Ecosystems as adaptive living circuits

TL;DR

This paper introduces a framework for understanding ecosystems as adaptive living circuits that self-organize their structure and energy dissipation, revealing a phase transition from equilibrium to dissipative states driven by local feedback mechanisms.

Contribution

It develops a novel theoretical framework modeling ecosystems as adaptive circuits with structure that coevolves with energy dissipation, highlighting a phase transition and emergent complexity.

Findings

Ecosystems exhibit a phase transition from equilibrium to dissipative states.

Adaptive rules lead to near-maximal dissipation without global optimization.

Higher energy drive results in more complex circuit structures.

Abstract

Unlike many physical nonequilibrium systems, in biological systems, the coupling to external energy sources is not a fixed parameter but adaptively controlled by the system itself. We do not have theoretical frameworks that allow for such adaptability. As a result, we cannot understand emergent behavior in living systems where structure formation and non-equilibrium drive coevolve. Here, using ecosystems as a model of adaptive systems, we develop a framework of living circuits whose architecture changes adaptively with the energy dissipated in each circuit edge. We find that unlike traditional nonequilibrium systems, living circuits exhibit a phase transition from equilibrium death to a nonequilibrium dissipative state beyond a critical driving potential. This transition emerges through a feedback mechanism that saves the weakest edges by routing dissipation through them, even though the adaptive rule locally rewards the strongest dissipating edges. Despite lacking any global optimization principle, living circuits achieve near-maximal dissipation, with higher drive promoting more complex circuits. Our work establishes ecosystems as paradigmatic examples of living circuits whose structure and dissipation are tuned through local adaptive rules.