Nitrogen surplus: An environmental performance indicator for sustainable food supply chains

Authors: MCLELLAN, EILEEN - ENVIRONMENTAL DEFENSE; CASSMAN, KENNETH - UNIVERSITY OF NEBRASKA; SELA, SHAI - CORNELL UNIVERSITY; VAN ES, HAROLD - CORNELL UNIVERSITY; Venterea, Rodney - Rod; WOODBURY, PETER - CORNELL UNIVERSITY; TONITTO, CHRISTINA - CORNELL UNIVERSITY

Submitted to: International Nitrogen Conference
Publication Type: Proceedings
Publication Acceptance Date: 8/9/2016
Publication Date: 12/4/2016
Citation: Mclellan, E., Cassman, K., Sela, S., Van Es, H., Venterea, R.T., Woodbury, P., Tonitto, C. 2016. Nitrogen surplus: An environmental performance indicator for sustainable food supply chains. Proceedings of the 7th International Nitrogen Initiative Conference (INI2016). Melbourne, Australia. December 4-8, 2016.

Interpretive Summary: Nitrogen pollution and negative impacts on human and environmental health are embodied in crop commodities traded domestically and internationally. Food supply chain companies can play a catalytic role in reducing that burden by helping to decrease the environmental nitrogen load from agriculture. The challenge is how best to achieve this goals. We see opportunities for upstream food processors and retailers to reduce N losses associated with grain and grain-derived products they purchase. We describe how such commitments might work and how progress towards them can be tracked using a simple, robust and scalable indicator: N surplus. Using model simulations and empirical data on U.S. maize production we show that N surplus, the difference between annual N inputs and outputs, is strongly related to N losses at field to regional scales. This analysis suggests that supply chain companies can set performance goals related to reductions in N surplus, which in turn could translate into large improvements in environmental outcomes. Recognizing that individual producers will need guidance and motivation on how to reduce N surplus, we present a conceptual model for using farmer-derived data in a social learning context to identify combinations of management practices that most effectively reduce N losses and improve crop yield or profit. Finally, we suggest an additional pathway for companies seeking to reduce their overall N surplus at the scale of sustainable sourcing regions: the creation of nitrogen offsets through the restoration of riparian buffers, wetlands, and other loci of denitrification at landscape scale.

Technical Abstract: Nitrogen pollution and negative impacts on human and environmental health are embodied in crop commodities traded domestically and internationally. Food supply chain companies can play a catalytic role in reducing that burden by helping to decrease the environmental nitrogen load from agriculture. The challenge is how best to achieve this goals. We see opportunities for upstream food processors and retailers to reduce N losses associated with grain and grain-derived products they purchase. We describe how such commitments might work and how progress towards them can be tracked using a simple, robust and scalable indicator: N surplus. Using model simulations and empirical data on U.S. maize production we show that N surplus, the difference between annual N inputs and outputs, is strongly related to N losses at field to regional scales. This analysis suggests that supply chain companies can set performance goals related to reductions in N surplus, which in turn could translate into large improvements in environmental outcomes. Recognizing that individual producers will need guidance and motivation on how to reduce N surplus, we present a conceptual model for using farmer-derived data in a social learning context to identify combinations of management practices that most effectively reduce N losses and improve crop yield or profit. Finally, we suggest an additional pathway for companies seeking to reduce their overall N surplus at the scale of sustainable sourcing regions: the creation of nitrogen offsets through the restoration of riparian buffers, wetlands, and other loci of denitrification at landscape scale.