Comparative study of otolith and sulcus morphology for stock discrimination of yellow drum along the Chinese coast

  • Junjie Song
  • Bo Zhao
  • Jinhu Liu
  • Liang Cao
  • Shuozeng DouEmail author


Otolith morphology is widely used for fish stock identification. The sulcus, a structure on the medial side of the otolith, is an important feature in morphological analysis. This study was conducted to evaluate the feasibility of using sulcus morphology for stock identification and to compare its performance with commonly used otolith morphology analysis. Otoliths were collected and analyzed from three geographical groups (the Huanghe (Yellow) River estuary, HHE; the Jiaozhou Bay, JZB; and the Changjiang (Yangtze) River estuary, CJE) of yellow drum Nibea albiflora. The results show that the analysis of sulcus morphology based on shape indices (SIs), elliptic Fourier coefficients (EFc), and a combination of the two parameters identified stocks at overall classification rates of 51.0%, 72.5%, and 73.2%, respectively. These classification rates are similar to those obtained using otolith morphology analysis (57.0%, 73.8%, and 76.5% by SIs, EFc, and their combination, respectively). The findings suggest that sulcus morphology is comparable to the commonly used otolith morphology for identifying stocks of sciaenids, such as the yellow drum. For both otolith and sulcus morphology, EFc could identify the stocks more efficiently than SIs, while the combination of SIs and EFc was even better.


otolith sulcus shape indices elliptic Fourier analysis stock discrimination Nibea albiflora 


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We thank Dr. YU Xin, Ocean University of China, for his help in the statistical analysis.

