Quantitative assessment of benefits and losses from the influence of atmospheric nitrogen deposition on cropland ecosystems in China

China is facing severe atmospheric nitrogen (N) deposition. Assessing the economic benefits and damage costs induced by N deposition can help to develop effective mitigation strategies for N emissions. A net economic benefit method was used to assess the economic impact of N deposition in cropland ecosystems in China in 2020. The results showed that atmospheric N deposition gained an economic benefit of $4896.0 million through increased yields of major grain crops and a climate benefit of $1259.3 million through cooling effects. On the other hand, N deposition induced economic losses of $6257.1 and $1063.4 million, respectively to human health and ecosystem health; excessive N deposition induced damages of $137.8 million due to reduced crop yields and $168.4 million due to the increased greenhouse gas emissions. In general, the net economic benefit was -$1471.5 million (-$5324.7 ∼ $921.4 million), indicating that China is suffering economic losses due to N deposition in cropland ecosystems. These results would provide scientific data for the government to enact efficient measures to reduce N pollution.

Potential benefits of cropping pattern change in the climate-sensitive regions of rice production in China

Rice production is a primary contributor to global greenhouse gas emissions, with unclear pathways towards carbon neutrality. Here, through a comprehensive assessment of direct greenhouse gas (GHG) emission using DNDC model and indirect GHG emission using emission factor methods, we estimated the annual crop yield, GHG emission amount and intensity, and economic benefits of different cropping patterns in the climate-sensitive regions of rice production in China. Through the expansion of single-rice and cropping pattern change from the wheat-rice to wheat-rice-rice in the climate-sensitive regions of single and triple-cropping cultivations, the total grain yield increased by 4.4 % and 4.5 % compared with the current national grain production, the GHG emission would increase by 2.4 % and 5.4 % of the current national GHG emissions from rice and wheat production, the net economic benefits could increase 0.9 % and decrease 2.0 % of the national output value of rice and wheat production. The study takes the entire-life cycle of crop growth as the principal line, and could provide a valuable reference for the regulation of the cropping pattern and the formulation of carbon reduction policies in the climate-sensitive region.

Modeling denitrification nitrogen losses in China's rice fields based on multiscale field-experiment constraints

Denitrification plays a critical role in soil nitrogen (N) cycling, affecting N availability in agroecosystems. However, the challenges in direct measurement of denitrification products (NO, N2 O, and N2 ) hinder our understanding of denitrification N losses patterns across the spatial scale. To address this gap, we constructed a data-model fusion method to map the county-scale denitrification N losses from China's rice fields over the past decade. The estimated denitrification N losses as a percentage of N application from 2009 to 2018 were 11.8 ± 4.0% for single rice, 12.4 ± 3.7% for early rice, and 11.6 ± 3.1% for late rice. The model results showed that the spatial heterogeneity of denitrification N losses is primarily driven by edaphic and climatic factors rather than by management practices. In particular, diffusion and production rates emerged as key contributors to the variation of denitrification N losses. These findings humanize a 38.9 ± 4.8 kg N ha-1  N loss by denitrification and challenge the common hypothesis that substrate availability drives the pattern of N losses by denitrification in rice fields.

Simulated nitrous oxide emissions from multiple agroecosystems in the U.S. Corn Belt using the modified SWAT-C model

Agriculture is a major source of nitrous oxide (N2O) emissions into the atmosphere. However, assessing the impacts of agricultural conservation practices, land use change, and climate adaptation measures on N2O emissions at a large scale is a challenge for process-based model applications. Here, we integrated six N2O emission algorithms for the nitrification processes and seven N2O emission algorithms for the denitrification process into the Soil and Water Assessment Tool-Carbon (SWAT-C). We evaluated the different combinations of methods in simulating N2O emissions under corn (Zea mays L.) production systems with various conservation practices, including fertilization, tillage, and crop rotation (represented by 14 experimental treatments and 83 treatment-years) at five experimental sites across the U.S. Midwest. The SWAT-C model exhibited wide variability in simulating daily average N2O emissions across treatment-years with different method configurations, as indicated by the ranges of R2, NSE, and BIAS (0.04-0.68, -1.78-0.60, and -0.94-0.001, respectively). Our results indicate that the denitrification process has a stronger impact on N2O emissions than the nitrification process. The best performing N2O emission algorithms are those rooted in the CENTURY model, which considers soil pH and respiration effects that were overlooked by other algorithms. The optimal N2O emission algorithm explained about 63% of the variability of annual average N2O emissions, with NSE and BIAS of 0.60 and -0.033, respectively. The model can reasonably represent the impacts of agricultural conservation practices on N2O emissions. We anticipate that the improved SWAT-C model, with its flexible configurations and robust modeling and assessment capabilities, will provide a valuable tool for studying and managing N2O emissions from agroecosystems.

Simulating agroecosystem soil inorganic nitrogen dynamics under long-term management with an improved SWAT-C model

Despite the extensive application of the Soil and Water Assessment Tool (SWAT) for water quality modeling, its ability to simulate soil inorganic nitrogen (SIN) dynamics in agricultural landscapes has not been directly verified. Here, we improved and evaluated the SWAT-Carbon (SWAT-C) model for simulating long-term (1984-2020) dynamics of SIN for 40 cropping system treatments in the U.S. Midwest. We added one new nitrification and two new denitrification algorithms to the default SWAT version, resulting in six combinations of nitrification and denitrification options with varying performance in simulating SIN. The combination of the existing nitrification method in SWAT and the second newly added denitrification method performed the best, achieving R, NSE, PBIAS, and RMSE of 0.63, 0.29, -4.7 %, and 16.0 kg N ha^-1, respectively. This represents a significant improvement compared to the existing methods. In general, the revised SWAT-C model's performance was comparable to or better than other agroecosystem models tested in previous studies for assessing the availability of SIN for plant growth in different cropping systems. Sensitivity analysis showed that parameters controlling soil organic matter decomposition, nitrification, and denitrification were most sensitive for SIN simulation. Using SWAT-C for improved prediction of plant-available SIN is expected to better inform agroecosystem management decisions to ensure crop productivity while minimizing the negative environmental impacts caused by fertilizer application.

Simulation-based assessment of the soil organic carbon sequestration in grasslands in relation to management and climate change scenarios

Soil organic carbon (SOC) is crucial for the quality and productivity of terrestrial ecosystems and its sequestration plays an important role in mitigating climate change. Understanding the effects of agricultural management under future climate on the SOC balance helps decision making in environmental policies. Thereby, grasslands will play a key role, since future climate change may prolong the vegetation period. We used 24 representative grassland sites in Germany to assess the SOC balance obtained from the CANDY model in relation to ten management regimes, 18 future climate change scenarios and different soil types. Simulations were conducted over a period of 110 years. For most of the selected grassland sites an increase in both air temperature and precipitation was observed in the future climate. The effect of management on the SOC balance largely exceeded the effect of soil type and climate. An increasing management intensity (i.e. three to five cuts) generally increased the SOC balance, while extensive management (i.e. two or fewer cuts) lead to SOC losses. The seasonal variation of precipitation was the most important climate metric, with increased SOC sequestration rates being observed with increasing growing season precipitation. Clay soils had the potential for both highest gains and highest losses depending on management and precipitation. Given an overall lower SOC storage potential in sands and loams, the SOC balance in those soil types varied the least in response to climate change. We conclude that fostering SOC sequestration is possible in grassland soils by increasing management intensity, which involves increased fertilizer input and field traffic. This however may stand in conflict with other policy aims, such as preserving biodiversity. Multicriterial assessments are required to estimate the nett greenhouse gas balance and other aspects associated with these management practices at a farm scale.

Overestimated nitrogen loss from denitrification for natural terrestrial ecosystems in CMIP6 Earth System Models

Denitrification and leaching nitrogen (N) losses are poorly constrained in Earth System Models (ESMs). Here, we produce a global map of natural soil ¹⁵N abundance and quantify soil denitrification N loss for global natural ecosystems using an isotope-benchmarking method. We show an overestimation of denitrification by almost two times in the 13 ESMs of the Sixth Phase Coupled Model Intercomparison Project (CMIP6, 73 ± 31 Tg N yr^-1), compared with our estimate of 38 ± 11 Tg N yr^-1, which is rooted in isotope mass balance. Moreover, we find a negative correlation between the sensitivity of plant production to rising carbon dioxide (CO₂) concentration and denitrification in boreal regions, revealing that overestimated denitrification in ESMs would translate to an exaggeration of N limitation on the responses of plant growth to elevated CO₂. Our study highlights the need of improving the representation of the denitrification in ESMs and better assessing the effects of terrestrial ecosystems on CO₂ mitigation.

