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基于最大熵模型和地理信息系统地构叶生态适宜性研究 被引量:4

Study on Ecology Suitability of Speranskia tuberculata Based on MaxEnt and GIS
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摘要 目的探讨地构叶在我国的生态适宜性区划。方法利用最大熵模型和ArcGIS10.5软件对实地调查的35个地构叶分布信息数据、中国数字植物标本馆获取的172条地构叶分布信息及55种生态因子数据进行运算分析。结果调查显示,影响地构叶生长的7个主要生态因子为11月降水量、3月温度、9月降水量、温度季节性变化标准差、土壤含黏土量最干季节降水量、最干季节均温,甘肃东南部、陕西南部、山西南部、河北西南部、山东中部为地构叶的主要分布区。结论应用此方法研究地构叶生态适宜性区划具有较好的精确度和可信度,研究结果与实际分布相契合,可为地构叶野生资源勘测和保护地区的选择提供参考依据。 Objective To explore the ecological suitability of Speranskia tuberculata in China.Methods The maximum entropy model and ArcGIS10.5 software were used to analyze the 35 information data of Speranskia tuberculata in field survey,172 information data obtained in Chinese Virtual Herbarium and 55 ecological factor data.Results The results showed that the seven main ecological factors affecting Speranskia tuberculata were the rainfall in November,the temperature in March,the rainfall in September,the seasonal variation of temperature,the clay content in the soil the rainfall in driest season,and the mean temperature in driest season.The southeastern part of Gansu,the southern part of Shaanxi,the southern part of Shanxi,the southwestern part of Hebei and central Shandong were the main distribution areas of Speranskia tuberculate.Conclusion The application of this method to study the ecological suitability zoning of Speranskia tuberculata has good precision and credibility.The research results are consistent with the actual distribution,which can provide references for the selection of protection areas and wild resources survey of Speranskia tuberculata.
作者 吕蓉 韦翡翡 崔治家 晋玲 LYU Rong;WEI Feifei;CUI Zhijia;JIN Ling(College of Pharmacy,Gansu University of Chinese Medicine,Lanzhou 730000,China;Research Institute of Chinese(Tibetan)Medicinal Resources,Lanzhou 730000,China)
出处 《中国中医药信息杂志》 CAS CSCD 2020年第2期1-3,共3页 Chinese Journal of Information on Traditional Chinese Medicine
基金 中央本级重大增减支项目-名贵中药资源可持续利用能力建设(2060302) 国家中医药管理局中药饮片标准化项目(ZYBZH-Y-GS-10) 甘肃省地方药材质量标准提升研究(17ZD2FAOO9)。
关键词 地构叶 最大熵模型 生态因子 生态适宜性 地理信息系统 知识服务 Speranskia tuberculata maximum entropy model ecological factors ecological suitability ArcGIS knowledge service
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