An assessment of N-cycling and sources of N2O during a simulated rain event using natural abundance 15N

In order to accurately predict N2O emissions from agricultural soils and to develop effective management strategies, it is important to understand mechanisms underlying N2O emissions under field conditions. This involves identification of sources of N2O, which is currently methodologically challenging, especially under field conditions. We assessed the suitability of 15N tracers and natural abundance 15N to study N cycling and sources of N2O after a rainfall simulation in an annual cropping system in the Central Valley of California. Our natural abundance 15N approach differed from other studies due to a combination of emphasizing a per-event (e.g. rainfall simulation in this study) assessment of N2O emissions, applying high temporal sampling frequency during this event, determination of 15N of NH4+ and NO3− in addition to N2O, and data analysis using isotope models. In our study, the suitability of 15N tracers to assess N cycling and sources of N2O emissions was limited, likely due to a combination of a fine soil texture, the use of undisturbed soil cores, and a low 15N application rate. Based on natural abundance 15N, we were able to calculate gross NH4+ mineralization, NH4+ immobilization, nitrification and NO3− immobilization rates of 5.37 ± 1.72, 2.70 ± 1.72, 3.01 ± 1.13 and 0.15 ± 0.29 μg N g−1 soil d−1, respectively. Natural abundance 15N was, however, a rather poor predictor of the contribution of nitrification versus denitrification to N2O production. Nevertheless, important trends in N2O reduction rates could be observed, showing a sharp increase from 48% to 78% in reduction of produced N2O between 2 hours and 24 hours after rainfall simulation, followed by a gradual decrease to 46% of reduction by the fifth day after rainfall simulation. We conclude that the natural abundance 15N approach is very promising to elucidate mechanisms driving N-cycling and N2O emissions during agricultural management or weather events, especially if isotope dynamics are incorporated in site-specific biogeochemical process models.

► Natural abundance δ15N has potential to quantify in situ N transformation rates.
► Simulation models greatly improve interpretation of natural abundance δ15N.
► Models are best fitted to event-specific time series of natural abundance δ15N.
► For source partitioning N2O, natural abundance δ15N in NH4+ and NO3− is crucial.