地理科学进展 ›› 2009, Vol. 28 ›› Issue (3): 449-459.doi: 10.11820/dlkxjz.2009.03.019

• 生态与环境变化 • 上一篇    下一篇

天山—阿尔泰山拟南芥种群分布与环境的关系

陶冶1,2,3|刘彤1   

  1. 1. 石河子大学生命科学学院|石河子 832000; 2. 中国科学院新疆生态与地理研究所|乌鲁木齐 830011;
    3. 中国科学院研究生院, 北京 100049
  • 出版日期:2009-05-25 发布日期:2009-05-25
  • 通讯作者: 刘 彤 (1968-),男,博士,教授 E-mail:liutong1968@yahoo.com.cn
  • 作者简介:陶 冶 (1983-)|男|安徽宿州人|硕士研究生|研究方向: 植物生态。E-mail: xishanyeren@163.com
  • 基金资助:

    国家自然科学基金项目(30760047);中国大学生环境教育基地科研资助项目

Relationships between Arabidopsis thaliana Populations Distribution and Environmental Factors in the Tianshan-Altay Mountain Region, China

TAO Ye1,2,3, LIU Tong1   

  1. 1. College of Life Sciences, Shihezi University, Shihezi 832000, China|
    2. Xinjiang Institute of Ecology and Geography, CAS, Urumqi 830011, China|
    3. Graduate University of Chinese Academy of Sciences, Beijing 100049, China
  • Online:2009-05-25 Published:2009-05-25

摘要:

中国的天山及其附近山脉是世界拟南芥及其近缘种的主要分布区之一。在对天山—阿尔泰山的浅山地带拟南芥生存分布多年调查的基础上,选取13个代表性样地及18个相关环境因子,研究了拟南芥种群生存分布与环境因子的关系。结果表明:双向指示种分析(TWINSPAN)将13个拟南芥样地分为4个群落类型:新疆绢蒿、新疆绢蒿—猪毛菜、新疆绢蒿—刺叶锦鸡儿—草原苔草、勿忘草—密穗雀麦—草原苔草4类,各类型对应的环境因子异质性明显。不同群落类型在去势对应分析(DCA)、主成分分析(PCA)和典范对应分析(CCA)各排序图中区分明显,与物种对应较好,与TWINSPAN分类结果基本一致。环境因子的PCA分析发现,坡向、有机质、电导率、pH、土壤含水量和有效钾(均为2个土层)是导致样地间环境异质的主要因素,且这些因子间多呈显著关联。CCA分析发现坡向、有机质、pH、电导率和土壤含水量(均为2个土层)与排序轴相关性最大,分析认为上述环境因子是决定物种分布及多样性格局的主导因子,与环境因子的PCA分析结果基本一致。研究还发现,坡向、土壤含水量(第2层)、有机质(第1层)和pH(两层)是影响各样地十字花科种数变化的主要因素,电导率(第1层)是影响拟南芥数量分布的主要因素。

关键词: 植被—环境关系;地形因子;土壤因子;分类与排序;相关分析;环境异质性;新疆

Abstract:

Tianshan Mountains and the nearby mountains are one of the main distribution regions of Arabidopsis thaliana and its closely related species in the world. Based on comprehensive field surveys on the distribution of A. thaliana in the Tianshan-Altay mountain region, 13 plots in low mountain zone Shihezi, the 143rd Corps, Shawan, Dushanzi, Yili Guozigou, Emin and Altay were selected and 18 environmental factors were measured, the relationship between A. thaliana populations distribution and environmental factors were studied. Classification of the vegetation was analyzed using two-way indicator species analysis (TWINSPAN) technique. Ordination techniques as detrended correspondence analysis (DCA), principal component analysis (PCA) and canonical correspondence analysis (CCA) were used to examine the relationships between vegetation and environmental parameters. Lastly, the correlation coefficients between cruciferous species, A. thaliana and environmental variables were also examined. The results showed that 13 plots were classified into 4 community types by TWINSPAN using important values (IV) data of 53 main species: Seriphidium kaschgaricum, Seriphidium kaschgaricum-Salsola collina, S.kaschgaricum-Cara acanthophylla-Carex liparocarpos, and Myosotis sylvatica-Bromus sewerzowii-C. liparocarpos. And environmental heterogeneity obviously appeared between each community type. Distributions of community types in DCA, PCA and CCA ordination figures showed obvious distinction, and they corresponded to species distribution well. The result was basically the same as TWINSPAN classification. PCA analysis on environmental factors showed that slope, organic matter, electric conductivity, pH, soil moisture and available potassium (both 2 soil layers) were the main factors affecting environmental heterogeneity in different plots, and these factors were most significantly associated with each other. CCA analysis showed that slope, organic matter, pH, electrolytic conductivity and soil moisture (both 2 soil layers) were associated with ordination axes, this result indicated that those environmental variables were the dominant factors to determine the patterns of species distribution and plant diversity, and it is the same as PCA basically. The study also found that aspect, soil water content (2nd layer), organic matter (1st layer) and pH (2 layers) were the major factors impacting the change in the number of Cruciferae species, and electrolytic conductivity (1st layer) played an very important role in the number distribution of A. thaliana.

Key words: classification and ordination, correlation analysis, environmental heterogeneity, soil factor, terrain factor, vegetation-environment relationship, Xinjiang