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Factors Influencing the Spatial Distribution of Soil Total Phosphorus Based on Structural Equation Modeling

Author

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  • Yameng Jiang

    (Key Laboratory of Poyang Lake Watershed Agricultural Resources and Ecology (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Jiangxi Agricultural University, Nanchang 330045, China)

  • Jun Huang

    (Basic Geological Survey Institute of Jiangxi Geological Survey and Exploration Institute (Jiangxi Nonferrous Geological Mineral Exploration and Development Institute), Nanchang 330045, China)

  • Xi Guo

    (Key Laboratory of Poyang Lake Watershed Agricultural Resources and Ecology (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Jiangxi Agricultural University, Nanchang 330045, China)

  • Yingcong Ye

    (Key Laboratory of Poyang Lake Watershed Agricultural Resources and Ecology (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Jiangxi Agricultural University, Nanchang 330045, China)

  • Jia Liu

    (Key Laboratory of Poyang Lake Watershed Agricultural Resources and Ecology (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Jiangxi Agricultural University, Nanchang 330045, China)

  • Yefeng Jiang

    (Key Laboratory of Poyang Lake Watershed Agricultural Resources and Ecology (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Jiangxi Agricultural University, Nanchang 330045, China)

Abstract

Soil total phosphorus plays an important role in soil fertility, plant growth, and bioge-ochemical cycles. This study aims to determine the spatial distribution characteristics of soil total phosphorus and identify its main influencing factors in the study area, thereby providing a basis for the scientific management of soil total phosphorus. Here, we conducted a comprehensive analysis by combining classical statistical analysis, ge-ostatistics methods, Pearson correlation analysis, one-way analysis of variance (ANOVA), and structural equation modeling (SEM) to explore the spatial distribution patterns of soil total phosphorus and its influencing factors. The results showed that soil total phosphorus in the study area ranged from 161.00 to 991.00 mg/kg, with an average of 495.71 mg/kg. Spatially, soil total phosphorus exhibited a patchy distribu-tion pattern, with high values primarily concentrated in cultivated areas along rivers and low values mainly located in forested areas in the southeastern and central re-gions. Additionally, the nugget effect of soil total phosphorus was 71.5%, indicating a moderate level of spatial variability. The Pearson correlation analysis revealed that soil total phosphorus content was significantly correlated with multiple factors, including land use types, soil parent material, distance from settlements, slope, and soil pH. Based on these findings, we employed ANOVA to analyze the impacts of various fac-tors. The results indicated that soil total phosphorus content showed significant differences under the influence of different factors. Subsequently, we further explored in depth the action paths through which these factors affect soil total phosphorus us-ing SEM. The SEM results showed that the absolute values of the total effects of the influencing factors on soil total phosphorus, ranked from highest to lowest, were as follows: land use types (0.499) > soil parent material (0.240) > distance from settle-ments (0.178) > slope (0.161) > elevation (0.127) > soil pH (0.114) > normalized differ-ence vegetation index (0.103). These findings provide a scientific foundation for the effective management of soil total phosphorus in similar study areas.

Suggested Citation

  • Yameng Jiang & Jun Huang & Xi Guo & Yingcong Ye & Jia Liu & Yefeng Jiang, 2025. "Factors Influencing the Spatial Distribution of Soil Total Phosphorus Based on Structural Equation Modeling," Agriculture, MDPI, vol. 15(9), pages 1-17, May.
    • Handle: RePEc:gam:jagris:v:15:y:2025:i:9:p:1013-:d:1650893
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    References listed on IDEAS

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    1. Rumi Wang & Runyan Zou & Jianmei Liu & Luo Liu & Yueming Hu, 2021. "Spatial Distribution of Soil Nutrients in Farmland in a Hilly Region of the Pearl River Delta in China Based on Geostatistics and the Inverse Distance Weighting Method," Agriculture, MDPI, vol. 11(1), pages 1-12, January.
    2. Pham Thi Phuong Thuy & Nguyen My Hoa & Warren A. Dick, 2020. "Reducing Phosphorus Fertilizer Input in High Phosphorus Soils for Sustainable Agriculture in the Mekong Delta, Vietnam," Agriculture, MDPI, vol. 10(3), pages 1-11, March.
    3. Hua Wang & Yuxin Zhu & Jinghao Wang & Hubiao Han & Jiqiang Niu & Xueye Chen, 2022. "Modeling of spatial pattern and influencing factors of cultivated land quality in Henan Province based on spatial big data," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-17, April.
    4. Yang Li & Zhong Baorong & Xu Xiaohong & Liang Zijun, 2022. "Application of a semivariogram based on a deep neural network to Ordinary Kriging interpolation of elevation data," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-12, April.
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