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 time-series 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/spl trade/ modeling environment. The spread of invasive species is driven by the habitat quality layer, which regulates its dispersal rate.
['S. Clifton Parks', 'Maxim Garifullin', 'Rainer Dronzek']
Argus invasive species spread model constructed using agent-based modeling approach and cellular automata