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Abstract: Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi‐species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi‐model ensembles to predict productivity and nitrous oxide (N2O) emissions for wheat, maize, rice and temperate grasslands. Using a multi‐stage modelling protocol, from blind simulations (stage 1) to partial (stages 2–4) and full calibration (stage 5), 24 process‐based biogeochemical models were assessed individually or as an ensemble against long‐term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N2O emissions. Results showed that across sites and crop/grassland types, 23%–40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N2O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N2O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2–4) markedly reduced prediction errors of the full model ensemble E‐median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N2O emissions. Yield‐scaled N2O emissions (N2O emissions divided by crop yields) were ranked accurately by three‐model ensembles across crop species and field sites. The potential of using process‐based model ensembles to predict jointly productivity and N2O emissions at field scale is discussed. [ABSTRACT FROM AUTHOR]

There is a lack of information on how placement in soil and nitrification inhibitors affects nitrous oxide (N2O) and ammonia (NH3) emissions from pig slurry (PS) applied under no-till (NT) conditions. Our objective was to determine the impact of injecting PS and treating it with the nitrification inhibitor dicyandiamide (DCD) on NH3 and N2O emissions from soils under NT in subtropical southern Brazil. The emissions of these gases were compared for shallow (~ 10 cm) injection and surface broadcasting of PS with and without DCD (8.1-10.0 kg ha-1; 6.5-8.4% of applied NH4-N). Measurements were made at two sites during two summer growing seasons under NT corn crops. Injection reduced NH3 volatilization by 70% but increased N2O emissions 2.4-fold (from 2628 to 6198 g N2O N ha-1) compared with surface broadcast application. Adding DCD to PS inhibited nitrification and reduced N2O emissions by an average of 28% (730 g N2O-N ha-1) for surface broadcast and 66% (4105 g N2O-N ha-1) for injection but did not increase NH3 volatilization. Consequently, N2 O emission factors were much higher for injection (3.6%) than for surface broadcast (1.3%) application and were reduced (0.9%) when DCD was added to injected PS. In conclusion, the injection of DCD-treated slurry is a recommendable practice for reducing NH3 and N2O emissions when applying PS on NT corn in southern Brazil. [ABSTRACT FROM AUTHOR]

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