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Sun Li-Yong, Jiang Zheng, Liu Chen-Ni, Yin Zeng-Fang. Analysis of the adaptive and geographical distribution of Yulania liliiflora based on DIVA-GIS[J]. Plant Science Journal, 2018, 36(6): 804-811. DOI: 10.11913/PSJ.2095-0837.2018.60804
Citation: Sun Li-Yong, Jiang Zheng, Liu Chen-Ni, Yin Zeng-Fang. Analysis of the adaptive and geographical distribution of Yulania liliiflora based on DIVA-GIS[J]. Plant Science Journal, 2018, 36(6): 804-811. DOI: 10.11913/PSJ.2095-0837.2018.60804
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Analysis of the adaptive and geographical distribution of Yulania liliiflora based on DIVA-GIS

  • Co-Innovation Center for Sustainable Forestry in Southern China, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China

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This work was supported by grants from the Natural and Science Foundation of Jiangsu Province (BK20171451), Priority Academic Program Development of Jiangsu Higher Education Institutions, and Excellent Doctoral Dissertation Innovation Foundation of Nanjing Forestry University.

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  • Received Date: June 20, 2018
  • Available Online: October 31, 2022
  • Published Date: December 27, 2018
    Graphical Abstract
    • Abstract
  • Based on 39 geographical distributions and 19 bio-climatic factors, the potential distribution regions of Yulania liliiflora (Desr.) D. L. Fu were predicted using the BIOCLIM model. Results showed that natural populations were distributed in Yunnan, Sichuan, Guizhou, Hubei, Gansu, Chongqing, and Fujian provinces, mainly within elevations ranging from 300 m to 1600 m. Under the present climatic conditions, the most suitable region was the Miaoling Mountains in Guizhou Province. Based on future global warming (with double CO2 concentrations), the potential distribution regions of Y. liliiflora should contract to higher altitudes but spread to central Hunan and eastern Zhejiang along the northeast boundary. Hydrothermal conditions (e.g., heat and moisture) significantly affected the geographical distribution pattern of Y. liliiflora. Results forecasted through the BIOCLIM model demonstrated high accuracy according to ROC curve analysis, which showed a high AUC value (0.998). In the context of global warming, our analysis on the adaptability of Y. liliiflora should provide a good basis for the protection and utilization of germplasm resources.
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    • References (31)
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