Stock identification of horse mackerel (Trachurus trachurus) through the analysis of body shape

Murta, Alberto G.; Pinto, Ana Luisa Daibert; Abaunza, Pablo

doi:10.1016/j.fishres.2007.09.026

Cited by 47 publications

(47 citation statements)

References 36 publications

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“…Assuming that the fish stocks are distributed in space as gradients (Murta et al, 2008), it is unlikely that fish from Bay of Bengal could belong to the Arabian Sea but the possibility of the fish of one stock within the coast is much higher. The misclassification results of discriminant function clearly support this theory.…”

Section: Discussionmentioning

confidence: 99%

Stock structure analysis of Decapterus russelli (Ruppell, 1830) from east and west coast of India using truss network analysis

Sen¹,

Jahageerdar²,

Jaiswar³

et al. 2011

Fisheries Research

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a b s t r a c tDecapterus russelli (Indian Scad) is an important pelagic carangid distributed on both east and west coast of India. Despite its wide distribution, the stock structure of the species is not well known. The present study was conducted to investigate stock structure of D. russelli, based on body shape morphometrics using truss network system. A total number of 360 samples of the species were collected from two centres, Digha and Visakhapatnam in Bay of Bengal from east coast and on the west coast from Mumbai and Cochin in Arabian Sea. A truss network was constructed by interconnecting 11 landmarks to form a total of 23 distance variables extracted from digital images of samples using tps Dig2 and PAST software platforms. The transformed truss measurements were subjected to factor analysis and classification by cross-validation of discriminant analysis. Factor analysis showed meaningful loading of the middle portion, the portion below the second dorsal fin, above anal fin, and the caudal portion on first and second factor, respectively. The factor analysis revealed the existence of two morphologically different stocks of D. russelli between east and west coast of India. The discriminant analysis was conducted by the combination of the truss distances that loaded on Factor-1 and Factor-2. The measurements that belonged to the middle portion and caudal portion of the body produced minimum misclassification rate of 5% between the coasts; whereas, the misclassification was 28% for all the four stocks. The misclassification was higher between the stocks within the coast. The high rate of misclassification observed within the coast is probably the result of no demarcation in fishing area. The occurrence of a separate stock on each coast may be the result of different physical and ecological condition of Bay of Bengal and Arabian Sea.

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Section: Discussionmentioning

confidence: 99%

Stock structure analysis of Decapterus russelli (Ruppell, 1830) from east and west coast of India using truss network analysis

Sen¹,

Jahageerdar²,

Jaiswar³

et al. 2011

Fisheries Research

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show abstract

“…Discriminant function analysis (DFA) could be a useful method to distinguish different stocks of the same species (Murta et al, 2008). In the present study, the DFA of morphometric characters produced four functions, which explained 100% of the accumulated population variance (Table 4).…”

Section: Resultsmentioning

confidence: 64%

“…Measurement, description and analysis of the morphological variations are fundamental steps to answer questions of biological adaptability (Ge and Hong, 1995). Due to genetic differences or environmental factors, morphological characters of aquatic animals are often varying along with geographic gradient among wide-ranged coastal marine animals (Tzeng et al, 2001;O'Reilly and Horn, 2004;Murta et al, 2008). Intra-specific variation in animals is usually regarded as the adaptive mechanism to different environments (Orensanz et al, 1991;Cadrin, 2000;Tzeng et al, 2001;Marquez et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…Studies on the morphological variations of target species can reveal the dynamics of populations and such information can be used to design management strategies (Orensanz et al, 2005). As one of the solid evaluation parameters, morphological variation has been widely used in population studies (Murta, 2000;Tzeng et al, 2001;Chen et al, 2010), stock discrimination (Cadrin et al, 2005;Turan et al, 2006;Murta et al, 2008) and bio-geographical evaluation (Von et al, 2005). In molluscs, shell shape variation has been reported to distinguish species of similar shape (Innes and Bates, 1999;Aguirre et al, 2006;Rufino et al, 2006;Costa et al, 2008Costa et al, , 2010 or to analyse intra-specific variation along a wide geographical range (Palmer et al, 2004;Krapivka et al, 2007;Marquez et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Morphological variations of the winged pearl oyster Pteria penguin (Roding, 1798) from South China Sea

et al. 2017

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The present study was undertaken to evaluate the morphological variations of Pteria penguin (Roding, 1798) in wild as well as cultured populations from South China Sea. A total of 307 samples were collected from five different geographic locations comprising three wild (Pop. 1, 2 and 4) and two cultured (Pop. 3 and 5) populations and 10 measured traits were analysed. Principal component analysis (PCA), discriminant analysis and cluster analysis were used to evaluate the morphological variations in the collected samples. Results showed a low intra-population variation within the five sampled populations. Multivariate analyses indicated that the five populations were more or less differentiated on the basis of body characters, particularly those related to major dimensions of the shell outline and their ratios. Discriminant analysis revealed that the overall random assignment of individuals into their original groups was high (81.8%), indicating that these populations are highly divergent from each other. The proportion of individuals correctly classified into their original groups was 96.9, 76.7, 75.0, 78.0 and 82.0% for populations 1, 2, 3, 4 and 5 respectively. Cluster analysis showed highest morphological variation between Pop.1 and Pop. 2. All other populations (Pop.3, Pop.4 and Pop.5) were found to be morphologically similar and consistent with the respective geographical location. Results of the present study will be of use in resource assessment and management of P. penguin in the South China Sea.

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“…To standardise all variables to the mean length of all sampled individuals, the equation (Lleonart et al, 2000;Murta et al, 2008):…”

Section: Descriptionmentioning

confidence: 99%

The effects of freezing on the morphometrics of sardine Sardinops sagax (Jenyns, 1842)

2010

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Stock identification of horse mackerel (Trachurus trachurus) through the analysis of body shape

Cited by 47 publications

References 36 publications

Stock structure analysis of Decapterus russelli (Ruppell, 1830) from east and west coast of India using truss network analysis

Stock structure analysis of Decapterus russelli (Ruppell, 1830) from east and west coast of India using truss network analysis

Morphological variations of the winged pearl oyster Pteria penguin (Roding, 1798) from South China Sea

The effects of freezing on the morphometrics of sardine Sardinops sagax (Jenyns, 1842)

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