Future Ecological Theory (FET): A Cross-Domain Verifiable Ecological Regulation Framework Based on Two-Stage Constrained Collision

Abstract

The Future Ecological Theory (FET) is an operable theoretical system centered on ecological systems and compatible with cross-domain applications. Its core framework is derived from the "two-stage constrained collision" logic: the generation operator \lozenge_C couples initial carriers and coupling carriers to generate an intermediate state (e.g., ecological energy flow), which is then integrated with environmental/physical constraints via the constraint decoding operator \otimes_D to ultimately emerge stable system outputs (e.g., community stability, monitoring accuracy). Supported by five axioms, the theory emphasizes modal representability, operator calibratability, and trigger criticality, realizing cross-domain mapping between ecological systems and fields such as quantum topology, quantum biology, and social information through a unified operator template. To validate the theory’s effectiveness, four reproducible numerical experiments were conducted: 1) Comparison of symbolic regression with/without dimensional constraints, demonstrating that dimensional constraints significantly improve the recovery rate of ecological formulas (especially under low-to-medium noise and sample sizes ≥300); 2) Energy efficiency analysis of wetware-hardware hybrid agents, showing that higher modal matching degrees enable hybrid systems to outperform pure digital solutions in both prediction accuracy and energy consumption; 3) Robustness testing of cross-domain mapping, revealing predictable sensitivity of system outputs to changes in coupling strength (\beta_C) and constraint slope (k); 4) Bifurcation and hysteresis verification under trigger thresholds and local amplification, confirming the existence of multi-stable regions and hysteretic behavior in ecological systems. Complementary ecological-focused experiments (ecological criticality test and hybrid agent demonstration) further validated the theory’s engineering applicability: setting the energy flow trigger threshold ≥0.03 and maximum gain amplification ≤3.0 can reduce community collapse probability to below 0.1 while maintaining low prediction error (~0.14–0.19) and energy consumption advantages for monitoring agents. All experiments provide complete parameters, reproducible code, and statistical results (including 95% confidence intervals), ensuring the theory’s falsifiability and practical operability. FET bridges theoretical ecology, cross-domain physics, and engineering applications, offering a systematic tool for ecological monitoring, community regulation, and hybrid agent optimization. Its emphasis on reproducibility, physical constraints, and cross-domain compatibility addresses key gaps in traditional ecological theories, providing actionable guidance for protecting ecological stability and advancing sustainable ecological management.