Soil nitrogen processes have been investigated in detail at the process and the molecular-microbiological level, mostly using laboratory scale analyses, with recent research efforts focusing on quantifying the overall nitrogen turnover across spatial scales. However, challenges like methodological limitations, large spatial and temporal variability, and complex interacting control factors hinder accurate quantification and understanding of soil nitrogen turnover. While controls of nitrogen cycle processes are well established in the laboratory, applying these insights to field, regional and (cross)continental scales remains difficult and therefore also the validation of these processes and their controls in large-scale biogeochemical models due to the scarcity of in-situ data.
We here propose and demonstrate an isotope fractionation approach which is non-invasive (no addition of 15N labeled compounds in dissolved form) and allows to explore in-situ dynamics of soil nitrogen cycling from the field scale to continental spatial patterns. The approach allows to determine the flux partitioning between the coupled pools of organic nitrogen in plants, soils and microbes, ammonium, nitrate, and gaseous nitrogen forms. Fluxes estimated include depolymerization, microbial uptake, mineralization, nitrification, and soil nitrogen losses. We present examples across a European climate, bedrock and land use transect on how to quantify (i) microbial nitrogen use efficiency, and (ii) fractions of inorganic nitrogen loss through hydrological or gaseous loss pathways (leaching of nitrate or gaseous losses via nitrification/denitrification in the form of NO, N2O and N2), based on isotope fractionation modeling of natural 15N abundance data of soil nitrogen pools.
How to cite: Wanek, W. and Zhang, S.: Natural 15N abundances in coupled soil ecosystem nitrogen pools allow to determine nitrogen flux partitioning based on isotope fractionation modeling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16224, https://doi.org/10.5194/egusphere-egu25-16224, 2025.
Quick and frequent freeze-thaw cycles (FTCs) are expected to increase due to climate change-induced warming in mid- and high- latitude regions. Warming trends during winter can impact biogeochemical cycles in land and water bodies. Bioaccumulation of soil nitrogen (N) products (nitrate, ammonium, and total nitrogen) on the soil surface during early spring and elevated N levels of streams hint at N movement within soil during winter. Natural field observations may not capture changes occurring during quick FTCs, and therefore, we developed a laboratory experiment to observe the movement of soil N products and unfrozen soil water during quick FTCs. Active solute transport occurs within a soil column during winter, as not all soil water undergoes freezing. Winter soil warming has been found to influence biogeochemical reactions within the top 100 cm, with high impact on solute movement in the top 30 cm depth. A 100-cm soil column filled uniformly with freely draining sandy loam (3.35 mm or finer grain size) was used for successive freezing and thawing for 4 days. Soil freezing was enabled using a 30-cm long freezing jacket with 10-cm wide detachable layers to adjust freezing depths over each 10-cm depth. Soil freezing for the top 10-cm, 20-cm, and 30-cm depths were enabled for three scenarios to observe the effects of freezing depth on solute movement during a 4-day FTC. An intensity-controlled infrared lamp above the soil column was used to thaw the soil. Soil moisture and temperature were monitored at the surface and at column depths of 15 cm, 30 cm, 45 cm and 60 cm. Soil water samplers collected porewater samples from 5 cm, 15 cm, 25 cm, 55 cm, and 80 cm depth. The depth below 60 cm was considered for the movement of solute towards or away from the freezing front during a FTC. There was an upward N migration observed during the 10-cm freezing depth scenario. N migration was the highest in the 10-cm freezing depth scenario. The observations obtained during FTCs were compared with a control scenario (no soil freezing) for the same duration. This experiment identified the direction of migration of solutes during FTCs. These results can help in soil nutrient management by controlling the availability of excess soil nitrogen, thus mitigating the impact of climate-warming on soil and water resources at a catchment scale.
How to cite: Sahoo, M., Thornton, S., and Baú, D.: Quick Freeze-Thaw Cycles enable Rapid Solute Movement in Vertical Soil Columns , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1594, https://doi.org/10.5194/egusphere-egu25-1594, 2025.
Efficient management of nitrogen (N) in agricultural systems is crucial for mitigating greenhouse gas (GHG) emissions, reducing nutrient losses, and maintaining crop productivity. The aim of this study was to evaluate the N cycle on German cropland using the process-based MONICA model. In particular, the processes of denitrification, nitrification and N leaching, as these have a significant influence on N losses. The study relied on data from the German Agricultural Soil Survey (BZE-LW), which provides detailed crop sequence information, annual fertilization rates, and yields across 1235 sites. These data were supplemented with meteorological information from the German Weather Service (DWD) and environmental variables derived from remote sensing. An algorithm was developed to predict the timing of operations such as fertilization and tillage, to address the challenge of limited temporal resolution in management data, generating daily management information. This enhancement enabled high-temporal-resolution simulations for nine major crops cultivated in Germany between 2001 and 2018. Initial model evaluation applied MONICA to simulate crop yields, N leaching, and N₂O emissions, using large-scale plausibility checks based on emission factors and leaching loss estimates. While the model demonstrated reasonable performance in estimating nitrogen fluxes, challenges were identified in replicating reported yields. These were largely due to uncertainties in input data and unrepresented processes in the current model framework. Planned refinements to MONICA, in collaboration with project partners, aim to improve its representation of denitrification losses (N₂ and N₂O) using experimental data. Preliminary results underline the potential of MONICA for high-resolution simulation of agroecosystem N dynamics, though sensitivity analyses highlight the significant influence of uncertainties in soil properties and management inputs on model outputs. This work advances the MONICA model as a robust tool for simulating high-resolution N fluxes and evaluating mitigation strategies in agricultural systems. The insights gained provide a foundation for improving N management practices at regional scales, contributing to sustainable and climate-resilient agricultural systems in Germany.
