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.

Data sets

WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas (https://www.worldclim.org/) S. E. Fick and R. J. Hijmans https://doi.org/10.1002/joc.5086

Data from: HistMapR: Rapid digitization of historical land-use maps in R Alistair G. Auffret, Adam Kimberley, Jan Plue, Helle Skånes, Simon Jakobsson, Emelie Waldén, Marika Wennbom, Heather Wood, James M. Bullock, Sara A. O. Cousins, Mira Gartz, Danny A. P. Hooftman, and Louise Tränk https://doi.org/10.17045/sthlmuni.4649854.v2

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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.