Denitrification and the challenge of scaling microsite knowledge to the globe

Machine learning reveals dynamic controls of soil nitrous oxide emissions from diverse long-term cropping systems

Soil nitrous oxide (N2O) emissions exhibit high variability in intensively managed cropping systems, which challenges our ability to understand their complex interactions with controlling factors. We leveraged 17 years (2003-2019) of measurements at the Kellogg Biological Station Long-Term Ecological Research (LTER)/Long-Term Agroecosystem Research (LTAR) site to better understand the controls of N2O emissions in four corn-soybean-winter wheat rotations employing conventional, no-till, reduced input, and biologically based/organic inputs. We used a random forest machine learning model to predict daily N2O fluxes, trained separately for each system with 70% of observations, using variables such as crop species, daily air temperature, cumulative 2-day precipitation, water-filled pore space, and soil nitrate and ammonium concentrations. The model explained 29%-42% of daily N2O flux variability in the test data, with greater predictability for the corn phase in each system. The long-term rotations showed different controlling factors and threshold conditions influencing N2O emissions. In the conventional system, the model identified ammonium (>15 kg N ha-1) and daily air temperature (>23°C) as the most influential variables; in the no-till system, climate variables such as precipitation and air temperature were important variables. In low-input and organic systems, where red clover (Trifolium repens L.; before corn) and cereal rye (Secale cereale L.; before soybean) cover crops were integrated, nitrate was the predominant predictor of N2O emissions, followed by precipitation and air temperature. In low-input and biologically based systems, red clover residues increased soil nitrogen availability to influence N2O emissions. Long-term data facilitated machine learning for predicting N2O emissions in response to differential controls and threshold responses to management, environmental, and biogeochemical drivers.

The distribution of particulate organic matter in the heterogeneous soil matrix - Balancing between aerobic respiration and denitrification

Denitrification, a key process in soil nitrogen cycling, occurs predominantly within microbial hotspots, such as those around particulate organic matter (POM), where denitrifiers use nitrate as an alternative electron acceptor. For accurate prediction of dinitrogen (N2) and nitrous oxide (N2O) emissions from denitrification, a precise quantification of these microscale hotspots is required. The distribution of POM is of crucial importance in this context, as the local oxygen (O2) balance is governed not only by its high O2 demand but also by the local O2 availability. Employing a unique combination of X-ray CT imaging, microscale O2 measurements, and 15N labeling, we were able to quantify hotspots of aerobic respiration and denitrification. We analyzed greenhouse gas (GHG) fluxes, soil oxygen supply, and the distribution of POM in intact soil samples from grassland and cropland under different moisture conditions. Our findings reveal that both proximal and distal POM, identified through X-ray CT imaging, contribute to GHG emissions. The distal POM, i.e. POM at distant locations to air-filled pores, emerged as a primary driver of denitrification within structured soils of both land uses. Thus, the higher denitrification rates in the grassland could be attributed to the higher content of distal POM. Conversely, despite possessing compacted areas that could favor denitrification, the cropland had only small amounts of distal POM to stimulate denitrification in it. This underlines the complex interaction between soil structural heterogeneity, organic carbon supply, and microbial hotspot formation and thus contributes to a better understanding of soil-related GHG emissions. In summary, our study provides a holistic understanding of soil-borne greenhouse gas emissions and emphasizes the need to refine predictive models for soil denitrification and N2O emissions by incorporating the microscale distribution of POM.

Ecological Trait-Based Digital Categorization of Microbial Genomes for Denitrification Potential

