Dissolved organic matter (DOM) fuels the majority of in-stream microbial processes, including the removal of nitrate via denitrification. However, little is known about how the chemical composition of DOM influences denitrification rates. Water and sediment samples were collected across an ecosystem gradient, spanning the alpine to plains, in central Colorado to determine whether the chemical composition of DOM was related to denitrification rates. Laboratory bioassays measured denitrification potentials using the acetylene block technique and carbon mineralization via aerobic bioassays, while organic matter characteristics were evaluated using spectroscopic and fractionation methods. Denitrification potentials under ambient and elevated nitrate concentrations were strongly correlated with aerobic respiration rates and the percent mineralized carbon, suggesting that information about the aerobic metabolism of a system can provide valuable insight regarding the ability of the system to additionally reduce nitrate. Multiple linear regressions (MLR) revealed that under elevated nitrate concentrations denitrification potentials were positively related to the presence of protein-like fluorophores and negatively related to more aromatic and oxidized fractions of the DOM pool. Using MLR, the chemical composition of DOM, carbon, and nitrate concentrations explained 70% and 78% of the observed variability in denitrification potential under elevated and ambient nitrate conditions, respectively. Thus, it seems likely that DOM optical properties could help to improve predictions of nitrate removal in the environment. Finally, fluorescence measurements revealed that bacteria used both protein and humic-like organic molecules during denitrification providing further evidence that larger, more aromatic molecules
are not necessarily recalcitrant in the environment.
Barnes, R.T., R.L. Smith, and G.R. Aiken (2012): Linkages between denitrification and organic matter quality, Boulder Creek Watershed, CO. Journal of Geophysical Research- VOL. 117, G01014, 14 PP. DOI: 10.1029/2011JG001749
This Paper/Book acknowledges NSF CZO grant support.