Meeting Agronomic and Environmental Goals: Nitrogen Surplus As a Performance Indicator for Sustainable Food Supply.

How can we increase agricultural productivity to feed a projected global population of 9+ billion without further compromising the water quality, biodiversity and climate stability on which that population also depends?  Global food supply chains provide opportunities to improve sustainability not available through national or regional policy and regulation. A variety of multi-stakeholder initiatives focus on improving the sustainability of food supply chains from retailers all the way back to agricultural producers.  A key challenge for these initiatives is identifying performance metrics that meet the following criteria: outcome-oriented; scientifically-robust; implementable and scalable from individual fields to large sourcing regions; meaningful to a range of stakeholders (especially farmers); and consistent with economic, social and environmental pillars of sustainability. Given the importance of nitrogen (N) fertilizer to crop production and soil fertility, and the risks for human and ecosystem health created by N losses to the environment, we suggest that having at least one practical N performance metric is a critical component of food supply chain sustainability initiatives. We further propose that yield-scaled N surplus (N inputs to the crop, minus N removed in the harvested crop) meets the criteria listed above.  The N surplus approach is based on the notion that production and environmental goals are generally compatible within a certain mass balance range, i.e., where yields are not compromised and losses are ecologically tolerable.  We will demonstrate that the N surplus metric is a good proxy indicator for environmental N losses. We will review its potential implementation by producers through an adaptive management approach based on the 4R’s of fertilizer management, which can help drive continuous improvement in crop production systems. In addition, we will show how N surplus can be quantified and tracked at a variety of spatial and temporal scales using a limited suite of routine farm management data.