IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i15p6331-d1441858.html
   My bibliography  Save this article

Prediction of Adaptability of Typical Vegetation Species in Flood Storage Areas under Future Climate Change: A Case in Hongze Lake FDZ, China

Author

Listed:
  • Liang Wang

    (School of Water Resources Science and Engineering, Yangzhou University, Yangzhou 225009, China)

  • Jilin Cheng

    (School of Water Resources Science and Engineering, Yangzhou University, Yangzhou 225009, China)

  • Yushan Jiang

    (School of Water Resources Science and Engineering, Yangzhou University, Yangzhou 225009, China)

  • Nian Liu

    (Suqian Water Conservancy Bureaut, Suqian 223800, China)

  • Kai Wang

    (Suqian Water Conservancy Bureaut, Suqian 223800, China)

Abstract

China experiences frequent heavy rainfall and flooding events, which have particularly increased in recent years. As flood storage zones (FDZs) play an important role in reducing disaster losses, their ecological restoration has been receiving widespread attention. Hongze Lake is an important flood discharge area in the Huaihe River Basin of China. Previous studies have preliminarily analyzed the protection of vegetation zones in the FDZ of this lake, but the future growth trend of typical vegetation in the area has not been considered as a basis for the precise protection of vegetation diversity and introductory cultivation of suitable species in the area. Taking the FDZ of Hongze Lake as an example, this study investigated the change trend of the suitability of typical vegetation species in the Hongze Lake FDZ based on future climate change and the distribution pattern of the suitable areas. To this end, the distribution of potentially suitable habitats of 20 typical vegetation species in the 2040s was predicted under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 climate scenarios using the latest Coupled Model Intercomparison Project CMIP6. The predicted distribution was compared with the current distribution of potentially suitable habitats. The results showed that the model integrating high-performance random forest, generalized linear model, boosted tree model, flexible discriminant analysis model, and generalized additive model had significantly higher TSS and AUC values than the individual models, and could effectively improve model accuracy. The high sensitivity of these 20 typical vegetation species to temperature and rainfall related factors reflects the climatic characteristics of the study area at the junction of subtropical monsoon climate and temperate monsoon climate. Under future climate scenarios, with reference to the current scenario of the 20 typical species, the suitability for Nelumbo nucifera Gaertn decreased, that for Iris pseudacorus L. increased in the western part of the study area but decreased in the eastern wetland and floodplain, and the suitability of the remaining 18 species increased. This study identified the trend of potential suitable habitat distribution and the shift in the suitability of various typical vegetation species in the floodplain of Hongze Lake. The findings are important for the future enhancement of vegetation habitat conservation and suitable planting in the study area, and have implications for the restoration and conservation of vegetation diversity in most typical floodplain areas.

Suggested Citation

  • Liang Wang & Jilin Cheng & Yushan Jiang & Nian Liu & Kai Wang, 2024. "Prediction of Adaptability of Typical Vegetation Species in Flood Storage Areas under Future Climate Change: A Case in Hongze Lake FDZ, China," Sustainability, MDPI, vol. 16(15), pages 1-22, July.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:15:p:6331-:d:1441858
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/15/6331/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/15/6331/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Forest Isbell & Andrew Gonzalez & Michel Loreau & Jane Cowles & Sandra Díaz & Andy Hector & Georgina M. Mace & David A. Wardle & Mary I. O'Connor & J. Emmett Duffy & Lindsay A. Turnbull & Patrick L. T, 2017. "Linking the influence and dependence of people on biodiversity across scales," Nature, Nature, vol. 546(7656), pages 65-72, June.
    2. Peter McCullagh, 2008. "Sampling bias and logistic models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 643-677, September.
    Full references (including those not matched with items on IDEAS)

