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Digital Mapping of Soil Organic Carbon Contents and Stocks in Denmark

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  • Kabindra Adhikari
  • Alfred E Hartemink
  • Budiman Minasny
  • Rania Bou Kheir
  • Mette B Greve
  • Mogens H Greve

Abstract

Estimation of carbon contents and stocks are important for carbon sequestration, greenhouse gas emissions and national carbon balance inventories. For Denmark, we modeled the vertical distribution of soil organic carbon (SOC) and bulk density, and mapped its spatial distribution at five standard soil depth intervals (0−5, 5−15, 15−30, 30−60 and 60−100 cm) using 18 environmental variables as predictors. SOC distribution was influenced by precipitation, land use, soil type, wetland, elevation, wetness index, and multi-resolution index of valley bottom flatness. The highest average SOC content of 20 g kg−1 was reported for 0−5 cm soil, whereas there was on average 2.2 g SOC kg−1 at 60−100 cm depth. For SOC and bulk density prediction precision decreased with soil depth, and a standard error of 2.8 g kg−1 was found at 60−100 cm soil depth. Average SOC stock for 0−30 cm was 72 t ha−1 and in the top 1 m there was 120 t SOC ha−1. In total, the soils stored approximately 570 Tg C within the top 1 m. The soils under agriculture had the highest amount of carbon (444 Tg) followed by forest and semi-natural vegetation that contributed 11% of the total SOC stock. More than 60% of the total SOC stock was present in Podzols and Luvisols. Compared to previous estimates, our approach is more reliable as we adopted a robust quantification technique and mapped the spatial distribution of SOC stock and prediction uncertainty. The estimation was validated using common statistical indices and the data and high-resolution maps could be used for future soil carbon assessment and inventories.

Suggested Citation

  • Kabindra Adhikari & Alfred E Hartemink & Budiman Minasny & Rania Bou Kheir & Mette B Greve & Mogens H Greve, 2014. "Digital Mapping of Soil Organic Carbon Contents and Stocks in Denmark," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-13, August.
  • Handle: RePEc:plo:pone00:0105519
    DOI: 10.1371/journal.pone.0105519
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    Citations

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    Cited by:

    1. Shahin Nozari & Luboš Borůvka, 2023. "The effects of slope and altitude on soil organic carbon and clay content in different land-uses: A case study in the Czech Republic," Soil and Water Research, Czech Academy of Agricultural Sciences, vol. 18(3), pages 204-218.
    2. Kingsley JOHN & Isong Abraham Isong & Ndiye Michael Kebonye & Esther Okon Ayito & Prince Chapman Agyeman & Sunday Marcus Afu, 2020. "Using Machine Learning Algorithms to Estimate Soil Organic Carbon Variability with Environmental Variables and Soil Nutrient Indicators in an Alluvial Soil," Land, MDPI, vol. 9(12), pages 1-20, December.
    3. Nmehielle F. & Ogoro M. & Obafemi A. A., 2023. "Evaluating the Flood Control Measures and Resilience Employed by Communities Along the New Calabar River Catchment," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 10(9), pages 289-302, September.
    4. Ranjith P. Udawatta & Lalith Rankoth & Shibu Jose, 2019. "Agroforestry and Biodiversity," Sustainability, MDPI, vol. 11(10), pages 1-22, May.
    5. Chiara Piccini & Rosa Francaviglia & Alessandro Marchetti, 2020. "Predicted Maps for Soil Organic Matter Evaluation: The Case of Abruzzo Region (Italy)," Land, MDPI, vol. 9(10), pages 1-14, September.
    6. Shuai Wang & Qiubing Wang & Kabindra Adhikari & Shuhai Jia & Xinxin Jin & Hongbin Liu, 2016. "Spatial-Temporal Changes of Soil Organic Carbon Content in Wafangdian, China," Sustainability, MDPI, vol. 8(11), pages 1-16, November.
    7. Odunayo David Adeniyi & Alexander Brenning & Alice Bernini & Stefano Brenna & Michael Maerker, 2023. "Digital Mapping of Soil Properties Using Ensemble Machine Learning Approaches in an Agricultural Lowland Area of Lombardy, Italy," Land, MDPI, vol. 12(2), pages 1-17, February.
    8. Sandra Duarte-Guardia & Pablo L. Peri & Wulf Amelung & Douglas Sheil & Shawn W. Laffan & Nils Borchard & Michael I. Bird & Wouter Dieleman & David A. Pepper & Brian Zutta & Esteban Jobbagy & Lucas C. , 2019. "Better estimates of soil carbon from geographical data: a revised global approach," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(3), pages 355-372, March.

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