Nitrogen management in agroecosystems: Applying models and data in policy development.
Tonitto, Christina*,1, David, Mark2, Drinkwater, Laurie1, Li, Changsheng 3, 1 Cornell University, Ithaca, NY, USA2 University of Illinois, Urbana, IL, USA3 University of New Hampshire, Durham, NH, USA
ABSTRACT- Human action has doubled the global flux of reactive nitrogen (N), with agricultural management accounting for 75% of this perturbation. Anthropogenic forcing of the N cycle has multiple ecosystem consequences which operate at a variety of scales. Reactive forms of N are moderated by local-scale, biological activity, but are transported at regional and global scales based on abiotic drivers. Methods for scaling the impact of local land management on regional and global N dynamics are limited by the difficulty of accurately quantifying N fluxes and transport from a management unit. Nonetheless, evidence of significant freshwater and estuarine nitrate pollution, as well as increasing N2O contribution to the greenhouse gas effect, mandates policy development. Intensively managed agricultural systems based on Haber-Bosch N fertilization loose 50% of applied N on average, suggesting the potential for alternative management to drastically reduce human impact on N cycling. We quantitatively assessed the potential for management of diversified rotations to increase agroecosystem N retention, while providing a viable livelihood for farmers. We assessed cash crop yields and N dynamics in diversified rotations with an annual cash crop using meta-analysis and the Denitrification-Decomposition (DNDC) model. Meta-analysis and model results showed diversified rotations which include dependence on biological N-fixation (BNF) result in viable yields and increased agroecosystem N retention. However, though DNDC results showed good agreement between modeled and observed nitrate leaching, water flux, and crop yield, modeled soil organic matter (SOM) dynamics in conventional and diversified systems did not agree with field observations. Sparse field data are available to quantify NO3- and N2O losses from agricultural land, resulting in increased dependence on model dynamics. Successful N management policy will require nuanced approaches to linking observational and modeling studies.
Key words: nitrogen, scaling, agroecosystems, policy
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