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Pyrolysis-molecular beam mass spectrometry to characterize soil organic matter composition in chemically isolated fractions from differing land uses
Authors:Alain F. Plante  Kim Magrini-Bair  Merle Vigil  Eldor A. Paul
Affiliation:1. Department of Earth & Environmental Science, University of Pennsylvania, Hayden Hall, 240 South 33rd Street, Philadelphia, PA, 19104-6316, USA
2. National Renewable Energy Laboratory, Golden, CO, 80401, USA
3. USDA-ARS, Akron, CO, 80720, USA
4. Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, 80521-1499, USA
Abstract:Today’s questions concerning the role of soil organic matter (SOM) in soil fertility, ecosystem functioning and global change can only be addressed through knowledge of the controls on SOM stabilization and their interactions. Pyrolysis molecular beam mass spectrometry (py-MBMS) provides a powerful and rapid means of assessing the biochemical composition of SOM. However, characterization of SOM composition alone is insufficient to predict its dynamic behavior. Chemical fractionation is frequently used to isolate more homogeneous SOM components, but the composition of fractions is frequently unknown. We characterized biochemical SOM composition in two previously studied soils from the USA, under contrasting land uses: cultivated agriculture and native vegetation. Bulk soils, as well as chemically isolated SOM fractions (humic acid, humin and non-acid hydrolysable), were analyzed using py-MBMS. Principal components analysis (PCA) showed distinct differences in the SOM composition of isolated fractions. Py-MBMS spectra and PCA loadings were dominated by low molecular weight fragments associated with peptides and other N-containing compounds. The py-MBMS spectra were similar for native whole-soil samples under different vegetation, while cultivation increased heterogeneity. An approach based on previously published data on marker signals also suggests the importance of peptides in distinguishing samples. While the approach described here represents significant progress in the characterization of changing SOM composition, a truly quantitative analysis will only be achieved using multiple internal standards and by correcting for inorganic interference during py-MBMS analysis. Overall, we have provided proof of principle that py-MBMS can be a powerful tool to understand the controls on SOM dynamics, and further method development is underway.
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