Extreme weather‐year sequences have nonadditive effects on environmental nitrogen losses

The frequency and intensity of extreme weather years, characterized by abnormal precipitation and temperature, are increasing. In isolation, these years have disproportionately large effects on environmental N losses. However, multi-year sequences of extreme weather years (e.g., wet-dry vs. dry-wet) and annual crop rotation (legume-cereal vs. cereal-legume) may interact to affect cumulative N losses across the complete crop rotation sequence. We calibrated and validated the DAYCENT model with a comprehensive set of biogeophysical measurements from a maizesoybean rotation managed at three different N fertilizer inputs with and without a winter cereal rye cover crop in Iowa, USA. Our objectives were to determine: i) how two-year sequences of extreme weather years interact with annual crop rotation sequence to affect two-year cumulative N losses, and ii) if the inclusion of a winter cover crop between corn and soybean and N fertilizer management mitigate the effect of extreme weather on N losses. Using historical weather data (1951-2013), we created nine two-year weather scenarios with all possible combinations of the hottest and driest (‘dry’), coolest and wettest (‘wet’), and average (‘normal’) weather years. We analyzed the effects of these scenarios following a period of relatively normal weather. Compared to the normal-normal two-year weather scenario, two-year extreme weather scenarios affected two-year cumulative NO3- leaching (range: -28 to +295%) more than N2O emissions (range: -54 to +21%). Moreover, the two-year weather scenarios had non-additive effects on N losses: although dry weather decreased NO3- leaching in isolation, two-year cumulative NO3- losses from the dry-wet scenario were 89% greater than the normal-normal scenario. Cover crops reduced the effect of extreme weather on NO3- leaching, but not N2O emissions. As the frequency of extreme weather events is expected to increase, understanding of interactions between crop rotation and interannual weather patterns can be used to mitigate the effect of extreme weather on environmental N losses

CHARACTERIZING NITROGEN LOSS AND GREENHOUSE GAS FLUX ACROSS AN INTENSIFICATION GRADIENT IN DIVERSIFIED VEGETABLE SYSTEMS

The area of vegetable production is growing rapidly world-wide, as are efforts to increase production on existing lands in these labor- and input-intensive systems. Yet information on nutrient losses, greenhouse gas emissions, and input efficiency is lacking. Sustainable intensification of these systems requires knowing how to optimize nutrient and water inputs to improve yields while minimizing negative environmental consequences. This work characterizes soil nitrogen (N) dynamics, nitrate (NO3¯) leaching, greenhouse gas emissions, and crop yield in five diversified vegetable systems spanning a gradient of intensification that is characterized by inputs, tillage and rotational fallow periods. The study systems included a low input organic system (LI), a mechanized, medium scale organic system (CSA), an organic movable high tunnel system (MOV), a conventional system (CONV) and an organic stationary high tunnel system (HT). In a three-year vegetable crop rotation with three systems (LI, HT and CONV), key N loss pathways varied by system; marked N2O and CO2 losses were observed in the LI system and NO3– leaching was greatest in the CONV system. Yield-scaled global warming potential (GWP) was greater in the LI system compared to HT and CONV, driven by greater greenhouse gas flux and lower yields in the LI system. The field data from CONV system were used to calibrate the Root Zone Water Quality Model version 2 (RZWQM2) and HT and LI vegetable systems were used to validate the model. RZWQM2 simulated soil NO3¯-N content reasonably well in crops grown on bare ground and open field (e.g. beet, collard, bean). Despite use of simultaneous heat and water (SHAW) option in RZWQM2 to incorporate the use of plastic mulch, we were not able to successfully simulate NO3¯-N data. The model simulated cumulative N2O emissions from the CONV vegetable system reasonably well, while the model overestimated N2O emissions in HT and LI systems