From grazing lands to meat packing, beef production systems in the United States are striving to meet global demands without compromising environmental quality or local profitability. These challenges and opportunities are manifest in four US regions connected ecologically and socially through beef production: the American Southwest, the Ogallala Aquifer region, the Northern Plains, and the Upper Midwestern Corn Belt. Most calves raised on extensive, arid Southwestern ranches are exported to the Ogallala Aquifer region for finishing on grains that are grown either locally on Ogallala Aquifer water or imported from the Upper Midwest. Changes in climate, vegetation, and human demographics threaten the sustainability of the regionally-interconnected system. Heritage cattle genetics, precision ranching, and alternative supply chain options are three strategies that show promise for addressing these sustainability threats, but major knowledge gaps exist. For instance, while environmentally-friendly landscape use by Raramuri Criollo, a heritage cattle type, has been identified in several arid rangeland settings, little is known about their performance in conventional feed yards. While precision agriculture is already prevalent in croplands, less is known about how such technologies can be cost effective in arid rangelands. Moreover, many perceive grass-finishing on rangeland as environmentally friendly and beneficial for local agricultural communities, but tradeoffs involving greenhouse gas emissions, increased rangeland use, and disruption of cattle feeding systems of the Ogallala Aquifer region must be assessed. Here we introduce a USDA-NIFA Coordinated Agricultural Project designed to fill these knowledge gaps and advance sustainability of beef production linked to the US Southwest. With a boundary-spanning approach of education, participatory research, and extension, the project is identifying tradeoffs of the three strategies with explicit attention to pericoupling (i.e., socioeconomic and environmental interactions) of regions connected by beef production and full consideration of the coupled ecological and social systems within those regions.

Animal welfare monitoring relies on sensor accuracy for detecting changes in animal well-being. We compared the distance calculations based on global positioning system (GPS) data alone or combined with motion data from triaxial accelerometers. The assessment involved static trackers placed outdoors or indoors vs. trackers mounted on cows grazing on pasture. Trackers communicated motion data at 1 min intervals and GPS positions at 15 min intervals for seven days. Daily distance walked was determined using the following: (1) raw GPS data (RawDist), (2) data with erroneous GPS locations removed (CorrectedDist), or (3) data with erroneous GPS locations removed, combined with the exclusion of GPS data associated with no motion reading (CorrectedDist_Act). Distances were analyzed via one-way ANOVA to compare the effects of tracker placement (Indoor, Outdoor, or Animal). No difference was detected between the tracker placement for RawDist. The computation of CorrectedDist differed between the tracker placements. However, due to the random error of GPS measurements, CorrectedDist for Indoor static trackers differed from zero. The walking distance calculated by CorrectedDist_Act differed between the tracker placements, with distances for static trackers not differing from zero. The fusion of GPS and accelerometer data better detected animal welfare implications related to immobility in grazing cattle.

Virtual fencing systems have emerged as a promising technology for managing the distribution of livestock in extensive grazing environments. This study provides comprehensive documentation of the learning process involving two conditional behavioral mechanisms and the documentation of efficient, effective, and safe animal training for virtual fence applications on nursing Brangus cows. Two hypotheses were examined: (1) animals would learn to avoid restricted zones by increasing their use of containment zones within a virtual fence polygon, and (2) animals would progressively receive fewer audio-electric cues over time and increasingly rely on auditory cues for behavioral modification. Data from GPS coordinates, behavioral metrics derived from the collar data, and cueing events were analyzed to evaluate these hypotheses. The results supported hypothesis 1, revealing that virtual fence activation significantly increased the time spent in containment zones and reduced time in restricted zones compared to when the virtual fence was deactivated. Concurrently, behavioral metrics mirrored these findings, with cows adjusting their daily travel distances, exploration area, and cumulative activity counts in response to the allocation of areas with different virtual fence configurations. Hypothesis 2 was also supported by the results, with a decrease in cueing events over time and increased reliance with animals on audio cueing to avert receiving the mild electric pulse. These outcomes underscore the rapid learning capabilities of groups of nursing cows in responding to virtual fence boundaries.