Horses can contribute to the maintenance of grassland. To determine the potential contribution of grassland to horse nutrition, we investigated the seasonal variation of herbage on offer and its nutritional quality in an inventory on six practical horse farms in Central Germany during 2019. On all horse-grazed pastures compressed sward height (CSH) was measured monthly and converted into aboveground herbage (AGH) to allocated short and tall grass sward areas (area-specific) via calibration cuts. In addition, four focus pastures were selected for monthly obtained area-specific herbage quality samples. The farm-specific management was monitored using questionnaires and grazing diaries to determine underlying factors influencing herbage biomass and quality. The proportion of short grass sward areas increased during the grazing season (p=0.0010), which was related to high stocking intensity in terms of livestock unit grazing days (LUGD, p <.0001). On most farms, LUGD were constant throughout the growing season and not adjusted to changing grass growth. Herbage crude protein (CP, p=0.0038), metabolizable energy (ME, p <.0001) concentrations and acid detergent fibre in the organic matter (ADF, p <.0001) differed among the grass sward areas. The results suggest that sufficient ME (4.2 +/- 0.32 - 8.4 +/- 0.15 MJ ME kg(-1) DM) for maintenance and pre-caecal digestible CP (pcdCP) (37.0 +/- 3.86 - 77.4 +/- 4.44 g kg(-1) DM) could be provided during the grazing season. The study highlights the need to incentivise grassland management for herbage provision among horse owners to exploit the potential of grassland during the grazing season.

Sensor technologies, such as the Global Navigation Satellite System (GNSS), produce huge amounts of data by tracking animal locations with high temporal resolution. Due to this high resolution, all animals show at least some co-occurrences, and the pure presence or absence of co-occurrences is not satisfactory for social network construction. Further, tracked animal contacts contain noise due to measurement errors or random co-occurrences. To identify significant associations, null models are commonly used, but the determination of an appropriate null model for GNSS data by maintaining the autocorrelation of tracks is challenging, and the construction is time and memory consuming. Bioinformaticians encounter phylogenetic background and random noise on sequencing data. They estimate this noise directly on the data by using the average product correction procedure, a method applied to information-theoretic measures. Using Global Positioning System (GPS) data of heifers in a pasture, we performed a proof of concept that this approach can be transferred to animal science for social network construction. The approach outputs stable results for up to 30% missing data points, and the predicted associations were in line with those of the null models. The effect of different distance thresholds for contact definition was marginal, but animal activity strongly affected the network structure.

Heterogeneous extensive grassland offers herbivores a variation of potential bite items (BI) from which they can select. But there is a lack of knowledge on the relationship between the actually available (BIa) and the grazed (BIg) BI diversity albeit this information is essential to understand grass sward composition. We assessed the BIa in the sward and the BIg to evaluate the BI diversity under two grazing intensities in two seasons in the replicated long-term grazing experiment Forbioben. The BIa diversity was measured pre-grazing using a modified sward stick (200 measurement points per 1-ha paddock) whereby at each point the botanical composition, phenological stage, color and height were recorded and consequently structured into BIa. Herbage samples were taken for each BI and analyzed via near-infrared-reflectance spectroscopy for the concentration of crude protein (CP), acid-detergent fiber in the organic matter (ADF), in vitro digestibility of the organic matter (ivdOM) and metabolizable energy (ME) and labeled as grazed and non-grazed. For the BIg diversity each cow was observed in the morning and afternoon four times, 2 min each on 1 d each season using an app for counting the bites and following video analysis to determine the composition of the BIg. A reduction in growth rates during the hot and dry summer might have caused the decline of BIa diversity of 25% under moderate and 22% under lenient grazing towards autumn (p < 0.0001). This also influenced the BIg as in spring 50% and 53% of the BIa diversity were grazed under moderate and lenient grazing, respectively. In autumn only 36% and 28% were grazed, respectively corresponding well to the generally lower herbage nutritive value of BI in autumn as the offered grassland resource changed over time and provided greater ivdOM and ME in spring compared to autumn (p < 0.0001). This shows a greater selectivity from the limited choice in autumn. All cows were able to maintain a good quality diet irrespective of grazing intensity which is underlined by the fact that the digestibility of ingested herbage was the same among the grazing intensities but greater in spring than in autumn.