How to cite: Ouattara, B., Aiteew, K., Jarrah, M., and Dechow, R.: Modelling Nitrogen Balances of German Croplands: Advancing the MONICA Model for High-Resolution N Flux Estimates, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2095, https://doi.org/10.5194/egusphere-egu25-2095, 2025.
Climate change and nitrogen application significantly influence agricultural productivity and soil greenhouse gas emissions. However, the impacts of interannual climate variability and the legacy effects of nitrogen application on corn yield and soil nitrous oxide (N2O) emissions remain poorly understood. In this study, we utilized the DeNitrification-DeComposition (DNDC) model to simulate corn yield and soil N2O emissions over a 40-year period (1981~2020). We designed a series of experiments by shifting climate year data and altering nitrogen application rates to quantify interannual variability in corn yield and soil N2O emissions, as well as to disentangle the contributions of climate variability and nitrogen legacy effects. The results showed large interannual variability in both corn yield and soil N2O emissions. Corn yield was primarily driven by changes in growing season precipitation, while soil N2O emissions were influenced by precipitation, exchangeable NH4+, nitrification-denitrification processes. Severe drought strongly reduced corn yield, while soil N2O emissions exhibited a gradual yet pronounced legacy effect of nitrogen application, increasing from 2 kg N ha-1 to approximately 5 kg N ha-1 over the 40-year period. High nitrogen application rates amplified the interannual variability of both corn yield and soil N2O emission. This study highlights the relatively weak influence of interannual climate variability compared to the stronger legacy effects of nitrogen application on crop yield and soil N2O emissions, providing valuable insights for sustainable agricultural and environmental management.
How to cite: Hui, D., Christian, J., Hayat, F., Fatima, M., and Ricciuto, D.: Interannual variability and legacy impacts of climate change and nitrogen fertilization on corn yield and soil nitrous oxide emissions: a modeling approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15201, https://doi.org/10.5194/egusphere-egu25-15201, 2025.
A number of methods are available for the analysis of nitrate in soil, each with its own advantages and limitations. One of the main limitations of existing methods is that they involve destructive soil sampling with subsequent extraction. Therefore, there is a demand for a rapid, sensitive, and accurate procedure for analysis of nitrate levels in the soil. Here, we developed and tested a method for quantitative analysis of nitrate in soils based on electrochemical reduction of the nitrate ion to gaseous nitrogen (N) species and subsequent real-time and online quantification of the emitted N gases. For this purpose, we subjected slurries from different soils to electrolysis with different electrode materials under a range of conditions. The N gases developing in the slurry during electrolysis were continuously purged out of the solution into the headspace of the electrolysis cell by a stream of dry nitrogen gas and directed to an infrared laser absorption analyzer for online analysis.
We found that the emission of N2O, one of the products of the electrolysis of nitrate in the soil slurry, was the most suitable indicator of the nitrate concentration in the sample because it is easy to measure with high sensitivity. To test the linearity of the method, the soil samples were amended with different amounts of nitrate, resulting in nitrate contents of the soils ranging from 20 to 180 mg NO3--N kg-1. Preliminary results showed a linear correlation between nitrate concentrations and N2O production. However, it became evident that the variability in soil structure and pH significantly impacted the electrochemical reduction pathways and efficiency. To address these limitations, a phosphate buffer was introduced to stabilize the soil pH. This adjustment minimized pH fluctuations, thereby reducing their influence on N2O production. This newly developed method offers advantages such as fast analysis time and the ability to measure nitrate directly in situ.
How to cite: Kachalova, L. and Brüggemann, N.: Non-destructive soil nitrate detection via electrochemical reduction, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9864, https://doi.org/10.5194/egusphere-egu25-9864, 2025.
Soil erosion is a key driver of soil redistribution, often causing nutrient losses from agricultural fields and contributing to nutrient overload in natural ecosystems. The removal of topsoil leads to truncated soil profiles on shoulder slopes, in which the plough can incorporate deeper soil material. This can change soil properties and, thus, alter biogeochemical cycling. Despite the increased interest in understanding SOM turnover in eroded topsoils, studies on N cycling in this context are rare and often focus only on isolated aspects of the N cycle (Berhe et al., 2018).
