• Scopus
  • Chinese Science Citation Database (CSCD)
  • A Guide to the Core Journal of China
  • CSTPCD
  • F5000 Frontrunner
  • RCCSE
Advanced search
Tang Yan, Zhao Runan, Ren Gang, Cao Fuliang, Zhu Zunling. Prediction of potential distribution of Lycium chinense based on MaxEnt model and analysis of its important influencing factors[J]. Journal of Beijing Forestry University, 2021, 43(6): 23-32. DOI: 10.12171/j.1000-1522.20200103
Citation: Tang Yan, Zhao Runan, Ren Gang, Cao Fuliang, Zhu Zunling. Prediction of potential distribution of Lycium chinense based on MaxEnt model and analysis of its important influencing factors[J]. Journal of Beijing Forestry University, 2021, 43(6): 23-32. DOI: 10.12171/j.1000-1522.20200103

Prediction of potential distribution of Lycium chinense based on MaxEnt model and analysis of its important influencing factors

More Information
  • Received Date: April 08, 2020
  • Revised Date: May 21, 2020
  • Available Online: April 13, 2021
  • Published Date: June 29, 2021
  •   Objective  In most areas of China, Lycium chinense is in a wild state and its application is limited. In the context of global climate change, the prediction of current and future suitable distribution areas of L. chinense is of great significance for the protection of its germplasm resources, rational introduction and cultivation, and large-scale promotion.
      Method  Based on ArcGIS and MaxEnt models, we used 124 distribution data of L. chinense and 8 climatic variables to evaluate the main climatic factors restricting its geographical distribution and discuss its current and future potential distribution areas.
      Result  At present, the total suitable area of L. chinense occupied about 36.73% of the national land area, and the horizontal distribution interval was about 18°−45°N and 90°−123°E. Core suitable areas were mainly located in the Qinling Mountains, Taihang Mountains of northern China; and Zhejiang, Jiangsu and Anhui in eastern China; Yunnan, Guizhou, Chongqing and Sichuan in the southwestern China; Gansu, Ningxia in the northwestern China and their neighboring areas. The main climatic factors affecting its distribution were the Min. temperature of the coldest month, the precipitation of the wettest month, the precipitation of the driest month, and the Max. temperature of the warmest month. With the future climate warming, the total suitable area of L. chinense was not much different from the current one, but its main core suitable area tended to “expansion at high altitudes”, “migration in coastal areas” and “central gathering”. The specific manifestation was the expansion to high-altitude areas in Shaanxi, Gansu and other Qinling areas of northwestern China; the eastern coastal areas gradually formed a narrow strip core suitable area; the central Hunan and Hubei areas gradually formed a large area of flaky core suitable area.
      Conclusion  The suitable areas of L. chinense is mainly wide and continuous, while core suitable area is narrow and discontinuous. The climatic factors affecting its geographical distribution are mainly temperature and rainfall, and the Min. temperature of the coldest month is the most important climatic factor limiting its distribution. In the future, the eastern coastal areas of China, Dabie Mountains, Qinling Mountains and Daba Mountains in central China, southwestern regions such as Sichuan, Chongqing and their adjacent areas are suitable for the introduction, cultivation and promotion of L. chinense.
  • [1]
    郭彦龙, 卫海燕, 路春燕, 等. 气候变化下桃儿七潜在地理分布的预测[J]. 植物生态学报, 2014, 38(3):249−261. doi: 10.3724/SP.J.1258.2014.00022

    Guo Y L, Wei H Y, Lu C Y, et al. Predictions of potential geographical distribution of Sinopodophyllum hexandrum under climate change[J]. Chinese Journal of Plant Ecology, 2014, 38(3): 249−261. doi: 10.3724/SP.J.1258.2014.00022
    [2]
    气候变化2007: 自然科学基础[J]. 世界环境, 2007(2):13−22.

    Climate change 2007: the physical science basis[J]. World Environment, 2007(2): 13−22.
    [3]
    David R R, Andreas H. Predicting potential climate change impacts with bioclimate envelope models: a palaeoecological perspective[J]. Global Ecology & Biogeography, 2012, 21(2): 121−133.
    [4]
    《气候变化国家评估报告》(摘要)[J]. 世界环境, 2007(2):23−33.

