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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
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    References listed on IDEAS

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    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.
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    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.

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