Towards applying N balance as a sustainability indicator for the US Corn Belt: realistic achievable targets, spatio-temporal variability and policy implications

Abstract

Abstract Gains in nitrogen use efficiency in the production of corn (Zea mays L.) remain low due to management constraints and difficulties in accurately predicting the optimum fertilizer application rate. Retailers and consumers are looking for robust sustainability indicators to help drive the industry towards more sustainable food production, including the simple input-output based ‘N balance’ metric. Seven-year simulations for 25 locations across five US Corn Belt States (NE, IA, MN, IL, IN) were conducted using the biogeochemical Adapt-N® model to determine (i) realistically achievable N balance values when N rates are optimized, (ii) the effects of climate and soil type on achievable N balance values, and (iii) the relative importance of N application timing (fall, spring, split in-season) and formulation (+/− nitrapyrin) in reducing N balance. Split in-season applications reduced N rates by 39% and 22% over fall and spring applications and N balance by 36% and 22%, respectively. Adding nitrapyrin to fall or spring preplant applications modestly reduced N inputs by 9% and 4% and N balance by 18% and 12%. Split N management reduced N losses by 52% and 31% of total area-scaled N losses compared to fall and spring N applications and adding nitrapyrin by 13% and 10%, respectively. Benefits from improved timing and formulation were greater in the more humid eastern part of the region. Split in-season N management allows farmers to reach sustainable N balance levels in 88% of cases, with the remainder mostly affected by mid-season droughts. Economic assessment found partial profit to be enhanced with lower N balance, suggesting that N balance reductions may be achieved through voluntary approaches. The model simulations offered ranges of realistic N balance values that can be used to inform policy discussions. It appears that N balance is best applied when averaged over multiple seasons and threshold levels should be guided by characteristics of the production environment, including soil type and climate.