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缢蛏7群体的形态差异与判别分析
引用本文:刘达博,牛东红,姜志勇,李家乐.缢蛏7群体的形态差异与判别分析[J].海洋渔业,2009,31(4):363-368.
作者姓名:刘达博  牛东红  姜志勇  李家乐
作者单位:上海海洋大学水产与生命学院,农业部水产种质资源与养殖生态重点开放实验室,上海,201306
基金项目:国家高技术研究发展计划(863计划),上海市重点学科建设项目 
摘    要:运用多变量形态度量学分析方法,对我国沿海庄河、汉沽、海阳、盐城、崇明、宁波、漳州7个地理群体缢蛏的12个形态性状进行了形态差异研究。聚类分析和主成分分析结果表明,汉沽群体和海阳群体首先与庄河群体聚类,之后依次与崇明群体和盐城群体聚类,最后与宁波和漳州群体聚为一支。主成分分析构建了3个主成分,其贡献率:主成分1为36.28%,主成分2为22.23%,主成分3为12.72%,累积贡献率为71.23%。判别分析结果表明,7群体间形态差异显著(P<0.01)。建立7群体缢蛏的判别函数,其判别准确率P1为66.67%~86.67%,P2为68.96%~100%。7群体的综合判别率为77.93%。

关 键 词:缢蛏  地理群体  形态差异  判别分析

Morphological variations and discriminant analysis of seven populations of sinonovacula constricta
LIU Da-bo,NIU Dong-hong,JIANG Zhi-yong,LI Jia-le.Morphological variations and discriminant analysis of seven populations of sinonovacula constricta[J].Marine Fisheries,2009,31(4):363-368.
Authors:LIU Da-bo  NIU Dong-hong  JIANG Zhi-yong  LI Jia-le
Abstract:The multivariate morphometrics analysis method was used to study twelve morphological characters of seven geographical populations of Sinonovacula constricta from Zhuang-he, Han-gu, Hai-yang, Yan-cheng, Chong-ming, Ning-bo and Zhang-zhou, along the coast of China. The results of cluster and principal component analysis revealed that Han-gu and Hai-yang populations first clustered with Zhuang-he population, then with Chong-ming and Yan-cheng polulations, finally clustered with Ning-bo and Zhang-zhou populations. In the principal component analysis, three principal components were constructed, the contributory ratios of the three principal components were 36.28%, 22.23% and 12.72% respectively, and the cumulative contributory ratio was 71.231% . The results of discriminant analysis revealed that there were significant differences among the seven populations ( P <0.01). The discriminant functions of seven populations were established, and the accuracy was 66.67%-86.67% ( P_1) and 68.96%-100% ( P_2) respectively. The comprenensive discriminant accuracy was 77.93%.
Keywords:Sinonovacula constricta  geographic populations  morphological variation  discriminant analysis
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