Analysis of Morphological Variations among Seven Populations of Erythroculter ilishaeformis
Yunkai Li
Abstract
Yunkai Li
Abstract
The morphological variations among seven populations of Erythroculter ilishaeformis were analyzed in three multivariation analysis methods based on 31 proportional parameters of morphometric characters.The results of cluster analysis have revealed that the seven populations were clustered into three clades.The first group included populations of Xingkaihu Lake,Taihu Lake,Nan Wan Reservoir and the artificial cultured population;Liangzihu Lake and Sanxikou Reservoir populations were clustered as the second group;the third group was the Fuqiaohe Reservoir population alone.Principal component analysis showed that there was the most contribution of principal components to total variances in the length of head and tail among the 31 proportional parameters metric characters and truss network.Discriminant analysis indicated that the total discriminant accuracy of the discriminant functions of these populations was 90%.All results showed that there were a certain extent differences among the seven populations and the seven populations could be identified in three multivariation analysis methods.
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The morphological variations among seven populations of Erythroculter ilishaeformis were analyzed in three multivariation analysis methods based on 31 proportional parameters of morphometric characters.The results of cluster analysis have revealed that the seven populations were clustered into three clades.The first group included populations of Xingkaihu Lake,Taihu Lake,Nan Wan Reservoir and the artificial cultured population;Liangzihu Lake and Sanxikou Reservoir populations were clustered as the second group;the third group was the Fuqiaohe Reservoir population alone.Principal component analysis showed that there was the most contribution of principal components to total variances in the length of head and tail among the 31 proportional parameters metric characters and truss network.Discriminant analysis indicated that the total discriminant accuracy of the discriminant functions of these populations was 90%.All results showed that there were a certain extent differences among the seven populations and the seven populations could be identified in three multivariation analysis methods.
Key concepts: Principal component analysis, Linear discriminant analysis, Biology, Population, Statistics, Zoology, Mathematics, Demography