Increasing sward phytodiversity has been suggested as having potential to increase primary production of grasslands, but whether any such gains are converted into secondary production, through improved performance of grazing livestock, remains uncertain. Animal production by cattle and sheep can also be enhanced by mixed-grazing. To our knowledge, this effect has never been studied in relation to differences in sward phytodiversity. Therefore, a rotational grazing experiment was conducted over 5 years (2007–2011) on permanent grassland in Germany using sheep and cattle in mono- (single-species) or mixed-grazing of swards differing in plant species richness. Herbicides against dicotyledonous plant species were used to create different sward types: species-poor, grass-dominated swards in contrast to untreated “diverse” control swards. We found no differences in herbage production between the sward types. However, compared to the grass-dominated sward, the diverse sward showed greater concentrations of crude protein and lower contents of acid detergent fiber in the herbage dry-matter. Lamb live weight gains were slightly greater on the diverse-swards (P < 0.05), but calf performance was unaffected by sward type. Mixed-grazing increased daily average live weight gains of suckler cows (g cow⁻¹ d⁻¹) (P < 0.05) as well as area-related daily live weight gains (kg ha⁻¹ d⁻¹) and total live weight gains (kg ha⁻¹) during the complete grazing season (P < 0.001). This indicates advantages of combining livestock species, attributed to complementary pasture use. We suggest that mixed-grazing of cattle and sheep on phytodiverse swards is an effective and sustainable means to enhance ecological and agronomic traits such as livestock production and plant species conservation. Lamb production especially showed benefits under mixed-grazing, with a 17% increase in live weight gain. Compared to the grass-dominated sward, diverse swards resulted in an average 12% increase of live weight gains (across grazing systems and livestock species).

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.