Quantifying nitrous oxide production rates from nitrification and denitrification under various moisture conditions in agricultural soils: Laboratory study and literature synthesis

Biogenic nitrous oxide (N₂O) from nitrification and denitrification in agricultural soils is a major source of N₂O in the atmosphere, and its flux changes significantly with soil moisture condition. However, the quantitative relationship between N₂O production from different pathways (i.e., nitrification vs. denitrification) and soil moisture content remains elusive, limiting our ability of predicting future agricultural N₂O emissions under changing environment. This study quantified N₂O production rates from nitrification and denitrification under various soil moisture conditions using laboratory incubation combined with literature synthesis. ¹⁵N labeling approach was used to differentiate the N₂O production from nitrification and denitrification under eight different soil moisture contents ranging from 40 to 120% water-filled pore space (WFPS) in the laboratory study, while 80 groups of data from 17 studies across global agricultural soils were collected in the literature synthesis. Results showed that as soil moisture increased, N₂O production rates of nitrification and denitrification first increased and then decreased, with the peak rates occurring between 80 and 95% WFPS. By contrast, the dominant N₂O production pathway switched from nitrification to denitrification between 60 and 70% WFPS. Furthermore, the synthetic data elucidated that moisture content was the major driver controlling the relative contributions of nitrification and denitrification to N₂O production, while NH₄ ⁺ and NO₃ ^- concentrations mainly determined the N₂O production rates from each pathway. The moisture treatments with broad contents and narrow gradient were required to capture the comprehensive response of soil N₂O production rate to moisture change, and the response is essential for accurately predicting N₂O emission from agricultural soils under climate change scenarios.

Modeling impacts of drought-induced salinity intrusion on carbon dynamics in tidal freshwater forested wetlands

Tidal freshwater forested wetlands (TFFW) provide critical ecosystem services including an essential habitat for a variety of wildlife species and significant carbon sinks for atmospheric carbon dioxide. However, large uncertainties remain concerning the impacts of climate change on the magnitude and variability of carbon fluxes and storage across a range of TFFW. In this study, we developed a process-driven Tidal Freshwater Wetlands DeNitrification-DeComposition model (TFW-DNDC) that has integrated new features, such as soil salinity effects on plant productivity and soil organic matter decomposition to explore carbon dynamics in the TFFW in response to drought-induced saltwater intrusion. Eight sites along the floodplains of the Waccamaw River (USA) and the Savannah River (USA) were selected to represent the TFFW transition from healthy to moderately and highly salt-impacted forests, and eventually to oligohaline marshes. The TFW-DNDC was calibrated and validated using field observed annual litterfall, stem growth, root growth, soil heterotrophic respiration, and soil organic carbon storage. Analyses indicate that plant productivity and soil carbon sequestration in TFFW could change substantially in response to increased soil pore water salinity and reduced soil water table due to drought, but in interactive ways dependent on the river simulated. These responses are variable due to nonlinear relationships between carbon cycling processes and environmental drivers. Plant productivity, plant respiration, soil organic carbon sequestration rate, and storage in the highly salt-impacted forest sites decreased significantly under drought conditions compared with normal conditions. Considering the high likelihood of healthy and moderately salt-impacted forests becoming highly salt-impacted forests under future climate change and sea-level rise, it is very likely that the TFFW will lose their capacity as carbon sinks without up-slope migration.

Soil moisture-atmosphere feedback dominates land N2 O nitrification emissions and denitrification reduction

Soil moisture (SM) is essential to microbial nitrogen (N)-cycling networks in terrestrial ecosystems. Studies have found that SM-atmosphere feedbacks dominate the changes in land carbon fluxes. However, the influence of SM-atmosphere feedbacks on the N fluxes changes, and the underlying mechanisms remain highly unsure, leading to uncertainties in climate projections. To fill this gap, we used in situ observation coupled with gridded and remote sensing data to analyze N₂ O fluxes emissions globally. Here, we investigated the synergistic effects of temperature, hydroclimate on global N₂ O fluxes, as the result of SM-atmosphere feedback impact on N fluxes. We found that SM-temperature feedback dominates land N₂ O emissions by controlling the balance between nitrifier and denitrifier genes. The mechanism is that atmospheric water demand increases with temperature and thereby reduces SM, which increases the dominant N₂ O production nitrifier (containing amoA AOB gene) and decreases the N₂ O consumption denitrifier (containing the nosZ gene), consequently will potential increasing N₂ O emissions. However, we find that the spatial variations of soil-water availability as a result of the nonlinear response of SM to vapor pressure deficit caused by temperature are some of the greatest challenges in predicting future N₂ O emissions. Our data-driven assessment deepens the understanding of the impact of SM-atmosphere interactions on the soil N cycle, which remains uncertain in earth system models. We suggest that the model needs to account for feedback between SM and atmospheric temperature when estimating the response of the N₂ O emissions to climatic change globally, as well as when conducting field-scale investigations of the response of the ecosystem to warming.

Integrating major agricultural practices into the TRIPLEX-GHG model v2.0 for simulating global cropland nitrous oxide emissions: Development, sensitivity analysis and site evaluation

Nitrous oxide (N₂O) emissions from croplands are one of the most important greenhouse gas sources while the estimation of which remains large uncertainties globally. To simulate N₂O emissions from global croplands, the process-based TRIPLEX-GHG model v2.0 was improved by coupling the major agricultural activities. Sensitivity experiment was used to measure the impact of the integrated processes to modeled N₂O emission found chemical N fertilization have the highest relative effect sizes. While the coefficient of the NO₃^- consumption rate for denitrification (COE_dNO3), controlling the first step of the denitrification process was identified to be the most sensitive parameter based on sensitivity analysis of model parameters. The model performed well when simulating the magnitude of the daily N₂O emissions for 39 calibration sites and the continental mean of the parameters were used to producing reasonable estimations for the means of the measured daily N₂O fluxes (R² = 0.87, slope = 1.07) and emission factors (EFs, R² = 0.70, slope = 0.72) during the experiment periods. The model reliability was further confirmed by model validation. General trend of modeled daily N₂O emissions were reasonably consistent with the observations of selected validated sites. In addition, high correlations between the results of modeled and observed mean N₂O emissions (R² = 0.86, slope = 0.82) and EFs (R² = 0.66, slope = 0.83) from 68 validation sites were obtained. Further improvement on more detailed estimations for the variation of the environmental factors, management effects as well as accurate model input model driving data are required to reduce the uncertainties of model simulations. Consequently, our simulation results demonstrate that the TRIPLEX-GHG model v2.0 can reliably estimate N₂O emissions from various croplands at the global scale, which contributes to closing global N₂O budget and sustainable development of agriculture.

How can process-based modeling improve peat CO2 and N2O emission factors for oil palm plantations?

Oil palm plantations on peat and associated drainage generate sizeable GHG emissions. Current IPCC default emission factors (EF) for oil palm on organic soil are based on a very limited number of observations from young plantations, thereby resulting in large uncertainties in emissions estimates. To explore the potential of process-based modeling to refine oil palm peat CO₂ and N₂O EFs, we simulated peat GHG emissions and biogeophysical variables over 30 years in plantations of Central Kalimantan, Indonesia. The DNDC model simulated well the magnitude of C inputs (litterfall and root mortality) and dynamics of annual heterotrophic respiration and peat decomposition N₂O fluxes. The modeled peat onsite CO₂-C EF was lower than the IPCC default (11 Mg C ha^-1 yr^-1) and decreased from 7.7 ± 0.4 Mg C ha^-1 yr^-1 in the first decade to 3.0 ± 0.2 and 1.8 ± 0.3 Mg C ha^-1 yr^-1 in the second and third decades of the rotation. The modeled N₂O-N EF from peat decomposition was higher than the IPCC default (1.2 kg N ha^-1 yr^-1) and increased from 3.5 ± 0.3 kg N ha^-1 yr^-1 in the first decade to 4.7-4.6 ± 0.5 kg N ha^-1 yr^-1 in the following ones. Modeled fertilizer-induced N₂O emissions were minimal and much less than 1.6% of N inputs recommended by the IPCC in wet climates regardless of soil type. Temporal variations in EFs were strongly linked to soil C:N ratio and soil mineral N content for CO₂ and fertilizer-induced N₂O emissions, and to precipitation, water table level and soil NH₄⁺ content for peat decomposition N₂O emissions. These results suggest that current IPCC EFs for oil palm on organic soil could over-estimate peat onsite CO₂ emissions and underestimate peat decomposition N₂O emissions and that temporal variation in emissions should be considered for further improvement of EFs.