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  1. Agüera A, Brophy D. 2011. Use of saggital otolith shape analysis to discriminate Northeast Atlantic and Western Mediterranean stocks of Atlantic saury, Scomberesox saurus saurus (Walbaum). Fish. Res., 110(3): 465–471.CrossRefGoogle Scholar
  2. Avigliano E, Comte G, Rosso J J, Mabragaña E, Rosa P D, Sanchez S, Volpedo A, del Rosso F, Schenone N F. 2015. Identification of fish stocks of river crocker (Plagioscion ternetzi) in Paraná and Paraguay rivers by using otolith morphometric analysis. Lat. Am. J. Aquat. Res., 43(4): 718–725.Google Scholar
  3. Avigliano E, Martinez C F R, Volpedo A V. 2014. Combined use of otolith microchemistry and morphometry as indicators of the habitat of the silverside (Odontesthes bonariensis) in a freshwater–estuarine environment. Fish. Res., 149: 55–60.CrossRefGoogle Scholar
  4. Begg G A, Brown R W. 2000. Stock identification of haddock Melanogrammus aeglefinus on Georges Bank based on otolith shape analysis. Trans. Am. Fish. Soc., 129(4): 935–945.CrossRefGoogle Scholar
  5. Begg G A, Waldman J R. 1999. An holistic approach to fish stock identification. Fish. Res., 43 (1–3): 35–44.CrossRefGoogle Scholar
  6. Bolles K L, Begg G A. 2000. Distinction between silver hake (Merluccius bilinearis) stocks in U.S. waters of the northwest Atlantic based on whole otolith morphometrics. Fish. Bull., 98(3): 451–462.Google Scholar
  7. Campana S E, Casselman J M. 1993. Stock discrimination using otolith shape analysis. Can. J. Fish. Aquat. Sci., 50(3): 1 062–1 083.CrossRefGoogle Scholar
  8. Campana S E, Neilson J D. 1985. Microstructure of fish otoliths. Can. J. Fish. Aquat. Sci., 42(5): 1 014–1 032.CrossRefGoogle Scholar
  9. Cardinale M, Doering–Arjes P, Kastowsky M, Mosegaard H. 2004. Effects of sex, stock, and environment on the shape of known–age Atlantic cod (Gadus morhua) otoliths. Can. J. Fish. Aquat. Sci., 61(2): 158–167.CrossRefGoogle Scholar
  10. Castonguay M, Simard P, Gagnon P. 1991. Usefulness of Fourier analysis of otolith shape for Atlantic mackerel (Scomber scombrus) stock discrimination. Can. J. Fish. Aquat. Sci., 48(2): 296–302.CrossRefGoogle Scholar
  11. Chen D G. 1991. Fish Ecology of the Bohai Sea and Yellow Sea. Ocean Press, Beijing. p.288–292. (in Chinese)Google Scholar
  12. Chen J S. 2006. Theories of River Water Quality and Water Quality of Chinese Rivers. Science Press, Beijing. p.103–168. (in Chinese)Google Scholar
  13. Crampton J S. 1995. Elliptic Fourier shape analysis of fossil bivalves: some practical considerations. Lethaia, 28(2): 179–186.CrossRefGoogle Scholar
  14. de Carvalho B M, Vaz–dos–Santos A M, Spach H L, Volpedo A V. 2015. Ontogenetic development of the sagittal otolith of the anchovy, Anchoa tricolor, in a subtropical estuary. Sci. Mar., 79(4): 409–418.Google Scholar
  15. Ferguson G J, Ward T M, Gillanders B M. 2011. Otolith shape and elemental composition: complementary tools for stock discrimination of mulloway (Argyrosomus japonicus) in southern Australia. Fish. Res., 110(1): 75–83.CrossRefGoogle Scholar
  16. Fisheries and Fisheries Administration of the Ministry of Agriculture. 2016. China Fisheries Yearbook. China Agriculture Press, Beijing. 45p. (in Chinese)Google Scholar
  17. Gauldie R W. 1988. Function, form and time–keeping properties of fish otoliths. Comp. Biochem. Physiol. A: Physiol., 91(2): 395–402.CrossRefGoogle Scholar
  18. Han Z Q, Gao T X, Yanagimoto T, Sakurai Y. 2008. Genetic population structure of Nibea albiflora in Yellow Sea and East China Sea. Fish. Sci., 74(3): 544–552.CrossRefGoogle Scholar
  19. Hilborn R, Walters C J. 1992. Quantitative Fisheries Stock Assessment: Choice, Dynamics, and Uncertainty. Chapman and Hall, New York. 67p.CrossRefGoogle Scholar
  20. Kuhl F P, Giardina C R. 1982. Elliptic Fourier features of a closed contour. Comput. Graph. Image Process., 18(3): 236–258.CrossRefGoogle Scholar
  21. Li X Z, Liu L S, Li B Q. 2010. Macrobenthos in China Sea: Research and Practice. Ocean Press, Beijing. 378p. (in Chinese)Google Scholar
  22. Libungan L A, Pálsson S. 2015. ShapeR: an R package to study otolith shape variation among fish populations. PLoS One, 10 (3): e0121102.CrossRefGoogle Scholar
  23. Lleonart J, Salat J, Torres G J. 2000. Removing allometric effects of body size in morphological analysis. J. Theor. Biol., 205(1): 85–93.CrossRefGoogle Scholar
  24. Montanini S, Stagioni M, Valdrè G, Tommasini S, Vallisneri M. 2015. Intra–specific and inter–specific variability of the sulcus acusticus of sagittal otoliths in two gurnard species (Scorpaeniformes, Triglidae). Fish. Res., 161: 93–101.CrossRefGoogle Scholar
