中文摘要：

采用协惯量分析（PCA-CACOIA）和典范对应分析（CCA）两种排序方法,对北京小龙门林场的黄檗（Phellodendron amurense）群落进行了分析,并用Spearman秩相关系数检验了对应排序轴的相关性。两种排序方法得出的结果基本一致,两者的第一排序轴都反映了海拔高度和坡向对群落分布的影响,而各自第二、第三排序轴所代表的环境意义有所差异,并出现了交叉,但是两者的前3个排序轴均反映了海拔、坡位、土壤厚度和凋落物层厚度的变化趋势,说明在环境因子个数较少或共线性效应不明显的情况下,协惯量分析也能达到CCA的分析效果,并且在排序轴特征值解释量上高于典范对应分析。

英文摘要：

Aims Co-inertia analysis is infrequently used when there are few environmental variables or little collinearity among them. Ecologists usually prefer the widely used canonical correspondence analysis. Our objective was to compare the results of co-inertia analysis and canonical correspondence analysis in the ordination of a plant community in a habitat represented by few environmental variables. Methods We compared the results of PCA-CA co-inertia analysis （PCA-CA COIA） and canonical correspondence analysis （CCA） ordination of a Phellodendron amurense community in Xiaolong- men woodland, Beijing, China. The correlation of corresponding ordination axes of two methods was measured by Spearman＇s rho correlation. Important findings PCA-CA COIA and CCA produced mostly consistent results. Both first axes were correlated with elevation, whereas the second axis of PCA-CA COlA corresponded to the third axis of CCA and the third axis of CCA corresponded to the second axis of PCA-CA COLA. The first three axes of both methods were significantly correlated with elevation, slope position, soil thickness and litter layer thickness. The eigenvalues of the ordination axes and the cumulative percentage variance of species-environment relation in PCA-CA COIA were higher than that in CCA.