    China’s Nation Assessment Report on climate change (summary)[J]. World Environment, 2007(2): 23−33.
    [5]
    Bellard C, Bertelsmeier C, Leadley P, 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
    [6]
    柳嘉佳. 基于MaxEnt模型的米槁潜在适生区分布及其格局模拟[D]. 贵州: 贵州大学, 2018.

    Liu J J. Prediction and simulation of distribution of Cinnamomum migao based on MaxEnt model and GIS[D]. Guizhou: Guizhou University, 2018.
    [7]
    杨晓龙, 杨超杰, 胡成业, 等. 物种分布模型在海洋潜在生境预测的应用研究进展[J]. 应用生态学报, 2017, 28(6):2063−2072.

    Yang X L, Yang C J, Hu C Y, et al. Application of species distribution models in the prediction of marine potential habitat: a review[J]. Chinese Journal of Applied Ecology, 2017, 28(6): 2063−2072.
    [8]
    Stas M, Aerts R, Hendrickx M, et al. An evaluation of species distribution models to estimate tree diversity at genus level in a heterogeneous urban-rural landscape[J]. Landscape and Urban Planning, 2020, 198: 103770. doi: 10.1016/j.landurbplan.2020.103770
    [9]
    Grenié M, Violle C, Munoz F. Is prediction of species richness from stacked species distribution models biased by habitat saturation?[J]. Ecological Indicators, 2020, 111: 105970−105977. doi: 10.1016/j.ecolind.2019.105970
    [10]
    李熠, 唐志尧, 闫昱晶, 等. 物种分布模型在大型真菌红色名录评估及保护中的应用: 以冬虫夏草为例[J]. 生物多样性, 2020, 28(1):99−106. doi: 10.17520/biods.2019158

    Li Y, Tang Z Y, Yan Y J, et al. Incorporating species distribution model into the red list assessment and conservation of macrofungi: a case study with Ophiocordyceps sinensis[J]. Biodiversity Science, 2020, 28(1): 99−106. doi: 10.17520/biods.2019158
    [11]
    刘晓彤, 袁泉, 倪健. 中国植物分布模拟研究现状[J]. 植物生态学报, 2019, 43(4):273−283. doi: 10.17521/cjpe.2018.0237

    Liu X T, Yuan Q, Ni J. Research advances in modelling plant species distribution in China[J]. Chinese Journal of Plant Ecology, 2019, 43(4): 273−283. doi: 10.17521/cjpe.2018.0237
    [12]
    Yang X Q, Kushwaha S P S, Saran S, et al. Maxent modeling for predicting the potential distribution of medicinal plant, Justicia adhatoda L. in Lesser Himalayan foothills[J]. Ecological Engineering, 2013, 51: 83−87. doi: 10.1016/j.ecoleng.2012.12.004
    [13]
    Steven J P, Robert P A, Robert E S. Maximum entropy modeling of species geographic distributions[J]. Ecological Modelling, 2006, 190(3): 231−259.
    [14]
    中国植物志编委会. 中国植物志: 1分册[M]. 67卷. 北京: 科学出版社, 1998.

    China Botany Editorial Board. Flora of China: book 1[M]. Vol. 67. Beijing: Science Press, 1998.
    [15]
    国家药典委员会. 中华人民共和国药典(一部) [M]. 北京: 化学工业出版社, 2015: 249.

    National Pharmacopoeia Commission. Pharmacopoeia of the People’s Republic of China (part one) [M]. Beijing: Chemical Industry Press, 2015: 249.
    [16]
    闫秀梅, 董静洲, 王瑛. 枸杞和宁夏枸杞叶片主要活性成分含量比较研究[J]. 食品科学, 2010, 31(1):29−32.

    Yan X M, Dong J Z, Wang Y. Comparison studies of main active compounds in young leaves of Lycium bararum and Lycium chinense[J]. Food Science, 2010, 31(1): 29−32.
    [17]
    张兴旺, 李垚, 方炎明. 麻栎在中国的地理分布及潜在分布区预测[J]. 西北植物学报, 2014, 34(8):1685−1692.

    Zhang X W, Li Y, Fang Y M. Geographical distribution and prediction of potential ranges of Quercus acutissima in China[J]. Acta Botanica Boreali-Occidentalia Sinica, 2014, 34(8): 1685−1692.
    [18]
    曹雪萍, 王婧如, 鲁松松, 等. 气候变化情景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.

