A cellular automata model for population dynamics simulation of two plant species with different life strategies

Physical and social systems can be conceptualized in complexity theory which provides a framework for a refined analysis of local effects on global behaviors. And spatial dynamic models based on discrete time can be referred to as cellular automata (henceforth CA) models, which show advantages for modeling complex systems in a way that is conceptually clearer, more accurate and more complete than most conventional models of natural phenomena. In order to acquire more general knowledge of the behavior of complex natural systems, in this paper, we compare different life strategies of two plant species, i.e., Changium Smyrnioides and Anthriscus Sylvestris, via population dynamics simulations based on a spatially explicit CA model. And we further analyze some emergent effects (reproductive rate and the minimum viable population in particular) based on statistic features from the field investigated data. The results show that C. smyrnioides adopts a population reproducing strategy of low reproductive rate and low space occupying, with stable population dynamics, while the strategy of A. sylvestris can be characterized as high reproductive rate and space occupying, with unstable population dynamics under habitat fragmentation. Therefore, in the environment with external disturbances, the alternative strategies may lead to divergent global behaviors and patterns in the long-term, which is indeed the case in reality that C. smyrnioides turned to be an endangered species and A. sylvestris turned to be an invasive one, respectively.