IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i8p4920-d796467.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/8/4920/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/8/4920/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Alberto Abadie & Guido W. Imbens, 2016. "Matching on the Estimated Propensity Score," Econometrica, Econometric Society, vol. 84, pages 781-807, March.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Miao He & An Cliquet, 2020. "Challenges for Protected Areas Management in China," Sustainability, MDPI, vol. 12(15), pages 1-29, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xu, Xibao & Jiang, Bo & Chen, Minkun & Bai, Yang & Yang, Guishan, 2020. "Strengthening the effectiveness of nature reserves in representing ecosystem services: The Yangtze River Economic Belt in China," Land Use Policy, Elsevier, vol. 96(C).
    2. Irene Bertschek & Joern Block & Alexander S. Kritikos & Caroline Stiel, 2024. "German financial state aid during Covid-19 pandemic: Higher impact among digitalized self-employed," Entrepreneurship & Regional Development, Taylor & Francis Journals, vol. 36(1-2), pages 76-97, January.
    3. Zhipeng Tang & Ziao Mei & Jialing Zou, 2021. "Does the Opening of High-Speed Railway Lines Reduce the Carbon Intensity of China’s Resource-Based Cities?," Energies, MDPI, vol. 14(15), pages 1-18, July.
    4. Parvaneh Sobhani & Hassan Esmaeilzadeh & Seyed Mohammad Moein Sadeghi & Marina Viorela Marcu, 2022. "Estimation of Ecotourism Carrying Capacity for Sustainable Development of Protected Areas in Iran," IJERPH, MDPI, vol. 19(3), pages 1-19, January.
    5. Cuong Van Hoang & Tuyen Quang Tran & Yen Hai Thi Nguyen & Lan Thanh Nguyen, 2020. "Forest resources and household welfare: Empirical evidence from North Central Vietnam," Natural Resources Forum, Blackwell Publishing, vol. 44(4), pages 311-333, November.
    6. Ghisetti, Claudia, 2017. "Demand-pull and environmental innovations: Estimating the effects of innovative public procurement," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 178-187.
    7. Fan, Xiaomin & Xu, Yingzhi, 2023. "Does high-speed railway promote urban innovation? Evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    8. Frida Carmina Caballero-Rico & Ramón Ventura Roque-Hernández & Ricardo de la Garza Cano & Eduardo Arvizu-Sánchez, 2022. "Challenges for the Integrated Management of Priority Areas for Conservation in Tamaulipas, México," Sustainability, MDPI, vol. 14(1), pages 1-28, January.
    9. Nicolas Moreau, 2018. "A SAS macro to estimate Average Treatment Effects with Propensity Score Matching," Working Papers hal-01691528, HAL.
    10. Müller, Tobias & Schmid, Christian & Gerfin, Michael, 2023. "Rents for Pills: Financial incentives and physician behavior," Journal of Health Economics, Elsevier, vol. 87(C).
    11. Mörk, Eva & Sjögren, Anna & Svaleryd, Helena, 2019. "Consequences of Parental Job Loss on the Family Environment and on Human Capital Formation: Evidence from Plant Closures," IZA Discussion Papers 12559, Institute of Labor Economics (IZA).
    12. Hünermund, Paul & Czarnitzki, Dirk, 2019. "Estimating the causal effect of R&D subsidies in a pan-European program," Research Policy, Elsevier, vol. 48(1), pages 115-124.
    13. Luo, Yu & Graham, Daniel J. & McCoy, Emma J., 2023. "Semiparametric Bayesian doubly robust causal estimation," LSE Research Online Documents on Economics 117944, London School of Economics and Political Science, LSE Library.
    14. Anabela Santos & Michele Cincera & Paulo Neto & Maria Manuel Serrano, 2019. "How internationalization and competitiveness contribute to get public support to innovation? The Portuguese case," GEE Papers 0121, Gabinete de Estratégia e Estudos, Ministério da Economia, revised May 2019.
    15. Susan Athey & Raj Chetty & Guido Imbens, 2020. "Combining Experimental and Observational Data to Estimate Treatment Effects on Long Term Outcomes," Papers 2006.09676, arXiv.org.
    16. Dragana Radicic & Geoffrey Pugh & David Douglas, 2020. "Promoting cooperation in innovation ecosystems: evidence from European traditional manufacturing SMEs," Small Business Economics, Springer, vol. 54(1), pages 257-283, January.
    17. Li Liang & Greene Tom, 2013. "A Weighting Analogue to Pair Matching in Propensity Score Analysis," The International Journal of Biostatistics, De Gruyter, vol. 9(2), pages 215-234, July.
    18. Andr'es Ram'irez-Hassan & Raquel Vargas-Correa & Gustavo Garc'ia & Daniel Londo~no, 2020. "Optimal selection of the number of control units in kNN algorithm to estimate average treatment effects," Papers 2008.06564, arXiv.org.
    19. Brian J. Reich & Shu Yang & Yawen Guan & Andrew B. Giffin & Matthew J. Miller & Ana Rappold, 2021. "A Review of Spatial Causal Inference Methods for Environmental and Epidemiological Applications," International Statistical Review, International Statistical Institute, vol. 89(3), pages 605-634, December.
    20. Mark A. C. Kattenberg & Wolter H. J. Hassink, 2017. "Who Moves Out of Social Housing? The Effect of Rent Control on Housing Tenure Choice," De Economist, Springer, vol. 165(1), pages 43-66, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:8:p:4920-:d:796467. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.