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Nitrification, a key step in soil nitrogen cycling, is a biologically mediated process crucial to the ecological environment. However, how nitrifiers drive nitrification under different soil properties and climatic factors at large spatial scales is poorly understood. Here, using metagenomic sequencing and network‐based approaches, we identified key nitrifying species of upland agricultural soils in northern China, which spans a wide range of climates and geographic distances. We found that potential nitrification rates (PNRs) varied in different soils and were positively correlated with soil pH (5.42–8.46) and mean annual temperature (MAT) and negatively correlated with the C/N ratio. Network analysis revealed that one module (module 3) was significantly correlated with PNR. In this module, 16 dominant nodes were associated with AOB Nitrosomonas and most nodes were significantly correlated with environmental factors, suggesting that abiotic conditions are important for determining the assembly of these key nitrifiers. Our study advanced the understanding of the key nitrifying populations and their environmental drivers in upland agricultural soil across different soil and climate types. [ABSTRACT FROM AUTHOR]

Arable soil continues to be the dominant anthropogenic source of nitrous oxide (N2O) emissions owing to application of nitrogen (N) fertilizers and manures across the world. Using laboratory and in situ studies to elucidate the key factors controlling soil N2O emissions remains challenging due to the potential importance of multiple complex processes. We examined soil surface N2O fluxes in an arable soil, combined with in situ high‐frequency measurements of soil matrix oxygen (O2) and N2O concentrations, in situ 15N labeling, and N2O 15N site preference (SP). The in situ O2 concentration and further microcosm visualized spatiotemporal distribution of O2 both suggested that O2 dynamics were the proximal determining factor to matrix N2O concentration and fluxes due to quick O2 depletion after N fertilization. Further SP analysis and in situ 15N labeling experiment revealed that the main source for N2O emissions was bacterial denitrification during the hot‐wet summer with lower soil O2 concentration, while nitrification or fungal denitrification contributed about 50.0% to total emissions during the cold‐dry winter with higher soil O2 concentration. The robust positive correlation between O2 concentration and SP values underpinned that the O2 dynamics were the key factor to differentiate the composite processes of N2O production in in situ structured soil. Our findings deciphered the complexity of N2O production processes in real field conditions, and suggest that O2 dynamics rather than stimulation of functional gene abundances play a key role in controlling soil N2O production processes in undisturbed structure soils. Our results help to develop targeted N2O mitigation measures and to improve process models for constraining global N2O budget. [ABSTRACT FROM AUTHOR]

Soil nitrous oxide (N2O) is an important greenhouse gas contributing to climate change. Many processes produce N2O in soil and the production rate of each process is affected by climatic-edaphic factors, making the soil-to-atmosphere N2O flux extremely dynamic. Experimental approaches, including natural and enriched isotopic methods, have been developed to separate and quantify the N2O production from different processes. However, these methods are often costly and tedious, hampering their wide application. This study aimed to develop a mechanistic model quantifying the soil N2O production from nitrifier nitrification (NN), nitrifier denitrification (ND), and heterotrophic denitrification (HD), which are considered as the most important biological processes, and to investigate how climatic-edaphic factors affect N2O production from individual process as well as total N2O production. The developed model demonstrated its robustness and capability by reliably reproducing the N2O production from NN, ND, and HD in different types of soils under various moisture contents or oxygen concentrations. The model simulations unraveled how environmental conditions and soil properties control the total N2O production rate by variably regulating individual processes. Therefore, the mechanistic model can potentially elucidate the large spatiotemporal variances of in-situ soil N2O flux and improve the assessment of soil N2O emission at regional and global scales. [ABSTRACT FROM AUTHOR]

Optimizing crop rotations is one of the proposed sustainable management strategies for increasing carbon sequestration. The main aim of this study was to evaluate the DeNitrification-DeComposition (DNDC) model for estimating soil parameters (temperature, moisture and exchangeable NO3− and NH4+), crop yield and nitrous oxide (N2O) emissions for long-term multi-cropping systems in Hebei, China. The model was validated using five years of data of soil parameters, crop yields and N2O emissions. The DNDC model effectively simulated daily soil temperature, cumulative soil nitrogen and crop yields of all crops. It predicted the trends of observed daily N2O emissions and their cumulative values well but overestimated the magnitude of some peaks. However, the model underestimated daily water filled pore space, especially in dry seasons, and had difficulties in correctly estimating daily exchangeable NO3− and NH4+. Both observed and simulated cumulative N2O results showed that optimized and alternative cropping systems used less nitrogen fertiliser, increased grain yield and decreased N2O emissions compared to the conventional cropping system. Our study shows that although the DNDC model (v. 9.5) is not perfect in estimating daily N2O emissions for these long-term multi-cropping systems, it could still be an effective tool for predicting cumulative emissions. [ABSTRACT FROM AUTHOR]

