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Spatiotemporal Evolution of Landscape Ecological Risk Based on Geomorphological Regionalization during 1980–2017: A Case Study of Shaanxi Province, China

Author

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  • Di Liu

    (College of Urban and Environmental Science, Northwest University, Xi’an 710127, China
    Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Xi’an 710127, China)

  • Hai Chen

    (College of Urban and Environmental Science, Northwest University, Xi’an 710127, China
    Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Xi’an 710127, China)

  • Hang Zhang

    (College of Urban and Environmental Science, Northwest University, Xi’an 710127, China
    Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Xi’an 710127, China)

  • Tianwei Geng

    (College of Urban and Environmental Science, Northwest University, Xi’an 710127, China
    Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Xi’an 710127, China)

  • Qinqin Shi

    (College of Urban and Environmental Science, Northwest University, Xi’an 710127, China
    Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Xi’an 710127, China)

Abstract

Land surface elements, such as land use, are in constant change and dynamically balanced, driving changes in global ecological processes and forming the regional differentiation of surface landscapes, which causes many ecological risks under multiple sources of stress. The landscape pattern index can quickly identify the disturbance caused by the vulnerability of the ecosystem itself, thus providing an effective method to support the spatial heterogeneity of landscape ecological risk. A landscape ecological risk model based on the degree of interference and fragility was constructed and spatiotemporal differentiation of risk between 1980 and 2017 in Shaanxi Province was analyzed. The spatiotemporal migration of risk was demonstrated from the perspective of geomorphological regionalization and risk gravity. Several conclusions were drawn: The risk of Shaanxi Province first increased and then decreased, at the same time, the spatial differentiation of landscape ecological risk was very significant. The ecological risk presented a significant positive correlation but the degree of autocorrelation decreased. The risk of the Qinba Mountains was low and the risk of the Guanzhong Plain and Han River basin was high. The risk of Loess Plateau and sandstorm transition zone decreased greatly and their risk gravities shifted to the southwest. The gravity of the Guanzhong Plain and Qinling Mountains had a northward trend, while the gravity of the Han River basin and Daba Mountains shifted to the southeast. In the analysis of typical regions, there were different relationships between morphological indicators and risk indexes under different geomorphological features. The appropriate engineering measures and landscape management for different geomorphological regionalization were suggested for effective reduction of ecological risks.

Suggested Citation

  • Di Liu & Hai Chen & Hang Zhang & Tianwei Geng & Qinqin Shi, 2020. "Spatiotemporal Evolution of Landscape Ecological Risk Based on Geomorphological Regionalization during 1980–2017: A Case Study of Shaanxi Province, China," Sustainability, MDPI, vol. 12(3), pages 1-16, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:3:p:941-:d:313612
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    References listed on IDEAS

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    1. Di Liu & Xiaoying Liang & Hai Chen & Hang Zhang & Nanzhao Mao, 2018. "A Quantitative Assessment of Comprehensive Ecological Risk for a Loess Erosion Gully: A Case Study of Dujiashi Gully, Northern Shaanxi Province, China," Sustainability, MDPI, vol. 10(9), pages 1-16, September.
    2. Solecka, Iga & Raszka, Beata & Krajewski, Piotr, 2018. "Landscape analysis for sustainable land use policy: A case study in the municipality of Popielów, Poland," Land Use Policy, Elsevier, vol. 75(C), pages 116-126.
    3. Peng Tian & Jialin Li & Hongbo Gong & Ruiliang Pu & Luodan Cao & Shuyao Shao & Zuoqi Shi & Xiuli Feng & Lijia Wang & Riuqing Liu, 2019. "Research on Land Use Changes and Ecological Risk Assessment in Yongjiang River Basin in Zhejiang Province, China," Sustainability, MDPI, vol. 11(10), pages 1-20, May.
    4. Focks, Andreas & ter Horst, Mechteld & van den Berg, Erik & Baveco, Hans & van den Brink, Paul J., 2014. "Integrating chemical fate and population-level effect models for pesticides at landscape scale: New options for risk assessment," Ecological Modelling, Elsevier, vol. 280(C), pages 102-116.
    5. Jialin Li & Ruiliang Pu & Hongbo Gong & Xu Luo & Mengyao Ye & Baixiang Feng, 2017. "Evolution Characteristics of Landscape Ecological Risk Patterns in Coastal Zones in Zhejiang Province, China," Sustainability, MDPI, vol. 9(4), pages 1-18, April.
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    2. Xuebin Zhang & Jiale Yu & Haoyuan Feng & Litang Yao & Xuehong Li & Hucheng Du & Yanni Liu, 2024. "Landscape Ecological Risk and Drivers of Land-Use Transition under the Perspective of Differences in Topographic Gradient," Land, MDPI, vol. 13(6), pages 1-20, June.
    3. Yanping Yang & Jianjun Chen & Yanping Lan & Guoqing Zhou & Haotian You & Xiaowen Han & Yu Wang & Xue Shi, 2022. "Landscape Pattern and Ecological Risk Assessment in Guangxi Based on Land Use Change," IJERPH, MDPI, vol. 19(3), pages 1-20, January.
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    5. Yanbo Qu & Haining Zong & Desheng Su & Zongli Ping & Mei Guan, 2021. "Land Use Change and Its Impact on Landscape Ecological Risk in Typical Areas of the Yellow River Basin in China," IJERPH, MDPI, vol. 18(21), pages 1-26, October.
    6. Wenting Chen & Yongcai Wang & Tong Li & Huawei Wan & Yuxuan Chen, 2022. "Construction of a System of Indices for Determining the Contribution of Biodiversity to Human Well-Being in the Sanjiangyuan Area: A Spatiotemporal Distribution Study," Land, MDPI, vol. 11(8), pages 1-22, July.
    7. Dong Wang & Xiang Ji & Cheng Li & Yaxi Gong, 2021. "Spatiotemporal Variations of Landscape Ecological Risks in a Resource-Based City under Transformation," Sustainability, MDPI, vol. 13(9), pages 1-21, May.

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