Argus Invasive Species Spread Model Constructed Using Agent-based Modeling Approach and Cellular Automata
S. Clifton Parks, Maxim Garifullin, Rainer Dronzek, Winter Simulation Conference-2005
science and education
agent based modeling
The stochastic Argus Invasive Species Spread Model (AISSM) is constructed using an Agent-Based Modeling (ABM) approach with cellular automata (CA) to account for spatial relationships and changes in those relationships over time. The model was constructed to support a wide range of geographical locations; however, this paper focuses on its application in the state of California. A timeseries of daily historical weather observations on a 6- kilometer grid was obtained for six weather variables important to insect and disease development. Weather conditions were then simulated using the K- nearest neighbor (K-nn) regional weather generator. The weather simulations were summarized into a monthly time-step and coupled with satellite land cover imagery to identify a habitat quality for each simulated month. This information was combined with the introduction of invasive species in the AnyLogic™ modeling environment. The spread of invasive species is driven by the habitat quality layer, which regulates its dispersal rate.