We designed a short-term mesocosm experiment, combining different 15N-tracing techniques, to quantify almost all N transformation processes in topsoils mixed with different amounts of subsoil to simulate three erosion levels. Nitrogen transformation pathways were simulated using the numerical model Ntrace (Rütting & Müller, 2007), considering N uptake by maize (Zea mays) at early development stages. The 15N labelling also allows the quantification of N2O and N2 losses, originating either from the soil NO3-N or NH4-N pool. N2O losses were determined automatically by a gas chromatograph and N2 by isotope ratio mass spectrometry by applying the 15N gas flux method in N2-depleted atmosphere (Kemmann et al., 2021).
The incorporation of subsoil material resulted in decreased Corg and Ntot contents with increasing erosion levels, leading to reduced nitrogen turnover and, consequently, lower N₂O and N₂ emissions in both maize-planted and unplanted treatments. Autotrophic nitrification was the dominating process across all erosion levels. Nevertheless, most N2O and N2 emissions originated from coupled nitrification-denitrification, even at water contents <40 % WFPS. Surprisingly, the growth of maize plants increased N2O and N2 emissions more than twice at early growth stages. However, the overall effect of the erosion level was considerably greater than the effect of plant presence. Our study contributes to a more comprehensive understanding of N cycling in agricultural soils of hilly landscapes, which is essential for enhancing nitrogen fertilizer use efficiencies and reducing N pollution.
References
Berhe, A. A., Barnes, R. T., Six, J., & Marín-Spiotta, E. (2018). https://doi.org/10.1146/annurev-earth-082517-010018
Kemmann, B., Wöhl, L., Fuß, R., Schrader, S., Well, R., & Ruf, T. (2021). https://doi.org/10.1111/gcbb.12879
Rütting, T., & Müller, C. (2007). https://doi.org/10.1016/j.soilbio.2007.04.006
How to cite: Schoof, J., Holz, M., Rütting, T., Well, R., and Buchen-Tschiskale, C.: Impact of different soil erosion levels on N transformation processes and gaseous N losses: An incubation study, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8721, https://doi.org/10.5194/egusphere-egu25-8721, 2025.
Nitrate (NO₃⁻) leaching from the rooting zone of agricultural land generally leads to increased NO₃⁻ concentrations in groundwater, thereby significantly contributing to the eutrophication of aquatic ecosystems. Denitrification—the biogeochemical reduction of NO₃⁻ and nitrite (NO₂⁻) to dinitrogen (N₂) and/or nitrous oxide (N₂O)—can mitigate NO₃⁻ inputs to groundwater. However, most research to date has predominantly focused on the root zone. Consequently, substantial uncertainties remain regarding the quantification of nitrate reduction in the unsaturated percolation zone below the root zone (referred to as the drainage zone). The extent to which this zone can reduce NO₃⁻ inputs into groundwater remains contentious, and its contribution to soil N₂O emissions has been scarcely studied.
To address these gaps, we assessed denitrification potential by determining the maximum denitrification capacity (Dcap) using the acetylene inhibition technique for the upper (1.5–2.0 m depth) and deeper (down to 7 m) drainage zone at multiple agricultural sites with contrasting soil textures. Experiments included the addition of seepage water with varying dissolved organic carbon (DOC) concentrations to evaluate the influence of key factors on denitrification in the drainage zone.
Additionally, a mesoscale laboratory incubation experiment was conducted to measure the denitrification rates under oxic and anoxic conditions. Substrates with differing textures were used, and the measurements were performed using the ¹⁵N gas flow method. Key factors influencing denitrification—such as the availability of NO₃⁻ and oxygen, water content, and DOC concentration—were systematically varied in a full factorial experimental design.
Preliminary results revealed very low denitrification emissions in both experiments; however, emissions were higher in the Dcap experiment. Contrary to expectations, initial results suggest less effect of water-filled pore space, NO₃⁻ concentration, or DOC content on denitrification-related emissions. So far, emissions were significantly higher in clayey sediments compared to sandy sediments, highlighting the role of soil texture in influencing denitrification within the drainage zone. These findings emphasize the importance of further research to better understand how the specific characteristics of the drainage zone regulate denitrification processes.
How to cite: Westphal, J., Klußmann, A.-E., Well, R., Schoner, D., Stange, F., and Buchen-Tschiskale, C.: Reassessing Denitrification in the drainage zone below agricultural soils, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1535, https://doi.org/10.5194/egusphere-egu25-1535, 2025.
Soil freeze-thaw (FT) cycles induce high nitrous oxide (N2O) emissions across all ecosystems, whereby flux rates are highest for agricultural systems, where more than half of the annual N2O emissions may result from FT related fluxes. Globally, neglecting FT related N2O emissions may lead to an underestimation of the annual N2O budget by almost a quarter. However, FT related N2O emissions are hardly implemented in and simulated by state-of-the-art ecosystem models yet, because of a lack of knowledge about the actual mechanisms explaining timing and magnitude of the observed N2O emission peaks.
