IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i14p11035-d1194120.html
   My bibliography  Save this article

Estimation of Potential Suitable Habitats for the Relict Plant Euptelea pleiosperma in China via Comparison of Three Niche Models

Author

Listed:
  • Huayong Zhang

    (Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing 102206, China)

  • Shuang Zheng

    (Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing 102206, China)

  • Tousheng Huang

    (Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing 102206, China)

  • Jiangnan Liu

    (Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing 102206, China)

  • Junjie Yue

    (Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing 102206, China)

Abstract

Climate change has a significant impact on species distribution, especially for the relict plants. Euptelea pleiosperma is a type of tertiary relict plant. This plant shows a decreasing trend in population size, and it is on the edge of extinction given the background of climate change. Understanding the change in suitable habitats of E. pleiosperma will provide significant academic value for investigating species conservation and sustainable development. According to the 236 distribution records of E. pleiosperma in China, and 11 environmental factors, the optimal model was selected from MaxEnt, BIOCLIM, and DOMAIN models, aiming to estimate the future potential suitable habitats and exploring the major environmental factors influencing the distribution of E. pleiosperma . By comparison, the BIOCLIM model was the optimal for estimation, since it achieved the highest precision and the lowest standard error. Our results demonstrated that temperature was the most important factor affecting the suitable habitats of E. pleiosperma , followed by precipitation and altitude. Under the medium- and high-emission scenarios, the future suitable habitats of E. pleiosperma will migrate northward to the high-latitude areas, whereas those under the low-emission scenario will migrate southward to the low-latitude areas. During 2041–2060, the suitable habitat areas will present a positive trend, while those during 2081–2100 will exhibit a negative trend to varying degrees. Consistent with the above results, it is advisable to establish natural reserves and seed resource banks of E. pleiosperma in the current high suitability areas, as well as to provide artificial assistance to guide its migration to the high suitability areas under the future climate scenarios. The findings in this research not only reveal the response of suitable habitats of E. pleiosperma to climate change but also lay a reliable foundation for its population resource conservation and sustainable development.

Suggested Citation

  • Huayong Zhang & Shuang Zheng & Tousheng Huang & Jiangnan Liu & Junjie Yue, 2023. "Estimation of Potential Suitable Habitats for the Relict Plant Euptelea pleiosperma in China via Comparison of Three Niche Models," Sustainability, MDPI, vol. 15(14), pages 1-22, July.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:11035-:d:1194120
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/14/11035/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/14/11035/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Seungbum Hong & Inyoung Jang & Daegeun Kim & Suhwan Kim & Hyun Su Park & Kyungeun Lee, 2022. "Predicting Potential Habitat Changes of Two Invasive Alien Fish Species with Climate Change at a Regional Scale," Sustainability, MDPI, vol. 14(10), pages 1-12, May.
    2. David Spurgeon, 2000. "Global warming threatens extinction for many species," Nature, Nature, vol. 407(6801), pages 121-121, September.
    3. Alexander Ly & Maarten Marsman & Eric†Jan Wagenmakers, 2018. "Analytic posteriors for Pearson's correlation coefficient," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(1), pages 4-13, February.
    4. Ren-Yan Duan & Xiao-Quan Kong & Min-Yi Huang & Wei-Yi Fan & Zhi-Gao Wang, 2014. "The Predictive Performance and Stability of Six Species Distribution Models," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-8, November.
    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. Huayong Zhang & Hang Yuan & Hengchao Zou & Xinyu Zhu & Yihe Zhang & Zhongyu Wang & Zhao Liu, 2024. "Global Warming Drives Expansion of Endangered Spruce Forest on the Tibetan Plateau," Sustainability, MDPI, vol. 16(5), pages 1-16, March.