Spatiotemporal changes in greenhouse gas emissions and soil organic carbon sequestration for major cropping systems across China and their drivers over the past two decades

Chinese agricultural systems have experienced dramatic changes in crop planting area, cropping system, irrigation and fertilization managements, and crop yields in recent decades. These changes can substantially affect greenhouse gases (GHG) emissions and soil organic carbon (SOC) sequestration in croplands. However, the spatiotemporal patterns, as well as their driving factors and mechanisms, have not been well understood. Here, the Denitrification-Decomposition model is calibrated and validated to estimate nitrous oxide (N₂O) and methane (CH₄) emissions and SOC sequestration for seven major cropping systems in China during 2001-2020. The Logarithmic Mean Divisia Index method is further applied to attribute the net GHG emissions (NGEs) trend to various drivers. The results show that the total N₂O emissions, CH₄ emissions, and SOC sequestration were approximately 23.7, 182.0, and 177.6 Tg CO₂-eq/year in the croplands across China. The national average NGEs per unit area ranged from -8705 to 8431 kg CO₂-eq ha^-1 year^-1 across the major cropping systems. During 2001-2020, the trend in national annual NGEs was 0.66 kg CO₂-eq ha^-1 year^-2, ranging from -78.9 to 82.2 kg CO₂-eq ha^-1 year^-2 across the major cropping systems. The paddy lands were mainly a carbon source due to the large amount of CH₄ emissions while the uplands could be a carbon sink owing to SOC sequestration. As a whole, the cropland in China was a carbon source with the NGEs equal to 28.4 Tg CO₂-eq/year, and the NGEs increased by 0.047 Tg CO₂-eq/year² in the past 20 years. Nationally, changes in crop planting area and yields reduced the NGEs whereas changes in nitrogen use efficiency and cropping systems increased them, although the major factors and their impacts varied greatly among regions. Optimizing cropping systems and nitrogen fertilization based on the local genotype, environment and management should be the most effective method to reduce the NGEs in croplands.

Contribution of Incorporating the Phosphorus Cycle into TRIPLEX-CNP to Improve the Quantification of Land Carbon Cycle

Phosphorus (P) is a key and a limiting nutrient in ecosystems and plays an important role in many physiological and biochemical processes, affecting both terrestrial ecosystem productivity and soil carbon storage. However, only a few global land surface models have incorporated P cycle and used to investigate the interactions of C-N-P and its limitation on terrestrial ecosystems. The overall objective of this study was to integrate the P cycle and its interaction with carbon (C) and nitrogen (N) into new processes model of TRIPLEX-CNP. In this study, key processes of the P cycle, including P pool sizes and fluxes in plant, litter, and soil were integrated into a new model framework, TRIPLEX-CNP. We also added dynamic P:C ratios for different ecosystems. Based on sensitivity analysis results, we identified the phosphorus resorption coefficient of leaf (rpleaf) as the most influential parameter to gross primary productivity (GPP) and biomass, and determined optimal coefficients for different plant functional types (PFTs). TRIPLEX-CNP was calibrated with 49 sites and validated against 116 sites across eight biomes globally. The results suggested that TRIPLEX-CNP performed well on simulating the global GPP and soil organic carbon (SOC) with respective R2 values of 0.85 and 0.78 (both p < 0.01) between simulated and observed values. The R2 of simulation and observation of total biomass are 0.67 (p < 0.01) by TRIPLEX-CNP. The overall model performance had been improved in global GPP, total biomass and SOC after adding the P cycle comparing with the earlier version. Our work represents the promising step toward new coupled ecosystem process models for improving the quantifications of land carbon cycle and reducing uncertainty.

Comprehensive quantification of global cropland ammonia emissions and potential abatement

Ammonia (NH₃) emissions mostly from agriculture result in air pollution and degrade human health. However, a full picture of soil NH₃ emissions and associated abatement in cropping systems are not well understood. Here we present a thorough analysis of cropland NH₃ emissions, discuss mitigation potential and assess associated abatement costs. Global cropland NH₃ emissions account for 26% of total soil nitrogen losses, and are estimated as 22.8-31.2 Tg N yr^-1 during 1996-2013 with the increase rate of 1.6% yr^-1. Our results also show that, with no increase in nitrogen fertilizer, climate change can contribute to an additional 10% increase in cropland NH₃ emissions in 2100 compared to the 2010 baseline. Instead, our scenario analysis show, cropland NH₃ emissions will decline by 26% from 2010 to 2100 given a 0.5% yr^-1 decrease in N fertilizer (with current technology and agricultural management level), considering the facts stronger control policies are expected to occur worldwide including Western Europe, the United States of America and China. The most ambitious management (with all known mitigation practices) can reduce cropland NH₃ emissions by up (71%, 17.6 Tg N yr^-1) at an abatement cost of US$524 billion. Our findings indicate that cropland NH₃ emissions can be mitigated through adoption of appropriate human management practices with considerable economic costs, providing a critical reference for the future NH₃ abatement strategies.

Greenhouse gas emissions and C costs of N release associated with cover crop decomposition are plant specific and depend on soil moisture: A microcosm study

Cover cropping is used to improve soil quality and increase N inputs in agricultural systems, but it also may enhance greenhouse gases (GHG) emissions. Here, a 47-d incubation study was conducted to track the decomposition process and evaluate GHG emissions and its drivers and to calculate the C costs of residue-derived N released following the addition of residues from cover crops (pigeon pea, cowpea, lablab bean, vetch, and black oat) and maize under two water-filled pore space (WFPS) levels (40 and 70%). For both WFPS levels, the increase in cumulative CO₂ fluxes in plots that received residues is mainly related with the increment of potentially mineralizable C. Crop residues increased the global warming potential (GWP) under both WFPS levels, with CO₂ emissions accounting for ≥98% of the GWP at 40% WFPS. At 70% WFPS, the GPW increment was driven by a notable increase in N₂ O emissions. The contribution of CH₄ in the GWP emissions was negligible for all the crop residues evaluated. Principal component analysis highlighted that the optimal conditions for production and release are specific for each GHG. The cleaner N source was cowpea at 40% WFPS, which produced only 17.7 kg CO₂ -eq kg^-1 N mineralized, compared with vetch residues, which produced 233 kg CO₂ -eq kg^-1 N mineralized. To integrate agronomic and climate change mitigation perspectives, we suggest considering the C costs of the residue-N released when choosing a cover crop.

Role of chemical reactions in the nitrogenous trace gas emissions and nitrogen retention: A meta-analysis

Increasing evidence has been found that chemical reactions affect significantly the terrestrial nitrogen (N) cycle, which was previously assumed to be mainly dominated by biological processes. Due to the limitation of knowledge and analytical techniques, it is currently challenging to discern the contribution of biotic and abiotic processes to the terrestrial N cycle for geobiologists and biogeochemists alike. To better understand the role of abiotic reactions in the terrestrial N cycle, it is necessary to comprehend the chemical controls on nitrogenous trace gas emissions and N retention in soil under various environmental conditions. In this manuscript, we assess the role of abiotic reactions in nitrous oxide (N₂O) and nitric oxide (NO) emissions as well as N retention through a meta-analysis using all related peer-reviewed publications before August 2020. Results show that abiotic reactions contributed 29.3-37.7% and 44.0-57.0% to the total N₂O emission and N retention, representing 3.7-4.7 and 4.0-6.0 Tg year^-1 of global terrestrial N₂O emission and N retention, respectively. Much higher NO production was observed in sterilized soils than that in unsterilized treatments indicating the major contribution of chemical reactions to NO emission and rapid microbial reduction of NO to N₂O and N₂. Chemical hydroxylamine oxidation accounts for the largest abiotic contribution to N₂O emission, while chemical nitrite reduction and fixation represent for the largest contribution to abiotic NO production and soil N retention, respectively. Factors influencing the abiotic processes include pH, total organic carbon (TOC), total nitrogen (TN), the ratio of carbon to nitrogen (C/N), and transition metals. These results broadened our knowledge about the mechanisms involved in chemical N reactions and provided a simplified estimation about their contribution to nitrogenous trace gas emission and N retention, which is meaningful to further study interactions of biologically and chemically mediated reactions in biogeochemical N cycle.

