基于最大熵模型的中药材半夏潜在适生区预测
Prediction of the Potential Suitable Habitat of Pinellia Ternata Based on the Maximum Entropy Model
DOI: 10.12677/sd.2025.158246, PDF,   
作者: 李雅婕*, 赵 可*, 郭甜雨, 苗文佳, 胡明丽#:湖北科技学院药学院,湖北 咸宁;宋林河:云南大学生态与环境学院,云南 昆明
关键词: 半夏Maxent模型适生区资源保护Pinellia Maxent Model Suitable Habitat Resource Protection
摘要: 目的:半夏(Pinellia ternata (Thunb.) Breit)具有重要药用和经济价值,目前半夏野生资源不断减少所以确定最适种植地和最佳保护区对于促进半夏资源的保育和利用发展至关重要。运用Maxent模型并结合ArcGIS软件,从而确定影响半夏生长发育的环境因子,预测半夏的适生区变化情况。结果显示,Maxent模型重复运行10次的ROC曲线的ACU平均训练值为0.909,结果具有较高的准确性。此外,确定了最干燥月份降雨量(bio_14)、最暖季节降水量(bio_18)和最寒冷月最低温(bio_6)为半夏隐性分布的主要环境因子。该成果的取得,为我国半夏资源的培养、保育及科学利用提供重要的科学和理论依据。我国半夏资源尚存在广阔的发展空间,在保障适宜温度、降水量和光照条件的前提下,可以在我国北部地区积极开展引种试种研究,从而更好地满足市场需要,并推动深化半夏资源的可持续利用与发展。
Abstract: Objective: Pinellia ternata (Thunb.) Breit has important medicinal and economic value. Currently, the wild resources of Pinellia ternata are decreasing. Therefore, determining the most suitable planting site and the best protection area is crucial to promote the conservation and utilization of Pinellia ternata resources. The Maxent model was used in combination with ArcGIS software to determine the environmental factors affecting the growth and development of Pinellia ternata and predict the changes in the suitable habitat of Pinellia ternata. The results showed that the average ACU training value of the ROC curve of the Maxent model repeated 10 times was 0.909, and the results had high accuracy. In addition, the rainfall in the driest month (bio_14), the precipitation in the warmest season (bio_18) and the minimum temperature in the coldest month (bio_6) were determined as the main environmental factors for the recessive distribution of Pinellia ternata. The achievement of this result provides an important scientific and theoretical basis for the cultivation, conservation and scientific utilization of my country’s Pinellia resources. There is still a broad space for the development of my country’s Pinellia resources. Under the premise of ensuring suitable temperature, precipitation and light conditions, we can actively carry out introduction and trial planting research in northern my country to better meet market needs and promote the sustainable utilization and development of Pinellia resources.
文章引用:李雅婕, 赵可, 宋林河, 郭甜雨, 苗文佳, 胡明丽. 基于最大熵模型的中药材半夏潜在适生区预测[J]. 可持续发展, 2025, 15(8): 303-313. https://doi.org/10.12677/sd.2025.158246

参考文献

[1] 周志伟, 李嫣然, 李海英. 半夏药材的进出口贸易现状及产业化发展思考[J]. 中药材, 2022, 45(5): 1021-1028.
[2] 裴艺菲. 基于物种-种质-器官三个维度的半夏资源学研究[D]: [博士学位论文]. 北京: 中国中医科学院, 2024.
[3] 徐丹洋, 张金星, 姚奕然, 等. UPLC-MS/MS法测定半夏中根茎膨大剂的残留[J]. 中南药学, 2024, 22(11): 3000-3005.
[4] 翟兴英, 曹浩时, 巫志辉, 等. 半夏属药用植物化学成分的研究进展[J]. 江西中医药大学学报, 2023, 35(6): 123-127+132.
[5] 中国科学院中国植物志编辑委员会. 中国植物志[M]. 北京: 北京科学出版社, 1979.
[6] 王化东, 吴发明. 我国半夏资源调查研究[J]. 安徽农业科学, 2012, 40(1): 150-151+200.
[7] 寸竹, 董益, 张广辉, 等. 云南省野生半夏资源调查及种质评价[J]. 南方农业学报, 2021, 52(8): 2069-2077.
[8] 穆二廷, 周建理. 半夏生药学研究概况[J]. 安徽中医学院学报, 2013, 32(5): 91-94.
[9] 窦全慧, 陈程浩, 曾太乙亥, 等. 基于优化的MaxEnt模型预测龙胆科重要药用植物在青藏高原的生境适宜性研究[J/OL]. 草地学报, 1-13.
https://link.cnki.net/urlid/11.3362.s.20250318.1817.014, 2025-03-19.
[10] Urbani, F., D’Alessandro, P., Frasca, R. and Biondi, M. (2015) Maximum Entropy Modeling of Geographic Distributions of the Flea Beetle Species Endemic in Italy (Coleoptera: Chrysomelidae: Galerucinae: Alticini). Zoologischer AnzeigerA Journal of Comparative Zoology, 258, 99-109. [Google Scholar] [CrossRef
[11] Yang, Y., He, J., Liu, Y., Zeng, J., Zeng, L., He, R., et al. (2023) Assessment of Chinese Suitable Habitats of Zanthoxylum nitidum in Different Climatic Conditions by Maxent Model, HPLC, and Chemometric Methods. Industrial Crops and Products, 196, Article ID: 116515. [Google Scholar] [CrossRef
[12] Xin, X.G., Wu, T.W. and Zhang, J. (2019) Introduction to the BCC Model and Its CMIP6 Experiment. Progress in Climate Change Research, 15, 533-539.
