A Computational Taxonomy of Transport Failure in Coupled Biological Networks v2.0

A Computational Taxonomy of Transport Failure in Coupled Biological Networks v2.0 presents a multi-layer computational framework for classifying how coupled biological transport systems degrade, reroute, congest, and adapt under perturbation. Synthesizing seven computational twin studies across tissue, follicular, sensory, and microtubule-scale architectures, the paper separates transport into four measurable layers: diffusive spread, spatial routing, temporal transport morphology, and adaptive compensation. The study introduces routing-sensitive diagnostics including the Routing Coherence Index (RCI) and Flux Routing Coherence Index (FRCI), demonstrating that diffusion-based coherence metrics alone are insufficient to detect topological disruption. Distinct transport-failure phenotypes — bottleneck, fragmentation, modular partition, intrinsic decay, and regime shift — emerge with separable spatial and temporal signatures. Adaptive transport experiments further reveal architecture-specific compensation strategies: bottleneck systems optimize within fixed constraints, fragmented systems sacrifice efficiency to preserve reachability, and intact systems only develop corridor reinforcement under imposed structural asymmetry and repeated-use history. Negative results and failed universality claims are explicitly preserved, including the divergence of actively pumped microtubule regimes from passive dissipative systems. Rather than proposing a universal biological law, the framework introduces a portable computational diagnostic architecture for studying transport failure across coupled biological networks. All findings are computational, falsifiable, sensitivity-audited, and accompanied by preserved provenance and reproducibility constraints.