Simulation of the volume-dependent changes in ẟ15N and ẟ18O for IAEA-NO3 and USGS-34 reference materials.

Table of Contents

• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Data Files
• Parameters
• Project Information
• Funding

Sampling and analytical procedures: 


Effects of sample volume and salinity on O atom exchange with water

Given the potential influences on NO₃^- N and O isotope ratios, which include bacterial blanks, dissolved atmospheric N₂O, contaminant NO₃^- in reference materials, O atom exchange with water, and incomplete N₂O recovery and associated isotope fractionation, we attempt to reproduce the volume-dependent changes in ẟ¹⁵N and ẟ¹⁸O that we observed for IAEA-NO3 and USGS-34 reference materials.

The observed ä¹⁵N and ä¹⁸O values of N₂O for IAEA-NO3 and USGS-34 samples were referenced to that expected for IAEA-NO3 vs. the N₂O reference tank. The expected IAEA-NO3 has a ä¹⁵N of 0‰ vs. IAEA-NO3, and that expected for USGS-34 is -6.5‰ vs. IAEA-NO3. Being uncertain of the ä¹⁸O of the industrial N₂O in the reference tank, we approximate the expected ä¹⁸O value for IAEA-NO3 vs. N₂O_ref to be that observed for the highest N₂O yield (at lower aliquot volumes – which is admittedly already subject to blanks). Referenced to itself, the expected ä¹⁸O of IAEA-NO3 is 0‰ (vs. IAEA-NO3), and that for USGS-34 is -52.2‰ (vs. IAEA-NO3).

We compare the simulated ä¹⁵N and ä¹⁸O values to the observed average of 3 trials in dataset “Incidence of volume effect.”

Processing notes from researcher:

• Data were processed using Microsoft Excel

NSF Award Abstract:
The nitrogen (N) cycle in the marine environment is controlled by biological processes. Unfortunately, quantifying these processes and assessing their effect on the N cycle is difficult by direct measurements because of large spatial and temporal differences. Isotopic composition measurements of N provide a means to constrain these processes indirectly; however, there is still a great deal to be understood about isotope fractionation of recycled nitrogen through biological processes, which has made interpretation of novel nitrogen isotope data difficult. A researcher from the University of Connecticut plans to determine the influence of biological consumption and production on the isotope fractionation in ammonium. By helping to understand the processes surrounding fractionation of recycled ammonium at the organism level, this research will create a basis for which future researchers can better interpret isotope composition data to infer nitrogen cycle dynamics. A graduate student, a postdoctoral fellow, and two or more undergraduate students will be involved in the research. The researcher plans to integrate science with community-engaged learning by developing an undergraduate field and laboratory course that will require the students to present their research to stakeholders in the community. There will be a manual created for this course that will be disseminated in open-access forums for teachers hoping to develop similar courses.

Biological nitrogen isotope fractionation associated with nitrogen recycling remains poorly constrained despite the advent of a variety of new techniques to analyze nitrogen isotopes in recent years. The use of isotopic composition data can be incredibly useful to interpreting nitrogen cycle processes in the ocean that are difficult to measure directly, which makes it crucial to further understand the processes behind fractionation to catch up with the advancement of the datasets available to researchers. This research will characterize the isotope fractionation dynamics of ammonium during biological consumption and production. The researchers will investigate whether the characteristic low concentrations of ammonium in the surface ocean affect isotope fractionation when the ammonium is recycled and whether there is a trophic isotope effect associated with ammonium recycling by protozoan grazers. With this research, there will be a baseline from which researchers can interpret recycled nitrogen dynamics from ammonium isotope datasets. The methods of comparing nitrogen cycling studies will become significantly clearer with such a standard making interpretation uniform by removing significant uncertainties.