    Cao X P, Wang J R, Lu S S, et al. Simulation of the potential distribution patterns of Picea crassifolia in climate change scenarios based on the maximum entropy (MaxEnt) model[J]. Acta Ecologica Sinica, 2019, 39(14): 5232−5240.
    [19]
    马青江, 孙操稳, 张乐英, 等. 东亚四照花群体中国潜在适生区预测研究[J]. 南京林业大学学报(自然科学版), 2019, 43(5):135−140.

    Ma Q J, Sun C W, Zhang L Y, et al. Identification of potential distribution region for East Asian dogwoods (Cornus) in China[J]. Journal of Nanjing Forestry University (Natural Sciences Edition), 2019, 43(5): 135−140.
    [20]
    张殷波, 高晨虹, 秦浩. 山西翅果油树的适生区预测及其对气候变化的响应[J]. 应用生态学报, 2018, 29(4):1156−1162.

    Zhang Y B, Gao C H, Qin H. Prediction of the suitable distribution and responses to climate change of Elaeagnus mollis in Shanxi Province, China[J]. Chinese Journal of Applied Ecology, 2018, 29(4): 1156−1162.
    [21]
    董静洲, 杨俊军, 王瑛. 我国枸杞属物种资源及国内外研究进展[J]. 中国中药杂志, 2008, 33(18):2020−2027. doi: 10.3321/j.issn:1001-5302.2008.18.003

    Dong J Z, Yang J J, Wang Y. Resources of Lycium species and related research progress[J]. China Journal of Chinese Materia Medica, 2008, 33(18): 2020−2027. doi: 10.3321/j.issn:1001-5302.2008.18.003
    [22]
    杨柳. 三种中药提取多糖及其复合多糖抗氧化作用研究[D]. 广州: 广东药科大学, 2017.

    Yang L. Study of antioxidant activity of polysaccharide and compound polysaccharide from three kinds of Chinese medicine[D]. Guangzhou: Guangdong Pharmaceutical University, 2017.
    [23]
    陈芳, 郑新恒, 王瑞, 等. 枸杞根化学成分研究[J]. 中草药, 2018, 49(5):1007−1012.

    Chen F, Zheng X H, Wang R, et al. Study on chemical constituents from roots of Lycium chinense[J]. Chinese Traditional and Herbal Drugs, 2018, 49(5): 1007−1012.
    [24]
    张仲保, 陈志叶, 马国江, 等. 日光温室后墙叶用枸杞立体基质栽培技术[J]. 中国蔬菜, 2015(5):87−88. doi: 10.3969/j.issn.1000-6346.2015.05.032

    Zhang Z B, Chen Z Y, Ma G J, et al. Three-dimensional substrate cultivation technology of Lycium chinense for leaves on the back wall of sunlight greenhouse[J]. China Vegetables, 2015(5): 87−88. doi: 10.3969/j.issn.1000-6346.2015.05.032
    [25]
    王林, 刘宁, 王慧, 等. 盐碱胁迫下枸杞和柽柳的水力学特性和碳代谢[J]. 植物科学学报, 2017, 35(6):865−873.

    Wang L, Liu N, Wang H, et al. Hydraulic characteristics and carbon metabolism of Lycium chinense Miller and Tamarix chinensis Lour under saline-alkali stress[J]. Plant Science Journal, 2017, 35(6): 865−873.
    [26]
    王亚军, 安巍, 石志刚, 等. 枸杞药用价值的研究进展[J]. 安徽农业科学, 2008, 36(30):13213−13214,13218. doi: 10.3969/j.issn.0517-6611.2008.30.088

    Wang Y J, An W, Shi Z G, et al. Research progress in wolfberry medicinal properties[J]. Journal of Anhui Agricultural Sciences, 2008, 36(30): 13213−13214,13218. doi: 10.3969/j.issn.0517-6611.2008.30.088
    [27]
    林丽, 晋玲, 王振恒, 等. 气候变化背景下藏药黑果枸杞的潜在适生区分布预测[J]. 中国中药杂志, 2017, 42(14):2659−2669.

