The forest fire model in statistical physics represents a paradigm for systems close to but not completely at criticality. For large tree growth probabilities $p$ we identify periodic attractors, where the tree density $\rho$ oscillates between discrete values. For lower $p$ this self-organized multistability persists with incrementing numbers of states. Even at low $p$ the system remains quasiperiodic with a frequency $\approx p$ on the way to chaos. In addition, the power-spectrum shows $1/f^2$ scaling (Brownian noise) at the low frequencies $f$, which turns into white noise for very long simulation times.

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• Cellular automata
• Chaos
• Self-organized systems
• Stochastic processes
• Lattice models in statistical physics
• Multiple time scale dynamics
• Stochastic dynamical systems
• Chaos & nonlinear dynamics
• Time series analysis