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Plant Diversity ›› 2014, Vol. 36 ›› Issue (02): 237-244.DOI: 10.7677/ynzwyj201413086

• 研究论文 • 上一篇    下一篇


 龚晔1, 景鹏飞1, 魏宇昆2, 黄卫昌2, 崔浪军1   

  1. 1 药用植物资源与天然药物化学教育部重点实验室,陕西师范大学生命科学学院,
    陕西 西安710010;2 上海辰山植物园,上海201602
  • 收稿日期:2013-04-12 出版日期:2014-03-25 发布日期:2013-07-10
  • 基金资助:


Potential Distribution of Bletilla striata (Orchidaceae) in China and Its Climate Characteristics

 GONG  Ye-1, JING  Peng-Fei-1, WEI  Yu-Kun-2, HUANG  Wei-Chang-2, CUI  Lang-Jun-1   

  1. 1 Key Laboratory of Medicinal Plant Resources and Natural Pharmaceutical Chemistry (Shaanxi Normal University),
    Ministry of Education, Xi’an 710010, China; 2 Chenshan Botanical Gargen, Shanghai 201602, China
  • Received:2013-04-12 Online:2014-03-25 Published:2013-07-10
  • Supported by:



基于白及(Bletilla striata)地理分布信息和影响白及分布的主导气象因子,利用最大熵模型和地理信息系统预测了中国白及的潜在分布与其气候特征。结果表明:所建模型经ROC曲线验证,预测效果非常好(AUC > 09);中国白及潜在分布区主要位于秦岭、淮河以南大部分地区,白及主要适生省份为云南、湖北、四川、湖南、江西、浙江;刀切法测试表明,4月和10月最低气温、年温度变化范围、11月平均降水量为影响白及潜在分布的最主要气象因子。研究结果可为白及资源的调查、保护与人工种植产业的发展提供理论指导。

关键词: 白及, 最大熵模型, 地理信息系统, 潜在分布, 气象因子


The potential distribution of Bletilla striata and its climate characteristics was predicted with MaxEnt model and ArcGIS. The data was based on the information of geographic distribution of the plant and its dominant climate factors. The results showed that the model built by dominant climate factors had an ideal forecasting effect, which was tested by the ROC curve (AUC > 09). The model revealed that the potential distribution areas were mainly in the south of the Qinling Mountains and Huai river. The major suitable provinces for the plant were mainly restricted to Yunnan, Hubei, Sichuan, Hunan and Jiangxi. A jackknife test in MaxEnt suggested that Min temperature of Apr(tmin4), Min temperature of  Oct (tmin10), Temperature annual range (bio7) and Precipitation of Nov (prc11) were the most important climate variables affecting the potential distribution of the plant. The results can provide some theoretical basis for the resources protection, germplasm collections and reasonable development and utilization of wild Bletilla striata.

Key words: Bletilla striata, MaxEnt model, ArcGIS, Climate factors, Potential distribution