Preprints
https://doi.org/10.5194/bg-2022-221
https://doi.org/10.5194/bg-2022-221
 
17 Nov 2022
17 Nov 2022
Status: this preprint is currently under review for the journal BG.

Process Rate Estimator: A novel model to predict total denitrification using natural abundance stable isotopes of N2O

Charlotte Decock1,2, Juhwan Lee2,3, Matti Barthel2, Elizabeth Verhoeven2,4, Franz Conen5, and Johan Six2 Charlotte Decock et al.
  • 1College of Agriculture, Food and Environmental Sciences, California Polytechnic State University, San Luis Obispo, CA 93407, USA
  • 2Department of Environmental Systems Science, ETH Zurich, 8092 Zurich, Switzerland
  • 3Department of Smart Agro-industry, Gyeongsang National University, Jinju-si, Gyeongsangnam-do, 52725, Republic of Korea
  • 4Department of Crop and Soil Science, Oregon State University, 3017 Agriculture and Life Sciences Building, Corvallis, OR 97331, USA
  • 5Department of Environmental Sciences, University of Basel, Bernoullistrasse 30, 4056 Basel, Switzerland

Abstract. Total denitrification, the natural process capable of removing reactive N from ecosystems through conversion to N2, is one of the most poorly constrained processes in terrestrial N cycling. In situ quantification of total denitrification could help identify mitigation options for N pollution. This study provides proof-of-concept for a novel natural abundance isotope based model for depth differentiated in situ quantification of total denitrification; it does so by examining the use-case of the impact of wheat (Triticum aestivum) varieties with different root biomass on total denitrification. We set up a mesocosm experiment in 1.5 m tall lysimeters with four wheat varieties, each replicated three times. Temporal data for soil moisture, nitrous oxide (N2O) concentrations in the soil pore space, site preference (SP) and δ18O values of soil pore space N2O were collected at soil depths of 7.5, 30, 60, 90 and 120 cm over a five month growing period and used as input variables in the new model. Here, we define total denitrification as gross N2O consumption, with N2O produced either through nitrification or denitrification. The model, further referred to as ‘Process Rate Estimator’ or PRE, constrains temporally explicit gross N2O production and consumption rates at each depth increment based on a combination of diffusion and isotope mixing and fractionation models. Estimated production and consumption of N2O, integrated over the five month experiment, ranged from 3.9 to 170.3 kg N ha-1, with a trend for greater N2O production from denitrification compared to nitrification. N2O concentrations where greatest at 60 and 90 cm depth, while N2O production and consumption peaked at 7.5 and 30 cm depth, illustrating the important role of N2O dynamics along the soil profile in understanding ecosystem N budgets. Both N2O production and consumption were greater in varieties that had previously been characterized to have greater root biomass. We demonstrate that PRE is able to constrain nitrification and denitrification leading to gross daily N2O production, and gross reduction to N2 across the depth profile, based on the temporal change in concentrations, δ18O and SP of N2O. We conclude that our results support the potential of PRE to estimate total denitrification in situ, which could form the basis for developing promising strategies to reduce N pollution.

Charlotte Decock et al.

Status: open (until 29 Dec 2022)

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Charlotte Decock et al.

Charlotte Decock et al.

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Short summary
One of the least well understood processes in the nitrogen (N) cycle is the loss of nitrogen gas (N2), referred to as total denitrification. This is mainly due to the difficulty of quantifying total denitrification in situ. In this study, we developed and tested a novel modeling approach to estimate total denitrification over the depth profile, based on concentrations and isotope values of N2O. Our method will help close N budgets and identify management strategies that reduce N pollution.
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