气候变化背景下软紫草在中国的潜在适生区预测

doi:10.13866/j.azr.2025.09.07

干旱区研究 ›› 2025, Vol. 42 ›› Issue (9): 1628-1639.doi: 10.13866/j.azr.2025.09.07 cstr: 32277.14.AZR.20250907

气候变化背景下软紫草在中国的潜在适生区预测

商淑静¹^,²^,³(), 刘丹辉¹^,²(), 周轶昕¹^,²^,⁴, 吴家驹⁵, 陆婷³, 李文军¹^,²^,⁴

1.中国-塔吉克斯坦生物资源保育与可持续利用“一带一路”联合实验室，中国科学院新疆生态与地理研究所，新疆乌鲁木齐 830011
2.中国科学院新疆生态与地理研究所，新疆抗逆植物基因资源保育与利用重点实验室，新疆乌鲁木齐 830011
3.新疆农业大学林学与风景园林学院，新疆乌鲁木齐 830052
4.中国科学院大学资源与环境学院，北京 100049
5.塔里木大学生命科学与技术学院，新疆阿拉尔 843300

收稿日期:2025-01-20 修回日期:2025-03-21 出版日期:2025-09-15 发布日期:2025-09-16
通讯作者: 刘丹辉. E-mail: liudanhui@ms.xjb.ac.cn
作者简介:商淑静（2000-），女，硕士研究生，主要从事园林植物应用研究. E-mail: 1337593428@qq.com
基金资助:
中国-塔吉克斯坦生物资源保育与可持续利用“一带一路”联合实验室建设与联合研究(2024YFE0214200);新疆抗逆植物基因资源保育与利用重点实验室开放基金资助;国家自然科学基金青年基金项目(32300183)

Prediction of the suitable distribution areas of Arnebia euchroma (Boraginaceae) in China under change climate conditions

SHANG Shujing¹^,²^,³(), LIU Danhui¹^,²(), ZHOU Yixin¹^,²^,⁴, WU Jiaju⁵, LU Ting³, LI Wenjun¹^,²^,⁴

1. China-Tajikistan Belt and Road Joint Laboratory on Biodiversity Conservation and Sustainable Use, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China
2. Xinjiang Key Laboratory of Conservation and Utilization of Resistant Resources, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China
3. College of Forestry and Landscape Architecture, Xinjiang Agricultural University, Urumqi 830052, Xinjiang, China
4. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
5. College of Life Sciences and Technologies, Tarim University, Alar 843300, Xinjiang, China

Received:2025-01-20 Revised:2025-03-21 Published:2025-09-15 Online:2025-09-16

摘要/Abstract

摘要：

探究软紫草（Arnebia euchroma）在中国的潜在适生区分布和其生态适应性，旨在为软紫草的野生植物资源保护及合理开发利用提供理论依据。本研究基于MaxEnt模型和ArcGIS软件，对软紫草在中国的51个分布点和11个环境因子进行潜在适生区预测，探讨影响软紫草分布的主要环境因子，并预测其在当前（1970—2000年）与未来（2021—2040年、2041—2060年）不同气候情境下的潜在适生区。结果表明：最湿季度平均温度（bio8）、季节性降水量（bio15）、最暖季度平均降水量（bio18）和海拔（elev）是影响软紫草分布的主导环境因子，贡献率分别为36.2%、13.9%、10.1%、8.5%；当前气候背景下，软紫草在国内主要分布于新疆中部和西藏西北部，潜在适生区总面积为96.26×10⁴ km²；与当前时期相比，未来4个时期气候情景下软紫草的潜在适生区分布变化不明显，适生区总面积呈减少趋势，但高适生区面积略有增加。

关键词: 软紫草, 最大熵模型, 潜在适生区预测, 气候变化

Abstract:

