Management-induced changes in soil organic carbon on global croplands

Kristine Karstens*, Benjamin Leon Bodirsky, Jan Philipp Dietrich, Marta Dondini, Jens Heinke, Matthias Kuhnert, Christoph Mueller, Susanne Rolinski, Pete Smith, Isabelle Weindl, Hermann Lotze-Campen, Alexander Popp

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
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Soil organic carbon (SOC), one of the largest terrestrial carbon (C) stocks on Earth, has been depleted by anthropogenic land cover change and agricultural management. However, the latter has so far not been well represented in global C stock assessments. While SOC models often simulate detailed biochemical processes that lead to the accumulation and decay of SOC, the management decisions driving these biophysical processes are still little investigated at the global scale. Here we develop a spatially explicit data set for agricultural management on cropland, considering crop production levels, residue returning rates, manure application, and the adoption of irrigation and tillage practices. We combine it with a reduced-complexity model based on the Intergovernmental Panel on Climate Change (IPCC) tier 2 method to create a half-degree resolution data set of SOC stocks and SOC stock changes for the first 30 cm of mineral soils. We estimate that, due to arable farming, soils have lost around 34.6 GtC relative to a counterfactual hypothetical natural state in 1975. Within the period 1975-2010, this SOC debt continued to expand by 5 GtC (0.14 GtC yr(-1)) to around 39.6 GtC. However, accounting for historical management led to 2.1 GtC fewer (0.06 GtC yr(-1)) emissions than under the assumption of constant management. We also find that management decisions have influenced the historical SOC trajectory most strongly by residue returning, indicating that SOC enhancement by biomass retention may be a promising negative emissions technique. The reduced-complexity SOC model may allow us to simulate management-induced SOC enhancement - also within computationally demanding integrated (land use) assessment modeling.

Original languageEnglish
Pages (from-to)5125-5149
Number of pages25
Issue number21
Publication statusPublished - 10 Nov 2022

Bibliographical note

Funding Information:
The work of Kristine Karstens has been funded by the DFG Priority Program “Climate Engineering: Risks, Challenges, Opportunities?” (SPP 1689), specifically the CEMICS2 project (grant no. ED78/3-2), and by the CDRSynTra project (grant no. 01LS2101G) funded by the German Federal Ministry of Education and Research (BMBF). The research leading to these results has received funding for Benjamin Leon Bodirsky from the European Union's Horizon 2020 Research And Innovation Programme (grant nos. 776479 (COACCH) and 821010 (CASCADES)). Benjamin Leon Bodirsky acknowledges support by the project ABCDR (grant no. 01LS2105A) funded by the BMBF. The work of Susanne Rolinski, Jens Heinke, and Isabelle Weindl has also been supported by CLIMASTEPPE (grant no. 01DJ8012), EXIMO (grant no. 01LP1903D), and FOCUS (grant no. 031B0787B), all funded by the BMBF. The input of Pete Smith, Matthias Kuhnert, and Marta Dondini contributes to the Soils-R-GGREAT project (grant no. NE/P019455/1) and CIRCASA (EU H2020; grant no. 774378).

Publisher Copyright:
Copyright © 2022 Kristine Karstens et al.

Data Availability Statement

We compiled our calculations as open-source R packages that are available at (Bodirsky et al., 2022a), for the management-related functions, (Karstens and Dietrich, 2022), for soil dynamic related functions, and (Bodirsky et al., 2022b), for validation data. All libraries are based on the MADRaT package available at (Dietrich et al., 2022), a framework which aims to improve the reproducibility and transparency in data processing. Model results, including C input data, are accessible at (Karstens, 2022). The software code for the paper and result preparation can be found under




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