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宜昌百里荒草山草坡群落物种分布的空间趋势分析
引用本文:辛晓平,王宗礼,李向林.宜昌百里荒草山草坡群落物种分布的空间趋势分析[J].生态学报,2003,23(8):1519-1525.
作者姓名:辛晓平  王宗礼  李向林
作者单位:1. 中国农业科学院农业自然资源与农业区划研究所,北京,100081
2. 中国农,业科学院草原研究所,呼和浩特,010010
3. 中国农业科学院畜牧研究所,北京,100091
基金项目:国家重点科技攻关资助项目 ( 960 1 60 2 0 2 ),国家“863”计划基金资助项目 ( 2 0 0 2 AA2 43 0 2 1 )~~
摘    要:通过基于CCA的趋势面分析和空间插值方法,研究了宜昌百里荒山地草场的群落结构空间变化,以及群落结构空间趋势与主要环境因子的相关性。结果表明,该群落物种空间中的群落结构面和物理空间中的空间趋势面可以很好地吻合,说明该群落的结构由一种具有强烈空间结构化特征的机制控制。对群落结构和空间趋势影响最显著的环境因素是土壤有效磷。

关 键 词:CCA排序  趋势面分析  群落结构  空间插值  草场
文章编号:1000-0933(2003)08-1519-07
收稿时间:2002/4/24 0:00:00
修稿时间:2003/5/26 0:00:00

Trend surface analysis on community structure of a grassland in Bailihuang, Yichang county
XIN Xiaoping,WANG Zongli and LI Xianglin.Trend surface analysis on community structure of a grassland in Bailihuang, Yichang county[J].Acta Ecologica Sinica,2003,23(8):1519-1525.
Authors:XIN Xiaoping  WANG Zongli and LI Xianglin
Institution:Institute of Natural Resources and Regional Planning; Chinese Academy of Agricultural Sciences; Beijing; China
Abstract:Spatial structure influenced the organization of community and ecosystem as a functional variable, other than the background in which biological and environmental factors act on community and ecosystem. This is why present-day ecologists and bio-geologists are interested in detecting the spatial arrangement of population and community. A large set of quantitative ecological methods related with spatial heterogeneity, spatial autocorrelation, spatial scales were developed in recent decades. Spatial trend surface analysis is one of the quantitative ecological methods that study the relation between spatial structure and species abundance distribution in community. In Canonical Correspondence Analysis (CCA), environmental variables can be instead by the spatial coordinates (x,y) of data points. In such case, an ordination of the species data can be obtained that will be constrained to be consistent with the spatial distribution of sampling localities. A high-degree polynomial of the x, y, x2, y2, xy and possible higher powers of basic coordinates can be used to fit to the species data in the manner of trend surface regression. A biplot of species and spatial coordinates of data points should indicate what species have the most important spatial structures. This paper studied the relation between community structure and spatial variability of a grassland in subtropical mid-mountainous region using trend surface analysis based on CCA ordination. In this paper a canonical ordination analysis on the species abundance data constrained by the spatial position of sampling localities was conducted. The first two eigenvalues are 0.116 and 0.056 respectively, they measure the species data that is explained by the first and the second canonical axes and, hence, by the spatial position of sampling localities. The first two canonical axes together account for 55.3% of the variance of 27-species-spatial localities relation, and for 18%of the total variance of species data. The community structure surface is obtained by kriging the sample scores which are weighted averages of species, while the data values for the spatial trend surface maps is based on trend surface regression function. For the canonical axis 1, the first community structure surface is pretty well approximated (correction = 87.6%) by the first spatial trend surface map. In other words, the trend surface regression function predicts the community structure from the simple knowledge of the sampling localities. The same goes for axis 2, the second community structure surface is well fitted (correction = 82.4%) with the second spatial trend surface map. This result suggests a community organization mechanism which is strongly spatial structured. Correlation between spatial trend of community structure and main environmental factors was also studied. Soil effective phosphor is significantly positively related with the first community structure surface and the first spatial trend surface, and significantly negatively related with the second community structure surface and the second spatial trend surface. That means the distribution of soil effective phosphor is spatial correlated, and soil effective phosphor affected the species combination and species abundance variance. The spatial structured distribution of soil effective phosphor is one reason of the spatial correlated community structure.
Keywords:CCA ordination  trend surface analysis  community structure
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