Computer simulations are widely used to explore options and quantify outcomes in agriculture. For example, mathematical models have been used to estimate how much of the nitrogen (N) and phosphorus (P) delivered to the Gulf of Mexico comes from agricultural sources (Alexander et al. 2008); to calculate changes in grain yields as management practices are varied (Chen et al. 2014); and to investigate the effects of different precipitation regimes on soil erosion (Nearing et al. 2005). Physical models can be linked with economic and behavioral data to calculate potential costs, such as those of treating or replacing household well water contaminated by nitrates (NO3) as grassland is converted to row crops (Keeler and Polasky 2014). Models can also estimate risk, such as that of crop failure in various climate change scenarios (Challinor et al. 2010). A wide variety of scales and systems can be simulated, from assessing farmers’ behavioral responses to climate change-related policies on a patchwork of single farms (Berger and Troost 2014), to predicting global losses of staple crops due to pest damage in a warmer world (Deutsch et al. 2018).

中文翻译：

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使用农业模型为政策提供信息：研究人员和政策制定者的讨论要点

计算机模拟被广泛用于探索农业的选择和量化结果。例如，数学模型已被用于估计输送到墨西哥湾的氮 (N) 和磷 (P) 有多少来自农业（Alexander 等人，2008 年）；计算谷物产量随着管理实践的变化而发生的变化（Chen 等人，2014 年）；并调查不同降水状况对土壤侵蚀的影响（Nearing 等人，2005 年）。物理模型可以与经济和行为数据相关联以计算潜在成本，例如在将草地转化为中耕作物时处理或更换受硝酸盐 (NO3) 污染的家庭井水的成本（Keeler 和 Polasky，2014 年）。模型还可以估计风险，例如各种气候变化情景下作物歉收的风险（Challinor 等人，2010 年）。