| 22 Jul 2026
The Implications of Microbial Functional Diversity on the Response of Soil Organic Matter Decomposition to Nitrogen Fertilization: A Theoretical Model
Abstract. Nitrogen (N) fertilization decreases carbon (C) decomposition, but there remain competing hypotheses underlying this response including reduced belowground C allocation, shifts in microbial diversity, and altered microbial function. Further, current soil organic matter (SOM) decomposition models lack the ability to test these hypothesized mechanisms. To theoretically test these mechanisms, we integrated the Carbon Acquisition Ecological Strategies (CAES) framework into the Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment (CORPSE) model. CAES represents a pathway for integrating functional diversity into microbial explicit soil decomposition models, with three microbial functional groups that specialize in decomposing and utilizing a different SOM pool: primary decomposers (1° decomposers) target complex SOM, secondary decomposers (2° decomposers) target microbial necromass, and passive consumers target simple SOM. We then used the refined model (Functional Group-CORPSE) to theoretically test hypotheses by leveraging long term data from a 30 year, watershed scale N fertilization experiment at the Fernow Experimental Forest in Parsons, WV. We performed modeling experiments to evaluate the microbial community response to varying C and N inputs, and to simulate hypothesized mechanisms of microbial response to N deposition. Varying substrate composition led to distinct microbial communities, reflecting substrate preferences between functional groups. However, only when both the function and abundance of complex C decomposers was reduced could FG-CORPSE capture the SOM dynamics observed at the Fernow. Collectively, our results show that FG-CORPSE enables the simulation of both functional and compositional shifts in microbial communities to facilitate the testing of microbe centric hypotheses for decomposition and C storage under N enrichment.
Integrating nutrient cycling dynamics and associated shifts in microbial community composition into Soil Organic Matter models is important to capture the complex interactions between soil nutrient and carbon dynamics and to advance our understanding of how changes in land-management affect soil carbon storage in the future. The authors address this challenge by adapting the existing CORPSE (Sulman et al., 2014) model to harbor three instead of just one microbial group (Functional Group-CORPSE) and define three distinct hypotheses of how nitrogen (N) deposition affects one of the newly defined microbial groups. The different hypotheses are then tested in scenario simulations of a 30-year N fertilization experiment and compared to corresponding catchment-scale observational data from the Fernow Experimental Forest. While the paper addresses an important and timely topic, there are several major concerns:
It is not clear how or whether at all nitrogen dynamics are represented in the model. The authors describe the use of the CORPSE model (Sulman et al., 2014) as the basis for the development of their functional group model and to test hypothesis about the effect of N deposition on microbial groups. However, the used version of CORPSE does not represent nitrogen dynamics and there is no indication suggesting that this was added to the model by the authors. This hinders a mechanistic representation of a microbial physiological response to N deposition. Instead, the hypothesized microbial physiological responses are implemented in an ad hoc manner by prescribing defined changes in individual parameter values for times when N deposition occurs. Thus, the model is not mechanistic and applicability to other scenarios is limited (how would microbial functionality respond to half, double, … the prescribed N deposition rate?). Beyond this limitation, it is not clear how robust the presented results (and hence conclusions) are to small variations in the altered parameter values that define the different scenarios or to the assumptions made in the implementation of the different hypothesis (see further comments below). Considering the large uncertainty in microbial parameters, the small differences between the tested scenarios (i.e., small changes in the numeric values of individual microbial parameters) are difficult to interpret mechanistically without additional extensive checks for robustness.
Previous developments of the CORPSE model have already included nitrogen dynamics as well as a coupling between soil microbial and plant dynamics (FUN-CORPSE, Sulman et al., 2017). Both these developments are immediately relevant to address the question raised here. In a recent publication (Ridgeway et al., 2026), FUN-CORPSE was indeed successfully used to generally capture the observed responses of soil carbon stocks to N deposition in seemingly the same (yet more extensive) dataset from the same experiment (30-year N fertilization in the Fernow Experimental Forest). In their study, the baseline implementation of FUN-CORPSE could reproduce the general effect of N deposition on soil C (increase in soil C and decrease in microbial biomass following N deposition) without invoking any of the processes tested here. While Ridgeway et al. (2026) acknowledge limitations in the representation of microbial community processes in their model, their results challenge the robustness of the presented results and conclusions.
Further comments:
It is not clear which and how model parameters were calibrated and how initialization was performed. How robust are the modeled microbial distributions to changes in initial conditions? Do they always converge to the same relative abundances or are other states possible? How would this affect results?
I struggle with the interpretation and implementation of some of the tested hypothesis. For instance, in H1 it is hypothesized that N deposition reduces 1° decomposer abundance, which was implemented by increasing the turnover rate of 1° decomposers when N deposition was active. While this forces the intended effect, it does not correspond to the hypothesized mechanism (reduced exudation of labile C from plants and hence reduced substrate supply for decomposers) but instead could be interpreted as a nitrogen-toxicity effect on 1° decomposers (i.e., an active dying of the organisms rather than reduced growth). In fact, all simulations show the hypothesized decline in degrader abundance making this process redundant. Decreased decomposer function (H3) is motivated by declining enzyme production, yet I wonder if this process can be regarded in isolation or whether this should be accompanied by an increase in CUE: microbes might use the resources they no longer invest into enzyme production to grow more efficiently? Instead, reduced CUE as in H2 might be associated with overflow respiration of carbon under N limitation rather than N addition (Manzoni et al., 2021). Generally, substrate and microbial stoichiometries might play an important role in regulating the microbial response to N deposition which could be considered more explicitly in the tested mechanisms.
A comparison of the here developed Functional Group-CORPSE to the base implementation of CORPSE would be helpful to understand the effect of including the functional groups. As the base implementation of CORPSE (Sulman et al., 2014) aims to implicitly capture a shift in microbial functional groups with a variable microbial turnover rate it would be interesting to see how this compares to an explicit representation of microbial functional groups.
A small mistake in Eq (1): as currently written, sum(M) would cancel in the last right-hand side term.
References
Manzoni, S., Chakrawal, A., Spohn, M., and Lindahl, B. D.: Modeling microbial adaptations to nutrient limitation during litter decomposition, Front. For. Glob. Change, 4, 686945, https://doi.org/10.3389/ffgc.2021.686945, 2021.
Ridgeway, J. R., Sulman, B. N., Weber, S. E., Juice, S. M., and Brzostek, E. R.: Microbially mediated nitrification improves modeled temperate forest responses to declining nitrogen deposition, Appl. Soil Ecol., 217, 106585, https://doi.org/10.1016/j.apsoil.2025.106585, 2026.
Sulman, B. N., Phillips, R. P., Oishi, A. C., Shevliakova, E., and Pacala, S. W.: Microbe-driven turnover offsets mineral-mediated storage of soil carbon under elevated CO2, Nat. Clim. Change, 4, 1099–1102, https://doi.org/10.1038/nclimate2436, 2014.
Sulman, B. N., Brzostek, E. R., Medici, C., Shevliakova, E., Menge, D. N. L., and Phillips, R. P.: Feedbacks between plant N demand and rhizosphere priming depend on type of mycorrhizal association, Ecol. Lett., 20, 1043–1053, https://doi.org/10.1111/ele.12802, 2017.