Reactive nitrogen (N) fluxes have increased tenfold over the last century, driven by increases in population, shifting diets, and increased use of commercial N fertilizers. Runoff of excess N from intensively managed landscapes threatens drinking water quality and disrupts aquatic ecosystems. Excess N is also a major source of greenhouse gas emissions from agricultural soils. While N emissions from agricultural landscapes are known to originate from not only current‐year N input but also legacy N accumulation in soils and groundwater, there has been limited access to fine‐scale, long‐term data regarding N inputs and outputs over decades of intensive agricultural land use. In the present work, we synthesize population, agricultural, and atmospheric deposition data to develop a comprehensive, 88‐year (1930–2017) data set of county‐scale components of the N mass balance across the contiguous United States (Trajectories Nutrient Dataset for nitrogen [TREND‐nitrogen]). Using a machine‐learning algorithm, we also develop spatially explicit typologies for components of the N mass balance. Our results indicate a large range of N trajectory behaviors across the United States due to differences in land use and management and particularly due to the very different drivers of N dynamics in densely populated urban areas compared with intensively managed agricultural zones. Our analysis of N trajectories also demonstrates a widespread functional homogenization of agricultural landscapes. This newly developed typology of N trajectories improves our understanding of long‐term N dynamics, and the underlying data set provides a powerful tool for modeling the impacts of legacy N on past, present, and future water quality.

中文翻译：

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新的TREND-氮数据集揭示了美国氮源和汇的长期变化（1930–2017）

在上个世纪，由于人口增加，饮食结构变化以及商业化氮肥的使用增加，反应性氮（N）通量增加了十倍。从集约化管理景观中流出的过量氮威胁饮用水质量并破坏水生生态系统。过量的氮也是农业土壤温室气体排放的主要来源。虽然已知农业景观中的氮排放不仅来自当年的氮输入，而且还来自土壤和地下水中的遗留氮积累，但在过去的几十年中，有关氮输入和输出的精细，长期数据的获取途径有限。集约化农业土地利用。在目前的工作中，我们综合了人口，农业和大气沉积数据，以开发出全面，美国连续88年（1930-2017年）的N质平衡的县级组成部分数据集（氮的轨迹营养数据集[TREND-nitrogen]）。使用机器学习算法，我们还为N质量平衡的组成部分开发了空间明确的类型学。我们的结果表明，由于土地使用和管理的差异，尤其是由于人口密集的城市地区与集约管理的农业区相比，氮动力学的驱动因素大不相同，因此在美国，氮的轨迹行为范围很广。我们对N轨迹的分析还证明了农业景观的广泛功能同质化。N轨迹的这种新近发展的分类方法使我们对N的长期动力学有了更深入的了解，