中国中医药信息杂志2025，Vol.32Issue(1)：12-17,6.DOI:10.19879/j.cnki.1005-5304.202405560
基于最大熵模型和地理信息系统的白头翁生态适宜性区划研究
Study on Ecological Suitability Distribution of Pulsatilla chinensis(Bge.)Regel Based on MaxEnt Model and GIS
摘要
Abstract
Objective To explore the environmental factors influencing the distribution of Pulsatilla chinensis(Bge.)Regel and to predict its potential habitat in China;To provide reference for the assessment of its wild resources and the introduction of its cultivation.Methods Totally 230 pieces of information on the distribution of sample sites were collected.Combined with data of 48 environmental factors,MaxEnt model and ArcGIS 10.8 software were used to select the dominant environmental factors that affect their distribution,and visual analysis of potential suitable areas was conducted.Results The prediction accuracy of the established model met the requirements(AUC＞0.9).The main environmental factors affecting the distribution of Pulsatilla chinensis(Bge.)Regel were the precipitation in the wettest season,the average temperature in November,the altitude,the standard deviation of the seasonal variation of temperature,the precipitation in May and the average temperature in August,with a cumulative contribution rate of 84.3％.The prediction results showed that it was mainly distributed in the North China and Northeast China,with a total suitability zone of about 2 382 461.60 km2,of which the low suitability zone was about 1 263 497.00 km2,the medium suitability zone was about 582 879.20 km2,and the high suitability zone was about 536 085.40 km2,accounting for approximately 53.03％,24.47％and 22.50％of the total suitability zone.Conclusion The results of the model are consistent with the literature records,which can provide theoretical reference for the sustainable utilization of Pulsatilla chinensis(Bge.)Regel.resources.关键词
白头翁/地理信息系统/最大熵模型/生态适宜性区划Key words
Pulsatilla chinensis(Bge.)Regel/GIS/MaxEnt model/ecological suitability distribution分类
医药卫生引用本文复制引用
吴莹莹,汪英俊,廖延武,刘顺..基于最大熵模型和地理信息系统的白头翁生态适宜性区划研究[J].中国中医药信息杂志,2025,32(1):12-17,6.基金项目
江苏省自然科学基金(BK20211395) （BK20211395）
