首页 > 过刊浏览>2017年第25卷第4期 >315-322. DOI:10.11926/jtsb.3702
PDF HTML阅读 XML下载 导出引用 引用提醒
浙闽樱桃地理分布模拟及气候限制因子分析
作者:
作者单位:

南京林业大学 生物与环境学院,南京林业大学 生物与环境学院,南京林业大学 生物与环境学院,南京林业大学 生物与环境学院,南京林业大学 生物与环境学院

基金项目:

江苏省林业三新工程项目（LYSX[2015]17）资助


Modeling the Geographical Distribution Pattern and Climatic Limited Factors of Cerasus schneideriana
Author:
Affiliation:

Nanjing Forestry University,Nanjing Forestry University,Nanjing Forestry University,Nanjing Forestry University,Nanjing Forestry University

  • 摘要
    • | |
  • 访问统计
    • |
  • 参考文献 [31]
    • |
  • 相似文献 [20]
    • |
  • 引证文献
    • | |
  • 文章评论
    摘要:

    为了解浙闽樱桃（Cerasus schneideriana）地理分布特征及与气候限制因子之间的关系，基于DIVA-GIS平台获取实际地理分布点的气候资料，利用BIOCLIM模型预测当下适生区范围以及预测其未来潜在分布。结果表明，浙闽樱桃实际分布区覆盖浙江、福建、安徽、江西、广西及湖南6省，浙闽交界的山区是自然分布的核心区，浙皖交界是其分布的北界。未来气候变化情境（CCM3）下，浙闽樱桃的潜在分布区概率将增大，且有北扩的趋势。主成分分析（PCA）表明，年降水量（bio12）、最湿季降雨量（bio16）、最暖季降雨量（bio18）、温度季节变化方差（bio4）是影响浙闽樱桃当下适生区的气候限制因子，频率直方图进一步确定他们的适宜范围分别为1503~2003 mm、604~951 mm、528~791 mm和601~872 （标准差*100）。ROC曲线检验表明BIOCLIM对浙闽樱桃分布预测的精度很高（AUC=0.998），结果是可信的。因此，浙闽樱桃适合生长在我国北亚热带温暖湿润区，水热因子是造成其分布格局的主导气候限制因子。

    Abstract:

    To understand the relationship between geographical distribution pattern of Cerasus schneideriana and its climatic limited factors,the DIVA-GIS software and BIOCLIM model were applied to predict the present and future potential spatial areas on the basis of actual distribution points.The results showed that the actual distributions of C.schneideriana covered 6 provinces of east China,including Zhejiang,Fujian,Anhui,Jiangxi,Guangxi and Hunan.The natural distribution core area located in mountain areas of Zhejiang-Fujian border,and the north boundary arrived at Zhejiang-Anhui border.Under future climate change situation (CCM3),the probability of potential areas of C.schneideriana would increase,and had a tendency to the north expansion.The principal component analysis (PCA) indicated that the annual precipitation (bio12),precipitation of the driest quarter (bio6),precipitation of the warmest quarter (bio18) and temperature seasonality (bio4) were the dominant factors for geographical distribution of C.schneideriana.The frequency histograms further showed the factor’s optimum range were 1503~2003 mm,604~951 mm,528~791 mm and 601~872(SD*100),respectively.Evaluation by the ROC curve proved the BIOCLIM model predicted the distribution accurately (AUC=0.998) and reliably.Therefore,these revealed that C.schneideriana were suited to live in north subtropical region of China,with warm and humid condition,water and heat were the two key climatic factors to the distribution pattern.