This study explored the potential distribution and ecological adaptability of Arnebia euchroma in China and provides a theoretical basis for the protection, rational development, and use of wild plant resources of A. euchroma. Based on the MaxEnt model and ArcGIS software, 51 distribution points and 11 environmental factors of A. euchroma in China were predicted as potentially suitable areas, and the main environmental factors that influence the distribution of A. euchroma were discussed. The potentially suitable areas in China were predicted under the present (1970-2000) and future (2021-2040, 2041-2060) climatic conditions. The results showed that precipitation of mean temperature of wettest quarter, precipitation seasonality, precipitation of warmest quarter, and elevation were the dominant environmental factors that affect A. euchroma distribution, with contribution rates of 36.2%, 13.9%, 10.1%, and 8.5%, respectively. Under the current climate background, A. euchroma in China is mainly distributed in the central part of Xinjiang and the northwest part of Xizang, with a total potential habitat area of 96.26×10⁴ km². Compared with the current period, the climate scenarios of the next four periods did not significantly change the distribution of potentially suitable areas for A. euchroma. The total suitable area decreased while the highly suitable area increased slightly.

Key words: Arnebia euchroma, MaxEnt, prediction of potential suitable areas, climate change

商淑静, 刘丹辉, 周轶昕, 吴家驹, 陆婷, 李文军. 气候变化背景下软紫草在中国的潜在适生区预测[J]. 干旱区研究, 2025, 42(9): 1628-1639.

SHANG Shujing, LIU Danhui, ZHOU Yixin, WU Jiaju, LU Ting, LI Wenjun. Prediction of the suitable distribution areas of Arnebia euchroma (Boraginaceae) in China under change climate conditions[J]. Arid Zone Research, 2025, 42(9): 1628-1639.

