Revisiting diffusion-based moisture functions: why do they fail?. (February 2022) - Zheng, Jianqiu
Abstract: Diffusion-based moisture functions could provide insight into soil physical processes and potentially represent a more rigorous approach to model soil moisture-respiration relationships. However, large prediction bias remains when these functions are evaluated with field observations. Here we revisit the concept of diffusion limited substrate bioaccessibility by coupling Michaelis-Menten microbial uptake kinetics with linear mass transfer. The analytical solution of this microbial-substrate system demonstrates that moisture interacts with heterogeneous substrate distribution to control the dynamic transitions between diffusion- and reaction-limited regimes, leading to deviations of mean-field rates from spatially averaged rates. This result highlights the inadequacy of current simplified diffusion-based moisture functions in capturing the nonlinearity between substrate distribution and microbial utilization, and calls for continued development of effective upscaling approaches and experimental validation. Highlights: Diffusion-based moisture functions overlook soil spatial heterogeneity. Transitions between diffusion- and reaction-limited regimes are dynamic. Macroscopic rates deviate from spatially averaged rates. Microscale nonlinearity is not captured by diffusion-based moisture functions.