Simulating ectomycorrhiza in boreal forests: implementing ectomycorrhizal fungi model MYCOFON in CoupModel (v5)

The symbiosis between plants and Ectomycorrhizal fungi (ECM) is shown to considerably influence the carbon (C) and nitrogen (N) fluxes between the soil, rhizosphere, and plants in boreal forest ecosystems. However, ECM are either neglected or presented as an implicit, undynamic term in most ecosystem models, which can potentially reduce the predictive power of models. In order to investigate the necessity of an explicit consideration of ECM in ecosystem models, we implement the previously developed MYCOFON model into a detailed process-based, soil–plant–atmosphere model, Coup-MYCOFON, which explicitly describes the C and N fluxes between ECM and roots. This new Coup-MYCOFON model approach (ECM explicit) is compared with two simpler model approaches: one containing ECM implicitly as a dynamic uptake of organic N considering the plant roots to represent the ECM (ECM implicit), and the other a static N approach in which plant growth is limited to a fixed N level (nonlim). Parameter uncertainties are quantified using Bayesian calibration in which the model outputs are constrained to current forest growth and soil C ∕ N ratio for four forest sites along a climate and N deposition gradient in Sweden and simulated over a 100-year period. The nonlim approach could not describe the soil C ∕ N ratio due to large overestimation of soil N sequestration but simulate the forest growth reasonably well. The ECM implicit and explicit approaches both describe the soil C ∕ N ratio well but slightly underestimate the forest growth. The implicit approach simulated lower litter production and soil respiration than the explicit approach. The ECM explicit Coup–MYCOFON model provides a more detailed description of internal ecosystem fluxes and feedbacks of C and N between plants, soil, and ECM. Our modeling highlights the need to incorporate ECM and organic N uptake into ecosystem models, and the nonlim approach is not recommended for future long-term soil C and N predictions. We also provide a key set of posterior fungal parameters that can be further investigated and evaluated in future ECM studies.