Using mid-infrared spectroscopy to estimate soil microbial properties at the continental scale

Understanding microbial community properties is critical to improving the predictions of biogeochemical processes that govern soil carbon sequestration . In this observational study , mid-infrared (MIR) spectroscopy and partial least squares regression were used to estimate soil microbial and chemical properties from diverse ecosystems across the continental USA . Random validation technique suggested the estimation potential for soil microbial properties using MIR spectra , with the strongest estimations for microbial respiration, followed by microbial biomass nitrogen, β-glucosidase activity and microbial biomass carbon, as well as soil chemical properties including organic carbon and organic nitrogen . Microbial properties were mainly positively correlated to spectral regions associated with aliphatic C-H groups and C=O stretches of polysaccharides and negatively correlated to quartz and silicate-associated regions. Overall, this work suggests that MIR spectroscopy can characterize soil microbial properties and be useful for the improvement of continental scale soil carbon modeling and prediction programs. • Continental scale study of soil microbial properties and soil spectroscopy • Microbial properties estimated by spectra and partial least squares regression • Respiration, biomass C/N, and β-glucosidase activity best estimated by spectra • Microbial properties positively correlated with organics, negatively with minerals