Estimating the biomass of microbial functional groups using rates of growth-related soil respiration

We developed a simple method that can be used to estimate the biomass and growth rates of microbial functional groups in soil. The method is derived from basic principles and can be used to estimate the biomass of organisms that can mineralize specific substrates added to soil. We adapted the substrate-induced growth-response (SIGR) model that was originally used to analyze curves of substrate disappearance or cumulative CO2 production. The present model utilizes data describing the rate of CO2 production from substrates added to soil. We used two unique systems to demonstrate the applicability of this method. In one test of the model we added glucose to alpine tundra soil to estimate the biomass that could respond to a labile carbon source. We also derived biomass estimates from a widely used substrate-induced respiration (SIR) model for the same soil. Overall the SIGR method yielded conservative biomass estimates (mean = 194 micrograms C g-1 soil) when compared to the SIR estimates (mean = 436 micrograms C g-1 soil). In the second test we used a soil to which a known biomass of a specific functional group (i.e. pentachlorophenol-mineralizers) was added. In this case the SIGR method also gave a conservative estimate of 0.05 micrograms C g-1 compared to a death-rate adjusted value of 0.11 micrograms C g-1 for the actual inoculum added to the soil. The SIGR model also estimated maximum specific growth rates (0.11-0.12 h-1) similar to those measured in independent experiments (0.09 h-1) for the Sphingomonas sp. that was added to the soil. Using our model we were able to obtain biomass estimates and growth rates for microbial functional groups without using calibrations needed for other physiological methods. Overall the SIGR approach gives conservative estimates of the active biomass that can mineralize specific carbon substrates added to soil.