Articles | Volume 9, issue 1
Original research article
11 Jan 2023
Original research article |  | 11 Jan 2023

Shapley values reveal the drivers of soil organic carbon stock prediction

Alexandre M. J.-C. Wadoux, Nicolas P. A. Saby, and Manuel P. Martin


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1034', Anonymous Referee #1, 11 Nov 2022
    • AC1: 'Reply on RC1', Alexandre Wadoux, 14 Nov 2022
  • RC2: 'Comment on egusphere-2022-1034', Anonymous Referee #2, 13 Nov 2022
    • AC2: 'Reply on RC2', Alexandre Wadoux, 14 Nov 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Revision (02 Dec 2022) by Peter Finke
AR by Alexandre Wadoux on behalf of the Authors (05 Dec 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (06 Dec 2022) by Peter Finke
ED: Publish as is (13 Dec 2022) by Engracia Madejón Rodríguez(Executive Editor)
Short summary
We introduce Shapley values for machine learning model interpretation and reveal the local and global controlling factors of soil organic carbon (SOC) stocks. The method enables spatial analysis of the important variables. Vegetation and topography determine much of the SOC stock variation in mainland France. We conclude that SOC stock variation is complex and should be interpreted at multiple levels.