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Analysis of Soil Carbon Stock Dynamics by Machine Learning—Polish Case Study

Author

Listed:
  • Artur Łopatka

    (Department of Soil Science Erosion and Land Protection, Institute of Soil Science and Plant Cultivation—State Research Institute, Czartoryskich 8, 24-100 Pulawy, Poland)

  • Grzegorz Siebielec

    (Department of Soil Science Erosion and Land Protection, Institute of Soil Science and Plant Cultivation—State Research Institute, Czartoryskich 8, 24-100 Pulawy, Poland)

  • Radosław Kaczyński

    (Department of Soil Science Erosion and Land Protection, Institute of Soil Science and Plant Cultivation—State Research Institute, Czartoryskich 8, 24-100 Pulawy, Poland)

  • Tomasz Stuczyński

    (Faculty of Science and Health, The John Paul II Catholic University of Lublin, Konstantynów 1 H, 20-708 Lublin, Poland)

Abstract

A simplified differential equation for the dynamics of soil organic carbon (SOC) that describes the rate of SOC change (dSOC/dt) was constructed using the LASSO regression—a regularized linear regression machine learning method. This method selects the best predefined explanatory variables and empirically evaluates the relevant parameters of the equation. The result, converted into a formula for the long-term equilibrium level of soil carbon, indicates the existence of carbon sequestration potential in the studied regions of Poland. In particular, the model predicts high SOC content in regions with a high Topographic Wetness Index (TWI), such as river valleys or areas with high cattle density, as expected.

Suggested Citation

  • Artur Łopatka & Grzegorz Siebielec & Radosław Kaczyński & Tomasz Stuczyński, 2023. "Analysis of Soil Carbon Stock Dynamics by Machine Learning—Polish Case Study," Land, MDPI, vol. 12(8), pages 1-14, August.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:8:p:1587-:d:1215523
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    References listed on IDEAS

    as
    1. Pat H. Bellamy & Peter J. Loveland & R. Ian Bradley & R. Murray Lark & Guy J. D. Kirk, 2005. "Carbon losses from all soils across England and Wales 1978–2003," Nature, Nature, vol. 437(7056), pages 245-248, September.
    2. Zihao Wu & Yaolin Liu & Guie Li & Yiran Han & Xiaoshun Li & Yiyun Chen, 2022. "Influences of Environmental Variables and Their Interactions on Chinese Farmland Soil Organic Carbon Density and Its Dynamics," Land, MDPI, vol. 11(2), pages 1-16, January.
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