Use of Biometric Tags and Remote Sensing to Monitor Grazing Behavior, Forage Production, and Pasture Utilization in Extensive Landscapes

Wearable sensors and remote sensing technologies are rapidly increasing opportunities to measure grazing animal behavior, energetics, and performance in extensive rangeland systems. However, despite significant advances in device capabilities, the livestock sector lacks an ecological framework that connects sensor data to the metabolic processes driving animal growth and efficiency. In this paper, we apply the movement ecology paradigm to grazing beef cattle as a demonstration of how metabolic theory, animal behavior, and landscape heterogeneity interact to influence energy budgets. We first describe the mechanistic relationships among basal metabolism, thermoregulation, activity, and forage intake, highlighting how movement patterns reflect underlying metabolic states. Next, we review key variables measurable through modern sensors, including GPS, accelerometers, rumen temperature boluses, and remote sensing of forage quantity and quality and explain how these data can be integrated into an information system to estimate energy expenditure, resource selection, and physiological stress. Finally, we show how combining movement, behavioral, and landscape data can yield meaningful indicators of performance and health, paving the way for precision livestock management grounded in ecological principles. Integrating metabolic and movement ecology with emerging technologies offers a strong framework for enhancing efficiency, welfare, and sustainability in grazing beef systems.