  25. Monteiro L R, Di Beneditto A P M, Guillermo L H, Rivera L A. 2005. Allometric changes and shape differentiation of sagitta otoliths in sciaenid fishes. Fish. Res., 74 (1–3): 288–299.CrossRefGoogle Scholar
  26. Næs T, Mevik B H. 2001. Understanding the collinearity problem in regression and discriminant analysis. J. Chemom., 15(4): 413–426.CrossRefGoogle Scholar
  27. Olejnik S F, Algina J. 1984. Parametric ANCOVA and the rank transform ANCOVA when the data are conditionally nonnormal and heteroscedastic. J. Educ. Behav. Stat., 9(2): 129–149.CrossRefGoogle Scholar
  28. Parisi–Baradad V, Lombarte A, Garcia–Ladona E, Cabestany J, Piera J, Chic O. 2005. Otolith shape contour analysis using affine transformation invariant wavelet transforms and curvature scale space representation. Mar. Freshw. Res., 56(5): 795–804.CrossRefGoogle Scholar
  29. Petursdottir G, Begg G A, Marteinsdottir G. 2006. Discrimination between Icelandic cod (Gadus morhua L.) populations from adjacent spawning areas based on otolith growth and shape. Fish. Res., 80 (2–3): 182–189.CrossRefGoogle Scholar
  30. Stransky C, Murta A G, Schlickeisen J, Zimmermann C. 2008. Otolith shape analysis as a tool for stock separation of horse mackerel (Trachurus trachurus) in the Northeast Atlantic and Mediterranean. Fish. Res., 89(2): 159–166.CrossRefGoogle Scholar
  31. Sun S, Sun X X. 2011. Atlas of Long–term Changes in the Jiaozhou Bay Ecosystem. Ocean Press, Beijing. 809p. (in Chinese)Google Scholar
  32. Torres G J, Lombarte A, Morales–Nin B. 2000a. Variability of the sulcus acusticus in the sagittal otolith of the genus Merluccius (Merlucciidae). Fish. Res., 46 (1–3): 5–13.CrossRefGoogle Scholar
  33. Torres G J, Lombarte A, Morales–Nin B. 2000b. Sagittal otolith size and shape variability to identify geographical intraspecific differences in three species of the genus Merluccius. J. Mar. Biol. Assoc. U. K., 80(2): 333–342.CrossRefGoogle Scholar
  34. Tracey S R, Lyle J M, Duhamel G. 2006. Application of elliptical Fourier analysis of otolith form as a tool for stock identification. Fish. Res., 77(2): 138–147.CrossRefGoogle Scholar
  35. Tuset V M, Lombarte A, Assis C A. 2008. Otolith atlas for the western Mediterranean, north and central eastern Atlantic. Sci. Mar., 72 (S1): 7–198.Google Scholar
  36. Tuset V M, Lozano I J, González J A, Pertusa J F, García–Díaz M M. 2003. Shape indices to identify regional differences in otolith morphology of comber, Serranus cabrilla (L., 1758). J. Appl. Ichthyol., 19(2): 88–93.CrossRefGoogle Scholar
  37. Vignon M, Morat F. 2010. Environmental and genetic determinant of otolith shape revealed by a non–indigenous tropical fish. Mar. Ecol. Prog. Ser., 411: 231–241.CrossRefGoogle Scholar
  38. Xu D D, Lou B, Shi H L, Geng Z, Li S L, Zhang Y R. 2012. Genetic diversity and population structure of Nibea albiflora in the China Sea revealed by mitochondrial COI sequences. Biochem. Syst. Ecol., 45: 158–165.CrossRefGoogle Scholar
  39. Zhang C, Fan Y N, Ye Z J, Li Z G, Yu H L. 2017. Identification of five Pampus species from the coast of China based on sagittal otolith morphology analysis. Acta Oceanol. Sin., 36(2): 51–56.CrossRefGoogle Scholar
  40. Zhang C, Ye Z J, Li Z G, Wan R, Ren Y P, Dou S Z. 2016. Population structure of Japanese Spanish mackerel Scomberomorus niphonius in the Bohai Sea, the Yellow Sea and the East China Sea: evidence from random forests based on otolith features. Fish. Sci., 82(2): 251–256.CrossRefGoogle Scholar
  41. Zhang W T, Dong W. 2004. Advanced Tutorial for Statistical Analysis Using SPSS. High Education Press, Beijing. p.263. (in Chinese)Google Scholar

Copyright information

© Chinese Society for Oceanology and Limnology, Science Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Junjie Song
    • 1
    • 3
  • Bo Zhao
    • 1
    • 3
  • Jinhu Liu
    • 1
    • 2
    • 4
  • Liang Cao
    • 1
    • 2
    • 4
  • Shuozeng Dou
    • 1
    • 2
    • 3
    • 4
    Email author
  1. 1.CAS Key Laboratory of Marine Ecology and Environmental Sciences, Institute of OceanologyChinese Academy of SciencesQingdaoChina
  2. 2.Laboratory for Marine Ecology and Environmental ScienceQingdao National Laboratory for Marine Science and TechnologyQingdaoChina
  3. 3.University of Chinese Academy of SciencesBeijingChina
  4. 4.Center for Ocean Mega–ScienceChinese Academy of SciencesQingdaoChina

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