Here we review recent advances in process understanding, which can be summarized into three approaches: (i) a frozen (top)soil (or snow) layer that acts as physical barrier for gas diffusion, (ii) the production of additional decomposable substrate during freezing-thawing, and (iii) temperature-depending changes in the biochemical balances within the denitrification process. We implemented the different mechanisms in the LandscapeDNDC ecosystem model, which provides an advanced representation of soil nitrogen processes, and validate their effects on site scale, before we evaluate their importance on regional scale and as part of the annual N2O budget. This will enable us to improve national to global estimates of annual N2O emissions and lower the current uncertainty due to the neglect of FT related N2O fluxes.
How to cite: Thurner, M. A., Blagodatsky, S., Kraus, D., Scheer, C., and Kiese, R.: Modelling freeze-thaw related N2O emissions: recent advances & future perspectives, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3461, https://doi.org/10.5194/egusphere-egu25-3461, 2025.
The world's population growth requires an increase in agricultural productivity. But this must be achieved by reducing the environmental impact of agricultural practices. The European Commission's European Green Deal includes targets for reducing nitrogen (N) application. This could be achieved by reducing fertilizer amounts in regions that are heavily fertilized. A second option to reduce N emissions would be the transport of organic amendments from region with high livestock/ biogas plant density into areas where fertilization of croplands are dominated by mineral fertilization. However, only few studies exist addressing the implications of fertilizer reduction on SOC stocks, N cycling and productivity in the long-term. Biogeochemical models can help to investigate the long-term effects of reduced fertilizer application on these system properties. For model calibration, data from two 2- and 3-year experiments on sandy and clayey soils, consisting of a no-fertilization control, 3 mineral fertilizer treatments with different N levels and 3 biogas digestate treatments with corresponding rates of total N (with 60%, 80% and 100% of maximum N applied) in two cereal/maize rotations were used. The digestate was applied by trailing hoses, and directly incorporated when maize was the subsequent crop. A long-term monitoring site in Lower Saxony was used to improve and validate the SOC sub-module of the model. The dataset consists of 45 field plots with documented soil data, management data and time series of SOC content. SOC content was measured on average every 4-5 years for 20 years in the upper 0-20 cm soil horizon. The management of the sites represents general agricultural practice. The results of the experiments were used to calibrate and improve the DNDCv.Can biogeochemical model. The calibrated model was used to simulate the development of SOC stocks, N budgets and productivity for the period 2020-2060. The model was run with three future climate scenarios. It was hypothesized that (i) the N use efficiency of digestate would be inferior to that of mineral nitrogen, and therefore more N from manure would be needed to achieve the same yield, but causing higher N2O and NH3 emissions, (ii) those discrepancies between mineral fertilization and organic fertilization level off in the long-term, (iii) reducing N fertilizer application rates does decrease N2O and NH3 emissions, (iv) reduced N application decreases carbon inputs, which may lead to a long-term reduction of soil SOC. Based on the calibrated model on experimental results we compare yield, SOC, N2O in long term (40 years) scenarios for Eastern Lower Saxony, Germany with factors a) fertilization type, b) fertilization amount, c) climate, d) soil type.
How to cite: Grosz, B., Greef, J. M., Tendler, L., Well, R., and Dechow, R.: Modeling of the long-term effects of reduced inputs of organic and inorganic fertilizers on SOC and N-balance of agricultural soils, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3552, https://doi.org/10.5194/egusphere-egu25-3552, 2025.
Mitigating nitrogen (N)-oxide emissions and optimizing N-use efficiency are important aspects of agricultural soil management. Studies that monitor net production of dinitrogen (N2) and nitrous oxide (N2O), including the spatial/temporal heterogeneity of denitrification in soils, provide much-needed data to inform models that support management decisions. However, to model denitrification in agricultural ecosystems more accurately, we need data-sets at lab to field scale including reliable measurement of processes and regulating factors of N2 and N2O production.
Analysing natural abundance isotopocule values of N2O (d15N, d18O and 15N site preference) in gas samples from closed chambers with data evaluation using the FRAME model (Lewicki, 2022) can be used to distinguish N2O production pathways and to quantify N2O reduction to N2. However, this approach usually fails to distinguish between N2O production by heterotrophic bacterial denitrification and nitrifier denitrification. Moreover, the accuracy is limited during periods of low activity due to the small fraction of soil-derived N2O in the samples. This might be overcome by analysing N2O isotopocule values of soil air were the fraction of soil-derived N2O is always higher compared to closed chamber samples.
While N2 and N2O fluxes from denitrification can be determined using the 15N gas flux method (15NGF), improvement of N2 sensitivity is needed to detect emissions beyond peak events which can be achieved by establishing an N2-depleted atmosphere (15NGF+ method, (Eckei et al., 2024).
