency activity and location data. We do this by (1) calculating habitat selection ratios, (2) determining daily activity patterns and based on those, (3) inferring grazing and resting sites in a group of cattle wearing virtual fencing collars in a coastal setting with grey, wooded and decalcified dunes, humid dune slacks and salt meadows. We found that GPS data, and a measure of activity, combined with accurate mapping of habitats can be an effective tool in assessing habitat preference. The animals preferred salt meadows over the other habitats, with wooded dunes and humid dune slacks being the least preferred. We were able to identify daily patterns in activity. By comparing general trends in activity levels to existing literature, it was possible to somewhat infer resting and grazing behaviour in the different habitats. According to our inference of behaviour the herd predominantly used the salt meadows for resting and ruminating. The approach used in this study allowed us to use GPS location data for measuring the activity and combine it with accurate habitat mapping in a cheap and effective way, which can be an important tool for guiding management decisions.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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