A. A. Osman et al., Y. (2021). Patterns of variations in populations of Parupeneus forsskali (Fourmanoir and Guézé, 1976) of the Red Sea, Gulf of Suez, and the Mediterranean Sea as reflected by otolith shape using ShapeR. Egyptian Journal of Aquatic Biology and Fisheries, 25(4), 603-614. doi: 10.21608/ejabf.2021.192459
Yassein A. A. Osman et al.. "Patterns of variations in populations of Parupeneus forsskali (Fourmanoir and Guézé, 1976) of the Red Sea, Gulf of Suez, and the Mediterranean Sea as reflected by otolith shape using ShapeR". Egyptian Journal of Aquatic Biology and Fisheries, 25, 4, 2021, 603-614. doi: 10.21608/ejabf.2021.192459
A. A. Osman et al., Y. (2021). 'Patterns of variations in populations of Parupeneus forsskali (Fourmanoir and Guézé, 1976) of the Red Sea, Gulf of Suez, and the Mediterranean Sea as reflected by otolith shape using ShapeR', Egyptian Journal of Aquatic Biology and Fisheries, 25(4), pp. 603-614. doi: 10.21608/ejabf.2021.192459
A. A. Osman et al., Y. Patterns of variations in populations of Parupeneus forsskali (Fourmanoir and Guézé, 1976) of the Red Sea, Gulf of Suez, and the Mediterranean Sea as reflected by otolith shape using ShapeR. Egyptian Journal of Aquatic Biology and Fisheries, 2021; 25(4): 603-614. doi: 10.21608/ejabf.2021.192459
Patterns of variations in populations of Parupeneus forsskali (Fourmanoir and Guézé, 1976) of the Red Sea, Gulf of Suez, and the Mediterranean Sea as reflected by otolith shape using ShapeR
Population structure and differentiation of Parupeneus forsskali(Fourmanoir & Guézé, 1976) was studied by otolith shape variation using the ShapeR package. The quantitative shape analysis was used for studying otolith shapes. The outlines were analyzed with univariate and multivariate methods of Wavelet and Fourier transformations. There were significant differences (P<0.05, ANOVA) between geographically distant populations of P.forsskali collected from the Red Sea, Gulf of Suez and the Mediterranean Sea. The differences between populations were 85 % for the first discrimination. Additionally, the classification success with cross-validation for the three populations was 65%. The misclassification error for the linear discrimination analysis was 0.353. The observed morphological differences were supposed to reflect environmental effects or might be attributed to differences in life-history strategies. Studying Population structure and differentiation is important for designing appropriate regulations for effective fisheries management.