Microbial biomass – not diversity – drives soil carbon and nitrogen mineralization in Spanish holm oak ecosystems - Bruni, Elisa; Yuste, Jorge Curiel; Menichetti, Lorenzo; Flores, Omar; Guasconi, Daniela; Guenet, Bertrand; Hereș, Ana-Maria; Lehtonen, Aleksi; Mäkipää, Raisa; Pallandt, Marleen; Pérez-Izquierdo, Leticia; Richy, Etienne; et al. (Elsevier, 2025)
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.
Keywords: biogeochemistry; modeling; climate change; microorganisms; biodiversity; forest soil