中国五类重要桦木属植物群系气候生态位
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摘要
选择我国面积大、分布广泛、资源数量多的五类桦木属植物群系(白桦(Betula.platyphylla)、黑桦(B.dahurica)、红桦(B.albosinensis)、亮叶桦(B.luminifera)、枫桦(B.costata)),在群系水平上探讨其气候生态位,通过拟合Weibull概率密度函数,定量分析其地理分布与各气象指标间的关系,据此估计其气候生态位核心分布区与最大分布范围,并以ROC曲线法检验各类桦木属植物群系的超体积生态位模拟的准确程度,结果均为极满意。说明综合文中几项气象指标可以较为准确的模拟五类桦木属植物群系(亚群系)的气候生态位模型。应用PCA双序分析,探讨了不同气象指标最适生态位与生态幅宽度对桦属植物分布的影响。显示,白桦属低温、低湿、宽生态幅种,红桦属高温、高湿、宽生态幅种;枫桦与黑桦属低温、低湿、窄生态幅种;亮叶桦属高温、高湿、窄生态幅种。白桦、红桦群系表现出较宽生态幅,与最适生态位指标相关性相对较弱。枫桦、黑桦群系分布特征受极端低温(T_(min))、最冷月均温(Tc)、年均降雨量(AP)、Kira温暖度指数(W_I)四项生态幅指标相关性较强,与最低温和蒸发量指标存在较强的正相关性,与年均温存在较强负相关。亮叶桦群系分布与最热月均温(Tw)、湿润指数(HI)、温暖指数(WI)及年均降雨量(AP)存在较强正相关,与极端低温(T_(min))、最冷月均温(Tc)等存在强负相关。研究成果可用于指导各类桦属植物的种质保护、引种绿化,同时在全球气候变化的背景下,可为五类桦属植物的潜在种质区域迁移提供科学依据。
Five widely distributed and resources abundant Betula [Betula platyphylla,B. dahurica,B. albosinensis,B. luminifera,B. costata] in China were chosen and their climatic ecological niche in formation level were studied. Weibull probability density function was used to quantitative analyze the relationship between each geographical distribution and climatic indices, and climatic niche core distribution area and maximum distribution range were estimated. The accuracy of the ultra-volume niche simulation of various species of Betula genus was tested by ROC curve method, and the results were extremely satisfactory, that indicated that several meteorological indicators in the comprehensive text can accurately simulate the climate niche model of five types of birch vegetation groups(sub-groups). PCA double-sequence analysis was used to explore the effect of the optimal niche of different meteorological indicators on the distribution of birch plants. The results showed that B. platyphylla belongs to low temperature and low humidity wide niche species, B. costata and B.dahurica belong to low temperature, low humidity and narrow niche species; B. luminifera belongs to high temperature, high humidity and narrow niche species. B. platyphylla and B. albosinensis showed a wider niche, and have relatively weak correlation with the optimal niche index. The distribution of B. costata and B.dahurica are strongly correlated with the four ecological indicators: extreme low temperature(T_(min)), coldest monthly average temperature(T_c), annual average precipitation(AP), and Kira warmness index(W_I). B. platyphylla and B. albosinensis show a strong positive correlation with the lowest temperature(T_(min)) and evaporation, and a strong negative correlation with the annual average temperature(T). There is a strong positive correlation between the distribution of B. luminifera and the hottest monthly mean temperature(Tw), wetness index(H_I), warming index(W_I) and average annual precipitation(AP), while a strong negative correlation with extreme low temperature(T_(min)) and coldest monthly average temperature(T_c). The research results can be used to guide the germplasm protection, introduction and greening of various birch plants, and provide a scientific basis for the migration of potential germplasm regions of five species of Betula in the context of global climate change.
Five widely distributed and resources abundant Betula [Betula platyphylla,B. dahurica,B. albosinensis,B. luminifera,B. costata] in China were chosen and their climatic ecological niche in formation level were studied. Weibull probability density function was used to quantitative analyze the relationship between each geographical distribution and climatic indices, and climatic niche core distribution area and maximum distribution range were estimated. The accuracy of the ultra-volume niche simulation of various species of Betula genus was tested by ROC curve method, and the results were extremely satisfactory, that indicated that several meteorological indicators in the comprehensive text can accurately simulate the climate niche model of five types of birch vegetation groups(sub-groups). PCA double-sequence analysis was used to explore the effect of the optimal niche of different meteorological indicators on the distribution of birch plants. The results showed that B. platyphylla belongs to low temperature and low humidity wide niche species, B. costata and B.dahurica belong to low temperature, low humidity and narrow niche species; B. luminifera belongs to high temperature, high humidity and narrow niche species. B. platyphylla and B. albosinensis showed a wider niche, and have relatively weak correlation with the optimal niche index. The distribution of B. costata and B.dahurica are strongly correlated with the four ecological indicators: extreme low temperature(T_(min)), coldest monthly average temperature(T_c), annual average precipitation(AP), and Kira warmness index(W_I). B. platyphylla and B. albosinensis show a strong positive correlation with the lowest temperature(T_(min)) and evaporation, and a strong negative correlation with the annual average temperature(T). There is a strong positive correlation between the distribution of B. luminifera and the hottest monthly mean temperature(Tw), wetness index(H_I), warming index(W_I) and average annual precipitation(AP), while a strong negative correlation with extreme low temperature(T_(min)) and coldest monthly average temperature(T_c). The research results can be used to guide the germplasm protection, introduction and greening of various birch plants, and provide a scientific basis for the migration of potential germplasm regions of five species of Betula in the context of global climate change.
