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The interactive effects of soil texture and type of N fertility (i.e., manure vs. commercial N fertilizer) on N2O and CH4 emissions have not been well established. This study was conducted to assess the impact of soil type and N fertility on greenhouse gas fluxes (N2O, CH4, and CO2) from the soil surface. The soils used were a sandy loam (789 g kg−1 sand and 138 g kg−1 clay) and a clay soil (216 g kg−1 sand, and 415 g kg−1 clay). Chamber experiments were conducted using plastic buckets as the experimental units. The treatments applied to each soil type were: (i) control (no added N), (ii) urea‐ammonium nitrate (UAN), and (iii) liquid swine manure slurry. Greenhouse gas fluxes were measured over 8 weeks. Within the UAN and swine manure treatments both N2O and CH4 emissions were greater in the sandy loam than in the clay soil. In the sandy loam soil N2O emissions were significantly different among all N treatments, but in the clay soil only the manure treatment had significantly higher N2O emissions. It is thought that the major differences between the two soils controlling both N2O and CH4 emissions were cation exchange capacity (CEC) and percent water‐filled pore space (%WFPS). We speculate that the higher CEC in the clay soil reduced N availability through increased adsorption of NH4+ compared to the sandy loam soil. In addition the higher average %WFPS in the sandy loam may have favored higher denitrification and CH4 production than in the clay soil.

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Accurate assessment of N2O emission from soil requires continuous year‐round and spatially extensive monitoring or the use of simulation that accurately and precisely predict N2O fluxes based on climatic, soil, and agricultural system input data. DAYCENT is an ecosystem model that simulates, among other processes, N2O emissions from soils. The purpose of the study was to compare N2O fluxes predicted by the DAYCENT model to measured N2O fluxes from an experimental corn field in central Iowa. Soil water content temperature and inorganic N, simulated by DAYCENT were compared to measured values of these variables. Field N2O emissions were measured using four replicated automated chambers at 6‐h intervals, from day of year (DOY) 42 through DOY 254 of 2006. We observed that DAYCENT generally accurately predicted soil temperature, with the exception of winter when predicted temperatures tended to be lower than measured values. Volumetric water contents predicted by DAYCENT were generally lower than measured values during most of the experimental period. Daily N2O emissions simulated by DAYCENT were significantly correlated to field measured fluxes; however, time series analyses indicate that the simulated fluxes were out of phase with the measured fluxes. Cumulative N2O emission calculated from the simulations (3.29 kg N2O‐N ha−1) was in range of the measured cumulative N2O emission (4.26 ± 1.09 kg N2O‐N ha−1).

Agricultural practices such as including perennial alfalfa ( L.), winter wheat ( L.), or red clover ( L.) in corn ( L.) rotations can provide higher crop yields and increase soil organic C (SOC) over time. How well process-based biogeochemical models such as DeNitrification-DeComposition (DNDC) capture the beneficial effects of diversified cropping systems is unclear. To calibrate and validate DNDC for simulation of observed trends in corn yield and SOC, we used long-term trials: continuous corn (CC) and corn-oats ( L.)-alfalfa-alfalfa (COAA) for Woodslee, ON, 1959 to 2015; and CC, corn-corn-soybean [ (L.) Merr.]-soybean (CCSS), corn-corn-soybean-winter wheat (CCSW), corn-corn-soybean-winter wheat + red clover (CCSW+Rc), and corn-corn-alfalfa-alfalfa (CCAA) for Elora, ON, 1981 to 2015. Yield and SOC under 21st century conditions were projected under future climate scenarios from 2016 to 2100. The DNDC model was calibrated to improve crop N stress and was revised to estimate changes in water availability as a function of soil properties. This improved yield estimates for diversified rotations at Elora (mean absolute prediction error [MAPE] decreased from 13.4-15.5 to 10.9-14.6%) with lower errors for the three most diverse rotations. Significant improvements in yield estimates were also simulated at Woodslee for COAA, with MAPE decreasing from 24.0 to 16.6%. Predicted and observed SOC were in agreement for simpler rotations (CC or CCSS) at both sites (53.8 and 53.3 Mg C ha for Elora, 52.0 and 51.4 Mg C ha for Woodslee). Predicted SOC increased due to rotation diversification and was close to observed values (58.4 and 59 Mg C ha for Elora, 63 and 61.1 Mg C ha for Woodslee). Under future climate scenarios the diversified rotations mitigated crop water stress resulting in trends of higher yields and SOC content in comparison to simpler rotations.

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