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Research article 11 Jul 2018

Research article | 11 Jul 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Biogeosciences (BG).

Early season N2O emissions under variable water management in rice systems: source-partitioning emissions using isotopocule signatures along a depth profile

Elizabeth Verhoeven1, Matti Barthel1, Longfei Yu2, Luisella Celi3, Daniel Said-Pullicino3, Steven Sleutel4, Dominika Lewicka-Szczebak5, Johan Six1, and Charlotte Decock1,6 Elizabeth Verhoeven et al.
  • 1Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland
  • 2Department of Air Pollution and Environmental Technology, EMPA, 8600 Dübendorf, Switzerland
  • 3Department of Agricultural, Forest and Food Sciences, University of Turin, 10095 Grugliasco, Italy
  • 4Department of Soil Management, Faculty of Bioscience and Engineering, 9000 Ghent University, Belgium
  • 5Thünen Institute of Climate-Smart Agriculture, 38116 Braunschweig, Germany
  • 6Department of Natural Resources Management and Environmental Sciences, California State University, 93407 San Luis Obispo, California, USA

Abstract. 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 isotopocule signatures (δ15N, δ18O and site preference, SP) of emitted and pore air N2O over the course of six weeks in the early rice growing season. Isotopocule 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 endmember mixing models to evaluate the contribution of nitrification, denitrification, 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 isotopocule mixing models to estimate N2 losses.

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Elizabeth Verhoeven et al.
Data sets

CastelloD'Agogna_waterMgmt2015,2016_dataset E. Verhoeven https://doi.org/10.5281/zenodo.1251895

Elizabeth Verhoeven et al.
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Short summary
This study utilized state of the art measurements of nitrogen isotopes to evaluate nitrogen cycling and to assess the biological sources of the potent greenhouse gas, N2O, in response to water saving practices in rice systems. Water saving practices did emit more N2O and high N2O production had a lower 15N isotope signature. Modeling and visual interpretation indicate that these emissions mostly came from denitrification or nitrifier-denitrification, controlled upstream by nitrification rates.
This study utilized state of the art measurements of nitrogen isotopes to evaluate nitrogen...