Canadian net forest CO2 uptake enhanced by heat drought via reduced respiration

Guanyu Dong, Fei Jiang, Yongguang Zhang, Weimin Ju, Shilong Piao, Philippe Ciais, Wouter Peters, Ingrid T. Luijkx, Junjie Liu, Frédéric Chevallier, Ning Zeng, Xiangjun Tian, Shamil Maksyutov, Oliver Sonnentag, M. Altaf Arain, Alan G. Barr, Yuanyuan Huang, Chao Yue, Wenping Yuan, Liangyun LiuLei Fan, Xu Yue, Jingfeng Xiao, Xing Li, Stephen Sitch, Pierre Friedlingstein, Michael O’Sullivan, Jürgen Knauer, Vivek Arora, Daniel Kennedy, Lei Ma, Peter E. Thornton, Roland Séférian, Tobias Nützel, Jens Heinke, Qing Sun, Sönke Zaehle, Philippe Peylin, Etsushi Kato, Haley Alcock, Bruno Lecavalier, Mousong Wu, Jun Wang, Lingyu Zhang, Guoyuan Lv, Yuanyuan Zhang, Dayang Zhao, Jing M. Chen

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The response of net forest carbon uptake to warm extremes remains elusive. The year 2023 was at the time ‘the hottest year on record’ globally, with Canada’s forests experiencing warm anomalies of above 2 °C and unprecedented drought and wildfires, providing a unique case to examine the response of boreal forest net carbon uptake to climate extremes. Here we combine satellite-based atmospheric CO2 flux inversions with ground-based in situ observations of CO2 fluxes and concentrations to investigate Canada’s forest net carbon uptake and its underlying mechanisms in 2023. We find that, compared with 2015–2022, Canada’s forest net carbon uptake was enhanced by 0.28 ± 0.23 PgC, offsetting 38–48% of Canadian wildfire emissions in 2023. This enhanced net uptake was dominated by large ecosystem respiration reductions, mainly attributable to severe root-zone soil moisture deficits and the unimodal temperature response of respiration. However, most dynamic global vegetation models failed to simulate the respiration reductions and the responses to hydrothermal conditions well. This study improves our understanding of boreal forest net carbon uptake in response to climate extremes and highlights an urgent need to improve vegetation models under global warming.

Original languageEnglish
Number of pages12
JournalNature Geoscience
DOIs
Publication statusE-pub ahead of print (In Press) - 2026

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