Microorganisms encode proteins that function in the transformations of useful and harmful nitrogenous compounds in the global nitrogen cycle. The major transformations in the nitrogen cycle are nitrogen fixation, nitrification, denitrification, anaerobic ammonium oxidation, and ammonification. The focus of this report is the complex biogeochemical process of denitrification, which, in the complete form, consists of a series of four enzyme-catalyzed reduction reactions that transforms nitrate to nitrogen gas. Denitrification is a microbial strain-level ecological trait (characteristic), and denitrification potential (functional performance) can be inferred from trait rules that rely on the presence or absence of genes for denitrifying enzymes in microbial genomes. Despite the global significance of denitrification and associated large-scale genomic and scholarly data sources, there is lack of datasets and interactive computational tools for investigating microbial genomes according to denitrification trait rules. Therefore, our goal is to categorize archaeal and bacterial genomes by denitrification potential based on denitrification traits defined by rules of enzyme involvement in the denitrification reduction steps. We report the integration of datasets on genome, taxonomic lineage, ecosystem, and denitrifying enzymes to provide data investigations context for the denitrification potential of microbial strains. We constructed an ecosystem and taxonomic annotated denitrification potential dataset of 62,624 microbial genomes (866 archaea and 61,758 bacteria) that encode at least one of the twelve denitrifying enzymes in the four-step canonical denitrification pathway. Our four-digit binary-coding scheme categorized the microbial genomes to one of sixteen denitrification traits including complete denitrification traits assigned to 3280 genomes from 260 bacteria genera. The bacterial strains with complete denitrification potential pattern included Arcobacteraceae strains isolated or detected in diverse ecosystems including aquatic, human, plant, and Mollusca (shellfish). The dataset on microbial denitrification potential and associated interactive data investigations tools can serve as research resources for understanding the biochemical, molecular, and physiological aspects of microbial denitrification, among others. The microbial denitrification data resources produced in our research can also be useful for identifying microbial strains for synthetic denitrifying communities.

Cover crop residue decomposition triggered soil oxygen depletion and promoted nitrous oxide emissions

Cover cropping is a promising strategy to improve soil health, but it may also trigger greenhouse gas emissions, especially nitrous oxide (N2O). Beyond nitrogen (N) availability, cover crop residue decomposition may accelerate heterotrophic respiration to limit soil O2 availability, hence promote N2O emissions from denitrification under sub-optimal water-filled pore space (WFPS) conditions that are typically not conducive to large N2O production. We conducted a 21-day incubation experiment to examine the effects of contrasting cover crop residue (grass vs legume) decomposition on soil O2 and biogeochemical changes to influence N2O and CO2 emissions from 15N labeled fertilized soils under 50% and 80% WFPS levels. Irrespective of cover crop type, mixing cover crop residue with N fertilizer resulted in high cumulative N2O emissions under both WFPS conditions. In the absence of cover crop residues, the N fertilizer effect of N2O was only realized under 80% WFPS, whereas it was comparable to the control under 50% WFPS. The N2O peaks under 50% WFPS coincided with soil O2 depletion and concomitant high CO2 emissions when cover crop residues were mixed with N fertilizer. While N fertilizer largely contributed to the total N2O emissions from the cover crop treatments, soil organic matter and/or cover crop residue derived N2O had a greater contribution under 50% than 80% WFPS. Our results underscore the importance of N2O emissions from cover crop-based fertilized systems under relatively lower WFPS via a mechanism of respiration-induced anoxia and highlight potential risks of underestimating N2O emissions under sole reliance on WFPS.

Genome-Resolved Metagenomics and Denitrifying Strain Isolation Reveal New Insights into Microbial Denitrification in the Deep Vadose Zone

The heavy use of nitrogen fertilizer in intensive agricultural areas often leads to nitrate accumulation in subsurface soil and nitrate contamination in groundwater, which poses a serious risk to public health. Denitrifying microorganisms in the subsoil convert nitrate to gaseous forms of nitrogen, thereby mitigating the leaching of nitrate into groundwater. Here, we investigated denitrifying microorganisms in the deep vadose zone of a typical intensive agricultural area in China through microcosm enrichment, genome-resolved metagenomic analysis, and denitrifying bacteria isolation. A total of 1000 metagenome-assembled genomes (MAGs) were reconstructed, resulting in 98 high-quality, dereplicated MAGs that contained denitrification genes. Among them, 32 MAGs could not be taxonomically classified at the genus or species level, indicating that a broader spectrum of taxonomic groups is involved in subsoil denitrification than previously recognized. A denitrifier isolate library was constructed by using a strategy combining high-throughput and conventional cultivation techniques. Assessment of the denitrification characteristics of both the MAGs and isolates demonstrated the dominance of truncated denitrification. Functional screening revealed the highest denitrification activity in two complete denitrifiers belonging to the genus Pseudomonas. These findings greatly expand the current knowledge of the composition and function of denitrifying microorganisms in subsoils. The constructed isolate library provided the first pool of subsoil-denitrifying microorganisms that could facilitate the development of microbe-based technologies for nitrate attenuation in groundwater.