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参考文献 39

[1]	Sekar C K, Thapliyal N, Bhojak P, et al. Early signals of climate change impacts on alpine plant diversity in Indian Himalaya[J]. Biodiversity and Conservation, 2024, 34(1): 1-27.
[2]	裴炳. 气候变化对植物多样性和景观设计的影响[J]. 分子植物育种, 2025, 23(1): 294-299.
	[Pei Bing. The impact of climate change on plant diversity and landscape design[J]. Molecular Plant Breeding, 2025, 23(1): 294-299.]
[3]	Céline B, Cleo B, Paul L, et al. Impacts of climate change on the future of biodiversity[J]. Ecology Letters, 2012, 15(4): 365-377. doi: 10.1111/j.1461-0248.2011.01736.x pmid: 22257223
[4]	赵卫, 王昊, 肖颖, 等. 气候变化对野生生物类自然保护区的影响及其风险[J]. 生态学报, 2023, 43(13): 5270-5280.
	[Zhao Wei, Wang Hao, Xiao Ying, et al. Effect and risk of climate change on wildlife nature reserves[J]. Acta Ecologica Sinica, 2023, 43(13): 5270-5280.]
[5]	黄智聪, 舒江平, 严岳鸿, 等. 基于最大熵模型的中国兜兰属植物潜在分布模拟[J]. 热带亚热带植物学报, 2024, 32(1): 17-26.
	[Huang Zhicong, Shu Jiangping, Yan Yuehong, et al. Simulation of potential distribution of Paphiopedilum in China based on MaxEnt model[J]. Journal of Tropical and Subtropical Botany, 2024, 32(1): 17-26.]
[6]	王鹏, 金正, 余婷, 等. 预测姜黄属植物在中国当前和未来气候情景下的潜在分布区变化[J]. 草业学报, 2024, 33(10): 14-27. doi: 10.11686/cyxb2023435
	[Wang Peng, Jin Zheng, Yu Ting, et al. Prediction of the potential distribution of Curcuma in China under current and future climate scenarios[J]. Acta Prataculturae Sinica, 2024, 33(10): 14-27.] doi: 10.11686/cyxb2023435
[7]	Li Y, Li M, Li C, et al. Optimized Maxent model predictions of climate change impacts on the suitable distribution of Cunninghamia lanceolata in China[J]. Forests, 2020, 11(3): 302-311.
[8]	杨颖伦. 基于MaxEnt模型的滇藏玉兰适生区分布预测研究[J]. 现代农业科技, 2024(3): 98-102.
	[Yang Yinglun. Prediction of suitable growing areas distribution of Yulania campbellii based on MaxEnt model[J]. Modern Agricultural Science and Technology, 2024(3): 98-102.]
[9]	杜志喧, 苏启陶, 周兵, 等. 不同气候变化情景下入侵植物大狼把草在中国的潜在分布[J]. 生态学杂志, 2021, 40(8): 2575-2582.
	[Du Zhixuan, Su Qitao, Zhou Bing, et al. Potential distribution of invasive species Bidens frondosa under different climate change scenarios in China[J]. Chinese Journal of Ecology, 2021, 40(8): 2575-2582.]
[10]	陈陆丹, 胡菀, 李单琦, 等. 珍稀濒危植物野生莲的适生分布区预测[J]. 植物科学学报, 2019, 37(6): 731-740.
	[Chen Ludan, Hu Wan, Li Danqi, et al. Prediction of suitable distribution areas of the endangered plant wild Nelumbo nucifera Gaertn. in China[J]. Plant Science Journal, 2019, 37(6): 731-740.]
[11]	林鑫, 李成义, 魏小成, 等. 基于MaxEnt模型和ArcGIS的红芪生境适宜性评价[J]. 中成药, 2023, 45(12): 4005-4010.
	[Lin Xin, Li Chengyi, Wei Xiaocheng, et al. MaxEnt model-ArcGIS-based evaluation of habitat suitability of Hedysari radix[J]. Chinese Traditional Patent Medicine, 2023, 45(12): 4005-4010.]
[12]	中国科学院中国植物志编辑委员会. 中国植物志第64卷(2)[M]. 北京: 科学出版社, 1989: 43-44.
	[Editorial Committee of Flora of China, Chinese Academy of Sciences. Flora of China Volume 64, Volume 2[M]. Beijing: Science Press, 1989: 43-44.]
[13]	Singh H, Chauhan R, Raina R. Population structure, ecological features and associated species of Arnebia euchroma[J]. Journal of Pharmacognosy and Phytochemistry, 2017, 6(4): 2005-2007.
[14]	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: 355.
	[Chinese Pharmacopoeia Commission. Pharmacopoeia of the People's Republic of China[M]. 2020 Edition. Beijing: China Medical Science Press, 2020: 355.]
[15]	国家林业和草原局, 农业农村部. 国家重点保护野生植物名录[EB/OL]. [2021-09-07]. https://www.forestry.gov.cn/c/www/gkml/11057.jhtml.
