Effectiveness of 4R Mitigation Practices to Reduce N2O Emissions of Corn Production Systems: A Modelling Approach

English Abstract:

Agricultural soils are the dominant source of nitrous oxide (N₂O), a potent greenhouse gas and a major cause of ozone layer depletion. Process-based models are increasingly being used to explore the impacts of management and climate in N₂O emissions from agriculture. Models used to establish emissions under current management practices can also be used to compare alternative management scenarios intended to reduce emissions.

SPACSYS is a multi-dimensional, field scale, weather-driven dynamic simulation model of C and N cycling, which operates with a daily time-step and outputs N₂O emissions (Wu, 2007). The objective of this study is to analyse the effect of different fertilizer management practices on corn as means to control N₂O emissions without incurring in yield penalties, using SPACSYS. The evaluated management practices are part of the 4R Nutrient Stewardship Program, which proposes a framework to increase agricultural production and improve environmental sustainability by maximizing fertilizer-use efficiency.

N₂O measurements were carried out at two field sites in southern Ontario with climate and soil conditions representative of the agricultural region where the sites are located (e.g. Wagner-Riddle et al., 2007). Field data covers different years from 2000 to 2010, contrasting fertilizer types (both mineral and organic) and application depths, providing suitable datasets for testing the sensitivity of SPACSYS to changes in environmental and management factors at a regional scale. Preliminary results of the statistical analysis used to test the model for cumulative N₂O fluxes showed no statistically significant total error (RMSE₉₅) or bias (E₉₅) when compared to measured estimates. A strong association was found between measured and simulated values (R = 0.95).

Our results will promote effective policies to achieve more sustainable corn agro-ecosystems by showing which management practices have the greatest potential to reduce N losses and how they can be prioritized.