Soils contain more carbon (C) than terrestrial (above ground) and atmospheric carbon combined. Mismanagement of soil C could lead to increased greenhouse gas emissions, whereas practices leading to increased C storage would help mitigate climate change while improving soil fertility and ecological functions. At the center of these complex feedbacks, soil microorganisms play a pivotal role in the cycling of C and nutrients, and thus in soil-climate interactions. However, this role is not fully understood; therefore, developing new methods for studying their dynamics is essential for an understanding of bio-physicochemical processes leading to mineralization or stabilization of soil organic matter (SOM).

Current soil C cycling models lack a robust upscaling approach that links SOM decomposition from process (μm) to observation scale (cm to km). Moreover, these models often neglect energy fluxes from microbial metabolism, which may provide additional constraints in model parameterization and alternative observable quantities such as heat dissipation rate to study decomposition processes. In this doctoral work, I investigated two aspects of microbial processes and their consequences for SOM dynamics: 1) use of energetics to constrain SOM dynamics by explicitly accounting for thermodynamics of microbial growth, and 2) spatial constraints at microscale resulting from the non-uniform distribution of microorganisms and substrates.

In the first part of the thesis, I developed a general mass and energy balance framework for the uptake of added substrates and native SOM. This framework provided the theoretical underpinnings for understanding variations in the calorespirometric ratios—the ratio of rates of heat dissipation to CO2 production—a useful metric used as a proxy for microbial carbon-use efficiency (CUE). Moreover, in a follow-up work, I extended this mass-energy framework to describe dynamic (time-varying) conditions, which was used to interpret rates of heat and CO2 evolution from different soils amended with glucose. The dynamic mass-energy framework was also used as a tool for data-model integration and estimation of microbial functional traits, such as their CUE and maximum substrate uptake rates. In the second part of the thesis, I linked the micro and macroscale dynamics of decomposition using scale transition theory. The findings of this study were further validated from laboratory experiments, in which spatial heterogeneity in the added substrate was manipulated.

Results from the first part show that the calorespirometric ratios can be used to identify active metabolic pathways and to estimate CUE. Further, the heat dissipation rate can be used as a reliable complement or alternative to mass fluxes such as respiration rates for estimating microbial traits and constraining model parameters. In the second part, I show that the co-location of microorganisms and substrates increased, and separation decreased the microbial activity measured as heat dissipation from the incubation experiment. These results were in line with the expectation from the scale transition theory. In summary, this work provides novel approaches for studying soil C cycling and explicitly highlights a way forward to address two fundamental issues in microbial decomposition—the role of spatial heterogeneities and of energetic constraints on microbial metabolisms.