Abstract
Heat dissipation from organic matter decomposition is a well-recognized proxy for microbial activity in soils, but only a few modeling studies have used heat signals to quantify microbial traits such as maximum substrate uptake rate, specific growth rate, mortality rate, and growth efficiency. In this contribution, a hierarchy of coupled mass-energy balance models is proposed to estimate microbial traits encoded in model parameters using heat dissipation and respiration data from glucose induced microbial activity. Moreover, the models are used to explain the observed variability in calorespirometric ratios (CR)—the ratio of heat dissipation to respiration rate. We parametrized four model variants using heat dissipation and respiration rates measured in an isothermal calorimeter during the lag-phase only or during the whole growth-phase. The four variants are referred to as: (i) complex physiological model, (ii) simplified physiological model, (iii) lag-phase model, and (iv) growth-phase model. Model parameters were determined using three combinations of data: A) only the heat dissipation rate, B) only the respiration rate, and C) both heat dissipation and respiration rates. We assumed that the ‘best’ parameter estimates were those obtained when using all the data (i.e., option C). All model variants were able to fit the observed heat dissipation and respiration rates. The parameters estimated using only heat dissipation data were similar to the ‘best’ estimates compared to using only respiration rate data, suggesting that the observed heat dissipation rate can be used to constrain microbial models and estimate microbial traits. However, the observed variability in CR was not well captured by some model variants such as the simplified physiological model, in contrast to the lag- and growth-phase model that predicted CR well. This suggests that CR can be used to scrutinize how well metabolic processes are represented in decomposition models.
Highlights
The activity of microorganisms in soils—a crucial driver of carbon (C) cycling—is mediated by functional traits that determine microbial responses to environmental conditions
Here we study the causes of variability in observed calorespirometric ratio (CR) using our coupled C and energy balance models and assess whether CR can be used to test model predictions of microbial metabolism
In the experiments we aim to model, a known amount of external substrate is added to soils, and the microbial response is measured as respiration and/or heat dissipation rates
Summary
The activity of microorganisms in soils—a crucial driver of carbon (C) cycling—is mediated by functional traits that determine microbial responses to environmental conditions. To assess these traits, measure ments of microbial respiration rate are often combined with stable isotope tracing. The oxidation state of organic matter cannot be obtained only from CO2 data but the combination of CO2 with oxygen uptake rate (Maskow et al, 2010) This leaves a potential gap between theory development and testing, which can be partly filled by leveraging complementary information, such as that provided by heat exchange measurements (Braissant et al, 2013; Maskow and Paufler, 2015; Chakrawal et al, 2020). We explore the potential of heat dissi pation measurements for estimating microbial traits encoded in model parameters
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