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引用本文:张凤琴,万广珍,胡慧芳,晋玲,陈娟*.基于最大熵模型的甘肃半夏生境适宜性评价[J].中国现代应用药学,2024,41(7):939-945.
ZHANG Fengqin,WAN Guangzhen,HU Huifang,JIN Ling,CHEN Juan*.Habitat Suitability Evaluation of Pinellia Ternata (Thunb.) Breit. in Gansu Province Based on Maximum Entropy Model[J].Chin J Mod Appl Pharm(中国现代应用药学),2024,41(7):939-945.
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基于最大熵模型的甘肃半夏生境适宜性评价
张凤琴1, 万广珍2, 胡慧芳3, 晋玲3, 陈娟*2
1.兰州市肺科医院,兰州 730000;2.兰州大学药学院,兰州 730000;3.甘肃中医药大学药学院,兰州 730000
摘要:
目的 探究半夏在甘肃省的潜在地理分布,明确其生境需求,为合理栽培提供理论依据。方法 基于100个半夏地理分布点和39个环境变量(包括19个生物气候变量、17个土壤变量和3个地形变量),利用最大熵模型(MaxEnt)和ArcGIS地理信息系统软件对其进行生境适宜性评价以及适生区划分,以刀切检验结果评价影响半夏生境的环境变量,ROC曲线下面积(AUC)评价预测结果可靠程度。结果 AUC值为0.993,表明MaxEnt模型预测结果可靠。月平均气温日较差、等温性、温度季节性变化标准差、年降水量、最湿月降水量、最干月降水量、最干季节降水量、最冷季节降水量和海拔是影响半夏生长主要环境变量。半夏在甘肃的适宜区主要集中在陇南、天水和平凉等地区,其中高适宜区、中适宜区和低适宜区的面积分别为16 180.4,15 413.96,21 204.84 km2结论 该研究结果可以为半夏资源保护和规范化栽培提供理论参考。
关键词:  半夏  MaxEnt模型  地理信息系统  适生区预测
DOI:10.13748/j.cnki.issn1007-7693.20221283
分类号:R282.7
基金项目:国家中医药管理局道地药材生态种植及质量保障项目子课题(2022030014)
Habitat Suitability Evaluation of Pinellia Ternata (Thunb.) Breit. in Gansu Province Based on Maximum Entropy Model
ZHANG Fengqin1, WAN Guangzhen2, HU Huifang3, JIN Ling3, CHEN Juan*2
1.Lanzhou Pulmonary Hospital, Lanzhou 730000, China;2.School of Pharmacy, Lanzhou University, Lanzhou 730000, China;3.College of Pharmacy, Gansu University of Chinese Medicine, Lanzhou 730000, China
Abstract:
OBJECTIVE To explore the potential geographic distribution of Pinellia Ternata (Thunb.) Breit. in Gansu province, clarify its habitat requirements, and provide a theoretical basis for rational cultivation. METHODS Based on 100 geographic distribution points of Pinellia Ternata (Thunb.) Breit. and 39 environmental variables (including 19 bioclimatic variables, 17 soil variables and 3 topographic variables), the maximum entropy model(MaxEnt) and ArcGIS geographic information system software were used to make the habitat suitable for its evaluation and classification of suitable areas, the result of Jackknife test was used to evaluate the environmental variables that affect the habitat of Pinellia Ternata (Thunb.) Breit., the area under the ROC curve(AUC) was used to evaluate the degree of reliability of the prediction results. RESULTS The AUC was 0.993, indicating that the prediction results of the MaxEnt model were reliable. Monthly average daily temperature difference, isotherm, standard deviation of seasonal variation of temperature, annual precipitation, the wettest month precipitation, the driest month precipitation, the driest season precipitation, the coldest season precipitation and altitude were the main environmental variables affecting the growth of Pinellia Ternata (Thunb.) Breit.. The suitable areas for Pinellia Ternata (Thunb.) Breit. in Gansu were mainly concentrated in Longnan, Tianshui and Pingliang, where the areas of high, medium and low suitable areas were 16 180.4, 15 413.96, 21 204.84 km2, respectively. CONCLUSION The research results can provide a theoretical reference for the protection and standardized cultivation of Pinellia Ternata (Thunb.) Breit. resources.
Key words:  Pinellia ternata (Thunb.) Breit.  MaxEnt model  geographic information system  prediction of suitable growing areas
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