Hot moments of nitrous oxide (N 2 O) emissions induced by interactions between weather and management make a major contribution to annual N 2 O budgets in agricultural soils. The causes of N 2 O production during hot moments are not well understood under field conditions, but emerging evidence suggests that short-term fluctuations in soil oxygen (O 2) concentration can be critically important. We conducted high time-resolution field observations of O 2 and N 2 O concentrations during hot moments in a dryland agricultural soil in Northern China. Three typical management and weather events, including irrigation (Irr.), fertilization coupled with irrigation (Fer.+Irr.) or with extreme precipitation (Fer.+Pre.), were observed. Soil O 2 and N 2 O concentrations were measured hourly for 24 h immediately following events and measured daily for at least one week before and after the events. Soil moisture, temperature, and mineral N were simultaneously measured. Soil O 2 concentrations decreased rapidly within 4 h following irrigation in both the Irr. and Fer.+Irr. events. In the Fer.+Pre. event, soil O 2 depletion did not occur immediately following fertilization but began following subsequent continuous rainfall. The soil O 2 concentration dropped to as low as 0.2% (with the highest soil N 2 O concentration of up to 180 ppmv) following the Fer.+Pre. event, but only fell to 11.7% and 13.6% after the Fer.+Irr. and Irr. events, which were associated with soil N 2 O concentrations of 27 ppmv and 3 ppmv, respectively. During the hot moments of all three events, soil N 2 O concentrations were negatively correlated with soil O 2 concentrations (r = −0.5, P < 0.01), showing a quadratic increase as soil O 2 concentrations declined. Our results provide new understanding of the rapid short response of N 2 O production to O 2 dynamics driven by changes in soil environmental factors during hot moments. Such understanding helps improve soil management to avoid transitory O 2 depletion and reduce the risk of N 2 O production. • N2O production instantly responded to rapid short O2 dynamics in in situ soils. • Soil N2O concentrations increased quadratically as soil O2 decreased at hot moments. • Anaerobic microsites existed widely in dryland soils after extreme rainfall. • O2 recovered within 24 h after short-term irrigation in in situ structured soils. • Hot moments of N2O production were promoted by intense rainfall not by irrigation. [ABSTRACT FROM AUTHOR]

Agricultural soils are a major source of anthropogenic N 2 O, but their N 2 O emission estimates are highly uncertain, mainly due to the complexity of nitrogen (N) processes. Most soil N models include only primary N processes such as nitrification and denitrification, which limits their ability to realistically simulate N transformations in soils and accurately estimate N 2 O emissions from soils. This study introduces a Microbial-Explicit Model incorporating Comprehensive Nitrogen processes (MEMCN) to evaluate and quantify the influences of various N processes on the production of N 2 O as well as NO and N 2 , including nitrification, denitrification, anaerobic ammonium oxidation (ANAMMOX), dissimilatory nitrate reduction to ammonium (DNRA), mineralization, and microbial assimilation (i.e., growth) and death. The MEMCN was evaluated in laboratory experiments using agricultural soils with different levels of N additions under anaerobic and aerobic conditions, and reproduced well the dynamics of NH 4 +, NO 3 −, NO 2 −, NO, N 2 O, and N 2. After nitrification and denitrification, ANAMMOX and assimilation were found to be most important in controlling N transformations in agricultural soils. ANAMMOX directly increased N 2 emissions by 139% at the beginning of the simulations (i.e., 48 h) under anaerobic conditions, while microbial assimilation indirectly reduced NO, N 2 O, and N 2 emissions by 88%, 54%, and 58%, respectively, at the end of the simulations (i.e., 336 h) under aerobic conditions. Correspondingly, the biomass of ANAMMOX bacteria increased significantly at the beginning of the simulations under anaerobic conditions, while the biomass of nitrite oxidizing bacteria increased substantially under aerobic conditions. In contrast, DNRA, mineralization and microbial death had minor effect on soil N transformations, and the biomass of DNRA bacteria and heterotrophs did not change significantly during the simulations. Our study shows that it is necessary to include ANAMMOX and microbial assimilation in soil N models, while explicit simulation of microbial biomass dynamics may only be necessary if microbial biomass pools change significantly. • Develope a Microbial-Explicit Model incorporating Comprehensive N processes. • Quantify contributions of individual N processes to gaseous N production. • ANAMMOX increased N 2 produciton under aerobic and anaerobic condtions. • Assimilation reduced NO, N 2 O, and N 2 emissions under aerobic condtions. • Micoribal biomass should be explicitly expressed as they change substantially. [ABSTRACT FROM AUTHOR]