Modeling the Maximum Potential of Rotational Grazing

Rotational grazing has been a popular sustainable farming practice, which has been shown to increase yields and environmental health compared to continuous grazing. In this grazing system, land is divided into several paddocks, and the livestock is moved from one to another after some time, while empty paddocks are allowed to fallow. On the contrary, continuous grazing involves containing the animals in one singular fenced area. In this project, agent-based modeling was used in a computer simulation to show the dynamical change and interaction of the cows and the grass in different paddock situations and rotation periods over time. This simulation incorporates an explicit spatial structure, unlike previous models, and was created in NetLogo, a computer programming language that creates multi-agent environment and allows the user to interact with its interface. In this simulation, grass and cows were used as agents. Data was collected and analyzed from the resulting simulation. The health of the cows and the energy of the grass were used to quantitatively describe the productivity of the pasture. Several experiments were conducted to test different variables that would affect productivity by changing quantities on the NetLogo interface. The results from running the simulation show that the smallest herd of cows on a short rotation schedule will result in the most productive rotational grazing system. Nevertheless, the model proved that the most productive is a continuous grazing system. Further development of the simulation will be necessary to create more realistic conditions.