A spatially explicit, agent-based model for simulating movements of cattle grazing corn residues

Crop residue grazing is considered one of the simplest and most economical approaches to integrate corn and cattle operations. Allowing cattle to graze crop residues left in the field after harvest can significantly lower feed costs for wintering cows; however, subsequent crop yield might be negatively affected. Developing management strategies to alleviate such impacts requires understanding the spatiotemporal characteristics of cattle location on cropland during grazing. This study has developed an agent-based approach to model cattle movement during crop residue grazing under various management scenarios, based on experimental data during a three-year residue grazing trial in Illinois. A GPS tracking system was implemented to track cattle locations during corn residue grazing under two grazing treatments (continuous grazing vs. strip grazing). The spatial dynamics of cattle movements were explicitly simulated as the results of behavioral decisions made by cattle, based on their internal biological state (e.g. hunger and hydration) and external environment (e.g. heterogeneous forage distribution, supplementation, water, day-night cycles, and management). Simulation results suggested that the model's performance was in good agreement with observed GPS data of cattle locations. This model can be used as an aid in future development of decision support for managing integrated crop-livestock systems.