    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. Claudia Múnera-Roldán & Dirk J. Roux & Matthew J. Colloff & Lorrae van Kerkhoff, 2020. "Beyond Calendars and Maps: Rethinking Time and Space for Effective Knowledge Governance in Protected Areas," Land, MDPI, vol. 9(9), pages 1-21, August.
    2. Sarah R. Weiskopf & Forest Isbell & Maria Isabel Arce-Plata & Moreno Di Marco & Mike Harfoot & Justin Johnson & Susannah B. Lerman & Brian W. Miller & Toni Lyn Morelli & Akira S. Mori & Ensheng Weng &, 2024. "Biodiversity loss reduces global terrestrial carbon storage," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    3. Jingfeng Zhu & Ning Ding & Dehuan Li & Wei Sun & Yujing Xie & Xiangrong Wang, 2020. "Spatiotemporal Analysis of the Nonlinear Negative Relationship between Urbanization and Habitat Quality in Metropolitan Areas," Sustainability, MDPI, vol. 12(2), pages 1-20, January.
    4. Trishita Mondal & Wade W. Bowers & Md Hossen Ali, 2024. "Sustainable Management of Sundarbans: Stakeholder Attitudes Towards Participatory Management and Conservation of Mangrove Forests," Journal of Sustainable Development, Canadian Center of Science and Education, vol. 14(3), pages 1-23, July.
    5. Yu-Pin Lin & Chi-Ju Chen & Wan-Yu Lien & Wen-Hao Chang & Joy R. Petway & Li-Chi Chiang, 2019. "Landscape Conservation Planning to Sustain Ecosystem Services under Climate Change," Sustainability, MDPI, vol. 11(5), pages 1-18, March.
    6. Pires, Aliny P.F. & Amaral, Aryanne G. & Padgurschi, Maíra C.G. & Joly, Carlos A. & Scarano, Fabio R., 2018. "Biodiversity research still falls short of creating links with ecosystem services and human well-being in a global hotspot," Ecosystem Services, Elsevier, vol. 34(PA), pages 68-73.
    7. Jing Ning & Jing Qin & Yu Shen, 2010. "Non‐parametric tests for right‐censored data with biased sampling," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(5), pages 609-630, November.
    8. Rafael Melo de Brito & Valente José Matlaba & Vera Lúcia Imperatriz-Fonseca & Tereza Cristina Giannini, 2020. "Perception of Nature’s Contributions to People in Rural Communities in the Eastern Amazon," Sustainability, MDPI, vol. 12(18), pages 1-21, September.
    9. Garibaldi, Lucas A. & Pérez-Méndez, Néstor, 2019. "Positive outcomes between crop diversity and agricultural employment worldwide," Ecological Economics, Elsevier, vol. 164(C), pages 1-1.
    10. Schutter, Marleen S. & Hicks, Christina C. & Phelps, Jacob & Belmont, Clara, 2021. "Disentangling ecosystem services preferences and values," World Development, Elsevier, vol. 146(C).
    11. Wang, Chengdong & Wang, Yutao & Tong, Xin & Ulgiati, Sergio & Liang, Sai & Xu, Ming & Wei, Wendong & Li, Xiao & Jin, Mingzhou & Mao, Jiafu, 2020. "Mapping potentials and bridging regional gaps of renewable resources in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    12. 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.
    13. repec:eee:ecoser:v:37:y:2019:i:c:p:- is not listed on IDEAS
    14. Richard Morris & Shannon Davis & Gwen-Aëlle Grelet & Crile Doscher & Pablo Gregorini, 2024. "A Model for Spatially Explicit Landscape Configuration and Ecosystem Service Performance, ESMAX: Model Description and Explanation," Sustainability, MDPI, vol. 16(2), pages 1-23, January.
    15. Moritz von Cossel & Yasir Iqbal & Iris Lewandowski, 2019. "Improving the Ecological Performance of Miscanthus ( Miscanthus × giganteus Greef et Deuter) through Intercropping with Woad ( Isatis tinctoria L.) and Yellow Melilot ( Melilotus officinalis L.)," Agriculture, MDPI, vol. 9(9), pages 1-12, September.
    16. Indunee Welivita & Simon Willcock & Amy Lewis & Dilshaad Bundhoo & Tim Brewer & Sarah Cooper & Kenneth Lynch & Sneha Mekala & Prajna Paramita Mishra & Kongala Venkatesh & Dolores Rey Vicario & Paul Hu, 2021. "Evidence of Similarities in Ecosystem Service Flow across the Rural-Urban Spectrum," Land, MDPI, vol. 10(4), pages 1-38, April.
    17. Kwadwo Kyenkyehene Kusi & Abdellatif Khattabi & Nadia Mhammdi, 2023. "Analyzing the impact of land use change on ecosystem service value in the main watersheds of Morocco," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(3), pages 2688-2715, March.
    18. Peter J. Diggle & Raquel Menezes & Ting‐li Su, 2010. "Geostatistical inference under preferential sampling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(2), pages 191-232, March.
    19. Minglu Hu & Xinghao Lu & Yuncai Wang, 2024. "The Effects of Spatial Structure and Development Intensity of the Urban Landscape on Bird Biodiversity in Anhui Province," Land, MDPI, vol. 13(10), pages 1-18, October.
    20. Massimiliano Scopelliti & Daniela Barni & Elena Rinallo, 2022. "My Parents Taught…Green Was My Growth! The Role of Intergenerational Transmission of Ecological Values in Young Adults’ Pro-Environmental Behaviors and Their Psychosocial Mechanisms," IJERPH, MDPI, vol. 19(3), pages 1-23, February.
    21. Cepic, Michael & Bechtold, Ulrike & Wilfing, Harald, 2022. "Modelling human influences on biodiversity at a global scale–A human ecology perspective," Ecological Modelling, Elsevier, vol. 465(C).

    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:jsusta:v:16:y:2024:i:15:p:6331-:d:1441858. 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.