    Lin L, Jin L, Wang Z H, et al. Prediction of the potential distribution of Tibetan medicinal Lycium ruthenicum in context of climate change[J]. China Journal of Chinese Materia Medica, 2017, 42(14): 2659−2669.
    [28]
    孙莉, 王山, 王正元, 等. 基于最大熵模型的枸杞生态适宜区预测[J]. 宁夏大学学报(自然科学版), 2018, 39(2):143−147.

    Sun L, Wang S, Wang Z Y, et al. Ecological suitable prediction of Lycium barbarum based on maximum entropy model[J]. Journal of Ningxia University (Natural Science Edition), 2018, 39(2): 143−147.
    [29]
    叶学敏, 陈伏生, 孙荣喜, 等. 基于MaxEnt模型的南酸枣潜在适生区预测[J]. 江西农业大学学报, 2019, 41(3):440−446.

    Ye X M, Chen F S, Sun R X, et al. Prediction of potential suitable distribution areas for Choerospondias axillaris besed on MaxEnt model[J]. Acta Agriculturae Universitatis Jiangxiensis, 2019, 41(3): 440−446.
    [30]
    Swets J A. Measuring the accuracy of diagnostic systems[J]. Science, 1988, 240: 1285−1293. doi: 10.1126/science.3287615
    [31]
    杨洋. 基于四种模型的肉苁蓉潜在地理分布预测及空间格局变化分析[D]. 西安: 陕西师范大学, 2017.

    Yang Y. Potential geographical distribution and spatial pattern analysis of Cistanche desertica based on four models[D]. Xi’an: Shaanxi Normal University, 2017.
    [32]
    Li G Q, Du S, Wen Z M. Mapping the climatic suitable habitat of oriental arborvitae (Platycladus orientalis) for introduction and cultivation at a global scale[J]. Scientific Reports, 2016, 6: 30009. doi: 10.1038/srep30009
    [33]
    Jaynes E. Information theory and statistical mechanics[J]. Physical Review, 1957, 106(4): 620−630. doi: 10.1103/PhysRev.106.620
    [34]
    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. doi: 10.11913/PSJ.2095-0837.2019.60731

    Chen L D, Hu W, Li D Q, 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. doi: 10.11913/PSJ.2095-0837.2019.60731
    [35]
    郭佳, 曹伟, 张悦, 等. 黄花刺茄在中国东北潜在分布区预测[J]. 草业科学, 2019, 36(10):2476−2484.

    Guo J, Cao W, Zhang Y, et al. Prediction of the potential distribution area of Solanum rostratum in northeast China[J]. Pratacultural Science, 2019, 36(10): 2476−2484.
    [36]
    Yi Y J, Cheng X, Yang Z F, et al. MaxEnt modeling for predicting the potential distribution of endangered medicinal plant (Homonoia riparia Lour) in Yunnan, China[J]. Ecological Engineering, 2016, 92: 260−269. doi: 10.1016/j.ecoleng.2016.04.010
    [37]
    于海彬, 张镱锂, 李士成, 等. 基于GIS和物种分布模型的高山植物长花马先蒿迁移路线模拟[J]. 应用生态学报, 2014, 25(6):1669−1673.

    Yu H B, Zhang Y L, Li S C, et al. Predicting the dispersal routes of alpine plant Pedicularis longiflora (Orobanchaceae) based on GIS and species distribution models[J]. Chinese Journal of Applied Ecology, 2014, 25(6): 1669−1673.
    [38]
    Pradeep K. Assessment of impact of climate change on Rhododendrons in Sikkim Himalayas using MaxEnt modelling: limitations and challenges[J]. Biodiversity and Conservation, 2012, 21(5): 1251−1266. doi: 10.1007/s10531-012-0279-1
    [39]
    钱丹, 纪瑞锋, 郭威, 等. 中国枸杞属种间亲缘关系和栽培枸杞起源研究进展[J]. 中国中药杂志, 2017, 42(17):3282−3285.

    Qian D, Ji R F, Guo W, et al. Advances in research on relationships among Lycium species and origin of cultivated Lycium in China[J]. China Journal of Chinese Materia Medica, 2017, 42(17): 3282−3285.
    [40]
    王晓宇, 陈鸿平, 银玲, 等. 中国枸杞属植物资源概述[J]. 中药与临床, 2011, 2(5):1−3, 50.

