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Wenxin Zhang

Researcher

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Storage, patterns, and environmental controls of soil organic carbon stocks in the permafrost regions of the Northern Hemisphere

Author

  • Tonghua Wu
  • Dong Wang
  • Cuicui Mu
  • Wenxin Zhang
  • Xiaofan Zhu
  • Lin Zhao
  • Ren Li
  • Guojie Hu
  • Defu Zou
  • Jie Chen
  • Xianhua Wei
  • Amin Wen
  • Chengpeng Shang
  • Yune La
  • Peiqing Lou
  • Xin Ma
  • Xiaodong Wu
Show all

Summary, in English

Large stocks of soil organic carbon (SOC) accumulated in the Northern Hemisphere permafrost regions may be vulnerable to climatic warming, but global estimates of SOC distribution and magnitude in permafrost regions still have large uncertainties. Based on multiple high-resolution environmental variables and a compiled soil sample dataset (>3000 soil profiles), we used machine-learning methods to estimate the size and spatial distribution of SOC for the top 3 m soils in the Northern Hemisphere permafrost regions. We also identified key environmental predictors of SOC. The results showed that the SOC storage for the top 3 m soil was 1079 ± 174 Pg C across the Northern Hemisphere permafrost regions (20.8 × 106 km2), including 1057 ± 167 Pg C in the northern permafrost regions and 22 ± 7 Pg C in the Third Pole permafrost regions. The mean annual air temperature and NDVI are the main controlling factors for the spatial distribution of SOC stocks in the northern and the Third Pole permafrost regions. Our estimations were more accurate than the existing global SOC stock maps. The results improve our understanding of the regional and global permafrost carbon cycle and their feedback to the climate system.

Department/s

  • Dept of Physical Geography and Ecosystem Science
  • BECC: Biodiversity and Ecosystem services in a Changing Climate
  • MERGE: ModElling the Regional and Global Earth system

Publishing year

2022-07-01

Language

English

Publication/Series

Science of the Total Environment

Volume

828

Document type

Journal article

Publisher

Elsevier

Topic

  • Soil Science
  • Earth and Related Environmental Sciences

Keywords

  • Machine learning
  • Northern Hemisphere
  • Permafrost
  • Soil organic carbon

Status

Published

ISBN/ISSN/Other

  • ISSN: 0048-9697