What does external morphometry tell us about stock discrimination of Sardina pilchardus stocks from Türkiye?

The analysis of shape is a fundamental part of much biological research. Morphometrics, which incorporates concepts from biology, geometry, and statistics, is the study of the geometrical form of organisms. In addition, morphometric characteristics can be used to differentiate ‘phenotypic stocks’ as groups with similar growth, mortality, and reproductive rates. In this study, 25 morphometric characters were used to discriminate European pilchard (Sardina pilchardus) stocks from Türkiye. Intraspecific variation of the European pilchard was investigated based on morphometric characters. Samples were collected from the Aegean Sea (AS; N = 54), the Sea of Marmara (MS; N = 50) and the Mediterranean Sea (MEDS; N = 50) during the 2019 fishing season. Principal Component Analysis (PCA) and Canonical Discriminant Analysis (CDA) were used for stock discrimination of the European pilchard. Univariate statistics (ANOVA) showed that 24 of the 25 measurements differed significantly between samples to a varying degree (p < 0.001). According to CDA, an overall classification success rate of 87.7% was achieved using 12 morphometric parameters. All samples were clearly separated from each other in the discriminant space, suggesting that there was no strong intermingling between populations. In addition, we would like to conclude that the morphological difference is not at the genetic level, and would like to emphasize the need for additional stock discrimination methods.

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Publication Details

Journal
Oceanological and Hydrobiological Studies
Published
2024-09-15
DOI
https://doi.org/10.26881/oahs-2024.3.08
Citations
2
Primary Topic
Fish Biology and Ecology Studies
Type
article
Field-Weighted Citation Impact
1.20
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article

What does external morphometry tell us about stock discrimination of Sardina pilchardus stocks from Türkiye?

Semra SAYGIN, Melek Özpiçak
2 citations
Oceanological and Hydrobiological Studies
Fish Biology and Ecology Studies
1.20
article

What does external morphometry tell us about stock discrimination of Sardina pilchardus stocks from Türkiye?

Semra SAYGIN, Melek Özpiçak
article en
2 citations

Abstract

The analysis of shape is a fundamental part of much biological research. Morphometrics, which incorporates concepts from biology, geometry, and statistics, is the study of the geometrical form of organisms. In addition, morphometric characteristics can be used to differentiate ‘phenotypic stocks’ as groups with similar growth, mortality, and reproductive rates. In this study, 25 morphometric characters were used to discriminate European pilchard (Sardina pilchardus) stocks from Türkiye. Intraspecific variation of the European pilchard was investigated based on morphometric characters. Samples were collected from the Aegean Sea (AS; N = 54), the Sea of Marmara (MS; N = 50) and the Mediterranean Sea (MEDS; N = 50) during the 2019 fishing season. Principal Component Analysis (PCA) and Canonical Discriminant Analysis (CDA) were used for stock discrimination of the European pilchard. Univariate statistics (ANOVA) showed that 24 of the 25 measurements differed significantly between samples to a varying degree (p < 0.001). According to CDA, an overall classification success rate of 87.7% was achieved using 12 morphometric parameters. All samples were clearly separated from each other in the discriminant space, suggesting that there was no strong intermingling between populations. In addition, we would like to conclude that the morphological difference is not at the genetic level, and would like to emphasize the need for additional stock discrimination methods.

Oceanological and Hydrobiological StudiesVol. 53(3)
Ondokuz Mayıs University (TR)
Openalex Percentile: Top 19%
Fish Biology and Ecology Studies
1.20
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What does external morphometry tell us about stock discrimination of Sardina pilchardus stocks from Türkiye? — Semra SAYGIN, Melek Özpiçak · Oceanological and Hydrobiological Studies (2024) | TGRS Research Map | TGRS