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

Abstract

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.