Virtual fencing (VF) represents a way to simplify traditional pasture management with its high labour and cost requirements for fencing and to make better use of the 'beneficial' agronomic and ecological effects of livestock grazing. In this study, the VF technology (® Nofence, AS, Batnfjordsøra Norway) was used with Fleckvieh heifers to investigate possible welfare impacts on the animals compared to conventionally fenced animals when they were trained to respond correctly to the system. The Nofence® collars (attached to the neck of the heifers) send acoustic signals as a warning when the animals approach the VF line, which was set up by GPS coordinates within the Nofence®-App, followed by an electric pulse when they do not stop or return. The heifers had no experience with VF prior to the study. Two treatments (VF versus physical fencing (PF)) were applied to six groups of four heifers each (three groups per treatment) over three 12-day time replicates. One VF line separated the pasture of the VF group into an accessible or non-accessible area. The control group had a PF line. Both groups were equipped with Nofence® collars (deactivated for the PF group). The trial took place on two adjacent paddocks of 1 000 m² each following a 12-day schedule which was divided into three sections: visual support of the VF line by a physical barrier (first 2 days), only virtual border without visual support, moving the VF line (on day 8). Each time replicate followed the next successively on different paddocks with two new groups of heifers, which were grazed 5 h daily. During the whole experiment, the behaviour of each of the four animals per group was continuously observed; 2 h a.m., 2 h p.m. Exclusion by the VF line was effective in our trial. None of the heifers crossed the virtual boundary, i.e. the time spent in exclusion zone was zero. The heifers received 2.70 ± 2.63 acoustic signals and 0.30 ± 0.36 electric pulses (mean ± SD) per heifer and hour during all time replicates. Main cattle behaviour on pasture was not affected by the fencing system. Live weight gain, herbage consumption and faecal cortisol metabolites also revealed no significant differences. The duration until the heifers restarted grazing after an electric pulse from the Nofence® collar was significantly shorter than after an electric pulse from the physical fence. We can summarise that in our study, cattle well-being on pasture was not negatively affected by VF compared to PF.

Virtual fencing (VF) is a modern fencing technology that requires the animal to wear a device (e.g. a collar) that emits acoustic signals to replace the visual cue of traditional physical fences (PF) and, if necessary, mild electric signals. The use of devices that provide electric signals leads to concerns regarding the welfare of virtually fenced animals. The objective of this review is to give an overview of the current state of VF research into the welfare and learning behavior of cattle. Therefore, a systematic literature search was conducted using two online databases and reference lists of relevant articles. Studies included were peer-reviewed and written in English, used beef or dairy cattle, and tested neck-mounted VF devices. Further inclusion criteria were a combination of audio and electrical signals and a set-up as a pasture trial, which implied that animals grazed in groups on grassland for four hours minimum while at least one fence side was virtually fenced. The eligible studies (n = 13) were assigned to one or two of the following categories: animal welfare (n studies = 8) or learning behavior (n studies = 9). As data availability for conducting a meta-analysis was not sufficient, a comparison of the means of welfare indicators (daily weight gain, daily lying time, steps per hour, daily number of lying bouts, fecal cortisol metabolites (FCM)) for virtually and physically fenced animals was done instead. In an additional qualitative approach, the results from the welfare-related studies were assembled and discussed. For the learning behavior, the number of acoustic and electric signals and their ratio were used in a linear regression model with duration in days as a numeric predictor to assess the learning trends over time. There were no significant differences between VF and PF for most welfare indicators (except FCM with lower values for VF; P = 0.0165). The duration in days did not have a significant effect on the number of acoustic and electric signals. However, a significant effect of trial duration on the ratio of electric to acoustic signals (P = 0.0014) could be detected, resulting in a decreasing trend of the ratio over time, which suggests successful learning. Overall, we conclude that the VF research done so far is promising but is not yet sufficient to ensure that the technology could not have impacts on the welfare of certain cattle types. More research is necessary to investigate especially possible long-term effects of VF.

Extensively grazed semi-natural grasslands contribute to a wide range of ecosystem services, including the preservation of biodiversity and provision of livestock feed. Depending on the grazing intensity, cattle are set in motion to fulfill their nutritional needs. In this way, they influence the vegetation composition, while at the same time the foraging behavior is affected by the vegetation. A better understanding of the relationship between grazing intensity and animal behavior is an essential component for strategies to improve the value of semi-natural grasslands and for gaining insights for the development of smart farming technologies. The long-term cattle grazing experiment “FORBIOBEN” with its replicated three paddock-scale (1 ha) grazing intensities [moderate (M), lenient (L), very lenient (VL)] was used to investigate the movement behavior of suckler cows during four grazing periods between 2017 and 2020. For this, pregnant suckler cows (Fleckvieh) were equipped with Vectronics GPS Plus (VECTRONIC Aerospace GmbH, Berlin) collars, which recorded the position of the animals at defined time intervals. The main outcomes were that with an increase in the grazing intensity, the herbage on offer declined and, consequently the herbage allowance. However, the spatial heterogeneity of the herbage on offer decreased with increasing grazing intensity (M < VL) which means that the amount of available herbage was lower but more evenly distributed under moderate grazing. Further, there was a tendency that the moderate grazing intensity was associated with the highest effort of walking compared to lenient and very lenient grazing in three out of four grazing periods. We found a strong (p < 0.001) negative correlation among walking distance vs. herbage variability across all treatments × periods. Consequently, the grazing intensity itself was not a good predictor of walking distances which were mainly a result of the available herbage, its distribution or heterogeneity. Future smart farming livestock management systems will, therefore, likely require interfaces with the grassland growth rates and heterogeneity benchmarks if decisions based on livestock movement should be reliable.