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太平洋鲱和大西洋鲱间的形态变异研究
刘名1, 贾宁1, 赵林林1, 庄志猛2, 金显仕2, 高天翔1
1.(1中国海洋大学教育部海水养殖重点实验室,青岛 266003);2.(2中国水产科学研究院黄海水产研究所,青岛266071)
摘要:
为阐明太平洋鲱和大西洋鲱种间形态上的差异,应用单因子方差分析、聚类分析和判别分析方法对两种鱼的23个形态学参数进行了研究。单因子方差分析结果表明:14个形态参数平均值存在极显著差异 (P<0.001),且种群间差异大于种内差异。聚类分析结果显示所有82个个体明显聚成两支。所有23个形态参数的判别分析结果表明,两种间的形态差异极显著 (P< 0.001);利用挑选后的11项参数判别分析,得出判别等式,两种鱼间的形态差异仍然极显著 (P< 0.001),判别准确率100%。所有23个形态参数的差异系数全部小于Mayr的75% 法则临界值,表明两个种间形态学上虽然存在一定分化,但分化程度尚未达到亚种水平。作者推测两个种间形态上低水平的分化可能由于分化的时间较短以及相似的生活环境造成的。
关键词:  太平洋鲱Clupea pallasii  大西洋鲱 Clupea harengus  形态差异  单因子方差分析  聚类分析  判别分析  差异系数
DOI:
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基金项目:The study was supported by Ocean University of China Students Innovation Training Program, National Basic Research Program〓〓 (2006CB400607) and State 863 High Technology R&D Project of China (2006AA09Z418)
Study of morphological variations between Pacific herring Clupea pallasii and Atlantic herring Clupea harengus
Abstract:
Twenty-three morphological parameters were analyzed using ANOVA, cluster analysis and discriminant analysis to study the morphological variations between Clupea pallasii and Clupea harengus. ANOVA results showed that there were extremely significant differences (P<0.001) in the means of 14 morphological parameters, greater variance between populations than within populations. Cluster analysis suggested that all of the 82 samples were divided into two clusters. Discriminant analysis based on 23 parameters showed that there were extremely significant differences between the two species (P<0.001); discriminant analysis with 11 selected parameters gave a discriminant formula with accuracy of 100%. However, the coefficients of difference of 23 parameters suggested that the differentiations between the two species were still under the level of different geographic populations within species according to Mayr’s 75% Rule. We postulated that the small scale divergence in morphology between the two species might be caused by a recent separation and similar ecology environment.
Key words:  Pacific herring Clupea pallisii  Atlantic herring Clupea harengus  Morphological variations  ANOVA  Cluster analysis  Discriminant analysis  Coefficient of difference