Stock structure analysis of ‘Bombay duck’ (<i>Harpadon nehereus</i>Hamilton, 1822) along the Indian coast using truss network morphometrics

Pazhayamadom, Deepak George; Chakraborty, S. K.; Jaiswar, A. K.; Sudheesan, Deepa; Sajina, A M; Jahageerdar, Shrinivas

doi:10.1111/jai.12629

Cited by 16 publications

(5 citation statements)

References 25 publications

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“…Morphological differences in factor 1 of A. Clupeoides could be due to its feeding behavior as for predator evasiveness and foraging adeptness, high locomotory performance is crucial (Chipps, Dunbar, & Wahl, 2004;Swain, Hutchings, Foote, Cadrin, & Friedland, 2005). For taking the optimum amount of food, body depth adaptations are essential for transient and topical swimmers (Pazhayamadom et al, 2014). It is reported that the deep healthy fish stocks from less turbulent waters perform faster speed with brief propulsion (Blake, 2004;Webb, 1984).…”

Section: Discussionmentioning

confidence: 99%

Multivariate morphometric variability in sardine, Amblygaster clupeoides (Bleeker, 1849), from the Bay of Bengal coast, Bangladesh

Hanif

Siddik

Islam

et al. 2019

JoBAZ

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Background: Sardine Amblygaster clupeoides is a reef-associated oceanic species having long-standing socioeconomic and ecological importance along the coast of Bay of Bengal, Bangladesh, but less is known about the morphometric variability of the species. To uncover this, morphometric variability of A. clupeoides based on truss network technique was employed Results: A total number of 160 specimens from four coastal regions (Sundarbans, Kuakata, Bhola, and Cox's Bazar) of the Bay of Bengal coast were used to determine whether separate populations could be distinguished. To test the hypothesis of differentiation, each sample was subjected to morphometric measurements consisting of twenty-eight landmarks. In one way ANOVA analysis, twenty-six out of 28 morphometric measurements showed significant differences among the four populations. The principal component analysis indicated shape variation and explained 70.11% of the total variance. About 68.39% of individuals into their original group were correctly classified in discriminating space, as determined by discriminant function (DF) analysis. Conclusion: Morphometric traits like body length, body depth, body diagonal, body height, head length, head depth, mouth length, anal fin length, dorsal fin length, and caudal length diagonal were mainly responsible for variation and discrimination of populations. The present investigation demonstrates that the population of the east coast (Cox's Bazar) is morphometrically different from other populations. Future stock assessment of A. clupeoides should be considered especially on the east coast (Cox's Bazar) while formulating management action plans.

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Section: Discussionmentioning

confidence: 99%

Multivariate morphometric variability in sardine, Amblygaster clupeoides (Bleeker, 1849), from the Bay of Bengal coast, Bangladesh

Hanif

Siddik

Islam

et al. 2019

JoBAZ

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“…A sufficient degree of isolation may result in notable morphological, meristic, and shape differentiation among stocks of a species which may be recognizable as a basis for identifying the stocks. The characteristics may be more applicable for studying short-term, environmentally induced disparities, and the findings can be effectively used for improved fisheries management [18][19][20][21]. The truss network system can effectively be used to distinguish between the hatchery and wild stocks.…”

Section: Truss Network Measurementsmentioning

confidence: 99%

Advanced Techniques for Morphometric Analysis in Fish

To¹,

Anumudu²

2015

J Aquac Res Development

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Information on the biology and population structure of any species is a prerequisite for developing management and conservation strategies. Morphometric characters of fish are the measurable characters common to all fishes. Some arbitrarily selected points on a fish body known as landmarks help the individual fish shape to be analyzed. A landmark is a point of correspondence on an object that matches between and within populations. Advanced techniques for morphometric analysis offers more efficient and powerful tools in identify differences between fish populations, detecting differences among groups and to differentiate between species of similar shape. Morphometric methods such as univariate comparisons, bivariate analyses of relative growth pattern and a series of multivariate methods have been developed and applied to discriminate stocks. The use of multivariate techniques such as principal components and discriminant analyses to quantify morphometric variables are also receiving increased attention in stock identification. Some of the advanced techniques developed for morphometric analysis in fish population are Truss network measurement, Image analysis-Univarite, Bivariate, and Multivariate, Principal Component Analysis (PCA).

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“…Although many researchers now use geometric morphometric (GM) methods (Zelditch et al, 2004) such as the thin-plate spline and relative warp analysis to study shape, MM is still used, for example, for fish stock identification (e.g. AnvariFar et al, 2011;Sajina et al, 2011;Kohestan-Eskandari et al, 2014;Pazhayamadom et al, 2015). Richtsmeier et al (2002) presented many of the assumptions, benefits, and liabilities of GM and MM.…”

Section: Discussionmentioning

confidence: 99%

Effects of freezing on white perch Morone americana (Gmelin, 1789): implications for multivariate morphometrics

Kočovský

2015

J. Appl. Ichthyol.

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Summary This study tested the hypothesis that duration of freezing differentially affects whole‐body morphometrics of a derived teleost. Whole‐body morphometrics are frequently analyzed to test hypotheses of different species, or stocks within a species, of fishes. Specimens used for morphometric analyses are typically fixed or preserved prior to analysis, yet little research has been done on how fixation or preservation methods or duration of preservation of specimens might affect outcomes of multivariate statistical analyses of differences in shape. To determine whether whole‐body morphometrics changed as a result of freezing, 23 whole‐body morphometrics of age‐1 white perch (Morone americana) from western Lake Erie (n = 211) were analyzed immediately after capture, after being held on ice overnight, and after freezing for 100 or 200 days. Discriminant function analysis revealed that all four groups differed significantly from one another (P < 0.0001). The first canonical axis reflected long‐axis morphometrics, where there was a clear pattern of positive translation along this axis with duration of preservation. Re‐classification analysis demonstrated fish were typically assigned to their original preservation class except for fish frozen 100 days, which assigned mostly to frozen 200 days. Morphometric comparisons using frozen fish must be done on fish frozen for identical periods of time to avoid biases related to the length of time they were frozen. Similar experiments should be conducted on other species and also using formalin‐ and alcohol‐preserved specimens.

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Stock structure analysis of ‘Bombay duck’ (Harpadon nehereusHamilton, 1822) along the Indian coast using truss network morphometrics

Cited by 16 publications

References 25 publications

Multivariate morphometric variability in sardine, Amblygaster clupeoides (Bleeker, 1849), from the Bay of Bengal coast, Bangladesh

Multivariate morphometric variability in sardine, Amblygaster clupeoides (Bleeker, 1849), from the Bay of Bengal coast, Bangladesh

Advanced Techniques for Morphometric Analysis in Fish

Effects of freezing on white perch Morone americana (Gmelin, 1789): implications for multivariate morphometrics

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