Recently, it has been shown that extending the FRAME modelling with results of the 15NGF conducted in parallel is suitable to better distinguish different denitrification pathways of N2O production (Micucci et al., 2025). A further advantage of using both approaches is the fact, that FRAME can be easily used outside the lab and in growing crops, while for 15NGF+, this is very challenging.
We combined three approaches, i.e. (1.) surface fluxes of N2O isotopocules using the closed chamber method, (2.) Experiments were established on lysimeters with two undisturbed soils cropped with barley.
We used results for FRAME modeling of natural abundance plots and combined them with 15NGF+ results to quantify (i) N2 and N2O fluxes from the 15N-labelled NO3- pool, (ii) the fraction of N2O emitted from other (unlabelled) N sources, and (iii) N2O pathways distinguished by the extended FRAME modelling including heterotrophic bacterial denitrification, nitrifier denitrification, fungal denitrification, nitrification and N2O reduction to N2. The latter will be compared to N2 fluxes obtained by 15NGF+. First results will be shown.
References:
Eckei, J., et al., 2024. Determining N2O and N2 fluxes in relation to winter wheat and sugar beet growth and development using the improved 15N gas flux method on the field scale. Biology and Fertility of Soils. DOI: 10.1007/s00374-024-01806-z
Lewicki, M.P.D.L.-S., Grzegorz Skrzypek, 2022. FRAME—Monte Carlo model for evaluation of the stable isotope mixing and fractionation. Plos One 17, e0277204.
Micucci, G., et al.., 2025. Combining the 15N Gas Flux Method and N2O Isotopocule Data for the Determination of Soil Microbial N2O Sources. Rapid Communications in Mass Spectrometry 39, e9971.
How to cite: Well, R., Buchen-Tschiskale, C., Freudiger, M., Lewicka-Szczebak, D., and Matson, A.: Lysimeter studies combining 15N tracing and natural abundance stable isotopes to determine N2 and N2O fluxes and processes in arable soils , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5928, https://doi.org/10.5194/egusphere-egu25-5928, 2025.
Hydroxylamine (NH2OH) is an intermediate in nitrification and a direct precursor for nitrous oxide (N2O) in both enzymatic and abiotic reactions. Although its importance for N2O emissions from soils has been recognized, NH2OH has never been measured in soils except for one acidic forest soil. This is mostly due to a lack of an adequate extraction method in the presence of soil minerals. Therefore, we here developed a soil extraction method that stabilizes NH2OH during the extraction by blocking its abiotic reactions by a combination of low pH, reducing agents and chelators. Furthermore, we optimized a colorimetric NH2OH assay for the conditions encountered in such soil extracts. The colorimetric assay reacts NH2OH with quinolin-8-ol under alkaline conditions and has a limit of detection of 0.5 µmol L-1. In a next step, we target to purify the derivatization product with solid phase extraction to measure its concentration and isotopic composition via UPLC-Orbitrap mass spectrometry. The final goal is to provide a workflow for the ultra-sensitive NH2OH measurement in soil 15N-tracer studies.
How to cite: Heldwein, N., Kitzinger, K., and Wanek, W.: A novel method for the extraction and measurement of hydroxylamine in soils, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6727, https://doi.org/10.5194/egusphere-egu25-6727, 2025.
Soil nematodes, the most abundant soil fauna, play a pivotal role in nitrogen cycling through their interactions with soil microorganisms, potentially influencing N₂O emissions. While it is well-established that N fertilization can increase N₂O emissions, the role of nematodes in modulating N₂O emissions across different N fertilization strategies remains underexplored. This study investigates the effect of soil nematodes on N₂O emissions under four N fertilization treatments: no nitrogen (CK), chemical fertilizer (CF), pig manure (PM), and green manure (GM). Over a 58-day soil microcosm incubation, we compared N₂O emissions with and without the presence of the entire soil nematode community across two soil textures—loamy sand and sandy loam. Our results revealed that soil texture, N fertilization, and nematode presence significantly influenced N₂O emissions. The most pronounced effect of nematodes was observed in loamy sand soil treated with PM, where nematodes contributed to a marked increase in N₂O emissions during the initial peak (0-5 days). In contrast, nematodes significantly elevated N₂O emissions from 5 to 58 days in sandy loam soil treated with GM. Both pig manure and green manure promoted nematode population growth; however, nematodes only notably enhanced nitrogen mineralization in unfertilized soil. These findings underscore the importance of incorporating soil fauna, particularly nematodes, into N₂O emission prediction and mitigation strategies for agricultural soils.
How to cite: Hu, J., Hernandez, M. M. A., Sluetel, S., and De Neve, S.: The Influence of Soil Nematodes on N₂O Emissions Under Chemical and Organic Nitrogen Fertilization, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7159, https://doi.org/10.5194/egusphere-egu25-7159, 2025.
