Global Biogeochemical Cycles, Volume 34, Issue 9


Anthology ID:
G20-190
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Year:
2020
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Venue:
GWF
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Publisher:
American Geophysical Union (AGU)
URL:
https://gwf-uwaterloo.github.io/gwf-publications/G20-190
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Long‐Term Shifts in U.S. Nitrogen Sources and Sinks Revealed by the New TREND‐Nitrogen Data Set (1930–2017)
D. Byrnes | K. J. Van Meter | Nandita B. Basu

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.