[Heterogeneity of fork length-weight relationship for juvenile Engraulis japonius based on linear mixed-effects models]

Ying Yong Sheng Tai Xue Bao. 2021 Dec;32(12):4532-4538. doi: 10.13287/j.1001-9332.202112.032.
[Article in Chinese]

Abstract

In order to examine the growth heterogeneity of juvenile Engraulis japonicus, we conducted heterogeneity analysis of fork length-weight relationships of the species based on the samples of juvenile E. japonius from April to June 2019 collected from the coastal waters of Zhejiang Province by using the generalized linear model and 9 linear mixed-effect models. The results showed that the fork length of juvenile E. japonius was between 14-74 mm, with an average of 33 mm. The dominant fork length group was 21-50 mm. The weight range was 0.01-2.96 g, with an average of 0.28 g, and the dominant body weight group was 0.01-0.50 g. According to Akaike information criterion (AIC), the growth-fitting model with both months and regions random effects on the growth parameters a and b of juvenile E. japonius fitted best.The reliable prediction results was testified by the cross-validation. In the best model, the fixed value of growth parameter a was 0.24×10-5 and its estimated value did not fluctuate significantly, while the fixed value of b was 3.246 and the estimated value ranged from 3.206 to 3.272, indicating that juvenile E. japonius was under positive allometric growth. Our results suggested that month and region significantly affected the fork length-weight relationships of juvenile E. japonius.

为了研究日本鳀幼鱼生长的异质性,本研究根据2019年4—6月在浙江沿岸海域进行专项特许捕捞中采集的日本鳀幼鱼样品,采用拟合广义线性模型和9个线性混合效应模型,分析日本鳀幼鱼叉长与体重关系的异质性。结果表明: 本次采样的日本鳀幼鱼叉长范围为14~74 mm,平均叉长为33 mm,优势叉长组为21~50 mm;体重范围为0.01~2.96 g,平均体重为0.28 g,优势体重组为0.01~0.50 g。根据赤池信息准则,具有月份和水域对生长参数a、b随机效应的线性混合效应模型的拟合效果最优;交叉验证结果也证明了其预测效果最优。在最优模型中,生长参数a的固定值为0.24×10-5,其估计值波动不明显,b的固定值为3.246,估计值范围为3.206~3.272,表示日本鳀幼鱼为正异速生长。这说明月份和水域对日本鳀幼鱼叉长与体重关系具有显著影响。.

Keywords: Zhejiang coast; fork length-weight relationship; juvenile Engraulis japonius; linear mixed-effects model.

MeSH terms

  • Animals
  • Fishes*
  • Linear Models