Prediction of potential distribution of Schisandra chinensis and Schisandra sphenanthera based on MaxEnt model and analysis of its important influencing factors

doi:10.14088/j.cnki.issn0439-8114.2024.01.021

Abstract

Abstract: Based on the geographical distribution records of 184 Schisandra sphenanthera, 129 Schisandra chinensis and 23 environmental factors, the maximum entropy （MaxEnt） ecological niche model was used to predict the potential suitable distribution areas of Schisandra sphenanthera and Schisandra chinensis. The main environmental factors restricting their geographical distribution were evaluated. The results showed that the area under the curve （AUC） of the training set and verification set of MaxEnt model of Schisandra chinensis and Schisandra sphenanthera were both greater than 0.90, and the prediction results of established models were accurate. The best habitats of Schisandra chinensis were mainly distributed in Changbai Mountain area of Liaoning Province and Jilin Province and Beijing City. The best habitats of Schisandra sphenanthera mainly distributed in Qinba Mountain area, Wuling Mountain Range of Hunan Province, Chenzhou City, Zhuzhou City and Hengyang City, Jinhua City of Zhejiang Province and other areas. The important environmental factors limiting the growth of Schisandra chinensis were precipitation in the wettest month, maximum temperature in the hottest month, soil pH, average precipitation in the warmest season, average precipitation in the coldest season and the monthly mean temperature difference between day and night. The environmental factors limiting the distribution of Schisandra sphenanthera were the lowest temperature in the coldest month, the average annual precipitation, the variance of temperature change and the variance of precipitation change. The potentially suitable areas of Schisandra sphenanthera and Schisandra chinensis showed regional distribution.

Key words: Schisandra chinensis, Schisandra sphenanthera, MaxEnt model, potential distribution, environmental factor

CLC Number:

S567.5

ZHANG Di, XUE Ming-ke, LIU Ming, SHANG Xiao-feng, ZHANG Xu-tong, LIU Jin-na. Prediction of potential distribution of Schisandra chinensis and Schisandra sphenanthera based on MaxEnt model and analysis of its important influencing factors[J]. HUBEI AGRICULTURAL SCIENCES, 2024, 63(1): 116-121.

References

[1] 国家药典委员会.中华人民共和国药典(2020年版)[M].北京:中国医药科技出版社,2020.
[2] 焦美钰,佟月,吴浩善,等.南、北五味子“辨色论质”机制及其定性识别模型研究[J].中国药房,2020,31(24): 3007-3012.
[3] 刘宇灵,付赛,樊丽姣,等.南北五味子化学成分、药理作用等方面差异的研究进展[J].中国实验方剂学杂志,2017,23(12):228-234.
[4] 包京姗,杨世海,傅金泉.北五味子种质资源及栽培技术研究进展[J].人参研究,2017,29(4):26-30.
[5] 冯格,翟健秀,陈万生,等.南北五味子及其制剂与其他药物相互作用的研究进展[J].中国医院药学杂志, 2017,37(21):2206-2209,2215.
[6] 牟倩倩,贺敬霞,卢一,等.电子鼻结合化学计量学方法在南五味子和北五味子鉴别上的应用研究[J].时珍国医国药,2017, 28(6):1356-1359.
[7] 左晓彬,孙小茗,王春宇,等.南、北五味子醇提物对对乙酰氨基酚诱导的药物性肝损伤保护作用及药效差异研究[J].中国中药杂志,2019,44(6):1238-1245.
[8] 闫伯前,罗遵兰,胡理乐.东北野生五味子种群特征及其与环境因子的关系[J].环境科学研究,2013,26(6): 618-623.
[9] 杨航,张丽鹏,孙伟,等.北五味子品种适宜栽培地及其与环境因子的关系[J].西北农业学报,2014,23(4): 92-98.
[10] 张童,黄治昊,彭杨靖,等.基于Maxent模型的软枣猕猴桃在中国潜在适生区预测[J].生态学报,2020,40(14):4921-4928.
[11] 孙李勇,蒋政,刘晨妮,等.基于DIVA-GIS的紫玉兰地理分布及适生性分析[J].植物科学学报,2018,36(6): 804-811.
[12] 段义忠,王驰,王海涛,等.不同气候条件下沙冬青属植物在我国的潜在分布——基于生态位模型预测[J].生态学报,2020,40(21):7668-7680.
[13] 王国峥,耿其芳,肖孟阳,等.基于4种生态位模型的金钱松潜在适生区预测[J].生态学报,2020,40(17):6096-6104.
[14] 郭彦龙,顾蔚,路春燕,等.基于五味子甲素与乙素的秦岭地区野生华中五味子的潜在空间分布[J].植物学报,2013,48(4):411-422.
[15] 胡理乐,张海英,秦岭,等.中国五味子分布范围及气候变化影响预测[J].应用生态学报,2012,23(9): 2445-2450.
[16] 朱耿平,刘国卿,卜文俊,等.生态位模型的基本原理及其在生物多样性保护中的应用[J].生物多样性,2013, 21(1):90-98.
[17] WU B C,ZHOU L J,QI S,et al.Effect of habitat factors on the understory plant diversity of Platycladus orientalis plantations in Beijing mountainous areas based on MaxEnt model[J].Ecological indicators,2021, 129:107917.
[18] WANG G,WANG C,GUO Z R,et al.Integrating Maxent model and landscape ecology theory for studying spatiotemporal dynamics of habitat: Suggestions for conservation of endangered Red-crowned crane[J].Ecological indicators,2020,116:106472.
[19] YUAN H-S,YULIAN W,WANG X.Maxent modeling for predicting the potential distribution of Sanghuang, an important group of medicinal fungi in China[J].Fungal ecology,2015,17:140-145.
[20] 张华,赵浩翔,王浩.基于Maxent模型的未来气候变化情景下胡杨在中国的潜在地理分布[J].生态学报,2020,40(18):6552-6563.
[21] FENG L,WANG H,MA X,et al.Modeling the current land suitability and future dynamics of global soybean cultivation under climate change scenarios[J].Field crops research,2021,263:108069.
[22] 赖长江生,魏旭雅,邱子栋,等.道地药材质量标准设计与应用[J].中国中药杂志,2020,45(24):6072-6080.
[23] 何冬梅,王海,陈金龙,等.中药微生态与中药道地性[J].中国中药杂志,2020,45(2):290-302.
[24] 雷捷,徐建国,张晓佳,等.银柴胡的道地性评价初探[J].时珍国医国药,2020,31(8):1973-1975.
[25] 孟祥才,沈莹,杜虹韦.道地药材概念及其使用规范的探讨[J].中草药,2019,50(24):6135-6141.
[26] 毛亚娟,卫海燕,尚忠慧,等.基于GIS与模糊物元模型的东北地区五味子生境适宜性评价[J].应用与环境生物学报,2016,22(2):241-248.
[27] 刘丽娟,秦佳梅,丛毓,等.栽培北五味子土壤营养因子变化规律研究[J].广东农业科学,2013,40(22): 79-81.
[28] 曹倩,高庆波,郭万军,等.基于MaxEnt模拟人类活动与环境因子对青藏高原特有植物祁连獐牙菜潜在分布的影响[J].植物科学学报,2021,39(1):22-31.
[29] 张正海,李爱民,张悦,等.修剪强度对北五味子新梢萌发和生长的影响[J].江苏农业科学,2014,42(9): 220-222.