Reactive nitrogen (N) is essential for agricultural productivity, yet its inefficient use contributes to emissions, N losses, and environmental impacts. Improving our understanding of reactive N turnover and fate is crucial for reducing uncertainties in N budgets and supporting sustainable nutrient management.
While the factors controlling N turnover are relatively well established under laboratory conditions, quantifying N transformations under field and landscape conditions remains a major challenge. High spatial and temporal variability, methodological limitations, and complex interactions among biological, chemical, and physical processes create substantial uncertainties in N turnover pathways and environmental controls.
Limited availability of in situ datasets hampers evaluation of mineralization, nitrification, and denitrification in process-based models, reducing confidence in predictions across scales. Addressing these challenges requires integrating experiments, field measurements, monitoring, and modelling across scales. Improved process understanding and quantification of N transformations are essential for predicting reactive N losses, assessing greenhouse gas emissions, and evaluating mitigation options.
This session welcomes contributions advancing understanding of reactive N turnover and fate in agricultural systems, focusing on linking measurements, monitoring, and modelling approaches across temporal and spatial scales.
Topics of interest include:
• Experimental studies investigating nitrogen transformation processes, turnover rates, and reactive N loss pathways under laboratory, field, or landscape conditions;
• Advances in field measurements and monitoring approaches for quantifying reactive N pools, fluxes, and turnover;
• Novel approaches to constrain N turnover, including 15N tracer techniques, isotopic methods, controlled incubation experiments, and other innovative methodologies;
• Process-based, data-driven, and hybrid modelling approaches for simulating N cycling and reactive N fate across scales;
• Studies evaluating management and mitigation strategies aimed at reducing reactive N losses and greenhouse gas emissions;
• Integration of measurements, monitoring, and modelling for improving N budgets, model evaluation, and uncertainty reduction;
• Linking N transformation processes with soil microbial communities, environmental drivers, and agricultural management practices.