文献类型： 外文期刊

作者： Wang Yingjun ¹ ; Ye Zhenjiang ¹ ; Liu Qun ¹ ; Wang Weiling ¹ ; Cao Liang ² ; Shen Wei ⁴ ;

作者机构： 1.Ocean Univ China, Coll Fisheries, Qingdao 266003, Peoples R China

2.Chinese Acad Sci, Inst Oceanol, Key Lab Marine Ecol & Environm Sci, Qingdao 266071, Peoples R China

3.Chinese Acad Fishery Sci, Yellow Sea Fisheries Res Inst, Key Lab Sustainable Utilizat Marine Fishery Resou, Qingdao 266071, Peoples R China

4.Minist Agr, Key Lab Marine & Estuarine Fisheries Resources &, Shanghai 200090, Peoples R China

关键词： Synechogobius ommaturus;otolith chemistry;stock identification

期刊名称：CHINESE JOURNAL OF OCEANOLOGY AND LIMNOLOGY （ 影响因子：1.068； 五年影响因子：0.983 ）

ISSN： 0254-4059

年卷期： 2011 年 29 卷 3 期

页码：

收录情况： SCI

摘要： This study explores the potential existence of local stocks of Synechogobius ommaturus using otolith chemical signatures. The concentrations of 10 elements (K, Ca, Na, Mg, Sr, Pb, Ba, Mn, Co, Zn) in the otoliths from eight stocks (Dandong, Dalian, Tianjin, Dongying, Weihai, Qingdao, Ganyu and Xiamen) of S. ommaturus were measured by Inductively Coupled Plasma Mass Spectrometry and regressed against otolith weight. No significant correlation between otolith weight and concentrations of Na, Mg, Ca, Sr, Co, Ba, Zn and Pb were observed. Concentrations of K and Mn were correlated with otolith weight. Consequently, the residuals of the regressions were used instead of the original concentrations in subsequent analyses. Analysis of variance (ANOVA) showed no significant difference between males and females in otolith chemical signatures. Differences were found among the locations for K, Sr, Mn, Co, Ba, Pb, but not for Ca, Na, Mg and Zn. Residuals of the regressions of elemental concentrations against otolith weight that fitted the normal distribution and homogeneity were studied by discriminant analysis. The success of the discriminant function to predict the location of S. ommaturus capture ranged from 100% for Weihai and Xiamen stocks, to only 44.4% and 62.5% for Qingdao and Dandong stocks, respectively. The average prediction success was 80.3%.