Universal temperature sensitivity of denitrification nitrogen losses in forest soils

Haoming Yu, Yihang Duan, Jan Mulder, Peter Dörsch, Weixing Zhu, Xu-Ri, Kai Huang, Zhoutao Zheng, Ronghua Kang, Chao Wang, Zhi Quan, Feifei Zhu, Dongwei Liu, Shushi Peng, Shijie Han, Yangjian Zhang () and Yunting Fang ()
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Haoming Yu: Chinese Academy of Sciences
Yihang Duan: Chinese Academy of Sciences
Jan Mulder: Norwegian University of Life Sciences
Peter Dörsch: Norwegian University of Life Sciences
Weixing Zhu: State University of New York
Xu-Ri: Chinese Academy of Sciences
Kai Huang: Chinese Academy of Sciences
Zhoutao Zheng: Chinese Academy of Sciences
Ronghua Kang: Chinese Academy of Sciences
Chao Wang: Chinese Academy of Sciences
Zhi Quan: Chinese Academy of Sciences
Feifei Zhu: Chinese Academy of Sciences
Dongwei Liu: Chinese Academy of Sciences
Shushi Peng: Peking University
Shijie Han: Qufu Normal University
Yangjian Zhang: Chinese Academy of Sciences
Yunting Fang: Chinese Academy of Sciences

Nature Climate Change, 2023, vol. 13, issue 7, 726-734

Abstract: Abstract Soil nitrous oxide (N2O) and dinitrogen (N2) emissions from denitrification are crucial to the nitrogen (N) cycle. However, the temperature sensitivities (Q10) of gaseous N losses in forest soils are poorly understood, with implications for prediction of N cycle responses to warming. Here, we quantify temperature sensitivities of denitrification-derived potential N2O and N2 production. Using soils from 18 forest sites in China along a 4,000 km north–south transect we find that N2O and N2 production rates increased with temperature, with large variations across soils. In contrast, the Q10 values for N2O (2.1 ± 0.5) and N2 (2.6 ± 0.6) were similar across soils. N2 was more sensitive to temperature than N2O, suggesting that warming could promote complete denitrification. Moreover, the Q10 for denitrification (2.3 ± 0.5) was comparable to Q10 for aquatic sediments. This finding of universal temperature sensitivity of gaseous N losses from denitrification will facilitate modelling N losses in response to warming globally.

Date: 2023
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DOI: 10.1038/s41558-023-01708-2

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