Morphological Variation among Wild Populations of Charybdis japonica from Coastal Waters of China
Zheng We
Abstract
Zheng We
Abstract
Morphological variation among seven geographic populations of Charybdis japonica was studied using one way-ANOVA analysis, principal component analysis, cluster analysis and discriminant analysis. One way-ANOVA analysis revealed the difference among C. japonica populations below geographical population levle. The cluster analysis showed that different C. japonica populations generally gathering in line with the distribution of different sea areas, and there was no apparent clustering related to the geographical distance. The principal component analysis resulted in four principal components, the contributory ratios of the four principal components were 47.639%, 19.004%, 12.270% and 10.178% respectively, and the cumulative contributory ratio was 89.090%. The discriminant analysis revealed that the discriminant accuracy of Weihai and Zhoushan population were the lowest and both were 40%, the discriminant accuracy of Yangtze estuary was the highest and was 73.3%, and the average discriminant accuracy was 56.5%. The contributory ratios of twocanonical discriminant functions established by discriminant analysis were 76.4% and 14.2%, respectively, and the cumulative contributory ratio was 90.7%. The discriminant analysis was almost the same with cluster analysis. This research showed that there were morphological differences between C. japonica populations in East China Sea, Bohai Sea and Yellow Sea.
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Morphological variation among seven geographic populations of Charybdis japonica was studied using one way-ANOVA analysis, principal component analysis, cluster analysis and discriminant analysis. One way-ANOVA analysis revealed the difference among C. japonica populations below geographical population levle. The cluster analysis showed that different C. japonica populations generally gathering in line with the distribution of different sea areas, and there was no apparent clustering related to the geographical distance. The principal component analysis resulted in four principal components, the contributory ratios of the four principal components were 47.639%, 19.004%, 12.270% and 10.178% respectively, and the cumulative contributory ratio was 89.090%. The discriminant analysis revealed that the discriminant accuracy of Weihai and Zhoushan population were the lowest and both were 40%, the discriminant accuracy of Yangtze estuary was the highest and was 73.3%, and the average discriminant accuracy was 56.5%. The contributory ratios of twocanonical discriminant functions established by discriminant analysis were 76.4% and 14.2%, respectively, and the cumulative contributory ratio was 90.7%. The discriminant analysis was almost the same with cluster analysis. This research showed that there were morphological differences between C. japonica populations in East China Sea, Bohai Sea and Yellow Sea.
Key concepts: Linear discriminant analysis, Principal component analysis, Japonica, Discriminant function analysis, Population, Biology, Statistics, Geography