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Croplands are highly productive ecosystems that contribute to land–atmosphere exchange of carbon, energy, and water during their short growing seasons. We evaluated and compared net ecosystem exchange (NEE), latent heat flux (LE), and sensible heat flux (H) simulated by a suite of ecosystem models at five agricultural eddy covariance flux tower sites in the central United States as part of the North American Carbon Program Site Synthesis project. Most of the models overestimated H and underestimated LE during the growing season, leading to overall higher Bowen ratios compared to the observations. Most models systematically under predicted NEE, especially at rain-fed sites. Certain crop-specific models that were developed considering the high productivity and associated physiological changes in specific crops better predicted the NEE and LE at both rain-fed and irrigated sites. Models with specific parameterization for different crops better simulated the inter-annual variability of NEE for maize-soybean rotation compared to those models with a single generic crop type. Stratification according to basic model formulation and phenological methodology did not explain significant variation in model performance across these sites and crops. The under prediction of NEE and LE and over prediction of H by most of the models suggests that models developed and parameterized for natural ecosystems cannot accurately predict the more robust physiology of highly bred and intensively managed crop ecosystems. When coupled in Earth System Models, it is likely that the excessive physiological stress simulated in many land surface component models leads to overestimation of temperature and atmospheric boundary layer depth, and underestimation of humidity and CO2 seasonal uptake over agricultural regions.

Farmers, food supply companies, and policymakers need practical yet scientifically robust methods to quantify how improved nitrogen (N) fertilizer management can reduce nitrous oxide (N 2 O) emissions. To meet this need, we developed an empirical model based on published field data for predicting N 2 O emission from rainfed maize (Zea mays L.) fields managed with inorganic N fertilizer in the United States and Canada. Nitrous oxide emissions ranged widely on an area basis (0.03-32.9 kg N ha -1 yr -1 ) and a yield-scaled basis (0.006-4.8 kg N Mg -1 grain yr -1 ). We evaluated multiple modeling approaches and variables using three metrics of model fit (Akaike information criteria corrected for small sample sizes [AICc], RMSE, and R 2 ). Our model explains 32.8% of the total observed variation and 50% of observed site-level variation. Soil clay content was very important for predicting N 2 O emission and predicting the change in N 2 O emission due to a change in N balance, with the addition of a clay fixed effect explaining 37% of site-level variation. Sites with higher clay content showed greater reductions in N 2 O emission for a given reduction in N balance. Therefore, high-clay sites are particularly important targets for reducing N 2 O emissions. Our linear mixed model is more suitable for predicting the effect of improved N management on N 2 O emission in maize fields than other published models because it (a) requires only input data readily available on working farms, (b) is derived from field observations, (c) correctly represents differences among sites using a mixed modeling approach, and (d) includes soil texture because it strongly influences N 2 O emissions., (© 2020 The Authors. Journal of Environmental Quality published by Wiley Periodicals LLC on behalf of American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.)

Farmers, food supply-chain entities, and policymakers need a simple but robust indicator to demonstrate progress toward reducing nitrogen pollution associated with food production. We show that nitrogen balance-the difference between nitrogen inputs and nitrogen outputs in an agricultural production system-is a robust measure of nitrogen losses that is simple to calculate, easily understood, and based on readily available farm data. Nitrogen balance provides farmers with a means of demonstrating to an increasingly concerned public that they are succeeding in reducing nitrogen losses while also improving the overall sustainability of their farming operation. Likewise, supply-chain companies and policymakers can use nitrogen balance to track progress toward sustainability goals. We describe the value of nitrogen balance in translating environmental targets into actionable goals for farmers and illustrate the potential roles of science, policy, and agricultural support networks in helping farmers achieve them.