    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. Steen, Bart & Broennimann, Olivier & Maiorano, Luigi & Guisan, Antoine, 2024. "How sensitive are species distribution models to different background point selection strategies? A test with species at various equilibrium levels," Ecological Modelling, Elsevier, vol. 493(C).
    2. Lu, Yongquan & Liu, Guilin & Xian, Yuyang & Tang, Jiaqi & Zhong, Liming, 2024. "Climate change brings both opportunities and challenges to rural revitalization in China: Evidence from apple geographical indication predictions," Agricultural Systems, Elsevier, vol. 216(C).
    3. Cheng Jin & Zhifeng Jia & Ge Li & Lingke Zhao & Yuze Ren, 2024. "Effect of Soil Moisture Content on Condensation Water in Typical Loess and Sandy Soil," Land, MDPI, vol. 13(7), pages 1-16, June.
    4. Santiago José Elías Velazco & Franklin Galvão & Fabricio Villalobos & Paulo De Marco Júnior, 2017. "Using worldwide edaphic data to model plant species niches: An assessment at a continental extent," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-24, October.
    5. Zhiyun Zhou & Haoling Liao & Hua Li, 2023. "The Symbiotic Mechanism of the Influence of Productive and Transactional Agricultural Social Services on the Use of Soil Testing and Formula Fertilization Technology by Tea Farmers," Agriculture, MDPI, vol. 13(9), pages 1-26, August.
    6. Morales Martínez, Jorge Luis & Segovia-Domínguez, Ignacio & Rodríguez, Israel Quiros & Horta-Rangel, Francisco Antonio & Sosa-Gómez, Guillermo, 2021. "A modified Multifractal Detrended Fluctuation Analysis (MFDFA) approach for multifractal analysis of precipitation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    7. Shugang Li & Hui Chen & Xin Liu & Jiayi Li & Kexin Peng & Ziming Wang, 2023. "Online Personalized Learning Path Recommendation Based on Saltatory Evolution Ant Colony Optimization Algorithm," Mathematics, MDPI, vol. 11(13), pages 1-19, June.
    8. Pecchi, Matteo & Marchi, Maurizio & Burton, Vanessa & Giannetti, Francesca & Moriondo, Marco & Bernetti, Iacopo & Bindi, Marco & Chirici, Gherardo, 2019. "Species distribution modelling to support forest management. A literature review," Ecological Modelling, Elsevier, vol. 411(C).
    9. Jan Altman & Kerstin Treydte & Vit Pejcha & Tomas Cerny & Petr Petrik & Miroslav Srutek & Jong-Suk Song & Valerie Trouet & Jiri Dolezal, 2020. "Tree growth response to recent warming of two endemic species in Northeast Asia," Climatic Change, Springer, vol. 162(3), pages 1345-1364, October.
    10. João Vitor Leme & Wallace Casaca & Marilaine Colnago & Maurício Araújo Dias, 2020. "Towards Assessing the Electricity Demand in Brazil: Data-Driven Analysis and Ensemble Learning Models," Energies, MDPI, vol. 13(6), pages 1-20, March.
    11. Jian Chen & Jiajun Zhu & Xu Qin & Wenxiang Xie, 2023. "Reducing Octane Number Loss in Gasoline Refining Process by Using the Improved Sparrow Search Algorithm," Sustainability, MDPI, vol. 15(8), pages 1-21, April.
    12. Karen E DeMatteo & Miguel A Rinas & Juan Pablo Zurano & Nicole Selleski & Rosio G Schneider & Carina F Argüelles, 2017. "Using niche-modelling and species-specific cost analyses to determine a multispecies corridor in a fragmented landscape," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-22, August.
    13. Jianwei Bu & Ziyong Sun & Rui Ma & Yunde Liu & Xulong Gong & Zhao Pan & Wenhao Wei, 2020. "Shallow Groundwater Quality and Its Controlling Factors in the Su-Xi-Chang Region, Eastern China," IJERPH, MDPI, vol. 17(4), pages 1-18, February.
    14. Ana Cristina Mosebo Fernandes & Rebeca Quintero Gonzalez & Marie Ann Lenihan-Clarke & Ezra Francis Leslie Trotter & Jamal Jokar Arsanjani, 2020. "Machine Learning for Conservation Planning in a Changing Climate," Sustainability, MDPI, vol. 12(18), pages 1-28, September.

    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:15:y:2023:i:14:p:11035-:d:1194120. 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.