    参考文献
    [1] BELLARD C, BERTELSMEIER C, LEADLEY P, et al. Impacts of climate change on the future of biodiversity[J]. Ecol Lett, 2012, 15(4):365-377. doi:10.1111/j.1461-0248.2011.01736.x.
    [2] LI G Q, LIU C C, LIU Y G, et al. Advances in theoretical issues of species distribution models[J]. Acta Ecol Sin, 2013, 33(16):4827-4835. doi:10.5846/stxb201212031735. 李国庆, 刘长成, 刘玉国, 等. 物种分布模型理论研究进展[J]. 生态学报, 2013, 33(16):4827-4835. doi:10.5846/stxb201212031735.
    [3] SUTHERST R W, MAYWALD G F, KRITICOS D J. CLIMEX, Version 3. CD and user's guide[CD]. Melbourne:CSIRO, 2007.
    [4] STOCKWELL D. The GARP modelling system:Problems and solutions to automated spatial prediction[J]. Int J Geograph Inf Sci, 1999, 13(2):143-158. doi:10.1080/136588199241391.
    [5] PHILLIPS S J, ANDERSON R P, SCHAPIRE R E. Maximum entropy modeling of species geographic distributions[J]. Ecol Model, 2006, 190(3/4):231-259. doi:10.1016/j.ecolmodel.2005.03.026.
    [6] MA S M, NIE Y B, GENG Q L, et al. Impact of climate change on suitable distribution range and spatial pattern in Amygdalus mongolica[J]. Chin J Plant Ecol, 2014, 38(3):262-269. doi:10.3724/SP.J.1258. 2014.00023. 马松梅, 聂迎彬, 耿庆龙, 等. 气候变化对蒙古扁桃适宜分布范围和空间格局的影响[J]. 植物生态学报, 2014, 38(3):262-269. doi:10.3724/SP.J.1258.2014.00023.
    [7] WANG G, MENG Y Q, SUN J, et al. Modeling the geographic distribution of Rhododendron maculiferum[J]. J NE Agri For Univ (Nat Sci), 2013, 41(5):173-177. 王刚, 孟艳琼, 孙婧, 等. 麻花杜鹃的地理分布模拟[J]. 西北农林科技大学学报(自然科学版), 2013, 41(5):173-177.
    [8] JIANG J F, FAN X C, ZHANG Y, et al. Modeling the geographic distribution of three endangered Vitis species in China[J]. Chin J Ecol, 2014, 33(6):1615-1622. 姜建福, 樊秀彩, 张颖, 等. 中国三种濒危葡萄属(Vitis L.)植物的地理分布模拟[J]. 生态学杂志, 2014, 33(6):1615-1622.
    [9] ZHANG X W, LI Y, FANG Y M. Geographical distribution and prediction of potential ranges of Quercus acutissimain China[J]. Acta Bot Boreal-Occid Sin, 2014, 34(8):1685-1692. doi:10.7606/j.issn. 1000-4025.2014.08.1685. 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. doi:10.7606/j.issn.1000-4025.2014.08.1685.
    [10] ZHANG L Y, YE X B, LIU N, et al. Research on geographic distribution and potential distribution of Mucuna birdwoodiana[J]. Guihaia, 2012, 32(1):27-32. doi:10.3969/j.issn.1000-3142.2012.01.008. 张蓝月, 叶向斌, 刘念, 等. 白花油麻藤的地理分布及适生区预测[J]. 广西植物, 2012, 32(1):27-32. doi:10.3969/j.issn.1000-3142. 2012.01.008.
    [11] WANG W G, TANG X Y, ZHU Q L, et al. Predicting the impacts of climate change on the potential distribution of major native non-food bioenergy plants in China[J]. PLoS One, 2014, 9(11):e111587. doi:10. 1371/journal.pone.0111587.
    [12] HAN Y Y, WANG Y, XIANG Y, et al. Prediction of potential distribution of Bursaphelenchus xylophilus in China based on Maxent ecological niche model[J]. J Nanjing For Univ (Nat Sci), 2015, 39(1):6-10. doi:10.3969/j.issn.1000-2006.2015.01.001. 韩阳阳, 王焱, 项杨, 等. 基于Maxent生态位模型的松材线虫在中国的适生区预测分析[J]. 南京林业大学学报(自然科学版), 2015, 39(1):6-10. doi:10.3969/j.issn.1000-2006.2015.01.001.