    Wang X Y, Chen H P, Yin L, et al. A brief overview on the plant resources of Lycium in China[J]. Pharmacy and Clinics of Chinese Materia Medica, 2011, 2(5): 1−3, 50.
    [41]
    林之光. 我国山区气候的研究[J]. 气象, 1981(1):27−28.

    Lin Z G. Study on mountain climate in China[J]. Meteorological Monthly, 1981(1): 27−28.
    [42]
    沈国权. 小网格雨量场的估算分析[J]. 气象, 1986(9):32−36.

    Shen G Q. Estimation and analysis of rainfall field in small grid[J]. Meteorological Monthly, 1986(9): 32−36.
    [43]
    唐文惠. 柴达木盆地东部地区发展枸杞产业的气候条件分析[J]. 现代农业科技, 2019, 743(9):74, 77.

    Tang W H. Analysis of the climatic conditions for the development of Lycium industry in the eastern part of Qaidam Basin[J]. Modern Agricultural Science and Technology, 2019, 743(9): 74, 77.
    [44]
    宋丽华, 周利伟. 气温升高对枸杞苗木生长的影响[J]. 林业科技, 2010, 35(2):62−64.

    Song L H, Zhou L W. Effect of temperature rise on growth of Chinese wolfberry seedlings[J]. Forestry Science & Technology, 2010, 35(2): 62−64.
    [45]
    赖正锋, 张少平, 李跃森, 等. 南方菜用枸杞周年栽培技术[J]. 中国蔬菜, 2013(17):63−64. doi: 10.3969/j.issn.1000-6346.2013.17.026

    Lai Z F, Zhang S P, Li Y S, et al. Annual cultivation techniques of Lycium chinense for vegetable in South China[J]. China Vegetables, 2013(17): 63−64. doi: 10.3969/j.issn.1000-6346.2013.17.026
    [46]
    于东哉. 枸杞生长的气候条件分析[J]. 农业与技术, 2012, 32(6):145. doi: 10.3969/j.issn.1671-962X.2012.06.111

    Yu D Z. Analysis of the climate conditions for the growth of Lycium[J]. Agriculture and Technology, 2012, 32(6): 145. doi: 10.3969/j.issn.1671-962X.2012.06.111
    [47]
    张红亮. 诺木洪种植枸杞生长的气候条件分析[J]. 农家参谋, 2018(13):74.

    Zhang H L. Analysis of the climate conditions for the growth of Lycium planted in Nomuhong[J]. The Farmers Consultant, 2018(13): 74.
    [48]
    白丽丽, 李玉龙, 巩健, 等. 枸杞幼苗对盐胁迫的生理响应[J]. 农产品加工, 2019, 478(8):50−56.

    Bai L L, Li Y L, Gong J, et al. Physiological response of Lycium barbarum seedlings to salt stress[J]. Farm Products Processing, 2019, 478(8): 50−56.
    [49]
    李柯妮, 王康才, 梁永富, 等. 江苏省盐城地区沿海滩涂野生枸杞资源调查与质量分析评价[J]. 中国现代中药, 2015, 17(7):646−650.

    Li K N, Wang K C, Liang Y F, et al. Resource investigation and quality evaluation of Lycium chinense of coastal tidal mudflat in Yancheng, Jiangsu[J]. Modern Chinese Medicine, 2015, 17(7): 646−650.
    [50]
    李双双, 芦佳玉, 延军平, 等. 1970-2015年秦岭南北气温时空变化及其气候分界意义[J]. 地理学报, 2018, 73(1):13−24.

    Li S S, Lu J Y, Yan J P, et al. Spatiotemporal variability of temperature in northern and southern Qinling Mountains and its influence on climatic boundary[J]. Acta Geographica Sinica, 2018, 73(1): 13−24.
    [51]
    吕振刚, 李文博, 黄选瑞, 等. 气候变化情景下河北省3个优势树种适宜分布区预测[J]. 林业科学, 2019, 55(3):13−21. doi: 10.11707/j.1001-7488.20190302

    Lü Z G, Li W B, Huang X R, et al. Predicting suitable distribution area of three dominant tree species under climate change scenarios in Hebei Province[J]. Scientia Silvae Sinicae, 2019, 55(3): 13−21. doi: 10.11707/j.1001-7488.20190302

Catalog

    Article views (1735) PDF downloads (138) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return