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引用本文:刘建勇,吴继兴,孙成波.我国东南沿海5 个波纹巴非蛤(Paphia undulata)地理群体的形态差异分析.海洋与湖沼,2010,41(1):114-120.
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我国东南沿海5 个波纹巴非蛤(Paphia undulata)地理群体的形态差异分析
刘建勇, 吴继兴, 孙成波
广东海洋大学水产学院
摘要:
采用聚类分析、主成分分析和判别分析3 种分析方法, 对我国东南沿海5 个野生波纹巴非蛤群体10 个形态性状进行比较研究。聚类分析和主成分分析结果表明, 广东东莞与福建厦门群体、广东湛江与海南海口群体的形态最为接近, 广西北海群体的趋异程度最大。主成分分析构建了3 个主成分, 贡献率: 主成分1 为23.237%, 主成分2 为16.109%, 主成分3 为13.009%, 累计贡献率为52.355%。判别分析结果表明, 5 群体间形态差异显著(P<0.01)。建立了5 群体的判别函数, 判别准确率P1 为47.1%—80.0%, P2 为45.7%—80.0%, 5 群体的综合判别率为63.8%。Mantel 检验结果表明欧氏距离与地理直线距离无明显相关性(r = 0.0822, P = 0.3820)。广西北海群体明显地与其它4 个地方分开, 可能已形成一个新的亚种。本研究可为我国巴非蛤种质资源保护及遗传育种提供依据。
关键词:  波纹巴非蛤, 地理群体, 形态差异, 多元分析
DOI:10.11693/hyhz201001016016
分类号:
基金项目:广东省科技计划项目, 2007A0204500001 号
附件
MORPHOLOGICAL VARIATIONS OF DIFFERENT GEOGRAPHIC POPULATIONS OF PAPHIA UNDULATA OFF SOUTHEAST CHINA
LIU Jian-Yong, WU Ji-Xing, SUN Cheng-Bo
Fisheries College of Guangdong Ocean University
Abstract:
With multi-variant morphological measurement data, the author used three multivariation analysis methods (cluster analysis, principal component analysis and discriminant analysis) to study the morphological variations among five geographic populations of Paphia undulata in south China: Dongguan and Zhanjiang (Guangdong), Xiamen (or Amoy, Fujian), Haikou (Hainan), and Beihai (Guangxi). Results indicate that populations of Dongguan, Xiamen, Zhanjiang and Haikou were morphologically grouped together, leaving Beihai population alone. Significant differences were found among the five populations (P<0.01) by discriminant analysis. The Mantel matrix tests of geographic and Euclidean distances indicated no significant relationship (r = 0.0822, P = 0.3820). As the Beihai population was shown quit different from other ones, it may have been generate a new subspecies. In general, the morphological variations of P. undulata may be resulted from a joint effect of genetics and environment. Therefore, more future works are called in molecular genetics for providing scientific basis for germ plasm resources protection and genetic breeding.
Key words:  Paphia undulata, Geographic population, Morphological variation, Mulitivariation analysis
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