    [13] ZHOU W, ZHAO H, YANG X. Prediction of potential geographic distribution areas for Rana catesbiana and Mikania micrantha in China using GARP modeling system[J]. J SW For Univ, 2012, 32(1):51-55. doi:10.3969/j.issn.2095-1914.2012.01.011. 周伟, 赵衡, 杨熙. 利用GARP生态位模型预测牛蛙和薇甘菊在中国的地理分布[J]. 西南林业大学学报, 2012, 32(1):51-55. doi:10. 3969/j.issn.2095-1914.2012.01.011.
    [14] KONG L B, LIN W, LI Z H, et al. A predication of potential geographic distribution of melon fruit fly based on climex and DIVA-GIS[J]. Acta Phytophyl Sin, 2008, 35(2):148-154. doi:10.3321/j. issn:0577-7518.2008.02.011. 孔令斌, 林伟, 李志红, 等. 基于CLIMEX和DIVA-GIS的瓜实蝇潜在地理分布预测[J]. 植物保护学报, 2008, 35(2):148-154. doi:10.3321/j.issn:0577-7518.2008.02.011.
    [15] ZHANG H T, LUO D, MU X D, et al. Predicting the potential suitable distribution area of the apple snail Pomacea canaliculata in China based on multiple ecological niche models[J]. Chin J Appl Ecol, 2016, 27(4):1277-1284. doi:10.13287/j.1001-9332.201604.027. 张海涛, 罗渡, 牟希东, 等. 应用多个生态位模型预测福寿螺在中国的潜在适生区[J]. 应用生态学报, 2016, 27(4):1277-1284. doi:10.13287/j.1001-9332.201604.027.
    [16] HIJMANS R J, GUARINO L, CRUZ M, et al. Computer tools for spatial analysis of plant genetic resources data:1. DIVA-GIS[J]. Plant Genet Resour Newslett, 2001(127):15-19.
    [17] XIE C P. Simple biogeography distribution picture draw based on DIVA-GIS[J]. Hubei Agri Sci, 2011, 50(11):2345-2348. doi:10. 3969/j.issn.0439-8114.2011.11.056. 谢春平. 基于DIVA-GIS生物地理分布图的绘制[J]. 湖北农业科学, 2011, 50(11):2345-2348. doi:10.3969/j.issn.0439-8114.2011.11.056.
    [18] SHAO H, TIAN J Q, GUO K, et al. Effects of sample size and species traits on performance of BIOCLIM in predicting geographical distri-bution of tree species:A case study with 12 deciduous Quercus species indigenous to China[J]. Chin J Plant Ecol, 2009, 33(5):870-877. doi:10.3773/j.issn.1005-264x.2009.05.005. 邵慧, 田佳倩, 郭柯, 等. 样本容量和物种特征对BIOCLIM模型模拟物种分布准确度的影响——以12个中国特有落叶栎树种为例[J]. 植物生态学报, 2009, 33(5):870-877. doi:10.3773/j.issn.1005-264x.2009.05.005.
    [19] LI C L, BARTHOLOMEW B. Cerasus Mill.[M]//WU C Y, RAVEN P H. Flora of China, Vol. 9. Beijing:Science Press & St. Louis:Missouri Botanical Garden Press, 2003:404-420.
    [20] CAO F X, XU Q J, CAO S J, et al. Advances of global warming impact on species distribution[J]. J CS Univ For Technol, 2008, 28(6):86-89. doi:10.3969/j.issn.1673-923X.2008.06.019. 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. doi:10.3969/j. issn.1673-923X.2008.06.019.
    [21] WU J G. Potential effects of climate change on the distribution of seven protected plants in China[J]. J Wuhan Bot Res, 2010, 28(4):437-452. doi:10.3724/SP.J.1142.2010.40437. 吴建国. 气候变化对7种保护植物分布的潜在影响[J]. 武汉植物学研究, 2010, 28(4):437-452. doi:10.3724/SP.J.1142.2010.40437.
    [22] CHEN L N. The research of the evaluation of Cerasus cultivars ornamental characteristics and the suitable areas for growing wild Chinese Cerasus in Zhejiang[D]. Hangzhou, China:Zhejiang Sci-Tech University, 2015:1-139. 陈丽娜. 樱属品种观赏性状评价及中国野生种浙江适生区研究[D]. 浙江杭州:浙江理工大学, 2015:1-139.
