The feature of morphological traits and their effects on body weight in the red crab (Charybdis feriata)

Key Laboratory of East China Sea and Oceanic Fishery Resources Exploitation, Ministry of Agriculture, East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai, China
DOI
10.7287/peerj.preprints.1620v1
Subject Areas
Aquaculture, Fisheries and Fish Science, Conservation Biology, Marine Biology, Zoology
Keywords
Correlation analysis, Morphological traits, Path analysis, Regression analysis, Charybdis Feriata
Copyright
© 2015 Zou et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
Cite this article
Zou X, Ma H, Lu J, Gong Y, Xia L. 2015. The feature of morphological traits and their effects on body weight in the red crab (Charybdis feriata) PeerJ PrePrints 3:e1620v1

Abstract

The red crab (Charybdis feriata) is one of most important fishery resources in China. In the present study, we first measured 17 morphological traits and body weight of C. feriata, characterized these 18 traits, and then estimated the effects of morphological traits on body weight by statistical methods including correlation coefficients, determination coefficients, path coefficients, and regression equation. All correlation coefficients between 17 morphological traits and body weight reached an extremely significant level (P<0.01). Determination and path coefficients analysis revealed the real correlation relationship between the independent variables and the dependent variable. Significant path coefficients were found between three morphological traits (stemum width, X8; meropodite length of pereopod 3, X16; meropodite length of pereopod 4, X17) and body weight that suggested these three traits were the key traits directly influence body weight. Multiple correlation index (R2) between above three morphological traits and body weight was of 0.977, which indicated that the main independent variables influencing body weight has been found. Finally a best-fit linear regression equation was established as Y = 13.078 X8 + 7.048 X16 - 4.902 X17 - 576.635, which provided an ideal model for better understanding the feature of morphological traits and body weight of C. feriata.

Author Comment

This is a submission to PeerJ for review.

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