The role of fungi in soil ecosystem sustainability is poorly understood, as is the extent to which it is affected by the microscale heterogeneity of soils with respect to structure, chemistry and biology. This is due to the complexity of soil ecosystems, presenting significant challenges to their study in situ. Many theoretical and simulation models have been developed to link nutrient levels to colony dynamics. Unfortunately, there is currently no model that can take both structural and nutritional microscale heterogeneity into account, and is parameterised for the soil environment. In this context, the objective of this article is to develop such a 3D spatially explicit model of fungal dynamics, and to calibrate it for a soil system using data from the literature. A sensitivity analysis is carried out to better understand the uncertainties in the input parameters and their effect on colony dynamics in terms of biomass yield and respiration rates. The results highlight simulation outcomes that are most suited to validation by experimentation. The results also indicate that predictions in biomass yield are sensitive to uncertainties in model parameters relative to the soil–fungal complex that at this point are insufficiently understood experimentally and still have to be estimated by model fitting. The latter parameters, which influence biomass yield and respiration, are associated with biomass recycling processes such as adsorption (,αni) desorption (βni, βi), insulation (ζni) and biomass yield efficiency (ɛ1), and translocation (Dv). The model now opens up great opportunities for hypothesis-driven research, combining theoretical models and novel types of experimentation, especially given the recently acquired ability to generate artificial, replicable soil-like microcosms on which to test model predictions.
Cazelles, K., Otten, W., Baveye, P. C., & Falconer, R. E. (2013). Soil fungal dynamics: parameterisation and sensitivity analysis of modelled physiological processes, soil architecture and carbon distribution. Ecological Modelling, 248, 165-173. https://doi.org/10.1016/j.ecolmodel.2012.08.008