Modeling Nitrous Oxide Emissions From Large-Scale Intensive Cropping Systems in the Southern Amazon

Nitrogen (N) fertilizer use is rapidly intensifying on tropical croplands and has the potential to increase emissions of the greenhouse gas, nitrous oxide (N2O). Since about 2005 Mato Grosso (MT), Brazil has shifted from single-cropped soybeans to double-cropping soybeans with maize, and now produces 1.5% of the world's maize. This production shift required an increase in N fertilization, but the effects on N2O emissions are poorly known. We calibrated the process-oriented biogeochemical DeNitrification-DeComposition (DNDC) model to simulate N2O emissions and crop production from soybean and soybean-maize cropping systems in MT. After model validation with field measurements and adjustments for hydrological properties of tropical soils, regional simulations suggested N2O emissions from soybean-maize cropland increased almost fourfold during 2001–2010, from 1.1 ± 1.1 to 4.1 ± 3.2 Gg 1014 N-N2O. Model sensitivity tests showed that emissions were spatially and seasonably variable and especially sensitive to soil bulk density and carbon content. Meeting future demand for maize using current soybean area in MT might require either (a) intensifying 3.0 million ha of existing single soybean to soybean-maize or (b) increasing N fertilization to ~180 kg N ha−1 on existing 2.3 million ha of soybean-maize area. The latter strategy would release ~35% more N2O than the first. Our modifications of the DNDC model will improve estimates of N2O emissions from agricultural production in MT and other tropical areas, but narrowing model uncertainty will depend on more detailed field measurements and spatial data on soil and cropping management.

Evaluation of LandscapeDNDC Model Predictions of CO2 and N2O Fluxes from an Oak Forest in SE England

Process-based biogeochemical models are valuable tools to evaluate impacts of environmental or management changes on the greenhouse gas (GHG) balance of forest ecosystems. We evaluated LandscapeDNDC, a process-based model developed to simulate carbon (C), nitrogen (N) and water cycling at ecosystem and regional scales, against eddy covariance and soil chamber measurements of CO2 and N2O fluxes in an 80-year-old deciduous oak forest. We compared two LandscapeDNDC vegetation modules: PSIM (Physiological Simulation Model), which includes the understorey explicitly, and PnET (Photosynthesis–Evapotranspiration Model), which does not. Species parameters for both modules were adjusted to match local measurements. LandscapeDNDC was able to reproduce daily micro-climatic conditions, which serve as input for the vegetation modules. The PSIM and PnET modules reproduced mean annual net CO2 uptake to within 1% and 15% of the measured values by balancing gains and losses in seasonal patterns with respect to measurements, although inter-annual variations were not well reproduced. The PSIM module indicated that the understorey contributed up to 21% to CO2 fluxes. Mean annual soil CO2 fluxes were underestimated by 32% using PnET and overestimated by 26% with PSIM; both modules simulated annual soil N2O fluxes within the measured range but with less interannual variation. Including stand structure information improved the model, but further improvements are required for the model to predict forest GHG balances and their inter-annual variability following climatic or management changes.

Ammonia volatilization modeling optimization for rice watersheds under climatic differences

The ammonia (NH₃) volatilization mechanism is complicated with pronounced watershed differences of climate conditions, soil properties, and tillage practices. The watershed NH₃ emission dynamics model was developed with the combination of field measurements, Soil Water Assessment Tool and NH₃ volatilization algorithms. The temporal NH₃ emissions patterns and the watershed NH₃ volatilization dynamics were simulated with the improved NH₃ volatilization modeling. Five monitoring sites and three case watersheds across China were selected to highlight the impacts of climatic conditions and validated the modeling. The average NH₃ emissions of the three watersheds ranged from 14.94 to 120.33 kg N ha^-1, which were mainly positively correlated with temperatures (r = 0.56, p < 0.01) and negatively correlated with soil organic carbon content (r = -0.33, p < 0.01). Analysis of similarities indicated that significant differences existed between the watersheds in terms of NH₃ volatilization (R_ANOSIM = 0.758 and 0.834, p < 0.01). These analysis imply that environmental variabilities were more important than N input amounts.

Modeling the effect of salt-affected soil on water balance fluxes and nitrous oxide emission using modified DNDC

Soil salinity restricts plant growth, affects soil water balance and nitrous oxide (N₂O) fluxes and can contaminate surface and groundwater. In this study, the Denitrification Decomposition (DNDC) model was modified to couple salt and water balance equations (SALT-DNDC) to investigate the effect of salinity on water balance and N₂O fluxes. The model was examined against four growing seasons (2008-11) of observed data from Lethbridge, Alberta, Canada. Then, the model was used to simulate water filled pore space (WFPS), salt concentration and the N₂O flux from agricultural soils. The results show that the effects of salinity on WFPS vary in different soil layers. Within shallow soil layers (<20 cm from soil surface) the salt concentration does not affect the average WFPS when initial salt concentrations range from 5 to 20 dS/m. However, in deeper soil layers (>20 cm from soil surface), when the initial salt concentration ranges from 5 to 20 dS/m it could indirectly affect the average WFPS due to changes of osmotic potential and transpiration. When AW is greater than 40%, the average growing season N₂O emissions increase to a range of 0.6-1.0 g-N/ha/d at initial salt concentrations (5-20 dS/m) from a range of 0.5-0.7 g-N/ha/d when the salt concentrations is 0 dS/m. The newly developed SALT-DNDC model provides a unique tool to help investigate interactive effects among salt, soil, water, vegetation, and weather conditions on N₂O fluxes.

Modelling spatio-temporal patterns of soil carbon and greenhouse gas emissions in grazing lands: Current status and prospects

The sustainability of grazing lands lies in the nexus of human consumption behavior, livestock productivity, and environmental footprint. Due to fast growing global food demands, many grazing lands have suffered from overgrazing, leading to soil degradation, air and water pollution, and biodiversity losses. Multidisciplinary efforts are required to understand how these lands can be better assessed and managed to attain predictable outcomes of optimal benefit to society. This paper synthesizes our understanding based on previous work done on modelling the influences of grazing of soil carbon (SC) and greenhouse gas emissions to identify current knowledge gaps and research priorities. We revisit three widely-used process-based models: DeNitrification DeComposition (DNDC), DayCent, and the Pasture Simulation model (PaSim) and two watershed models: The Soil & Water Assessment Tool (SWAT) and Variable Infiltration Capacity Model (VIC), which are widely used to simulate C, nutrient and water cycles. We review their structures and ability as process-based models in representing key feedbacks among grazing management, SOM decomposition and hydrological processes in grazing lands. Then we review some significant advances in the use of models combining biogeochemical and hydrological processes. Finally, we examine challenges of incorporating spatial heterogeneity and temporal variability into modelling C and nutrient cycling in grazing lands and discuss their weakness and strengths. We also highlight key research direction for improving the knowledge base and code structure in modelling C and nutrient cycling in grazing lands, which are essential to conserve grazing lands and maintain their ecosystem goods and services.

Coupled hydrological and biogeochemical modelling of nitrogen transport in the karst critical zone

Transport of nitrogen (N) in karst areas is more complex than in non-karst areas due to marked heterogeneity of hydrodynamic behaviour in the karst critical zone. Here, we present a novel, distributed, coupled hydrological-biogeochemical model that can simulate water and nitrogen transport in the critical zone of karst catchments. This new model was calibrated using integrated hydrometric, water stable isotope, and nitrogen-N concentration data at the outflow of Houzhai catchment in Guizhou province of Southwest China. Hydrological dynamics appears to control N load from the study catchment. Combining flow discharge and water stable isotopes significantly constrained model parameterisation and mitigate the equifinality effects of parameters on the simulated results. Karst geomorphology and land use have functional effects on spatiotemporal variations of hydrological processes and nitrogen transport. In the study catchment, agricultural fertilizer was the largest input source of N, accounting for 86% of the total. Plant uptake consumed about 45% of inputs, primarily in the low-lying valley bottom areas and the plain covered by relatively thick soils. Thus, a large amount of N released from soil reservoirs to the epikarst (via fractures or sinkholes) is then exported to the underground channel in the limestone area to the south. This N draining into groundwater could lead to extensive, potentially long-term contamination of the karst system. Therefore, improving the efficiency of fertilization and agricultural management in valleys/depressions is an urgent need to reduce N losses and contamination risk.

Ensemble projections elucidate effects of uncertainty in terrestrial nitrogen limitation on future carbon uptake

The magnitude of the nitrogen (N) limitation of terrestrial carbon (C) storage over the 21st century is highly uncertain because of the complex interactions between the terrestrial C and N cycles. We use an ensemble approach to quantify and attribute process-level uncertainty in C-cycle projections by analysing a 30-member ensemble representing published alternative representations of key N cycle processes (stoichiometry, biological nitrogen fixation (BNF) and ecosystem N losses) within the framework of one terrestrial biosphere model. Despite large differences in the simulated present-day N cycle, primarily affecting simulated productivity north of 40°N, ensemble members generally conform with global C-cycle benchmarks for present-day conditions. Ensemble projections for two representative concentration pathways (RCP 2.6 and RCP 8.5) show that the increase in land C storage due to CO₂ fertilization is reduced by 24 ± 15% due to N constraints, whereas terrestrial C losses associated with climate change are attenuated by 19 ± 20%. As a result, N cycling reduces projected land C uptake for the years 2006-2099 by 19% (37% decrease to 3% increase) for RCP 2.6, and by 21% (40% decrease to 9% increase) for RCP 8.5. Most of the ensemble spread results from uncertainty in temperate and boreal forests, and is dominated by uncertainty in BNF (10% decrease to 50% increase for RCP 2.6, 5% decrease to 100% increase for RCP 8.5). However, choices about the flexibility of ecosystem C:N ratios and processes controlling ecosystem N losses regionally also play important roles. The findings of this study demonstrate clearly the need for an ensemble approach to quantify likely future terrestrial C-N cycle trajectories. Present-day C-cycle observations only weakly constrain the future ensemble spread, highlighting the need for better observational constraints on large-scale N cycling, and N cycle process responses to global change.

