Simulating impacts of nitrogen fertilization using DAYCENT to optimize economic returns and environmental services from bioenergy sorghum production

Authors: WANG, YONG - TEXAS A&M UNIVERSITY; DOU, FUGEN - TEXAS A&M UNIVERSITY; PAUSTIAN, KEITH - COLORADO STATE UNIVERSITY; Del Grosso, Stephen - Steve; STORLIEN, JOSEPH - COLLEGE OF ST. BENEDICT & ST. JOHN'S UNIVERSITY; WIGHT, JASON - UNIVERSITY OF MARYLAND; HONS, FRANK - TEXAS A&M UNIVERSITY

Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/27/2020
Publication Date: 7/29/2020
Citation: Wang, Y., Dou, F., Paustian, K., Del Grosso, S.J., Storlien, J., Wight, J., Hons, F. 2020. Simulating impacts of nitrogen fertilization using DAYCENT to optimize economic returns and environmental services from bioenergy sorghum production. Agronomy Journal. 112:4861-4878. https://doi.org/10.1002/agj2.20390.
DOI: https://doi.org/10.1002/agj2.20390

Interpretive Summary: The ecosystem model, DAYCENT, was tested against measurements from an eight-year field trial in Texas and then used to predict the long-term effects of nitrogen (N) fertilization in bioenergy sorghum production to identify the optimum N rate. The model was capable of reproducing the field measurements for biomass yield,soil organic carbon (SOC), and nitrous oxide (N2O) emissions. These are important because biomass yield determines the amount of fossil fuel that can be replaced, SOC is a soil health indicator,and N2O is a greenhouse gas (GHG) that also contributes to depletion of ozone in the upper atmosphere. We ran model scenarios until the middle of this century with 0-350 kg N per hectare fertilization in increments of 70 kg N per hectare. Results indicated positive responses of biomass yield and SOC to increasing N but with little increase above 140 kg N per hectare. For all fertilized treatments, declining N use efficiency (NUE) and increasing net GHG emission at the field scale were predicted as N fertilization rate increased. When considering GHG mitigation from fossil fuel replacement, net GHG emission decreased first and leveled off at a N rate of 70-140 kg N per hectare before increasing. Net economic return to N (RTN) increased first and peaked when N application rate was around 140 kg N per hectare before decreasing. Model results indicated N fertilization at 140 kg N per hectare to be optimal for bioenergy sorghum production at our experimental site. Our study revealed that better representative ecosystem modeling and complete GHG analysis may provide more effective N application strategy for this emerging biofuel crop in terms of sustainability.

Technical Abstract: The biogeochemical model, DAYCENT, was verified with an eight-year field trial and then used to project the long-term effects of nitrogen (N) fertilization in bioenergy sorghum [Sorghum bicolor (L.) Moench] production, in order to find an optimum N rate through multi-aspect post analysis. The model was capable of reproducing the field measurements with r2 of 0.57, 0.47, 0.55, and 0.34 for aboveground biomass carbon (C), soil organic C (SOC), carbon dioxide (CO2), and nitrous oxide (N2O), respectively. Projection to the middle of this century with 0-350 kg N ha-1 fertilization in increments of 70 kg N ha-1 indicated positive responses of simulated aboveground biomass C and SOC to increasing N but with little increase above 140 kg N ha-1. For all fertilized treatments, declining N use efficiency (NUE) and increasing net greenhouse gas (GHG) emission at field scale were predicted as N fertilization rate increased. When considering GHG mitigation from fossil fuel replacement, net GHG emission decreased first and leveled off at a N rate of 70-140 kg N ha-1 before increasing. Net economic return to N (RTN) increased first and peaked when N application rate was around 140 kg N ha-1 before decreasing. Model projection results indicated N fertilization at 140 kg N ha-1 to be optimal for bioenergy sorghum production at our experimental site. Our study revealed that multi-aspect analysis with better representative biogeochemical modeling and up- and downstream net GHG analysis may provide more effective N application strategy for this emerging biofuel crop in terms of sustainability.