The potential and challenges of dynamic models for investigating microbial processes in soil using the Calorespirometric Ratio

Soil microbes obtain carbon (C), energy and nutrients from their environment to grow and to sustain themselves. Some of the matter and energy entering microbial metabolism leaves the soil system, e.g., as CO₂ and heat, while some is recycled via microbial death and turnover. All these matter and energy flows are intimately coupled according to stoichiometric relationships and the laws of thermodynamics, and unraveling the details of this coupling is essential for our understanding of soil functions mediated by microbes such as nutrient cycling and carbon storage.

The ratio of heat to CO₂ release, the so-called Calorespirometric Ratio (CR), obtained from soil incubation experiments with substrate amendment has been shown to hold valuable information about the major active metabolic pathways of the microbial community and the C and energy use efficiency. However, due to the complex and obscure nature of the soil system, measured CR values always require mechanistic models of the underlying processes for proper interpretation.

Here, we illustrate both the potential and the limitations of simple dynamic bioenergetic models for explaining experimental CR data and formulating testable hypotheses. For example, we highlight how such models may reveal shifts in metabolic pathways during growth and give clues about the dominant microbial sources of CO₂ and heat in the absence of easily degradable C substrates, e.g., during maintenance and turnover, based on observed temporal CR patterns.

At the same time, the CR framework and associated models face important challenges. First, the CR represents the black box sum of all heat and CO_2­ producing processes, and this complication can lead to different conclusions being drawn from the same data. Based on experiments with glucose amended soil, we explain how the CR pattern observed during the retardation phase after glucose depletion might be interpreted as resulting from either the decomposition of SOM or the formation of necromass or a combination of both. While this challenge prevents a definitive interpretation based on CO_{2 ­}and heat data alone, it can nonetheless play a vital role in informing and designing future experiments.

Second, evaluating the temporal patterns of the CR relies on synchronous measurements of heat and CO₂. In contrast, these two quantities are often measured separately in experiments, and their different diffusion rates may also cause a delay of CO₂ relative to heat in the case of simultaneous measurement. We demonstrate that even small shifts in the relative timing can cause a characteristic artificial pattern in observed CR data, with initially high CR values followed by a pronounced drop. We finally indicate how this issue may be accounted for in the structure of the dynamic models.

In summary, we present two major challenges – the black box nature of CR and shifts in relative timing – that arise from the interpretation of experimental rates of heat and CO₂ release using mechanistic dynamic models, and we show how these issues may be addressed, and even leveraged, to advance our understanding of microbial processes in soil.