Calibration and validation of the DNDC model to estimate nitrous oxide emissions and crop productivity for a summer maize-winter wheat double cropping system in Hebei, China

The main aim of this paper was to calibrate and evaluate the DeNitrification-DeComposition (DNDC) model for estimating N₂O emissions and crop productivity for a summer maize-winter wheat double cropping system with different N fertilizer rates in Hebei, China. The model's performance was assessed before and after calibration and model sensitivity was investigated. The calibrated and validated DNDC performed effectively in estimating cumulative N₂O emissions (coefficient of determination (1:1 relationship; r²) = 0.91; relative deviation (RD) = -13 to 16%) and grain yields for both crops (r² = 0.91; RD = -21 to 7%) from all fertilized treatments, but poorly estimated daily N₂O patterns. Observed and simulated results showed that optimal N fertilizer treatment decreased cumulative N₂O flux, compared to conventional N fertilizer, without a significant impact on grain yields of the summer maize-winter wheat double cropping system. The high sensitivity of the DNDC model to rainfall, soil organic carbon and temperature resulted in significant overestimation of N₂O peaks during the warm wet season. The model also satisfactorily estimated daily patterns/average soil temperature (^o C; 0-5 cm depth) (r² = 0.88 to 0.89; root mean square error (RMSE) = 4 °C; normalized RMSE (nRMSE) = 25% and index of agreement (d) = 0.89-0.97) but under-predicted water filled pore space (WFPS; %; 0-20 cm depth) (r² = 0.3 to 0.4) and soil ammonium and nitrate (exchangeable NH₄⁺ & NO₃^-; kg N ha^-1; r² = 0.97). With reference to the control treatment (no N fertilizer), DNDC was weak in simulating both N₂O emissions and crop productivity. To be further improved for use under pedo-climatic conditions of the summer maize-winter wheat double cropping system we suggest future studies to identify and resolve the existing problems with the DNDC, especially with the control treatment.

Modifying fertilizer rate and application method reduces environmental nitrogen losses and increases corn yield in Ontario

Nitrogen (N) use in corn production is an important driver of nitrous oxide (N₂O) emissions and 4R (Right source, Right rate, Right time and Right place) fertilizer practices have been proposed to mitigate emissions. However, combined 4R practices have not been assessed for their potential to reduce N₂O emissions at the provincial-scale while also considering trade-offs with other N losses such as leaching or ammonia (NH₃) volatilization. The objectives of this study were to develop, validate, and apply a Denitrification-Decomposition model framework at 270 distinct soil-climate regions in Ontario to simulate corn yield and N₂O emissions across eleven fertilizer management scenarios during 1986-2015. The results show that broadcasting fertilizer at the surface without incorporation had the highest environmental N loss which was primarily caused by NH₃ volatilization. When injected at planting or at sidedress, the NH₃ loss was reduced considerably. However, because more N was left in the soil, injection and sidedressing induced more losses by nitrate leaching and N₂O emissions. Reduction of N rate as proposed by the DNDC model did not affect crop yield but decreased leaching and N₂O emissions. Addition of inhibitors promoted a further reduction in N₂O emission (11-16%) although lesser than the reduction in N rate. Overall, our results emphasize that N rate adjustment following improvements in placement, use of inhibitors, and application timings can mitigate N₂O emissions by 42-57% and result in 3-4% greater yields compared to baseline scenario in Ontario corn production.

Modelling of nitrification inhibitor and its effects on emissions of nitrous oxide (N2O) in the UK

Global food demand requires increased uses of fertilizers, leading to nitrous oxide (N₂O) and nitrate leaching due to overuse of fertilizers and poor timing between fertilizer application and plant growth. Using nitrification inhibitors (NIs) can reduce the N₂O emissions but the effectiveness of NIs strongly depend on environmental conditions, and their benefits have been limited due to less than optimal nitrogen rates, timing, quantity, and placement of NIs. Process-based modelling can be helpful in improving the understanding of nitrogen fertilizer with NIs and their effects in different environmental conditions and agricultural practices. But few studies of modelling NIs with application to agricultural soils have been performed. In this paper, we developed a sophisticated biogeochemical reaction process of NIs applied to agricultural soils, which account for the factions of NIs with fertilizer by combining the application rate, soil moisture, and temperature within the DeNitrification DeComposition (DNDC) framework. This model was tested against the data from two agricultural farms in Preston Wynne and Newark in the UK. The results agreed well with the measured data and captured the measured soil moistures and N₂O emissions. In Newark, the average Mean Absolute Error of all blocks is 8.78 and 5.45 for ammonium nitrate or urea respectively while in Preston Wynne, 3.48 and 3.14. The results also showed that the warming climate can greatly reduce the efficiency of nitrification inhibitors, which will further amplify the greenhouse gas impacts. The modified DNDC model of nitrification inhibitor modules can reliably simulate the inhibitory effect of NIs on N₂O emissions and evaluate the efficiency of NIs. This enables end-users to optimize the amount of NIs used according to the time and climate conditions of fertilizer application for increasing crop yield and reducing N₂O emissions and provides a useful tool for estimating the efficiency of NIs in agricultural management.

Carbon Footprint of Mediterranean Pasture-Based Native Beef: Effects of Agronomic Practices and Pasture Management under Different Climate Change Scenarios

Simple Summary

The livestock sector requires a significant amount of natural resources and has an important role in climate change. Although the carbon footprint has become a widely accepted indicator for assessing the greenhouse gases emitted per unit of product, due to the lack of a commonly accepted methodology, there are still few studies that have included soil organic carbon sequestration in their calculations. In this study, by including soil organic carbon dynamics, the carbon footprint of a Mediterranean pasture-based beef cattle farm was estimated using current weather data and farming management policies. Subsequently, different soil management strategies, grazing systems, and climate scenarios were compared to the current ones to investigate the effects of these variables on the greenhouse gases emitted. The results showed that the current beef carbon footprint could be significantly reduced by switching to reduced tillage systems. The modeled combination of no-tillage practices with higher organic fertilizer application rates showed a greater potential carbon footprint reduction. No significant differences were found between carbon footprint values modeled under different climate scenarios and grazing systems. By including a process-based model into its carbon footprint calculations, this study highlights the climate mitigation potential of different farming practices and the importance of considering soil carbon sequestration.

Abstract

A better understanding of soil organic carbon (SOC) dynamics is needed when assessing the carbon footprint (CFP) of livestock products and the effectiveness of possible agriculture mitigation strategies. This study aimed (i) to perform a cradle-to-gate CFP of pasture-based beef cattle in a Mediterranean agropastoral system (ii) and to assess the effects on the CFP of alternative tillage, fertilizing, and grazing practices under current (NCC) and future climate change (CC) scenarios. Minimum (Mt) and no-tillage (Nt) practices were compared to current tillage (Ct); a 50% increase (Hf) and decrease (Lf) in fertilization was evaluated against the current (Cf) rate; and rotational grazing (Rg) was evaluated versus the current continuous grazing (Cg) system. The denitrification–decomposition (DNDC) model was run using NCC as well as representative concentration pathways to investigate the effects of farm management practices coupled with future CC scenarios on SOC dynamics, N₂O fluxes, and crop yield. Within NCC and CtCf, an emission intensity of 26.9 ± 0.7 kg CO_2eq per kg live body weight was estimated. Compared to Ct, the adoption of Mt and Nt reduced the CFP by 20% and 35%, respectively, while NtHf reduced it by 40%. Conservation tillage practices were thus shown to be effective in mitigating greenhouse gas emissions.

