Soil microbial communities drive essential ecosystem functions, catalyzing biogeochemical cycles and contributing to climate regulation. However, due to the complexity of microbial communities, the magnitude and direction of microbial biomass and diversity contributions to carbon (C) and nutrient cycling remain unclear. For this reason, most models predicting soil organic matter (SOM) dynamics at the ecosystem level do not explicitly describe the role of microorganisms as mediators of SOM decomposition. Incorporating microbial properties, and especially diversity, into ecosystem models remains an open question, requiring careful consideration of the tradeoff between model complexity and performance.

This work addresses this knowledge gap by implementing a simple C and nitrogen (N) cycling model to predict heterotrophic respiration and net N mineralization rates in soils sampled under different land-uses and tree health conditions across Spain. To understand the role of microorganisms on ecosystem functioning, we progressively incorporated microbial biomass and diversity (i.e., alpha diversity of taxa and of fungal functional groups), and selected the model that optimized prediction accuracy, while minimizing complexity.

We found that microbial biomass had a strong and positive effect on both C and N mineralization rates, with heterotrophic respiration being nearly linearly controlled by biomass. In contrast, microbial diversity had minimal but negative effects on mineralization processes, with land-use differences explaining part of the variability in these effects. Our study confirms microbial biomass as a key driver of C and N mineralization rates, while highlights that microbial diversity based on taxonomic identification inadequately explains microbial effects on these ecosystem functions.

Soil organic carbon (SOC) is the largest terrestrial carbon pool, but it is still uncertain how it will respond to climate change. Specifically, the fate of SOC due to concurrent changes in soil temperature and moisture is uncertain. It is generally accepted that microbially driven SOC decomposition will increase with warming, provided that sufficient soil moisture (and hence sufficient C substrate) is available for microbial decomposition. We use a mechanistic, microbially explicit SOC decomposition model, the Jena Soil Model (JSM), and focus on the depolymerisation of litter and microbial residues by microbes at different soil depths as well as the sensitivities of the depolymerisation of litter and microbial residues to soil warming and different drought intensities. In a series of model experiments, we test the effects of soil warming and droughts on SOC stocks, in combination with different temperature sensitivities (Q₁₀ values) for the half-saturation constant K_m (Q_10,Km) associated with the breakdown of litter or microbial residues. We find that soil warming can lead to SOC losses at a timescale of a century and that these losses are highest in the topsoil (compared with the subsoil). Droughts can alleviate the effects of soil warming and reduce SOC losses, by posing strong microbial limitation on the depolymerisation rates, and even lead to SOC accumulation, provided that litter inputs remain unchanged. While absolute SOC losses were highest in the topsoil, we found that the temperature and moisture sensitivities of K_m were important drivers of SOC losses in the subsoil – where microbial biomass is low and mineral-associated OC is high. Furthermore, a combination of drought and different Q_10,Km values associated with different enzymes for the breakdown of litter or microbial residues had counteracting effects on the overall SOC balance. In this study, we show that, while absolute SOC changes driven by soil warming and drought are highest in the topsoil, SOC in the subsoil is more sensitive to warming and drought due to the intricate interplay between K_m, temperature, soil moisture, and mineral-associated SOC.

Improved understanding of the mechanisms driving heterotrophic CO2 emissions after rewetting of a dry soil may improve projections of future soil carbon fate. While drying and rewetting (DRW) under laboratory conditions have demonstrated that heterotrophic CO2 emissions depend on DRW features and soil and environmental conditions, these laboratory insights have not been validated in field conditions. To this aim, we collated mean respiration rates over 48 h after rewetting from two data sources: 37 laboratory studies reporting data for more than 3 DRW cycles (laboratory respiration, LR) and 6 field datasets recording hourly heterotrophic respiration and soil moisture (field respiration, FR). LR and FR were explained by six predictors using random forest algorithms and partial dependence plots. Results indicated that the most important drivers of LR and FR were SOC and temperature, respectively. Both LR and FR increased with increasing SOC and temperature. LR increased with soil dryness before rewetting, but this trend was less clear in FR. LR decreased with soil moisture increments at rewetting, while FR increased with soil moisture increments. LR was higher in soils from humid climates than from arid climates, but this effect was not observed in FR. We concluded that laboratory insights could be partly validated with current datasets. Caution should be taken when extending laboratory insights for predicting fluxes in ecosystems.