	[National Forestry and Grassland Administration, Ministry of Agriculture and Rural Affairs. National Key Protected Wild Plants of China[EB/OL]. [2021-09-07]. https://www.forestry.gov.cn/c/www/gkml/11057.jhtml.]
[16]	徐海燕. 新疆软紫草属资源及其药材品质评价的研究[D]. 北京: 北京中医药大学, 2021.
	[Xu Haiyan. Study on the Quality Evaluation of Arnebia Resources and Its Medicinal Materials in Xinjiang[D]. Beijing: Beijing University of Chinese Medicine, 2021.]
[17]	Zhao J, Wang Y, Ding W, et al. Microsatellite marker-based analysis of the genetic diversity and population structure of three Arnebiae radix in western China[J]. Journal of Genetic Engineering and Biotechnology, 2024, 22(2): 100379.
[18]	付宇, 安慧君, 高明龙, 等. 基于气候变化背景的东北岩高兰潜在分布区预测[J]. 西北林学院学报, 2023, 38(5): 49-56.
	[Fu Yu, An Huijun, Gao Minglong, et al. Prediction of potential distribution area of Empetrum nigrum var. japonicum based on climate change background[J]. Journal of Northwest Forestry University, 2023, 38(5): 49-56.]
[19]	景丞, 姜彤, 苏布达, 等. 共享社会经济路径在土地利用、能源与碳排放研究的应用[J]. 大气科学学报, 2022, 45(3): 397-413.
	[Jing Cheng, Jiang Tong, Su Buda, et al. Multiple application of shared socioeconomic pathways in land use, energy and carbon emission research[J]. Transactions of Atmospheric Sciences, 2022, 45(3): 397-413.]
[20]	杨倩, 袁园, 苏旭, 等. 气候变化背景下糙果紫堇在中国适宜分布区的预测[J]. 植物研究, 2024, 44(1): 17-26. doi: 10.7525/j.issn.1673-5102.2024.01.004
	[Yang Qian, Yuan Yuan, Su Xu, et al. Prediction of suitable distribution area of Corydalis trachycarpa (Papaveraceae) in China under climate change[J]. Bulletin of Botanical Research, 2024, 44(1): 17-26.] doi: 10.7525/j.issn.1673-5102.2024.01.004
[21]	吴茹茹, 刘美珍, 谷仙, 等. 气候变化对巨柏适宜生境分布的潜在影响和预测[J]. 植物生态学报, 2024, 48(4): 445-458. doi: 10.17521/cjpe.2023.0218
	[Wu Ruru, Liu Meizhen, Gu Xian, et al. Prediction of suitable habitat distribution and potential impact of climate change on distribution patterns of Cupressus gigantea[J]. Chinese Journal of Plant Ecology, 2024, 48(4): 445-458.] doi: 10.17521/cjpe.2023.0218
[22]	陈程浩, 龙主多杰, 陆徐伟, 等. 基于优化MaxEnt模型的中国紫堇属植物生境适宜性研究[J]. 生态学报, 2023, 43(24): 10345-10362.
	[Chen Chenghao, Longzhuduojie, Lu Xuwei, et al. Habitat suitability of Corydalis based on the optimized MaxEnt model in China[J]. Acta Ecologica Sinica, 2023, 43(24): 10345-10362.]
[23]	叶雨, 樊丛照, 张际昭, 等. 基于MaxEnt和GIS的新疆紫草产地生态适宜性分析[J]. 中国现代中药, 2022, 24(5): 770-775.
	[Ye Yu, Fan Congzhao, Zhang Jizhao, et al. Ecological suitability of Arnebia euchroma producing area based on MaxEnt and GIS[J]. Modern Chinese Medicine, 2022, 24(5): 770-775.]
[24]	陈舒豪, 郭新安. 基于MaxEnt的小蓬草在中国的潜在适生区预测[J]. 湖北林业科技, 2024, 53(2): 35-40.
	[Chen Shuhao, Guo Xin'an. Prediction of potential suitable areas of Conyza canadensis using MaxEnt model[J]. Hubei Forestry Science and Technology, 2024, 53(2): 35-40.]
[25]	丁德永, 段洪, 李咪者, 等. 木荷适生区分析及未来气候下在中国潜在适生区预测[J]. 中国野生植物资源, 2024, 43(3): 114-123.
	[Ding Deyong, Duan Hong, Li Mizhe, et al. Analysis of suitable areas of Schima superba and prediction of potential suitable areas in China under future climate[J]. Chinese Wild Plant Resources, 2024, 43(3): 114-123.]
[26]	姜生秀, 胡静, 王方琳, 等. 基于MaxEnt模型的中国白刺属植物种群动态分析[J]. 中国野生植物资源, 2024, 43(11): 122-128.
	[Jiang Shengxiu, Hu Jing, Wang Fanglin, et al. Population dynamics analysis of Chinese Nitraria based on MaxEnt model[J]. Chinese Wild Plant Resources, 2024, 43(11): 122-128.]
[27]	王颖. 四川野生杜鹃花属植物资源的调查与评价[D]. 北京: 北京林业大学, 2008.