Cultivated soils contribute approximately 60% of global nitrous oxide (N2O) production due to nitrogen inputs, which underscores the urgent need for comprehension of N2O emissions at larger spatial and temporal scales. However, knowledge gaps persist due to the episodic nature of soil N2O emissions, which are driven by non-linear interactions among biophysical, and environmental factors over spatial and temporal domains.
This study aims to identify significant predictors of N2O emissions at the field scale using random forest algorithm. The soil N2O flux and various predictors (CO2, soil moisture content (SWC), temperature, mineral N, pH, bulk density, and air permeability, as well as digital elevation model (DEM), gamma ray count rate, and electrical conductivity data were measured between March and June 2024 in a 1.2 ha winter wheat field located in Foulumgård, Denmark. The N2O flux was measured at 96 locations in weekly to biweekly time intervals using the LiCOR 7820 analyzer.
The N2O flux spatially varied from 0.006 to 0.164 ug m-2 s-1, with the highest average fluxes of 0.148 ug m-2 s-1 approximately 7 to 10 days after fertilizer application. The CO2 flux ranged from 0.11 to 0.54 µg m-2 s-1 with an average of 0.35 µg m-2 s-1, while SWC varied from 0.11 - 0.30 m3 m-3 and soil temperature from 6.0 - 25.7 °C.
The preliminary random forest model identified key predictors for N2O emissions as soil respiration (CO2, 25%), temporal variability (Week, 13%), soil electrical conductivity, here a likely proxy for soil texture (EC, 11%), and SWC, 9%. Furthermore, the model was evaluated with a 90:10 data split, using 90% for training and 10% for validation. The absence of further predictors limited the model's performance, as reflected in the decline in R² from 89% in training to 60% in validation. The out-of-bag (OOB) error also showed the model explained only 29.4% of emission variability, emphasizing the need for additional variables to better capture N2O predictors.
These findings are a first step towards comprehending the importance of recognizing the non-linear underlying forces of N2O emissions and the intricate interplay between soil and environmental factors. Improving the model ability to predict N2O emissions will require comprehensive datasets that capture key biogeochemical drivers and the development of robust, non-linear modeling frameworks. In a next step, additional parameters such as soil nitrate (NO3-), ammonium (NH4+), and soil pH are included in the model to further improve model performance to understand spatial variation and temporal dynamic of N2O.
How to cite: Bimantara, D. S., Eriksen, J., Koganti, T., and Dold, C.: Drivers of N2O Emissions: Implications for Model Development Accounting for the Spatial Variation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7178, https://doi.org/10.5194/egusphere-egu25-7178, 2025.
A number of laboratory and field-based sample taking, handling, treatment and tracer application methods exist for the determination of gross nitrification rates in soil by 15N pool dilution. However, a comprehensive evaluation of method-induced effects on nitrification rates remains challenging.
With our study, we systematically investigate if laboratory and field techniques generally produce comparable gross nitrification rates determined by the 15N pool dilution method. Our investigations are conducted on three plots with sandy soil under the different land-uses forest, grassland and arable land in the Fuhrberger Feld region, Lower Saxony, Germany. For this, we conduct on every plot five sub-test series that vary tracer application and subsequent sample handling and/or treatment in the field and in the laboratory, and compare the impact of the different methods. The five sub-tests span over a range from established pure laboratory method for the determination of nitrification rates to almost pure field work (where soil is incubated and extracted in the field), covering different degrees of handling and treatment impacts. Because there are differences, we will use the experiment to analyze which treatment and/or handling steps change the determined rates the most.
How to cite: Stange, C. F. and Stadler, S.: Impact of field and laboratory techniques on the nitrification rate determined by 15N pool dilution , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9704, https://doi.org/10.5194/egusphere-egu25-9704, 2025.
Biogeochemical models continue to be improved in their ability to account for the impacts of agricultural management, soil characteristics, and climate on crop productivity and greenhouse gas emissions. Depending on the model, limitations still exist including the ability to characterize a limited range of management practices, the oversimplifications of crop physiology, and an inadequate simulation of soil microbial environments. This study uses a long-term 22-year field experiment in eastern Canada to calibrate and evaluate several agroecosystem models, including DayCent, DNDC, DSSAT, and STICS, for their ability to simulate crop productivity and nitrous oxide (N2O) emissions. Model performance was assessed against near-continuous N2O measurements using flux towers. Corn, wheat, soybean, and canola were grown over the 22 years for several treatments including manure versus inorganic fertilizer, fertilizer rate, timing of fertilizer applications, early and late planting, and use urease and nitrification inhibitors. Findings suggest that the ensemble of models could accurately predict corn, wheat and soybean yields in contrast to the general overprediction of canola yields. Growing season N2O emissions are generally well-simulated at the Ottawa site with weekly performance statistics showing Wilmot d values of 0.7 for conventional management and 0.75 for BMP management. However, challenges persist in accurately capturing daily emission patterns and estimating emissions during the spring-thaw period. The DSSAT and STICS models, which do not have explicit soil mechanisms related to spring thaw, simulated low N2O emissions and thus it is recommended that these mechanisms be incorporated in the future. Difficulties in modeling the timing of denitrification events highlighted limitations in the representation of microsite-level pedoclimatic conditions, diffusion processes, and the simulation of microbial activity. The model ensemble simulated an acceptable level of annual N2O emissions for most treatments with 5.8% overprediction across 22 years, with the overestimation mainly from the manure and dual inhibitor treatments. Comparing model strengths and weaknesses across different locations provides valuable insights for future model improvements.
