Simulating Nature: Cellular Automata in a Coding Journey to Ecological Modeling

ABSTRACT

Cellular automata (CA) have become an invaluable tool for simulating complex ecological processes, offering a computationally efficient approach to modeling spatially explicit dynamics. In ecological contexts, CA models can capture the emergent behaviors and nonlinear interactions that characterize real‐world ecosystems. This paper introduces a hands‐on, code‐driven approach to using CA in ecology through the development of the R package cellulaR . The package provides three core functions for simulating species and vegetation spread: c.neutral() , which models neutral spread on a homogeneous grid; c.fractal() , which generates a heterogeneous fractal landscape to simulate spatial variability; and c.weighted() , which combines the fractal landscape with terrain‐based effects, such as slope and habitat suitability, to simulate more ecologically realistic spread and mortality patterns. By demonstrating the practical implementation of these functions, this paper illustrates how cellulaR provides a lightweight and accessible framework for exploring selected ecological cellular‐automata concepts, including neutral spread, landscape heterogeneity, and environmentally weighted colonization dynamics. Ultimately, this work provides a practical introduction to ecological modeling with cellular automata, illustrating how simple CA rules can be implemented and extended within ecological simulation workflows.