Simulation of dissolved organic carbon concentrations and fluxes in Chinese monsoon forest ecosystems using a modified TRIPLEX-DOC model

Dissolved organic carbon (DOC) plays an important role in global and regional carbon cycles. However, the quantification of DOC in forest ecosystems remains uncertain. Here, the processed-based biogeochemical model TRIPLEX-DOC was modified by optimizing the function of soil organic carbon distribution with increasing depths, as well as DOC sorption-desorption efficiency. The model was validated by field measurements of DOC concentration and flux at five forest sites and Beijiang River basin in monsoon regions of China. Model validation indicated that seasonal patterns of DOC concentration across climatic zones were different, and these differences were captured by our model. Importantly, the modified model performed better than the original model. Indeed, model efficiency of the modified model increased from -0.78 to 0.19 for O horizon predictions, and from -0.46 to 0.42 for the mineral soils predictions. Likewise, DOC fluxes were better simulated by the modified model. At the site scale, the simulated DOC fluxes were strongly correlated with the observed values (R² = 0.97, EF = 0.91). At the regional scale, the DOC flux predicted in the Beijiang River basin was 16.44 kg C/ha, which was close to the observed value of 17 kg C/ha. Using sensitivity analysis, we showed that temperature, precipitation and temperature sensitivity of DOC decomposition (Q₁₀) were the most sensitive parameters when predicting DOC concentrations and fluxes in forest soils. We also found that both the percentage of DOC flux to forest net ecosystem productivity, and the retention of DOC by mineral soil were highly correlated with the amount of precipitation. Overall, our model validations indicated that the modified TRIPLEX-DOC model is a useful tool for simulating the dynamics of DOC concentrations and fluxes in forest ecosystems. We highlight that more accurate estimates of parameter Q₁₀ in deep mineral soils can reduce model uncertainty, when simulating DOC concentrations and fluxes in forest soils.

Dynamics and underlying mechanisms of N2O and NO emissions in response to a transient land-use conversion of Masson pine forest to tea field

Nowadays, there has been a rapid expansion of tea field converted from forestry for pursuing higher economic benefits. However, few researches focus on the effects of transient land-use conversion from Masson pine forest to artificial tea fields on soil N₂O and NO emissions and the underlying mechanisms. A parallel field experiment was conducted from Masson pine forest and a newly converted tea plantation from Masson pine forest from 2013 to 2017 in subtropical central China. Masson pine forest conversion to tea field dramatically increased soil N₂O and NO emissions (up to 4.00 ± 0.43 and 1.93 ± 0.45 kg N ha^-1 yr^-1, respectively) in the first year possibly due to enhanced soil organic N mineralization. With the extension of tea planting age, N₂O and NO emissions showed an upward trend (ranged from 1.19 to 5.28, and 0.15 to 1.78 kg N ha^-1 yr^-1, respectively) influenced by fertilization and soil organic matter accumulation. The direct emission factors for N₂O and NO in the newly converted tea fields were the largest in the first year (2.64 and 1.07%, respectively) after land-use conversion, and higher than the default value recommended by IPCC. The NO/N₂O ratio was mainly lower than 1 in the fertilized tea field, and soil N₂O and NO emission peaks mainly occurred in tea-growing season (wet season) with higher soil moisture and NH₄⁺-N concentrations, and dominated by amoA-containing bacteria (AOB), suggesting nitrifier-denitrification could be the dominant process involved in soil nitrogenous gases emissions in tea field. These results can be summarized as dramatically increased soil N₂O and NO emissions during the transient land-use conversion from Masson pine forest to tea field were possibly due to the substantial net soil organic N mineralization and the enhanced abundance of nitrification functional genes (AOB).

Oxygen Regulates Nitrous Oxide Production Directly in Agricultural Soils

Oxygen (O₂) plays a critical and yet poorly understood role in regulating nitrous oxide (N₂O) production in well-structured agricultural soils. We investigated the effects of in situ O₂ dynamics on N₂O production in a typical intensively managed Chinese cropping system under a range of environmental conditions (temperature, moisture, ammonium, nitrate, dissolved organic carbon, and so forth). Climate and management (fertilization, irrigation, precipitation, and temperature), and their interactions significantly affected soil O₂ and N₂O concentrations (P < 0.05). Soil O₂ concentration was the most significant factor correlating with soil N₂O concentration (r = -0.71) when compared with temperature, water-filled pore space, and ammonium concentration (r = 0.30, 0.25, and 0.26, respectively). Soil N₂O concentration increased exponentially with decreasing soil O₂ concentrations. The exponential model of N treatments and fertilization with irrigation/precipitation events predicted 74-90% and 58% of the variance in soil N₂O concentrations, respectively. Our results highlight that the soil O₂ status is the proximal, direct, and the most decisive environmental trigger for N₂O production, outweighing the effects of other factors and could be a key variable integrating the aggregated effects of various complex interacting variables. This study offers new opportunities for developing more sensitive approaches to predicting and through appropriate management interventions mitigating N₂O emissions from agricultural soils.

Drought Superimposes the Positive Effect of Silver Fir on Water Relations of European Beech in Mature Forest Stands

Research Highlights: Investigations of evapotranspiration in a mature mixed beech-fir forest stand do not indicate higher resilience towards intensified drying-wetting cycles as compared with pure beech stands. Background and Objectives: Forest management seeks to implement adaptive measures, for example, the introduction of more drought resistant species into prevailing monospecific stands to minimize forest mortality and monetary losses. In Central Europe this includes the introduction of native silver fir (Abies alba) into monospecific beech (Fagus sylvatica) stands. In order to determine, if the introduction of fir would improve the resilience against drier conditions, this study investigates water relations of a mature pure beech and a mature mixed beech-fir stand under natural as well as reduced water availability. Materials and Methods: Sap flow rates and densities were measured in two consecutive years using the heat ratio method and scaled using stand inventory data and modeling. Results: Transpiration rates estimated from sap flow were significantly higher for beech trees as compared with silver fir which was attributed to the more anisohydric water-use strategy of the beech trees. We estimate that stand evapotranspiration was slightly higher for mixed stands due to higher interception losses from the mixed stand during times of above average water supply. When precipitation was restricted, beech was not able to support its transpiration demands, and therefore there was reduced sap flow rates in the mixed, as well as in the pure stand, whereas transpiration of fir was largely unaffected, likely due to its more isohydric behavior toward water use and access to moister soil layers. Thus, we found the rates of evapotranspiration in the mixed beech-fir stand to be smaller during times with no precipitation as compared with the pure beech stand, which was accountable to the severely reduced transpiration of beech in the mixed stand. Conclusions: We conclude that smaller evapotranspiration rates in the mixed beech-fir stand might not be the result of increased water use efficiency but rather caused by restricted hydraulic conductivity of the root system of beech, making mixed beech-fir stands at this site less resilient towards drought.

Effect of silicon on barley growth and N2O emission under flooding

The global climate change is related with greenhouse gas emission from cultivated soils - carbon dioxide, methane and nitrous oxide. The emissions of N₂O also have negative influence on ozone layer of our planet. The major source of the nitrous oxide is denitrification process in soil, which controlled by specific soil microbe society. The pot experiment with flooding to accelerate the denitrification process and the application of the monosilicic acid as a source of soluble form of Si was carried out with barley. Several forms of nitrous oxide emission (unlimited carbon denitrification and potential denitrification with or without ethylene application) were measured. The obtained data showed that the application of monosilicic acid to brown soil when growing barley under conditions of soil flooding has a significant effect on nitrogen emission and can change the N₂O:N₂ ratio. The application of the monosilicic acid reduced the uC-D N₂O emission, while increased the PD N emission. Generally the application of the water soluble Si decreased the N₂O:N₂ ratio. We suggested that the presence of monosilicic acid in the system provides a more complete denitrification process with the formation of N₂ in the NO₃^- → NO₂^- → NO→N₂O → N₂ reaction sequence, while the deficiency of bioactive Si mainly provides the formation and emission of N₂O. Considering that N₂ is not a greenhouse gas, we can conclude that application of monosilicic acid to the soil can reduce greenhouse gas emissions and reduce the impact of global climate change on agricultural activity.

Data-driven estimates of global nitrous oxide emissions from croplands

Croplands are the single largest anthropogenic source of nitrous oxide (N₂O) globally, yet their estimates remain difficult to verify when using Tier 1 and 3 methods of the Intergovernmental Panel on Climate Change (IPCC). Here, we re-evaluate global cropland-N₂O emissions in 1961–2014, using N-rate-dependent emission factors (EFs) upscaled from 1206 field observations in 180 global distributed sites and high-resolution N inputs disaggregated from sub-national surveys covering 15593 administrative units. Our results confirm IPCC Tier 1 default EFs for upland crops in 1990–2014, but give a ∼15% lower EF in 1961–1989 and a ∼67% larger EF for paddy rice over the full period. Associated emissions (0.82 ± 0.34 Tg N yr^–1) are probably one-quarter lower than IPCC Tier 1 global inventories but close to Tier 3 estimates. The use of survey-based gridded N-input data contributes 58% of this emission reduction, the rest being explained by the use of observation-based non-linear EFs. We conclude that upscaling N₂O emissions from site-level observations to global croplands provides a new benchmark for constraining IPCC Tier 1 and 3 methods. The detailed spatial distribution of emission data is expected to inform advancement towards more realistic and effective mitigation pathways.