How to cite: Smith, W., Grant, B., Qian, B., Jego, G., Crepeau, M., del Grosso, S., Ogle, S., and Pelster, D.: Challenges and Insights for Simulating Nitrous Oxide Emissions in Eastern Canada: Evaluating an Agroecosystem Model Ensemble, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12649, https://doi.org/10.5194/egusphere-egu25-12649, 2025.
The accurate simulation of soil nitrogen (N) cycling is central to the process-based model Agricultural Production Systems sIMulator (APSIM) and increasingly the focus of modellers globally on account of a growing emphasis on quantifying N losses. Recently, 24 leading APSIM model users and developers from around the world came together to write a comprehensive review of APSIM’s soil N model (https://doi.org/10.1016/j.agsy.2024.104213). The review documents in detail how the model simulates N processes and synthesizes the findings of 131 model-data comparison studies conducted over the last 26 years. Overall, the review found that APSIM’s Soil N model performs well, simulating seasonal/annual soil N uptake and loss (e.g., leaching, denitrification) accurately across a wide range of treatments/environments. A number of studies, however, noted that the model struggled to capture the daily/sub-daily N dynamics and potentially underestimated the rate of mineralisation, especially under fallow conditions. In order to remedy these shortcomings, some researchers adjusted various parameter values, but due to the disjointed manner with which these model ‘improvements’ were proposed and adopted, most have not been tested under a wider scope than the singular target process or environment of the original study. The studies often differed in their approaches to evaluating and, at times, improving model performance, with the threshold for “good” performance differing depending on the focus and scope of the study. We therefore focused on extracting the insight of the studies’ authors and revisiting their model-data evaluations in the context of the other studies, thereby seeking to delve deeper into a more comprehensive understanding of the model’s performance. Such an approach led us to uncover target areas for future model development that were not evident in singular studies. For example, it highlighted the need to revisit how fresh organic matter in the model is initialised rather than increasing the rate of turnover of other soil C pools. The review has informed ongoing work, including testing the proposed parameter changes across a range of applications to identify potential unintended consequences that exist beyond the scope of isolated studies and investigating how to better model the environmental factors that dictate daily/sub-daily N dynamics. The flexibility of APSIM’s coding allows for sensitivity analyses on the processes currently included in APSIM and the development of prototypes for processes that are beyond the current model’s capacity. Future work will look to incorporate findings from new mechanistic and field experiments across different geographic/agroecological regions. Furthermore, there is value of doing similar exercises across other process-based models. Such reviews have the potential to streamline advancements in how models are evaluated and improved, leading to the development of models with more robust predictive capabilities and broader scopes.
How to cite: Pasley, H., Verburg, K., Biggs, J., Vogeler Cronin, I., Enli, W., Mielenz, H., Snow, V., Smith, C., Pasut, C., Basche, A., He, D., Archontoulis, S., Gaydon, D., Huth, N., Holzworth, D., Sharp, J., Cichota, R., Khaembah, E., Brown, H., Farrell, M., Janke, C., Vadakattu, G., and Thorburn, P.: APSIM's Soil N Model Review for Future Development, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14700, https://doi.org/10.5194/egusphere-egu25-14700, 2025.
Sustainable crop production as well as climate change mitigation require a better quantitative process understanding for nitrogen (N) transformations and their response to specific land management strategies. Here we investigated shifts in N transformations following the transition from conventional to soil health-oriented farming using a new combination of 15N stable isotope methods. Soil samples were taken from four different farms in two different regions in Lower Austria following a paired site approach, comparing a clay and a sandy textured soil under conventional vs. organic management. Soils were fertilized with single labelled NH415NO3 and incubated in a fully automated incubation system, with continuous monitoring of 15N2O. Changes in 15N enrichment in N pools were investigated by converting the N pools of interest into NO3-, and further to N2O via the Ti (III) reduction method, establishing the 15N enrichment via cavity ringdown spectroscopy (Picarro G5102-i). Changes in 15N in the NO3- pool showed that gross nitrification was higher in the clay as compared to the sandy textured soil, but did not respond to management. Gross NO3- consumption was however higher in organically managed soils, regardless of texture, and 15N enrichment in the soil microbial biomass indicated negligible assimilation of the applied 15N fertilizer under the conditions of the experiment. Combining classic 15N pool dilution and 15N tracing with Ti (III) reduction and cavity ringdown spectroscopy allowed for a timely determination of N pools and their 15N enrichment, obviating the need for costly and time-consuming analysis via isotope ratio mass spectroscopy. Further tests and analysis are needed to demonstrate the sensitivity of the approach for specific soil N pools, comparing results obtained to isotope ratio mass spectroscopy data. Analysis of the 15N2O data together with the 15N enrichment of the soil N pools will establish the significance of specific pathways of N2O production and their response conventional vs. soil health-oriented farming practices.
