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The many species of larkspur (Delphinium spp.) present one of the most serious, intractable, and complex challenges to livestock grazing management in the western United States. Larkspur plants contain numerous norditerpinoid alkaloids, which are potent neuromuscular paralytics that are particularly effective at killing cattle, with yearly herd losses estimated at 2-5% for those grazing in larkspur habitat. In addition, producers will often abandon or delay grazing in pastures with larkspur present, which creates a substantial opportunity cost and an impediment to the achievement of grazing management goals. Among the many challenges to improving our understanding of cattle-larkspur dynamics has been the difficulty of testing different grazing management strategies in the field, as the risk of dead animals is too great. Agent-based models (ABMs) provide a method of realistically testing alternate management strategies without risk to livestock. ABMs are bottom-up computational simulation tools that model the behavior of individuals as they interact with one another and the environment. They have been effectively applied in numerous disciplines, and have been recommended as an essential tool for understanding and managing complexity. We will introduce a spatially-explicit, behavior-based ABM of cattle grazing a real pasture with a dangerous amount Geyer�s larkspur (D. geyeri). This model provides significant insight for producers dealing with larkspur and demonstrates the great potential of ABMs to address questions in livestock grazing management, including not just other discrete challenges but also fundamental aspects of livestock behavior amidst heterogeneity.