Predicting greenhouse gas benefits of improved nitrogen management in North American maize

Abstract

Farmers, food supply companies, and policymakers need practical yet scientifically robust methods to quantify how improved nitrogen (N) fertilizer management can reduce nitrous oxide (N2O) emissions. To meet this need, we developed an empirical model based on published field data for predicting N2O emission from rainfed maize (Zea mays L.) fields managed with inorganic N fertilizer in the United States and Canada. Nitrous oxide emissions ranged widely on an area basis (0.03–32.9 kg N ha−1 yr−1) and a yield-scaled basis (0.006–4.8 kg N Mg−1 grain yr−1). We evaluated multiple modeling approaches and variables using three metrics of model fit (Akaike information criteria corrected for small sample sizes [AICc], RMSE, and R2). Our model explains 32.8% of the total observed variation and 50% of observed site-level variation. Soil clay content was very important for predicting N2O emission and predicting the change in N2O emission due to a change in N balance, with the addition of a clay fixed effect explaining 37% of site-level variation. Sites with higher clay content showed greater reductions in N2O emission for a given reduction in N balance. Therefore, high-clay sites are particularly important targets for reducing N2O emissions. Our linear mixed model is more suitable for predicting the effect of improved N management on N2O emission in maize fields than other published models because it (a) requires only input data readily available on working farms, (b) is derived from field observations, (c) correctly represents differences among sites using a mixed modeling approach, and (d) includes soil texture because it strongly influences N2O emissions.