Agent-based simulation of Muscovy duck movements using observed habitat transition and distance frequencies

This paper presents an agent based model simulating animal tracking datasets for individual animals based on observed habitat use characteristics, movement behaviours and environmental context. The model is presented as an alternative simulation methodology for movement trajectories for animal agents, useful in home range, habitat use and animal interaction studies. The model was implemented in NetLogo 5.1.0 using observed behavioural data for the Muscovy duck, obtained in a previous study. Four test scenarios were completed to evaluate the fidelity of model results to behavioural patterns observed in the field. Results suggest the model framework illustrated in this paper provides an effective alternative to traditional animal movement simulation methods such as correlated random walks.