The bioreactivity or susceptibility of dissolved organic matter (DOM) to microbial degradation in streams and rivers is of critical importance to global change studies, but a comprehensive understanding of DOM bioreactivity has been elusive due, in part, to the stunningly diverse assemblages of organic molecules within DOM. We approach this problem by employing a range of techniques to characterize DOM as it flows through biofilm reactors: dissolved organic carbon (DOC) concentrations, excitation emission matrix spectroscopy (EEMs), and ultrahigh resolution mass spectrometry.
The EEMs and mass spectral data were analyzed using a combination of multivariate statistical approaches. We found that 45% of stream water DOC was biodegraded by microorganisms, including 31–45% of the humic DOC. This bioreactive DOM separated into two different groups: (1) H/C centered at 1.5 with O/C 0.1–0.5 or (2) low H/C of 0.5–1.0 spanning O/C 0.2–0.7 that were positively correlated (Spearman ranking) with chromophoric and fluorescent DOM (CDOM and FDOM, respectively). DOM that was more recalcitrant and resistant to microbial degradation aligned tightly in the center of the van Krevelen space (H/C 1.0–1.5, O/C 0.25–0.6) and negatively correlated (Spearman ranking) with CDOM and FDOM. These findings were supported further by principal component analysis and 2-D correlation analysis of the relative magnitudes of the mass spectral peaks assigned to molecular formulas.
This study demonstrates that our approach of processing stream water through bioreactors followed by EEMs and FTICR-MS analyses, in combination with multivariate statistical analysis, allows for precise, robust characterization of compound bioreactivity and associated molecular level composition.
Sleighter, R. L., R. M. Cory, L. A. Kaplan, H. A. N. Abdulla, and P. G. Hatcher (2014): A coupled geochemical and biogeochemical approach to characterize the bioreactivity of dissolved organic matter from a headwater stream. Journal of Geophysical Research: Biogeochemistry 119 (8):1520-1537. DOI: 10.1002/2013JG002600
This Paper/Book acknowledges NSF CZO grant support.