Livestock distribution in extensive rangelands of North America can present management challenges to
land managers. Understanding the role of topography on livestock distribution, within and across diverse
rangeland ecosystems, could provide land managers valuable information for adaptive management of
livestock to address both conservation and production goals from these ecosystems. Here, we examine
the influence of topography on grazing distribution unevenness and intensity of use of beef cattle in seven rangeland ecosystems spanning arid, semiarid, and subtropical environments. We focused on grazing distribution during the late growing season (summer and autumn) periods when topographic variation in rangelands is more coupled to low and nonuniform availability of high-quality forage. Pasture size and water sources strongly influence grazing distribution across ecosystems. High unevenness of grazing occurred in pastures with extensive distances to water, low stock density, and more rugged topography. Conversely, more uniform grazing distribution occurred in smaller, well-watered pastures that support higher stock density (animals per unit area) and gentler terrain. Comparison of two topographic indices, topographic wetness index and topographic position class index, in terms of their ability to predict cattle grazing distribution, revealed that categorical topographic position classes were more effective. For most arid and semiarid rangelands, livestock grazing distributions showed affinities for lowlands and flat plains compared with open slopes and uplands. In contrast to drier rangelands, livestock grazing distributions exhibited preference for upland and sloped areas of subtropical pastures, as low-lying areas with water-inundation likely curtailed selection. Across these diverse rangeland ecosystems of North America, results provide benchmark information on livestock grazing distribution to formulate improvements in adaptive management and decision making and incorporate technological advancements in precision livestock management to integrate abiotic environmental information with spatial movements of livestock and temporal vegetation dynamics.