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Driving Mechanisms of Ecological Suitability Index in the Yellow River Basin from 1990 to 2020

Author

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  • Bingbing Zhang

    (School of Geography and Environment, Liaocheng University, Liaocheng 252000, China
    Bingbing Zhang and Yanjun Liu contributed equally to this work and should be considered co-first author.)

  • Yanjun Liu

    (School of Geography and Environment, Liaocheng University, Liaocheng 252000, China
    Bingbing Zhang and Yanjun Liu contributed equally to this work and should be considered co-first author.)

  • Shuyao Du

    (School of Geography and Environment, Liaocheng University, Liaocheng 252000, China)

  • Dengshuai Chen

    (School of Geography and Environment, Liaocheng University, Liaocheng 252000, China)

  • Xin Li

    (School of Geography and Environment, Liaocheng University, Liaocheng 252000, China)

  • Teng Liu

    (School of Geography and Environment, Liaocheng University, Liaocheng 252000, China)

  • Jianrong Cao

    (School of Geography and Environment, Liaocheng University, Liaocheng 252000, China
    Observation and Research Station of Seawater Intrusion and Soil Salinization in Laizhou Bay, MNR, Qingdao 266061, China
    Institute of Huanghe Studies, Liaocheng University, Liaocheng 252000, China)

  • Zengxin Zhang

    (School of Hydrology and Water Resources, Hohai University, Nanjing 210009, China)

Abstract

Ecological security is of central significance for maintaining the integrity and stability of regional ecosystems. Nevertheless, current academic research systematically studying the complex driving mechanisms behind ecological security is deficient. Therefore, this study utilised ecological sources ( ES s) and ecological resistance surfaces ( ERS s) to calculate and obtain the Ecological Suitability Index ( ESI ), thereby reflecting the ecological security status. The drivers of ESI in different areas of the Yellow River Basin (YRB) from 1990 to 2020 were explored using the random forest (RF) model and GeoDetector. The results of the study show that: (1) according to the results of the RF model, LANDUSE, NDVI, and PRE are the most important driving factors of the ESI in the upper (UYR), middle (MYR), and lower (LYR) reaches of the YRB; (2) according to the results of GeoDetector factor detection, in the UYR and MYR, the ESI is primarily influenced by natural factors such as NDVI and PRE, showing particularly significant impacts in 2010 and 2020; (3) in the LYR, the ESI is mainly influenced by NDVI, but the degree of influence from socioeconomic factors has significantly strengthened. This study provides a decision-making direction for ecological protection and coordinated development in the YRB.

Suggested Citation

  • Bingbing Zhang & Yanjun Liu & Shuyao Du & Dengshuai Chen & Xin Li & Teng Liu & Jianrong Cao & Zengxin Zhang, 2025. "Driving Mechanisms of Ecological Suitability Index in the Yellow River Basin from 1990 to 2020," Sustainability, MDPI, vol. 17(3), pages 1-17, February.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:3:p:1307-:d:1584666
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    References listed on IDEAS

    as
    1. Cao, Hui & Chen, Cheng & Chen, Jianglong & Song, Weixuan & He, Jiang & Liu, Chunhui, 2024. "Differentiation of urban-rural interface and its driving mechanism: A case study of Nanjing, China," Land Use Policy, Elsevier, vol. 140(C).
    2. Sorel, Luc & Viaud, Valérie & Durand, Patrick & Walter, Christian, 2010. "Modeling spatio-temporal crop allocation patterns by a stochastic decision tree method, considering agronomic driving factors," Agricultural Systems, Elsevier, vol. 103(9), pages 647-655, November.
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