引文
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[21] 应俊生.秦岭植物区系的性质、特点和起源[J].植物分类学报,1994,32(5):389-410.
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[23] Jiguet F,Gregory R D,Devictor V,et al.Population trends of European common birds are predicted by characteristics of their climatic niche[J].Global change biology,2010,16(2):497-505.
[24] Box I E.Herben T.E.O.Box macroclimate and plant forms:An introduction to predictive modeling in phytogeography[J].Folia Geobotanica Et Phytotaxonomica,2010,18(1):28-28.
[25] 蒋霞,倪健.西北干旱区10种荒漠植物地理分布与大气候的关系及其可能潜在分布区的估测[J].植物生态学报,2005,29(1):98-107.
[26] 刘丽华.桦树天然林生长发育规律的研究[D].保定:河北农业大学,2002:10.
[2] 方精云.植物气候生态位及三维空间分布的图示化-以水青冈属为例[J].山地学报,1999,17(1):35-40.
[3] Simon L M,Oliveira G,Barreto B S,et al.Effects of global climate changes on geographical distribution patterns of economically important plant species in cerrado[J].Revista árvore,2013,37(2):267-274.
[4] Klein D R,Bruun H H,Lundgren R,et al.Climate change influences on species interrelationships and distributions in high-Arctic greenland[J].Advances in Ecological Research,2008,40(7):81-100.
[5] Mateo R G,Gastón A,Aroca-Fernández M J,et al.Optimization of forest sampling strategies for woody plant species distribution modelling at the landscape scale[J].Forest Ecology & Management,2018,410:104-113.
[6] Fiaboe K K M,Peterson A T,Kairo M T K,et al.Predicting the potential worldwide distribution of the red palm weevil Rhynchophorus ferrugineus (Olivier) (Coleoptera:Curculionidae) using ecological niche modeling[J].Florida Entomologist,2012,95(3):659-673.
[7] 姜景民.中国桦木属植物地理分布的研究[J].林业科学研究,1990,3(1):55-62.
[8] 徐文铎.吉良的热量指数及其在中国植被中的应用[J].生态学杂志,1985(3):35-39.
[9] 张新时.植被的PE(可能蒸散)指标与植被-气候分类(二)-几种主要方法与PEP程序介绍[J].植物生态学与地植物学学报,1989,13(3):197-207.
[10] 孟猛,倪健,张治国.地理生态学的干燥度指数及其应用评述[J].植物生态学报,2004,28(6):853-861.
[11] 杨志香,周广胜,殷晓洁,贾丙瑞.中国兴安落叶松天然林地理分布及其气候适宜性[J].生态学杂志,2014,33(6):1429-1436.
[12] Fang J,Lechowicz M J.Climatic limits for the present distribution of beech (Fagus L.) species in the world[J].Journal of Biogeography,2006,33(10):1804-1819.
[13] R?hrig E,Ulrich B.Ecosystems of the World 7.Temperate Deciduous Forests[M].Amsterdam:Elsevier Science Publishers BV,1991:377-502.
[14] 曹伟,郑美林,刘童燕.东北地区主要树种分布与气候的关系[J].干旱区资源与环境,2013,27(3):132-136.
[15] 王运生,谢丙炎,万方浩,肖启明,戴良英.ROC曲线分析在评价入侵物种分布模型中的应用[J].生物多样性,2007,15(4):365-372.
[16] Carpenter G,Gillison A N,Winter J.DOMAIN:a flexible modelling procedure for mapping potential distributions of plants and animals[J].Biodiversity & Conservation,1993,2(6):667-680.
[17] 邵慧,田佳倩,郭柯,孙建新.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.
[18] Shelford V E.Animal Communities in Temperate America as Illustrated by the Chicago Region[M].Chicago :University of Chicago Press,1913:326.
[19] Wiley E O,Mcnyset K M,Peterson A T,et al.Niche modeling and geographic range predictions in the marine environment using a machine-learning algorithm[J].Oceanography,2003,16(3):120-127.
[20] Song C,Huang C,Liu H.Predictive vegetation mapping approach based on spectral data,DEM and generalized additive models[J].Chinese Geographical Science,2013,23(3):331-343.
[21] 应俊生.秦岭植物区系的性质、特点和起源[J].植物分类学报,1994,32(5):389-410.
[22] Schall J J,Pianka E R.Geographical trends in numbers of species[J].Science,1978,201(4357):679-686.
[23] Jiguet F,Gregory R D,Devictor V,et al.Population trends of European common birds are predicted by characteristics of their climatic niche[J].Global change biology,2010,16(2):497-505.
[24] Box I E.Herben T.E.O.Box macroclimate and plant forms:An introduction to predictive modeling in phytogeography[J].Folia Geobotanica Et Phytotaxonomica,2010,18(1):28-28.
[25] 蒋霞,倪健.西北干旱区10种荒漠植物地理分布与大气候的关系及其可能潜在分布区的估测[J].植物生态学报,2005,29(1):98-107.
[26] 刘丽华.桦树天然林生长发育规律的研究[D].保定:河北农业大学,2002:10.