Causality guided machine learning model on wetland CH4 emissions across global 
wetlands

Yuan, Kunxiaojia; Zhu, Qing; Li, Fa; Riley, William J.; Torn, Margaret; Chu, Housen; McNicol, Gavin; Chen, Min; Knox, Sara; Delwiche, Kyle; Wu, Huayi; Baldocchi, Dennis; Ma, Hongxu; Desai, Ankur R.; Chen, Jiquan; Sachs, Torsten; Ueyama, Masahito; Sonnentag, Oliver; Helbig, Manuel; Tuittila, Eeva-Stiina; Jurasinski, Gerald; Koebsch, Franziska; Campbell, David; Schmid, Hans Peter; Lohila, Annalea; Göckede, Mathias; Nilsson, Mats B.; Friborg, Thomas; Jansen, Joachim; Zona, Donatella; Euskirchen, Eugenie; Ward, Eric J.; Bohrer, Gil; Jin, Zhenong; Liu, Licheng; Iwata, Hiroki; Goodrich, Jordan; Jackson, Robert

doi:10.1016/j.agrformet.2022.109115

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Journal Article

Causality guided machine learning model on wetland CH₄ emissions across global wetlands

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Göckede, Mathias
Integrating surface-atmosphere Exchange Processes Across Scales - Modeling and Monitoring, Dr. Mathias Göckede, Department Biogeochemical Signals, Prof. Dr. Sönke Zaehle, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Citation

Yuan, K., Zhu, Q., Li, F., Riley, W. J., Torn, M., Chu, H., et al. (2022). Causality guided machine learning model on wetland CH₄ emissions across global wetlands. Agricultural and Forest Meteorology, 324: 109115. doi:10.1016/j.agrformet.2022.109115.

Cite as: https://hdl.handle.net/21.11116/0000-000B-4B47-2

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