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Assessment of the Ecological Protection Effectiveness of Protected Areas Using Propensity Score Matching: A Case Study in Sichuan, China

Author

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  • Zhifeng Zhang

    (Key Laboratory of Land Resources Evaluation and Monitoring in Southwest, Ministry of Education, Chengdu 610068, China
    The Faculty of Geography and Resources Sciences, Sichuan Normal University, Chengdu 610068, China)

  • Yuping Tang

    (Key Laboratory of Land Resources Evaluation and Monitoring in Southwest, Ministry of Education, Chengdu 610068, China
    The Faculty of Geography and Resources Sciences, Sichuan Normal University, Chengdu 610068, China)

  • Hongyi Pan

    (Key Laboratory of Land Resources Evaluation and Monitoring in Southwest, Ministry of Education, Chengdu 610068, China
    The Faculty of Geography and Resources Sciences, Sichuan Normal University, Chengdu 610068, China)

  • Caiyi Yao

    (Key Laboratory of Land Resources Evaluation and Monitoring in Southwest, Ministry of Education, Chengdu 610068, China
    The Faculty of Geography and Resources Sciences, Sichuan Normal University, Chengdu 610068, China)

  • Tianyi Zhang

    (Key Laboratory of Land Resources Evaluation and Monitoring in Southwest, Ministry of Education, Chengdu 610068, China
    The Faculty of Geography and Resources Sciences, Sichuan Normal University, Chengdu 610068, China)

Abstract

Protected areas constitute a global strategic resource for enhancing the effectiveness of ecological protection, which can alleviate the impact of unsustainable human production and living activities on the ecological environment. However, the spatiotemporal evolution of ecological protection effectiveness needs to be quantitatively revealed. The net primary productivity (NPP) of plants is an important measure of the effectiveness of ecological protection efforts. The main purpose of this study is to use the relative change in the annual average NPP to evaluate the ecological protection effectiveness of protected areas. We compared the historical changes in the annual average NPP of protected areas in Sichuan Province from 2000 to 2019. We added the spatial coordinates to the impact factor system and adopted propensity score matching (PSM) in a quasi-natural experimental method to determine the experimental group and the control group. The ecological protection effectiveness of the protected areas in the study area in 2000, 2005, 2010, 2015, and 2019 was measured and classified into three types of changes in protection effectiveness, namely effective, ineffective, or fluctuating. According to the administrative level, type, and spatial distribution, we determined the number and type of changes in the protection effectiveness of different protected areas. The results show that the annual average NPP of the protected areas in Sichuan Province generally fluctuated. The annual average NPP increased in 95.47% of the total protected area and decreased in 4.53%. The overall protection effectiveness of protected areas was positive and significant and gradually improved. Effective protected areas at the national, provincial, and county levels accounted for 40.27% of the total number of protected areas, and the other 14.77% of effective protected area was managed at other administrative levels. Among the different types of protected areas, the proportion of effective protected areas was highest in wild animal protected areas, followed by forest ecology protected areas, wild plant protected areas, and wetland ecology protected areas. The results of this study can provide an important reference for the verification and improvement of the ecological protection effectiveness of various protected areas.

Suggested Citation

  • Zhifeng Zhang & Yuping Tang & Hongyi Pan & Caiyi Yao & Tianyi Zhang, 2022. "Assessment of the Ecological Protection Effectiveness of Protected Areas Using Propensity Score Matching: A Case Study in Sichuan, China," IJERPH, MDPI, vol. 19(8), pages 1-15, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:8:p:4920-:d:796467
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    References listed on IDEAS

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    1. Alberto Abadie & Guido W. Imbens, 2016. "Matching on the Estimated Propensity Score," Econometrica, Econometric Society, vol. 84, pages 781-807, March.
    2. A. S. MacDougall & K. S. McCann & G. Gellner & R. Turkington, 2013. "Diversity loss with persistent human disturbance increases vulnerability to ecosystem collapse," Nature, Nature, vol. 494(7435), pages 86-89, February.
    3. Song, Zhenjiang & Zhou, Wei & Gao, Lan, 2021. "Development of Giant Panda Nature Reserves in China: Achievements and Problems," Journal of Forest Economics, now publishers, vol. 36(1-2), pages 1-25, February.
    4. O'Neill, Daniel W. & Abson, David J., 2009. "To settle or protect? A global analysis of net primary production in parks and urban areas," Ecological Economics, Elsevier, vol. 69(2), pages 319-327, December.
    5. Wu, Jian & Gong, Yazhen & Wu, JunJie, 2018. "Spatial distribution of nature reserves in China: Driving forces in the past and conservation challenges in the future," Land Use Policy, Elsevier, vol. 77(C), pages 31-42.
    6. Yanovitzky, Itzhak & Zanutto, Elaine & Hornik, Robert, 2005. "Estimating causal effects of public health education campaigns using propensity score methodology," Evaluation and Program Planning, Elsevier, vol. 28(2), pages 209-220, May.
    7. Ben Ma & Yuqian Zhang & Yilei Hou & Yali Wen, 2020. "Do Protected Areas Matter? A Systematic Review of the Social and Ecological Impacts of the Establishment of Protected Areas," IJERPH, MDPI, vol. 17(19), pages 1-13, October.
    8. Rao, Yongheng & Zhang, Jianjun & Wang, Ke & Wu, Xia, 2019. "How to prioritize protected areas: A novel perspective using multidimensional land use characteristics," Land Use Policy, Elsevier, vol. 83(C), pages 1-12.
    9. Bernard W T Coetzee & Kevin J Gaston & Steven L Chown, 2014. "Local Scale Comparisons of Biodiversity as a Test for Global Protected Area Ecological Performance: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-11, August.
    10. Miao He & An Cliquet, 2020. "Challenges for Protected Areas Management in China," Sustainability, MDPI, vol. 12(15), pages 1-29, July.
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    1. Jian Chen & Hong Shi & Xin Wang & Yiduo Zhang & Zihan Zhang, 2022. "Effectiveness of China’s Protected Areas in Mitigating Human Activity Pressure," IJERPH, MDPI, vol. 19(15), pages 1-16, July.

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