	[Wang Ying. Investigation and Evaluation of Wild Rhododendron Resources in Sichuan Province[D]. Beijing: Beijing Forestry University, 2008.]
[28]	倪健. 全球变化研究中的生物气候指标[J]. 第四纪研究, 2017, 37(3): 431-441.
	[Ni Jian. An intruduction to bioclimatic factors[J]. Quaternary Sciences, 2017, 37(3): 431-441.]
[29]	马生军, 耿阳, 马露, 等. 药用紫草研究进展[J]. 中国现代中药, 2021, 23(1): 177-184.
	[Ma Shengjun, Geng Yang, Ma Lu, et al. Advances in studies on medicinal Arnebiae radix[J]. Modern Chinese Medicine, 2021, 23(1): 177-184.]
[30]	张际昭, 邱远金, 赵亚琴, 等. 新疆紫草根际环境与药材药效成分含量相关性研究[J]. 中国中药杂志, 2023, 48(22): 6030-6038.
	[Zhang Jizhao, Qiu Yuanjin, Zhao Yaqin, et al. Correlation between rhizosphere environment and content of medicinal components of Arnebia euchroma[J]. China Journal of Chinese Materia Medica, 2023, 48(22): 6030-6038.] doi: 10.19540/j.cnki.cjcmm.20230725.101 pmid: 38114209
[31]	钱雪, 陈斌, 史晓芬, 等. 不同种类紫草对比研究[J]. 中国野生植物资源, 2020, 39(3): 68-71.
	[Qian Xue, Chen Bin, Shi Xiaofen, et al. Comparative study of different kinds of gromwell root[J]. Chinese Wild Plant Resources, 2020, 39(3): 68-71.]
[32]	丁文欢, 王东东, 王延蛟, 等. 新疆3种软紫草资源现状调查与分析[J]. 时珍国医国药, 2023, 34(1): 162-165.
	[Ding Wenhuan, Wang Dongdong, Wang Yanjiao, et al. Investigation and analysis of three species of Arnebia resource situation in Xinjiang[J]. Journal of Li-shizhen Traditional Chinese Medicine, 2023, 34(1): 162-165.]
[33]	李东宾, 魏晶晶, 许志斌, 等. 基于MaxEnt模型的华顶杜鹃潜在适生区预测和分析[J]. 浙江林业科技, 2024, 44(3): 1-10.
	[Li Dongbin, Wei Jingjing, Xu Zhibin, et al. Potential distribution of Rhododendron huadingense by MaxEnt model[J]. Journal of Zhejiang Forestry Science and Technology, 2024, 44(3): 1-10.]
[34]	陈思明, 邓钟, 张红月, 等. 气候变化对中国沿海红树林潜在分布格局的影响[J]. 湿地科学与管理, 2024, 20(3): 32-37, 44.
	[Chen Siming, Deng Zhong, Zhang Hongyue, et al. Impact of climate change on potential distribution of mangrove along the Chinese coast[J]. Wetland Science & Management, 2024, 20(3): 32-37, 44.]
[35]	史柠瑞, 朱珠, 王艳莉. 基于MaxEnt模型对2种青兰属植物在未来气候变化下潜在分布的预测研究[J]. 中国农学通报, 2023, 39(32): 115-123. doi: 10.11924/j.issn.1000-6850.casb2022-0874
	[Shi Ningrui, Zhu Zhu, Wang Yanli. Potential distribution prediction of two species of Dracocephalum L. under future climate change based on MaxEnt model[J]. Chinese Agricultural Science Bulletin, 2023, 39(32): 115-123.]
[36]	叶雨. 生态因子对新疆紫草生物学特性及品质的影响[D]. 乌鲁木齐: 新疆农业大学, 2022.
	[Ye Yu. Effects of Ecological Factors on Biological Characteristics and Quality of Arnebia euchroma[D]. Urumqi: Xinjiang Agricultural University, 2022.]
[37]	黄瑞, 戴胜云, 吴东雪, 等. 新疆紫草野生品与栽培品的质量比较研究[J]. 药物分析杂志, 2024, 44(5): 783-795. doi: 10.16155/j.0254-1793.2024.05.06
	[Huang Rui, Dai Shengyun, Wu Dongxue, et al. Comparative study on the quality of wild and cultivated Arnebiae Radix[J]. Chinese Journal of Pharmaceutical Analysis, 2024, 44(5): 783-795.]
[38]	陈松清, 东红芳, 岳怡锋, 等. 不同气候情景下中国沙棘的地理分布及动态变化预测[J]. 干旱区研究, 2024, 41(9): 1560-1571. doi: 10.13866/j.azr.2024.09.12
	[Chen Songqing, Dong Hongfang, Yue Yifeng, et al. Geographical distribution and dynamic change prediction of Hippophae rhamnoides subsp. sinensis under different climate scenarios[J]. Arid Zone Research, 2024, 41(9): 1560-1571.] doi: 10.13866/j.azr.2024.09.12
[39]	曹福祥, 徐庆军, 曹受金, 等. 全球变暖对物种分布的影响研究进展[J]. 中南林业科技大学学报, 2008, 28(6): 86-89.
	[Cao Fuxiang, Xu Qingjun, Cao Shoujin, et al. Advances of global warming impact on species distribution[J]. Journal of Central South University of Forestry & Technology, 2008, 28(6): 86-89.]

