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Application of Cmic/Corg in the Soil Fertility Evaluation of Typical Forests in the Yulin Sandy Area

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  • Yue Wang

    (School of Resources and Environmental Economics, Inner Mongolia University of Finance and Economics, Hohhot 010070, China
    Resource Utilization and Environmental Protection Coordinated Development Academician Expert Workstation in the North of China, Inner Mongolia University of Finance and Economics, Inner Mongolia, Hohhot 010070, China)

  • Shan Wang

    (School of Resources and Environmental Economics, Inner Mongolia University of Finance and Economics, Hohhot 010070, China
    Resource Utilization and Environmental Protection Coordinated Development Academician Expert Workstation in the North of China, Inner Mongolia University of Finance and Economics, Inner Mongolia, Hohhot 010070, China)

  • Chun-Sheng Zhou

    (School of Resources and Environmental Economics, Inner Mongolia University of Finance and Economics, Hohhot 010070, China
    Resource Utilization and Environmental Protection Coordinated Development Academician Expert Workstation in the North of China, Inner Mongolia University of Finance and Economics, Inner Mongolia, Hohhot 010070, China)

  • Wen-Feng Chi

    (School of Resources and Environmental Economics, Inner Mongolia University of Finance and Economics, Hohhot 010070, China
    Resource Utilization and Environmental Protection Coordinated Development Academician Expert Workstation in the North of China, Inner Mongolia University of Finance and Economics, Inner Mongolia, Hohhot 010070, China)

Abstract

The microbial quotient (Cmic/Corg) has been used extensively to evaluate agriculture soil fertility, but the microbial sensitivity should be considered during the forestry process. Therefore, the objective of this study was to examine a soil fertility evaluation method applied to four vegetation types in the Mu Us Sandland in northwestern China, using the relationship between the Cmic/Corg ratio and soil moisture, and soil temperature under the premise of microbial diversity. The final predictive value was C. microphylla (0.2198) > P. sylvestris (0.2175) > P. tabulaeformis (0.0872) > S. psammophila (0.0767). We verified the evaluation results using two traditional methods, the back-propagation (BP) artificial neural network model and principal component analysis, which are widely used to evaluate soil quality based on the soil nutrient concentration. The results were the same as the Cmic/Corg predictions. We conclude that when the soil microbes are used in soil quality evaluations, the changing pattern should be fully considered.

Suggested Citation

  • Yue Wang & Shan Wang & Chun-Sheng Zhou & Wen-Feng Chi, 2022. "Application of Cmic/Corg in the Soil Fertility Evaluation of Typical Forests in the Yulin Sandy Area," Land, MDPI, vol. 11(4), pages 1-11, April.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:4:p:559-:d:790865
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    References listed on IDEAS

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    1. Jizhong Zhou & Kai Xue & Jianping Xie & Ye Deng & Liyou Wu & Xiaoli Cheng & Shenfeng Fei & Shiping Deng & Zhili He & Joy D. Van Nostrand & Yiqi Luo, 2012. "Microbial mediation of carbon-cycle feedbacks to climate warming," Nature Climate Change, Nature, vol. 2(2), pages 106-110, February.
    2. W. Knorr & I. C. Prentice & J. I. House & E. A. Holland, 2005. "Long-term sensitivity of soil carbon turnover to warming," Nature, Nature, vol. 433(7023), pages 298-301, January.
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