Soil carbon sequestration potential in global croplands

José Padarian*, Budiman Minasny, Alex McBratney, Pete Smith

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)
3 Downloads (Pure)

Abstract

Improving the amount of organic carbon in soils is an attractive alternative to partially mitigate climate change. However, the amount of carbon that can be potentially added to the soil is still being debated, and there is a lack of information on additional storage potential on global cropland. Soil organic carbon (SOC) sequestration potential is region-specific and conditioned by climate and management but most global estimates use fixed accumulation rates or time frames. In this study, we model SOC storage potential as a function of climate, land cover and soil. We used 83,416 SOC observations from global databases and developed a quantile regression neural network to quantify the SOC variation within soils with similar environmental characteristics. This allows us to identify similar areas that present higher SOC with the difference representing an additional storage potential. We estimated that the topsoils (0-30 cm) of global croplands (1,410 million hectares) hold 83 Pg C. The additional SOC storage potential in the topsoil of global croplands ranges from 29 to 65 Pg C. These values only equate to three to seven years of global emissions, potentially offsetting 35% of agriculture's 85 Pg historical carbon debt estimate due to conversion from natural ecosystems. As SOC store is temperature-dependent, this potential is likely to reduce by 14% by 2040 due to climate change in a ''business as usual'' scenario. The results of this article can provide a guide to areas of focus for SOC sequestration, and highlight the environmental cost of agriculture.

Original languageEnglish
Article numbere13740
Number of pages21
JournalPeerJ
Volume10
DOIs
Publication statusPublished - 21 Jul 2022

Bibliographical note

Funding Information:
This project was funded by the ARC Discovery project DP200102542 ‘‘Forecasting soil conditions’’. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Funding Information:
The authors declare there are no competing interests. Budiman Minasny is a member of the GLADSOILMAP research consortium supported by LE STUDIUM Institute for Advanced Research Studies, France.

Data Availability Statement

The following information was supplied regarding data availability:

The data is available at WoSIS (Batjes, Ribeiro & Van Oostrum, 2020; doi:10.5194/essd-12-299-2020), CHLSOC (Pfeiffer et al., 2020; doi:10.5194/essd-12-457-2020), and the data described in Stockmann et al. (2015; doi:10.1016/j.gfs.2015.07.001).

The land cover information was extracted from the MCD12Q1v6 MODIS product (doi:10.5067/MODIS/MCD12Q1.006).

Keywords

  • Carbon sequestration
  • Digital soil mapping
  • Neural networks
  • Quantile regression

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