Articles | Volume 9, issue 1
https://doi.org/10.5194/soil-9-21-2023
https://doi.org/10.5194/soil-9-21-2023
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

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Cited articles

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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.