Early season N2O emissions under variable water management in rice systems: source-partitioning emissions using isotope ratios along a depth profile
Soil moisture strongly affects the balance between nitrification, denitrification and N2O reduction and therefore the nitrogen (N) efficiency and N losses in agricultural systems. In rice systems, there is a need to improve alternative water management practices, which are designed to save water and reduce methane emissions but may increase N2O and decrease nitrogen use efficiency. In a field experiment with three water management treatments, we measured N2O isotope ratios of emitted and pore air N2O (δ15N, δ18O and site preference, SP) over the course of 6 weeks in the early rice growing season. Isotope ratio measurements were coupled with simultaneous measurements of pore water NO3-, NH4+, dissolved organic carbon (DOC), water-filled pore space (WFPS) and soil redox potential (Eh) at three soil depths. We then used the relationship between SP × δ18O-N2O and SP × δ15N-N2O in simple two end-member mixing models to evaluate the contribution of nitrification, denitrification and fungal denitrification to total N2O emissions and to estimate N2O reduction rates. N2O emissions were higher in a dry-seeded + alternate wetting and drying (DS-AWD) treatment relative to water-seeded + alternate wetting and drying (WS-AWD) and water-seeded + conventional flooding (WS-FLD) treatments. In the DS-AWD treatment the highest emissions were associated with a high contribution from denitrification and a decrease in N2O reduction, while in the WS treatments, the highest emissions occurred when contributions from denitrification/nitrifier denitrification and nitrification/fungal denitrification were more equal. Modeled denitrification rates appeared to be tightly linked to nitrification and NO3- availability in all treatments; thus, water management affected the rate of denitrification and N2O reduction by controlling the substrate availability for each process (NO3- and N2O), likely through changes in mineralization and nitrification rates. Our model estimates of mean N2O reduction rates match well those observed in 15N fertilizer labeling studies in rice systems and show promise for the use of dual isotope ratio mixing models to estimate N2 losses.