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Predicting the Potential Distribution of Hylomecon japonica in China under Current and Future Climate Change Based on Maxent Model

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  • Zhen Cao

    (School of Pharmacy, Xi’an Jiaotong University, Xi’an 710061, China
    Shaanxi Traditional Chinese Medicine Extracts Engineering Technology Research Center, Xi’an 710061, China
    Shaanxi Key Laboratory of “Qiyao” Resources and Anti-Tumor Activities, Xi’an 710061, China)

  • Lei Zhang

    (School of Pharmacy, Xi’an Jiaotong University, Xi’an 710061, China
    Shaanxi Traditional Chinese Medicine Extracts Engineering Technology Research Center, Xi’an 710061, China
    Shaanxi Key Laboratory of “Qiyao” Resources and Anti-Tumor Activities, Xi’an 710061, China)

  • Xinxin Zhang

    (School of Pharmacy, Xi’an Jiaotong University, Xi’an 710061, China
    Shaanxi Traditional Chinese Medicine Extracts Engineering Technology Research Center, Xi’an 710061, China
    Shaanxi Key Laboratory of “Qiyao” Resources and Anti-Tumor Activities, Xi’an 710061, China)

  • Zengjun Guo

    (School of Pharmacy, Xi’an Jiaotong University, Xi’an 710061, China
    Shaanxi Traditional Chinese Medicine Extracts Engineering Technology Research Center, Xi’an 710061, China
    Shaanxi Key Laboratory of “Qiyao” Resources and Anti-Tumor Activities, Xi’an 710061, China)

Abstract

Hylomecon japonica is considered a natural medicinal plant with anti-inflammatory, anticancer and antibacterial activity. The assessment of climate change impact on its habitat suitability is important for the wild cultivation and standardized planting of H. japonica . In this study, the maximum entropy model (Maxent) and geographic information system (ArcGIS) were applied to predict the current and future distribution of H. japonica species, and the contributions of variables were evaluated by using the jackknife test. The area under the receiver operating characteristic curve (AUC) value confirmed the accuracy of the model prediction based on 102 occurrence records. The predicted potential distributions of H. japonica were mainly concentrated in Jilin, Liaoning, Shaanxi, Chongqing, Henan, Heilongjiang and other provinces (adaptability index > 0.6). The jackknife experiment showed that the precipitation of driest month (40.5%), mean annual temperature (12.4%), the precipitation of wettest quarter (11.6%) and the subclass of soil (9.7%) were the most important factors affecting the potential distribution of H. japonica . In the future, only under the shared socioeconomic Pathway 245 (SSP 245) scenario model in 2061–2080, the suitable habitat area for H. japonica is expected to show a significant upward trend. The area under other scenarios may not increase or decrease significantly.

Suggested Citation

  • Zhen Cao & Lei Zhang & Xinxin Zhang & Zengjun Guo, 2021. "Predicting the Potential Distribution of Hylomecon japonica in China under Current and Future Climate Change Based on Maxent Model," Sustainability, MDPI, vol. 13(20), pages 1-14, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:20:p:11253-:d:654564
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    References listed on IDEAS

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    1. Yining Ma & Xiaoling Lu & Kaiwei Li & Chunyi Wang & Ari Guna & Jiquan Zhang, 2021. "Prediction of Potential Geographical Distribution Patterns of Actinidia arguta under Different Climate Scenarios," Sustainability, MDPI, vol. 13(6), pages 1-14, March.
    2. Terry L. Root & Jeff T. Price & Kimberly R. Hall & Stephen H. Schneider & Cynthia Rosenzweig & J. Alan Pounds, 2003. "Fingerprints of global warming on wild animals and plants," Nature, Nature, vol. 421(6918), pages 57-60, January.
    3. Li, Su-Yuan & Miao, Li-Juan & Jiang, Zhi-Hong & Wang, Guo-Jie & Gnyawali, Kaushal Raj & Zhang, Jing & Zhang, Hui & Fang, Ke & He, Yu & Li, Chun, 2020. "Projected drought conditions in Northwest China with CMIP6 models under combined SSPs and RCPs for 2015–2099," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 11(3), pages 210-217.
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