Modeling soil moisture and oxygen effects on soil biogeochemical cycles including dissimilatory nitrate reduction to ammonium (DNRA)

Rubol, S.; Manzoni, Stefano; Bellin, Alberto; Porporato, Amilcare

doi:10.1016/j.advwatres.2013.09.016

Cited by 91 publications

(51 citation statements)

References 82 publications

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“…Temperature had no significant correlation with DNRA rates in this study, as the temperatures were quite similar for different sites in the same season (two‐factor ANOVA, F = 0.029, d f = 7, p = 1.000). However, the RDA analysis revealed that temperature still had a close relationship with DNRA rates, which implied that high temperature can contribute to higher DNRA rates by enhancing the metabolism of DNRA microorganisms [ Ferrón et al ., ; Rubol et al ., ; Smyth et al ., ]. Therefore, nitrate in aquatic ecosystems may tend to be converted to ammonium via DNRA during summer.…”

Section: Discussionmentioning

confidence: 99%

DNRA in intertidal sediments of the Yangtze Estuary

et al. 2017

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Dissimilatory nitrate reduction to ammonium (DNRA) plays an important role in regulating the fate of reactive nitrogen in estuarine and coastal ecosystems. In this work, intertidal sediments of the Yangtze Estuary were collected in January and August 2015. Potential rates of DNRA and associated functional gene were investigated with nitrogen isotope‐tracing and molecular techniques. The measured DNRA rates ranged from 0.14 to 5.57 μmol 15N kg−1 h−1 in the intertidal sediments. DNRA rates were tightly related to abundance of nrfA gene (p < 0.001), demonstrating that fermentation reaction may be the dominant pathway of DNRA in the study area. Redundancy analysis (RDA) showed a relationship between DNRA and organic matter and NO2−, suggesting that these substrates stimulated the metabolism of DNRA microorganisms. On the other hand, the correlation between abundances of nrfA gene and Fe2+ and sulfide in the RDA analysis implied that oxidation of both Fe2+ and sulfide can enhance fermentative DNRA by providing extra free energy. DNRA converted approximately 2.29 × 105 t of nitrate to ammonia annually in the sampling area of the Yangtze Estuary, and most of the converted ammonium was retained in the estuarine ecosystem. DNRA may further contribute to eutrophication in the Yangtze Estuary and also in the other hypereutrophic estuaries.

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Section: Discussionmentioning

confidence: 99%

DNRA in intertidal sediments of the Yangtze Estuary

et al. 2017

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“…We speculate that combining spatial diffusivity maps with soil inventories will be critical to properly identify and characterize GHG hot spots and hot moments in future work. Furthermore, the composition of the GHG fluxes will be partly controlled by soil temperature and other biotic factors [ Jarecke et al , ; Rubol et al , ]. A critical first step toward fully understanding hot spots, hot moments, and GHG composition is providing the underlying abiotic state variables that affect the flow of heat, vapor, and liquids in the subsurface.…”

Section: Discussionmentioning

confidence: 99%

“…Journal of Geophysical Research: Biogeosciences 10.1002/2017JG003837 Rubol et al, 2013]. A critical first step toward fully understanding hot spots, hot moments, and GHG composition is providing the underlying abiotic state variables that affect the flow of heat, vapor, and liquids in the subsurface.…”

Section: Spatio-temporal Interpolation Of Soil Properties and Statesmentioning

confidence: 99%

“…GHG fluxes involve complex abiotic and biotic processes and feedback operating at different scales [Hillel, 1998;Blagodatsky and Smith, 2012;Rubol et al, 2013;Mishra and Riley, 2015]. With respect to abiotic processes, the flow of heat, vapor, and liquids are represented by several key state variables, soil temperature, soil water content, and soil oxygen [Hillel, 1998].…”

Section: Introductionmentioning

confidence: 99%

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Spatiotemporal predictions of soil properties and states in variably saturated landscapes

Franz

Loecke

Burgin

et al. 2017

J. Geophys. Res. Biogeosci.

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Understanding greenhouse gas (GHG) fluxes from landscapes with variably saturated soil conditions is challenging given the highly dynamic nature of GHG fluxes in both space and time, dubbed hot spots, and hot moments. On one hand, our ability to directly monitor these processes is limited by sparse in situ and surface chamber observational networks. On the other hand, remote sensing approaches provide spatial data sets but are limited by infrequent imaging over time. We use a robust statistical framework to merge sparse sensor network observations with reconnaissance style hydrogeophysical mapping at a well‐characterized site in Ohio. We find that combining time‐lapse electromagnetic induction surveys with empirical orthogonal functions provides additional environmental covariates related to soil properties and states at high spatial resolutions (~5 m). A cross‐validation experiment using eight different spatial interpolation methods versus 120 in situ soil cores indicated an ~30% reduction in root‐mean‐square error for soil properties (clay weight percent and total soil carbon weight percent) using hydrogeophysical derived environmental covariates with regression kriging. In addition, the hydrogeophysical derived environmental covariates were found to be good predictors of soil states (soil temperature, soil water content, and soil oxygen). The presented framework allows for temporal gap filling of individual sensor data sets as well as provides flexible geometric interpolation to complex areas/volumes. We anticipate that the framework, with its flexible temporal and spatial monitoring options, will be useful in designing future monitoring networks as well as support the next generation of hyper‐resolution hydrologic and biogeochemical models.

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“…A lack of modular implementation, which makes it difficult to insert new developments into old models. Rubol et al (2013), for instance, have implemented a new model to take nitrate ammonification into account because of growing experimental evidence of the importance of this process. 4.…”

Section: Proposed Modelsmentioning

confidence: 99%

Mitigating N2O emissions from agriculture: A review of the current knowledge on soil system modelling, environmental factors and management practices influencing emissions

Regaert¹,

Aubinet²,

Moureaux³

2015

J. Soil Sci. Environ. Manage.

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The AgriGES project is a Concerted Research Action lead by Gembloux Agro-Bio Tech, aiming to quantify methane and nitrous oxide emission from pastures and crop fields, respectively. Besides quantification, a second important goal of the AgriGES project is to study the flux dynamics and to gain a better understanding of the biophysical processes coming into play. We focus here on N 2 O fluxes and first propose an overview of the current modelling efforts. Two main weaknesses of these models have been identified, and potential new developments are suggested to mitigate these issues, with an emphasis on the denitrification process. Secondly, we propose a review of the current knowledge on the main environmental factors influencing nitrous oxide emission. Several mitigation options are also explored.

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Modeling soil moisture and oxygen effects on soil biogeochemical cycles including dissimilatory nitrate reduction to ammonium (DNRA)

Cited by 91 publications

References 82 publications

DNRA in intertidal sediments of the Yangtze Estuary

DNRA in intertidal sediments of the Yangtze Estuary

Spatiotemporal predictions of soil properties and states in variably saturated landscapes

Mitigating N2O emissions from agriculture: A review of the current knowledge on soil system modelling, environmental factors and management practices influencing emissions

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