Mitigating nitrogen losses with almost no crop yield penalty during extremely 
wet years

Liu, Wenfeng; Li, Mengxue; Huang, Yuanyuan; Makowski, David; Su, Yang; Bai, Yawei; Schauberger, Bernhard; Du, Taisheng; Abbaspour, Karim C.; Yang, Kun; Yang, Hong; Ciais, Philippe

doi:10.1126/sciadv.adi9325

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学術論文

Mitigating nitrogen losses with almost no crop yield penalty during extremely wet years

Authors

Liu, Wenfeng
External Organizations;

Li, Mengxue
External Organizations;

Huang, Yuanyuan
External Organizations;

Makowski, David
External Organizations;

Su, Yang
External Organizations;

Bai, Yawei
External Organizations;

/persons/resource/schauberger

Schauberger, Bernhard
Potsdam Institute for Climate Impact Research;

Du, Taisheng
External Organizations;

Abbaspour, Karim C.
External Organizations;

Yang, Kun
External Organizations;

Yang, Hong
External Organizations;

Ciais, Philippe
External Organizations;

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フルテキスト (公開)

sciadv.adi9325.pdf
(出版社版), 3MB

付随資料 (公開)

sciadv.adi9325_sm.pdf
(付録資料), 6MB

引用

Liu, W., Li, M., Huang, Y., Makowski, D., Su, Y., Bai, Y., Schauberger, B., Du, T., Abbaspour, K. C., Yang, K., Yang, H., & Ciais, P. (2024). Mitigating nitrogen losses with almost no crop yield penalty during extremely wet years. Science Advances, 10(9):. doi:10.1126/sciadv.adi9325.

引用: https://publications.pik-potsdam.de/pubman/item/item_29787

要旨

Climate change–induced precipitation anomalies during extremely wet years (EWYs) result in substantial nitrogen losses to aquatic ecosystems (Nw). Still, the extent and drivers of these losses, and effective mitigation strategies have remained unclear. By integrating global datasets with well-established crop modeling and machine learning techniques, we reveal notable increases in Nw, ranging from 22 to 56%, during historical EWYs. These pulses are projected to amplify under the SSP126 (SSP370) scenario to 29 to 80% (61 to 120%) due to the projected increases in EWYs and higher nitrogen input. We identify the relative precipitation difference between two consecutive years (diffPr) as the primary driver of extreme Nw. This finding forms the basis of the CLimate Extreme Adaptive Nitrogen Strategy (CLEANS), which scales down nitrogen input adaptively to diffPr, leading to a substantial reduction in extreme Nw with nearly zero yield penalty. Our results have important implications for global environmental sustainability and while safeguarding food security.