    [23] HACK J J, KIEHL J T, HURRELL J W. The hydrologic and thermo-dynamic characteristics of the NCAR CCM3[J]. J Climate, 1998, 11(6):1179-1206. doi:10.1175/1520-0442(1998)011<1179:THATCO>2.0.CO;2.
    [24] WANG J, NI J. Modelling the distribution of five Caragana species in temperate northern China[J]. Chin J Plant Ecol, 2009, 33(1):12-24. doi:10.3773/j.issn.1005-264X.2009.01.002. 王娟, 倪健. 中国北方温带地区5种锦鸡儿植物的分布模拟[J]. 植物生态学报, 2009, 33(1):12-24. doi:10.3773/j.issn.1005-264X.2009. 01.002.
    [25] LEI J C, XU H G, WU J, et al. Advance in predicting the suitable habitat of species under future climate change[J]. Sichuan J Zool, 2015, 35(5):794-800. doi:10.11984/j.issn.1000-7083.20140487. 雷军成, 徐海根, 吴军, 等. 气候变化情景下物种适宜生境预测研究进展[J]. 四川动物, 2015, 35(5):794-800. doi:10.11984/j.issn. 1000-7083.20140487.
    [26] ROOT T L, PRICE J T, HALL K R, et al. Finger prints of global warming on wild animals and plants[J]. Nature, 2003, 421(6981):57-60. doi:10.1038/nature01333.
    [27] ZHANG L, LIU S R, SUN P S, et al. Comparative evaluation of multiple models of the effects of climate change on the potential distribution of Pinus massoniana[J]. Chin J Plant Ecol, 2011, 35(11):1091-1105. doi:10.3724/SP.J.1258.2011.01091. 张雷, 刘世荣, 孙鹏森, 等. 气候变化对马尾松潜在分布影响预估的多模型比较[J]. 植物生态学报, 2011, 35(11):1091-1105. doi:10. 3724/SP.J.1258.2011.01091.
    [28] NI J, SONG Y C. Potential changes under elevated Carbon dioxide of dominants and companions of evergreen broadleaved forest in sub-tropical China[J]. Acta Phytoecol Sin, 1997, 21(5):455-467. 倪健, 宋永昌. CO2倍增条件下中国亚热带常绿阔叶林优势种及常见种分布区的可能变迁[J]. 植物生态学报, 1997, 21(5):455-467.
    [29] LI M, YI X G, WANG H C, et al. Studies on the relationship between Cerasus serrulata distribution region and the environmental factors[J]. J Nanjing For Univ (Nat Sci), 2014, 38(S):74-80. doi:10.3969/j.issn. 1000-2006.2014.S1.016. 李蒙, 伊贤贵, 王华辰, 等. 山樱花地理分布与水热环境因子的关系[J]. 南京林业大学学报(自然科学版), 2014, 38(S):74-80. doi:10. 3969/j.issn.1000-2006.2014.S1.016.
    [30] LIU H L, ZHANG L W, ZHANG H X, et al. Distribution pattern of species richness for wild fruit trees in Xinjiang based on species distribution modeling[J]. Sci Silv Sin, 2015, 51(12):1-8. doi:10. 11707/j.1001-7488.20151201. 刘会良, 张玲卫, 张宏祥, 等. 基于物种分布模型的新疆野生果树物种丰富度分布格局[J]. 林业科学, 2015, 51(12):1-8. doi:10. 11707/j.1001-7488.20151201.
    [31] LI Y, ZHANG X W, FANG Y M. Responses of the distribution pattern of Quercus chenii to climate change following the Last Glacial Maximum[J]. Chin J Plant Ecol, 2016, 40(11):1164-1178. doi:10. 17521/cjpe.2016.0032. 李垚, 张兴旺, 方炎明. 小叶栎分布格局对末次盛冰期以来气候变化的响应[J]. 植物生态学报, 2016, 40(11):1164-1178. doi:10. 17521/cjpe.2016.0032.
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

朱弘,尤禄祥,李涌福,王华辰,王贤荣.浙闽樱桃地理分布模拟及气候限制因子分析[J].热带亚热带植物学报,2017,25(4):315~322

复制
分享
文章指标
  • 点击次数:1684
  • 下载次数: 1923
  • HTML阅读次数: 338
  • 引用次数: 0
历史
  • 收稿日期:2016-11-21
  • 最后修改日期:2017-01-15
  • 录用日期:2017-04-11
  • 在线发布日期: 2017-07-18
文章二维码
您是第16728123 位访问者
主管单位：中国科学院
主办单位：中国科学院华南植物园 广东省植物学会
地址：广州市天河区兴科路723号 中国科学院华南植物园 《热带亚热带植物学报》编辑部
电话：86 (0)20-3725 2514
热带亚热带植物学报 ® 2025 版权所有