Leveraging energy flows to quantify microbial traits in soils

Heat dissipation from organic matter decomposition is a well-recognized proxy for microbial activity in soils, but only few modeling studies have used heat signals to quantify traits such as maximum substrate uptake rate, specific growth mortality and efficiency. In this contribution, hierarchy of coupled mass-energy balance models proposed estimate encoded model parameters using respiration data glucose induced activity. Moreover, the are explain observed variability calorespirometric ratios (CR)—the ratio rate. We parametrized four variants rates measured an isothermal calorimeter during lag-phase or whole growth-phase. The referred as: (i) complex physiological model, (ii) simplified (iii) (iv) growth-phase model. Model were determined three combinations data: A) B) C) both rates. assumed that ‘best’ parameter estimates those obtained when all (i.e., option C). All able fit estimated similar compared rate data, suggesting can be constrain traits. However, CR was not well captured by some contrast lag- predicted well. This suggests scrutinize how metabolic processes represented models.