Quantification of multiple simultaneously occurring nitrogen flows in the euphotic ocean
- 1State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
- 2Shenzhen Marine Environment Monitoring Center Station, State Oceanic Administration, Shenzhen, China
- 3National Marine Environmental Monitoring Center, Dalian, China
- 4Environmental Sciences Department, School of the Coast & Environment, Louisiana State University, Baton Rouge, USA
Abstract. The general features of the N cycle in the sunlit region of the ocean are well known, but methodological difficulties have previously confounded simultaneous quantification of transformation rates among the many different forms of N, e.g., ammonium (NH4+), nitrite (NO2−), nitrate (NO3−), and particulate/dissolved organic nitrogen (PN/DON). However, recent advances in analytical methodology have made it possible to employ a convenient isotope labeling technique to quantify in situ fluxes among oft-measured nitrogen species within the euphotic zone. Addition of a single 15N-labeled NH4+ tracer and monitoring of the changes in the concentrations and isotopic compositions of the total dissolved nitrogen (TDN), PN, NH4+, NO2−, and NO3− pools allowed us to quantify the 15N and 14N fluxes simultaneously. Constraints expressing the balance of 15N and 14N fluxes between the different N pools were expressed in the form of simultaneous equations, the unique solution of which via matrix inversion yielded the relevant N fluxes, including rates of NH4+, NO2−, and NO3− uptake; ammonia oxidation; nitrite oxidation; DON release; and NH4+ uptake by bacteria. The matrix inversion methodology that we used was designed specifically to analyze the results of incubations under simulated in situ conditions in the euphotic zone. By taking into consideration simultaneous fluxes among multiple N pools, we minimized potential artifacts caused by non-targeted processes in traditional source–product methods. The proposed isotope matrix method facilitates post hoc analysis of data from on-deck incubation experiments and can be used to probe effects of environmental factors (e.g., pH, temperature, and light) on multiple processes under controlled conditions.