How to cite: Hood-Nowotny, R., Bachmann, J., Gallon, S., Breuzeville Calderon, A., Keiblinger, K., and Friedl, J.: Investigating shifts in nitrogen transformations in response to soil health oriented management using a new combination of stable isotope approaches, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21457, https://doi.org/10.5194/egusphere-egu25-21457, 2025.
Nitrous oxide emissions from agricultural land largely contribute to the greenhouse gas budget worldwide. Denmark’s glacial landscape has widespread small scale topographic depressions, typically flooded for 1-3 months per year. These depressions within agricultural land are considered as hotspots of N2O emissions, because of exposure to an increased nitrate availability and labile carbon due to fertilization and deposition of eroded soil material. Temporal waterlogging in these depression areas affects plant development, thus their ability to deplete available nitrogen in soil. Additionally, living plants provide substrates for denitrification through root exudates. However, the effect of living plants and roots on N2O emissions from glacial depressions is not very clear yet.
In this study, we aimed to elucidate how waterlogging influences nitrogen uptake and dissolved organic carbon (DOC) release from plants at different root growth stages, and to quantify how this would affect N2O emissions. We conducted a fully crossed mesocosm experiment with depression soils subjected to saturated or freely-drained water conditions, three different wheat growth stages to mimic possible different root N uptake, and an unplanted control. In order to differentiate how much N2O was produced from newly-added fertilizer, we applied a 15N tracer. For monitoring root development, roots were imaged through the translucent mesocosm walls on a weekly basis.
The growth stage of wheat significantly influenced the fate of mineral nitrogen and the dynamic of DOC in the soil solution, thereby affecting N2O emissions from these soil systems. The interaction between DOC and mineral nitrogen explained 53.9% of the variance in daily N2O fluxes. Therefore, these findings highlight the critical role of root development and soil water conditions in regulating N2O emissions from conditions representative for glacial depressions.
How to cite: Liu, Y., Kemmann, B., Ambus, P., Elberling, B., Dannenmann4, M., Thorup-Kristensen, K., W. Mueller, C., and M.N. Poultney, D.: How wheat root development can determine denitrification rates in soils of glacial depressions in Eastern Denmark, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7595, https://doi.org/10.5194/egusphere-egu25-7595, 2025.
Time-controlled grazing, i.e. short intensive grazing periods followed by a long rest, is promoted as a management form to counteract grassland degradation, increasing soil health, drought resilience and the sustainability and profitability of pastoral farming. Emissions of the potent greenhouse gas nitrous oxide (N2O) are known to respond to N substrate availability. Effects of grazing management on the distribution of N inputs and ensuing N2O emissions remain however largely unknown. This study investigated effects of continuous vs. time-controlled grazing on the magnitude and the spatial distribution of N2O emissions using a paired site approach. Emissions of N2O were measured before and after a simulated rainfall event across two extensively managed pasture sites in subtropical Queensland. Both sites were subdivided into four strata with 31 N2O sampling points per site, based on the distance to the water point. Mean N2O emissions across strata ranged from 23.5 to 22.8 g N2O-N m-2 day-1 and increased to 63.6 and 42.0 g N2O-N m-2 day-1 after the simulated rainfall event, for the continuous and time controlled grazing site, respectively. Emissions differed between strata, with highest emissions exceeding 60 g N2O-N m-2 day-1 within 100 m of the watering point and in shaded/forest areas, decreasing with distance to the water point. The spatial response of N2O emissions was consistent with NO3- concentration in the soil, likely reflecting areas of herd concentration with increased urine and dung deposition providing N substrate for N2O formation. Emissions of N2O were lower in shaded and forested areas, as well as in strata with >500 m distance to the water point under time controlled grazing as compared to continuous grazing management. The lack of treatment effect on NO3- availability and overall N2O emissions however shows no clear benefits of time controlled grazing on the distribution of N substrate availability under the conditions of this study, demanding further research to evaluate its benefits in regards to N2O mitigation from extensively managed pastures.
How to cite: Rohringer, V., Bernardini, L. G., Keiblinger, K., Rowlings, D. W., and Friedl, J.: Effects of time-controlled grazing on the magnitude and spatial distribution of N2O emissions from subtropical pastures in Australia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16162, https://doi.org/10.5194/egusphere-egu25-16162, 2025.
