Multi-scale biophysical modeling of fungal colony growth

Fungal colony growth is governed by hyphal elongation, branching, and anastomosis, forming intricate foraging networks. High-performance computing models capture these mechanics but are too computationally expensive for integrating into ecosystem simulators. Utilizing the BMX framework, researchers have developed a multiscale simulation method that combines detailed hyphal mechanics with a stochastic traveling-wave surrogate.

This approach reduces computational cost significantly while preserving essential accuracy. By focusing on demographic fluctuations at the colony's leading edge, the framework distinguishes between the directed movement of individual hyphae and their collective diffusion, accurately modeling the negative autotropism observed in 3D networks.

Simulations match experimental traveling wave patterns and reveal that interior network density stabilizes under nutrient-rich conditions through self-regulation by fusion. Sensitivity analysis highlights distinct microscopic parameters influencing expansion speed and network density. The physics of hyphal growth allows for networks that are both fast and dense, challenging the traditional trade-off between exploratory and exploitative strategies seen in nature.

Instead, metabolic constraints on local growth rules appear to be at play. This mathematically robust method bridges the gap between exascale-level cellular mechanics and macroscopic wave dynamics, facilitating the integration of trait-driven fluxes and carrying capacities into large-scale biogeochemical models.