[13] Zhang, K., Zhang, Y., Zhou, C., Meng, J., Sun, J., Zhou, T., et al. (2019) Impact of Climate Factors on Future Distributions of Paeonia ostii across China Estimated by Maxent. Ecological Informatics, 50, 62-67. [Google Scholar] [CrossRef
[14] Ünal, Y. (2023) Potential Distribution of the Caracal (Caracal Caracal Schreber, 1776) under Climate Change. Applied Ecology and Environmental Research, 21, 1109-1128. [Google Scholar] [CrossRef
[15] Azeem, A., Ahmed, S.R., Qadir, A. and Hussainy, A.S. (2021) Predictive Habitat Suitability Modelling of Axis porcinus (Hog Deer) under Current and Future Climate Change Scenarios in Punjab, Pakistan. Applied Ecology and Environmental Research, 19, 3181-3201. [Google Scholar] [CrossRef
[16] Karakaya, T. and Yücel, E. (2021) Potential Distribution Modelling and Mapping of Dog Rose (Rosa canina L.) in the Nur Mountains of Gaziantep District, Turkey. Applied Ecology and Environmental Research, 19, 2741-2760. [Google Scholar] [CrossRef
[17] Moreno, R., Zamora, R., Molina, J.R., Vasquez, A. and Herrera, M.Á. (2011) Predictive Modeling of Microhabitats for Endemic Birds in South Chilean Temperate Forests Using Maximum Entropy (Maxent). Ecological Informatics, 6, 364-370. [Google Scholar] [CrossRef
[18] 马松梅, 魏博, 李晓辰, 罗冲, 孙芳芳. 气候变化对梭梭植物适宜分布的影响[J]. 生态学杂志, 2017, 36(5): 1243-1250.
[19] 张晓玮, 蒋玉梅, 毕阳, 刘祥林, 李星, 孙涛, 陈浩宇, 李捷. 基于MaxEnt模型的中国沙棘潜在适宜分布区分析[J]. 生态学报, 2022, 42(4): 1420-1428.
[20] 曹雪萍, 王婧如, 鲁松松, 张晓玮. 气候变化情境下基于最大熵模型的青海云杉潜在分布格局模拟[J]. 生态学报, 2019, 39(14): 5232-5240.
[21] Swets, J.A. (1988) Measuring the Accuracy of Diagnostic Systems. Science, 240, 1285-1293. [Google Scholar] [CrossRef] [PubMed]
[22] 张童, 黄治昊, 彭杨靖, 王泳腾, 王萍, 王诗童, 崔国发. 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.
[23] Deb, J.C., Phinn, S., Butt, N. and McAlpine, C.A. (2017) The Impact of Climate Change on the Distribution of Two Threatened Dipterocarp Trees. Ecology and Evolution, 7, 2238-2248. [Google Scholar] [CrossRef] [PubMed]
[24] Tsoar, A., Allouche, O., Steinitz, O., Rotem, D. and Kadmon, R. (2007) A Comparative Evaluation of Presence‐Only Methods for Modelling Species Distribution. Diversity and Distributions, 13, 397-405. [Google Scholar] [CrossRef
[25] Tarroso, P., Carvalho, S.B. and Brito, J.C. (2012) Simapse—Simulation Maps for Ecological Niche Modelling. Methods in Ecology and Evolution, 3, 787-791. [Google Scholar] [CrossRef
[26] Guo, F.L., Xu, G.B., Lu, M.Z., Meng, Y.H., Yuan, C.Z. and Guo, K.Q. (2020) Analyzing the Potential Suitable Distribution Area of Poplar Based on MaxEnt Model. Forest Science, 56, 184-192.
[27] Song, C. and Liu, H. (2019) Habitat Differentiation and Conservation Gap of Magnolia biondii, M. denudata, and M. sprengeri in China. PeerJ, 6, e6126. [Google Scholar] [CrossRef] [PubMed]
[28] Ashrafi, M., Azimi-Moqadam, M., Moradi, P., MohseniFard, E., Shekari, F. and Kompany-Zareh, M. (2018) Effect of Drought Stress on Metabolite Adjustments in Drought Tolerant and Sensitive Thyme. Plant Physiology and Biochemistry, 132, 391-399. [Google Scholar] [CrossRef] [PubMed]
[29] Pant, P., Pandey, S. and Dall’Acqua, S. (2021) The Influence of Environmental Conditions on Secondary Metabolites in Medicinal Plants: A Literature Review. Chemistry & Biodiversity, 18, e2100345. [Google Scholar] [CrossRef] [PubMed]
[30] 王家禄, 王瑀, 牟兰, 等. 半夏全球生态适宜性分析与品质生态学研究[J]. 中国现代中药, 2021, 23(11): 1864-1868.