气候情景	时期	经度	纬度	质心迁移距离/km
-	当前	91.692°E	38.489°N	-
SSP1-2.6	2021—2040年	91.509°E	38.717°N	29.93
SSP1-2.6	2041—2060年	91.540°E	38.708°N	27.70
SSP2-4.5	2021—2040年	91.467°E	38.744°N	34.44
SSP2-4.5	2041—2060年	91.679°E	38.648°N	17.72
SSP3-7.0	2021—2040年	91.619°E	38.670°N	21.10
SSP3-7.0	2041—2060年	91.632°E	38.656°N	19.29
SSP5-8.5	2021—2040年	91.271°E	38.758°N	47.25
SSP5-8.5	2041—2060年	91.398°E	38.781°N	41.31

气候变化背景下软紫草在中国的潜在适生区预测

Prediction of the suitable distribution areas of Arnebia euchroma (Boraginaceae) in China under change climate conditions

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[2]	罗磊, 李曦光, 李萧婷, 王磊, 王蕾. 气候变化下沙棘在新疆潜在分布格局的变化[J]. 干旱区研究, 2025, 42(3): 511-522.
[3]	邹彬, 邹珊, 杨余辉. 1990—2023年新疆地表水体面积动态变化及其驱动因素[J]. 干旱区研究, 2025, 42(1): 40-50.
[4]	吕壮壮, 乔庆庆, 董孙艺, 汪冬. 中中新世气候适宜期全球变暖背景下亚洲内陆干旱区古气候演化特征及驱动机制[J]. 干旱区研究, 2024, 41(8): 1309-1322.
[5]	周杰, 王旭虎, 杜维波, 周晓雷, 杨洁, 张晓玮. 气候变化背景下的天山云杉潜在分布区预测[J]. 干旱区研究, 2024, 41(7): 1167-1176.
[6]	梁双河, 牛最荣, 贾玲. 祖厉河干流近65 a径流变化及归因分析[J]. 干旱区研究, 2024, 41(6): 928-939.
[7]	唐可欣, 郭建斌, 何亮, 陈林, 万龙. 中国旱区GPP时空演变特征及影响因素研究[J]. 干旱区研究, 2024, 41(6): 964-973.
[8]	张嘉琪, 刘招, 韩忠青, 王丽霞, 张晋霞, 岳甲寅, 管子隆. 气候变化下泾河流域蓝绿水变化趋势及预测[J]. 干旱区研究, 2024, 41(12): 2045-2055.
[9]	张倩, 曹广超, 张乐乐, 赵美亮. 祁连山南坡植被绿度时空变化及其对气候变化和人类活动的响应[J]. 干旱区研究, 2024, 41(12): 2143-2153.
[10]	胡广录, 樊亚仑, 陶虎, 李昊辰, 杨鹏华. 石羊河下游蔡旗站径流变化趋势及影响因素[J]. 干旱区研究, 2024, 41(11): 1842-1852.
[11]	杨斐, 张文韬, 张飞民, 王澄海. 1961—2022年祁连山气候特征及其变化[J]. 干旱区研究, 2024, 41(10): 1627-1638.
[12]	张音, 孙从建, 刘庚, 钞锦龙, 耿甜伟. 近20 a塔里木河流域山区NDSI对气候变化的响应[J]. 干旱区研究, 2024, 41(10): 1639-1648.
[13]	程倩, 齐月, 刘明春, 张鹏, 丁文魁, 李兴宇, 任丽雯, 杨华. 气候变化及人类活动背景下石羊河流域生态与水资源变化特征[J]. 干旱区研究, 2024, 41(10): 1672-1684.
[14]	樊玉科, 任菊, 王润龙, 周栋栋, 潘自凯, 张晓玮, 周晓雷. 气候变化背景下白皮松在中国潜在适宜分布预测[J]. 干旱区研究, 2024, 41(10): 1719-1730.
[15]	齐容镰, 李庆波, 任佳, 邹苗, 杨昊鹏, 魏耀峰, 唐琼. “三北”工程地区植被覆盖变化特征及其驱动力分析——以宁夏为例[J]. 干旱区研究, 2024, 41(10): 1740-1752.