Articles | Volume 7, issue 2
SOIL, 7, 377–398, 2021
https://doi.org/10.5194/soil-7-377-2021
SOIL, 7, 377–398, 2021
https://doi.org/10.5194/soil-7-377-2021

Original research article 06 Jul 2021

Original research article | 06 Jul 2021

Predicting the spatial distribution of soil organic carbon stock in Swedish forests using a group of covariates and site-specific data

Kpade O. L. Hounkpatin et al.

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Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (10 Mar 2021) by Nicolas P.A. Saby
AR by Ozias Hounkpatin on behalf of the Authors (20 Apr 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (30 Apr 2021) by Nicolas P.A. Saby
RR by Anonymous Referee #3 (10 May 2021)
RR by Anonymous Referee #1 (11 May 2021)
ED: Publish subject to technical corrections (24 May 2021) by Nicolas P.A. Saby
ED: Publish subject to technical corrections (01 Jun 2021) by Kristof Van Oost(Executive Editor)
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Short summary
Forests store large amounts of carbon in soils. Implementing suitable measures to improve the sink potential of forest soils would require accurate data on the carbon stored in forest soils and a better understanding of the factors affecting this storage. This study showed that the prediction of soil carbon stock in Swedish forest soils can increase in accuracy when one divides a big region into smaller areas in combination with information collected locally and derived from satellites.