Fraction of nitrous oxide production in nitrification and its effect on total soil emission: A meta-analysis and global-scale sensitivity analysis using a process-based model

Nitrification in terrestrial soils is one of the major processes of emission of nitrous oxide (N₂O), a potent greenhouse gas and stratospheric-ozone-depleting substance. We assessed the fraction of N₂O emission associated with nitrification in soil through a meta-analysis and sensitivity analysis using a process-based model. We corrected observational values of gross nitrification and associated N₂O emission rates from 71 records for various soils in the world spanning from 0.006% to 29.5%. We obtained a median value of 0.14%, and then assessed how the nitrification-associated N₂O emission fraction has been considered in terrestrial nitrogen cycle models. Using a process-based biogeochemical model, we conducted a series of sensitivity analyses for the effects of different values of nitrification-associated N₂O emission fraction on soil N₂O emission. Using an empirical relationship between soil pH and nitrification-associated N₂O emission fraction, the model well simulated global emission patterns (global total in the 2000s, 16.8 Tg N₂O yr^–1). Differences in the nitrification-associated N₂O emission fraction caused differences in total N₂O emission of as much as 2.5 Tg N₂O yr^–1. Therefore, to obtain reliable estimation of soil N₂O emission for nitrogen and climate management, it is important to constrain the parameterization in models by ensuring extensive and accurate observations.

Constraining N cycling in the ecosystem model LandscapeDNDC with the stable isotope model SIMONE

The isotopic composition (ic) of soil nitrogen (N) and, more recently, the intramolecular distribution of ¹⁵ N in the N₂ O molecule (site preference, SP) are powerful instruments to identify dominant N turnover processes, and to attribute N₂ O emissions to their source processes. Despite the process information contained in the ic of N species and the associated potential for model validation, the implementation of isotopes in ecosystem models has lagged behind. To foster the validation of ecosystem models based on the ic of N species, we developed the stable isotope model for nutrient cycles (SIMONE). SIMONE uses fluxes between ecosystem N pools (soil organic N, mineral N, plants, microbes) calculated by biogeochemical models, and literature isotope effects for these processes to calculate the ic of N species. Here, we present the concept of SIMONE, apply it to simulations of the biogeochemical model LandscapeDNDC, and assess the capability of ¹⁵ N-N₂ O and, to our knowledge for the first time, SP, to constrain simulated N fluxes by LandscapeDNDC. LandscapeDNDC successfully simulated N₂ O emission, soil nitrate, and ammonium, as well as soil environmental conditions of an intensively managed grassland site in Switzerland. Accordingly, the dynamics of ¹⁵ N-N₂ O and SP of soil N₂ O fluxes as simulated by SIMONE agreed well with measurements, though ¹⁵ N-N₂ O was on average underestimated and SP overestimated (root-mean-square error [RMSE] of 8.4‰ and 7.3‰, respectively). Although ¹⁵ N-N₂ O could not constrain the N cycling process descriptions of LandscapeDNDC, the overestimation of SP indicated an overestimation of simulated nitrification rates by 10-59% at low water content, suggesting the revision of the corresponding model parameterization. Our findings show that N isotope modeling in combination with only recently available high- frequency measurements of the N₂ O ic are promising tools to identify and address weaknesses in N cycling of ecosystem models. This will finally contribute to augmenting the development of model-based strategies for mitigating N pollution.

Modeling ammonia volatilization following urea application to winter cereal fields in the United Kingdom by a revised biogeochemical model

Urea accounts for over half of the global ammonia volatilization from synthetic nitrogen fertilization. Process-oriented models, such as the widely applied DeNitrification DeComposition 9.5 version (DNDC95), are expected to predict ammonia volatilization from agricultural urea applications under various conditions. However, compared to the wind-tunnel ammonia observations of a nationwide, seven-site/ten-case network in the United Kingdom, the DNDC95 greatly underestimated the ammonia volatilization from winter cereal fields applied with urea at a constant dose. The model was revised in this study mainly through (i) newly parameterizing the effects of clay fraction, plant standings and canopy wetting on ammonia release from the soil solution, and (ii) re-calibrating the parameters of the urea hydrolysis function and the original parameterizations of wind, soil temperature and moisture effects on ammonia volatilization using the observations in one case of the network. Next, the performances of the revised model (DNDC95_NH₃) in simulating grain yield, full crop nitrogen uptake, cumulative ammonia volatilization (CAV) and daily ammonia fluxes were evaluated using the observations of these variables in the other nine network cases. The DNDC95_NH₃ performed considerably better than the DNDC95. Particularly, the slopes of the zero-intercept regression for the observations versus simulations decreased from 1.97 to 0.86 and 1.65 to 0.75 for the CAV and daily ammonia fluxes, respectively. In addition, the number of the cases with significant discrepancies between simulated and observed CAV was reduced from six of the nine network cases to only two. The simulations by the revised model for these two cases showed a significant underestimation and an extremely large overestimation, respectively. However, reasons especially for the significant overestimation still remain unclear. Future studies still need to diagnose and solve the other existing problems so as to further improve the model's performance.

Global soil nitrous oxide emissions since the preindustrial era estimated by an ensemble of terrestrial biosphere models: Magnitude, attribution, and uncertainty

Our understanding and quantification of global soil nitrous oxide (N₂ O) emissions and the underlying processes remain largely uncertain. Here, we assessed the effects of multiple anthropogenic and natural factors, including nitrogen fertilizer (N) application, atmospheric N deposition, manure N application, land cover change, climate change, and rising atmospheric CO₂ concentration, on global soil N₂ O emissions for the period 1861-2016 using a standard simulation protocol with seven process-based terrestrial biosphere models. Results suggest global soil N₂ O emissions have increased from 6.3 ± 1.1 Tg N₂ O-N/year in the preindustrial period (the 1860s) to 10.0 ± 2.0 Tg N₂ O-N/year in the recent decade (2007-2016). Cropland soil emissions increased from 0.3 Tg N₂ O-N/year to 3.3 Tg N₂ O-N/year over the same period, accounting for 82% of the total increase. Regionally, China, South Asia, and Southeast Asia underwent rapid increases in cropland N₂ O emissions since the 1970s. However, US cropland N₂ O emissions had been relatively flat in magnitude since the 1980s, and EU cropland N₂ O emissions appear to have decreased by 14%. Soil N₂ O emissions from predominantly natural ecosystems accounted for 67% of the global soil emissions in the recent decade but showed only a relatively small increase of 0.7 ± 0.5 Tg N₂ O-N/year (11%) since the 1860s. In the recent decade, N fertilizer application, N deposition, manure N application, and climate change contributed 54%, 26%, 15%, and 24%, respectively, to the total increase. Rising atmospheric CO₂ concentration reduced soil N₂ O emissions by 10% through the enhanced plant N uptake, while land cover change played a minor role. Our estimation here does not account for indirect emissions from soils and the directed emissions from excreta of grazing livestock. To address uncertainties in estimating regional and global soil N₂ O emissions, this study recommends several critical strategies for improving the process-based simulations.

Tree stem bases are sources of CH4 and N2 O in a tropical forest on upland soil during the dry to wet season transition

Tropical forests on upland soils are assumed to be a methane (CH₄ ) sink and a weak source of nitrous oxide (N₂ O), but studies of wetland forests have demonstrated that tree stems can be a substantial source of CH₄ , and recent evidence from temperate woodlands suggests that tree stems can also emit N₂ O. Here, we measured CH₄ and N₂ O fluxes from the soil and from tree stems in a semi-evergreen tropical forest on upland soil. To examine the influence of seasonality, soil abiotic conditions and substrate availability (litter inputs) on trace greenhouse gas (GHG) fluxes, we conducted our study during the transition from the dry to the wet season in a long-term litter manipulation experiment in Panama, Central America. Trace GHG fluxes were measured from individual stem bases of two common tree species and from soils beneath the same trees. Soil CH₄ fluxes varied from uptake in the dry season to minor emissions in the wet season. Soil N₂ O fluxes were negligible during the dry season but increased markedly after the start of the wet season. By contrast, tree stem bases emitted CH₄ and N₂ O throughout the study. Although we observed no clear effect of litter manipulation on trace GHG fluxes, tree species and litter treatments interacted to influence CH₄ fluxes from stems and N₂ O fluxes from stems and soil, indicating complex relationships between tree species traits and decomposition processes that can influence trace GHG dynamics. Collectively, our results show that tropical trees can act as conduits for trace GHGs that most likely originate from deeper soil horizons, even when they are growing on upland soils. Coupled with the finding that the soils may be a weaker sink for CH₄ than previously thought, our research highlights the need to reappraise trace gas budgets in tropical forests.

