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基于DIVA-GIS的紫玉兰地理分布及适生性分析 被引量:14

Analysis of the adaptive and geographical distribution of Yulania liliiflora based on DIVA-GIS
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摘要 基于39个地理分布信息和19个生物气候因子,利用BIOCLIM生态位模型对紫玉兰(Yulania liliiflora(Desr.) D. L. Fu)潜在适生区进行预测。结果显示,紫玉兰自然分布于云南、四川、贵州、湖北、甘肃、重庆、福建等地海拔300~1600 m的中低山区。当前气候条件下,贵州苗岭是其主要适生区;随着全球气候变暖(CO2浓度倍增情况下),紫玉兰的适生区有向高海拔地区收缩的趋势,而在分布区的东北界,其潜在分布范围将扩散至湖南中部和浙江东部地区。影响紫玉兰地理分布格局的重要因素是水热条件的综合效应。ROC曲线检验的AUC值(0.998)表明,采用BIOCLIM模型对紫玉兰潜在分布区的预测结果准确性较高。本研究在气候变暖的大环境下分析紫玉兰的适生性,可为紫玉兰种质资源的保护利用提供依据。 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.
作者 孙李勇 蒋政 刘晨妮 尹增芳 Sun Li-Yong;Jiang Zheng;Liu Chen-Ni;Yin Zeng-Fang(Co-Innovation Center for Sustainable Forestry in Southern China,College of Biology and the Environment,Nanjing Forestry University,Nanjing 210037,China)
机构地区 南京林业大学
出处 《植物科学学报》 CAS CSCD 北大核心 2018年第6期804-811,共8页 Plant Science Journal
基金 江苏省自然科学基金项目(BK20171451) 江苏高校优势学科建设工程项目(PAPD) 南京林业大学优秀博士学位论文创新基金项目。
关键词 紫玉兰 BIOCLIM模型 分布 气候因子 Yulania liliiflora BIOCLIM model Geographical distribution Climatic factor
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