Farmers, food supply companies, and policymakers need practical yet scientifically robust methods to quantify how improved nitrogen (N) fertilizer management can reduce nitrous oxide (N2 O) emissions. To meet this need, we developed an empirical model based on published field data for predicting N2 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 R2 ). 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 N2 O emission and predicting the change in N2 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 N2 O emission for a given reduction in N balance. Therefore, high-clay sites are particularly important targets for reducing N2 O emissions. Our linear mixed model is more suitable for predicting the effect of improved N management on N2 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 N2 O emissions.

中文翻译：

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预测北美玉米改善氮管理的温室气体效益

农民、食品供应公司和政策制定者需要实用且科学可靠的方法来量化改进氮 (N) 肥料管理如何减少一氧化二氮 (N2 O) 排放。为了满足这一需求，我们根据已发表的田间数据开发了一个经验模型，用于预测美国和加拿大使用无机氮肥管理的雨养玉米 (Zea mays L.) 田地的 N2 O 排放。一氧化二氮的排放范围很广，以面积为基础（0.03-32.9 kg N ha-1 yr-1 ）和以产量为基础（0.006-4.8 kg N Mg-1 谷物 yr-1 ）。我们使用三个模型拟合指标（针对小样本量 [AICc]、RMSE 和 R2 校正的 Akaike 信息标准）评估了多种建模方法和变量。我们的模型解释了观察到的总变异的 32.8% 和观察到的站点级变异的 50%。土壤粘土含量对于预测 N2 O 排放和预测由于 N 平衡变化引起的 N2 O 排放变化非常重要，添加粘土固定效应解释了 37% 的场地水平变化。对于给定的 N 平衡减少，具有较高粘土含量的场地显示出更多的 N2 O 排放减少。因此，高粘土场地是减少 N2 O 排放的特别重要的目标。与其他已发表的模型相比，我们的线性混合模型更适合预测改进的氮管理对玉米田中 N2 O 排放的影响，因为它 (a) 只需要在工作农场现成的输入数据，(b) 来自田间观察， (c) 使用混合建模方法正确表示地点之间的差异，并且 (d) 包括土壤质地，因为它强烈影响 N2 O 排放。