Modeling nitrous oxide emissions from digestate and slurry applied to three agricultural soils in the United Kingdom: Fluxes and emission factors

Organic fertilizers, such as digestates and manure, are increasingly applied in agricultural systems because of the benefits they provide in terms of plant nutrients and soil quality. However, there are few investigations of N₂O emissions following digestate application to agricultural soils using process-based models. In this study, we modified the UK-DNDC model to include digestate applications to soils by adding digestate properties to the model and considering the effect of organic fertilizer pH. Using the modified model, N₂O emissions were simulated from two organic fertilizers (digested food waste and livestock slurry) applied to three farms in the United Kingdom: one growing winter wheat at Wensum (WE) and two grasslands at Pwllpeiran (PW) and North Wyke (NW). The annual cumulative gross (i.e. not excluding control emission) N₂O emissions were calculated using MATLAB trapezoidal numerical integration. The relative errors of the modeled annual cumulative emissions to the measured emissions ranged from -5.4% to 48%. Two-factor models, including linear, exponential and hyperbola responses, correlating total N loading and soil clay content to calculations of N₂O emissions and N₂O emission factors (EFs) were developed for calculations of emission fluxes and EFs. The squares of the correlation coefficients of the measured and two-factor linear modeled emissions were 0.998 and 0.999 for digestate and slurry, respectively, and the corresponding squares of correlation coefficients of the EFs were 0.998 and 0.938. The two-factor linear model also predicted that the EFs increased linearly with decreasing clay content and the maximum EFs for digestate and slurry were 0.95 and 0.76% of total N applied, respectively. This demonstrates that the modified UK_DNDC is a good tool to simulate N₂O emission from digestate and slurry and to calculate UK EFs using TIER 3 methodology..

Tundra landscape heterogeneity, not interannual variability, controls the decadal regional carbon balance in the Western Russian Arctic

Across the Arctic, the net ecosystem carbon (C) balance of tundra ecosystems is highly uncertain due to substantial temporal variability of C fluxes and to landscape heterogeneity. We modeled both carbon dioxide (CO₂ ) and methane (CH₄ ) fluxes for the dominant land cover types in a ~100-km² sub-Arctic tundra region in northeast European Russia for the period of 2006-2015 using process-based biogeochemical models. Modeled net annual CO₂ fluxes ranged from -300 g C m^-2  year^-1 [net uptake] in a willow fen to 3 g C m^-2  year^-1 [net source] in dry lichen tundra. Modeled annual CH₄ emissions ranged from -0.2 to 22.3 g C m^-2  year^-1 at a peat plateau site and a willow fen site, respectively. Interannual variability over the decade was relatively small (20%-25%) in comparison with variability among the land cover types (150%). Using high-resolution land cover classification, the region was a net sink of atmospheric CO₂ across most land cover types but a net source of CH₄ to the atmosphere due to high emissions from permafrost-free fens. Using a lower resolution for land cover classification resulted in a 20%-65% underestimation of regional CH₄ flux relative to high-resolution classification and smaller (10%) overestimation of regional CO₂ uptake due to the underestimation of wetland area by 60%. The relative fraction of uplands versus wetlands was key to determining the net regional C balance at this and other Arctic tundra sites because wetlands were hot spots for C cycling in Arctic tundra ecosystems.

Long-term Trends in Corn Yields and Soil Carbon under Diversified Crop Rotations

Agricultural practices such as including perennial alfalfa ( L.), winter wheat ( L.), or red clover ( L.) in corn ( L.) rotations can provide higher crop yields and increase soil organic C (SOC) over time. How well process-based biogeochemical models such as DeNitrification-DeComposition (DNDC) capture the beneficial effects of diversified cropping systems is unclear. To calibrate and validate DNDC for simulation of observed trends in corn yield and SOC, we used long-term trials: continuous corn (CC) and corn-oats ( L.)-alfalfa-alfalfa (COAA) for Woodslee, ON, 1959 to 2015; and CC, corn-corn-soybean [ (L.) Merr.]-soybean (CCSS), corn-corn-soybean-winter wheat (CCSW), corn-corn-soybean-winter wheat + red clover (CCSW+Rc), and corn-corn-alfalfa-alfalfa (CCAA) for Elora, ON, 1981 to 2015. Yield and SOC under 21st century conditions were projected under future climate scenarios from 2016 to 2100. The DNDC model was calibrated to improve crop N stress and was revised to estimate changes in water availability as a function of soil properties. This improved yield estimates for diversified rotations at Elora (mean absolute prediction error [MAPE] decreased from 13.4-15.5 to 10.9-14.6%) with lower errors for the three most diverse rotations. Significant improvements in yield estimates were also simulated at Woodslee for COAA, with MAPE decreasing from 24.0 to 16.6%. Predicted and observed SOC were in agreement for simpler rotations (CC or CCSS) at both sites (53.8 and 53.3 Mg C ha for Elora, 52.0 and 51.4 Mg C ha for Woodslee). Predicted SOC increased due to rotation diversification and was close to observed values (58.4 and 59 Mg C ha for Elora, 63 and 61.1 Mg C ha for Woodslee). Under future climate scenarios the diversified rotations mitigated crop water stress resulting in trends of higher yields and SOC content in comparison to simpler rotations.

A process-oriented hydro-biogeochemical model enabling simulation of gaseous carbon and nitrogen emissions and hydrologic nitrogen losses from a subtropical catchment

Quantification of nitrogen losses and net greenhouse gas (GHG) emissions from catchments is essential for evaluating the sustainability of ecosystems. However, the hydrologic processes without lateral flows hinder the application of biogeochemical models to this challenging task. To solve this issue, we developed a coupled hydrological and biogeochemical model, Catchment Nutrients Management Model - DeNitrification-DeComposition Model (CNMM-DNDC), to include both vertical and lateral mass flows. By incorporating the core biogeochemical processes (including decomposition, nitrification, denitrification and fermentation) of the DNDC into the spatially distributed hydrologic framework of the CNMM, the simulation of lateral water flows and their influences on nitrogen transportation can be realized. The CNMM-DNDC was then calibrated and validated in a small subtropical catchment belonged to Yanting station with comprehensive field observations. Except for the calibration of water flows (surface runoff and leaching water) in 2005, stream discharges of water and nitrate in 2007, the model validations of soil temperature, soil moisture, crop yield, water flows in 2006 and associated nitrate loss, fluxes of methane, ammonia, nitric oxide and nitrous oxide, and stream discharges of water and nitrate in 2008 were statistically in good agreement with the observations. Meanwhile, our initial simulation of the catchment showed scientific predictions. For instance, it revealed the following: (i) dominant ammonia volatilization among the losses of nitrogenous gases (accounting for 11-21% of the applied annual fertilizer nitrogen in croplands); (ii) hotspots of nitrate leaching near the main stream; and (iii) a net GHG sink function of the catchment. These results implicate the model's promising capability of predicting ecosystem productivity, hydrologic nitrogen loads, losses of gaseous nitrogen and emissions of GHGs, which could be used to provide strategies for establishing sustainable catchments. In addition, the model's capability would be further proved by applying in other catchments with different backgrounds.

Modelling CO2 emissions from water surface of a boreal hydroelectric reservoir

To quantify CO₂ emissions from water surface of a reservoir that was shaped by flooding the boreal landscape, we developed a daily time-step reservoir biogeochemistry model. We calibrated the model using the measured concentrations of dissolved organic and inorganic carbon (C) in a young boreal hydroelectric reservoir, Eastmain-1 (EM-1), in northern Quebec, Canada. We validated the model against observed CO₂ fluxes from an eddy covariance tower in the middle of EM-1. The model predicted the variability of CO₂ emissions reasonably well compared to the observations (root mean square error: 0.4-1.3gCm^-2day^-1, revised Willmott index: 0.16-0.55). In particular, we demonstrated that the annual reservoir surface effluxes were initially high, steeply declined in the first three years, and then steadily decreased to ~115gCm^-2yr^-1 with increasing reservoir age over the estimated "engineering" reservoir lifetime (i.e., 100years). Sensitivity analyses revealed that increasing air temperature stimulated CO₂ emissions by enhancing CO₂ production in the water column and sediment, and extending the duration of open water period over which emissions occur. Increasing the amount of terrestrial organic C flooded can enhance benthic CO₂ fluxes and CO₂ emissions from the reservoir water surface, but the effects were not significant over the simulation period. The model is useful for the understanding of the mechanism of C dynamics in reservoirs and could be used to assist the hydro-power industry and others interested in the role of boreal hydroelectric reservoirs as sources of greenhouse gas emissions.