ArticleScientific reports2026
Using sagittal otolith morphometrics and shape to discriminate three Nemipterus species (Teleostei: Nemipteridae) from Hurghada, Red Sea, Egypt.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Otolith morphology and morphometrics have been widely used to investigate taxonomic distinctions and infer potential relationships among fish species. This study focuses on the sagittal otolith shape and morphological traits of three Nemipterus species (N. zysron, N. randalli, and N. bipunctatus), employing size parameters, shape descriptors, Elliptic Fourier Analysis (EFA), and Scanning Electron Microscopy (SEM). Linear relationships were observed between otolith morphometric parameters namely, feret length (OL), feret width (OH), weight (OW), area (OA), and perimeter (OP) and fish biometric traits, including standard length (SL) and body weight (W). Ten shape descriptors, including Circularity (CI), Roundness (RO), and Ellipticity (EL), were evaluated and corrected for size effects. The strongest correlations were noted in OP-OL for N. zysron and N. randalli, and OA-OL for N. bipunctatus Uncorrected descriptors correlated significantly with SL, OL, OH, and OW, whereas corrected descriptors showed mostly non-significant correlations, indicating the effect of size correction. EFA revealed interspecific differences in otolith contour patterns. N. randalli and N. bipunctatus displayed greater morphological similarity, while N. zysron appeared more morphologically distinct. SEM provided detailed structural insights, revealing interspecific differences in the sulcus acusticus, rostrum, and margins, with six unique traits distinguishing N. zysron. This study demonstrates otolith shape analysis as a cost-effective and reliable method for fish species discrimination. These findings underscore the value of otolith-based approaches as alternatives to genetic marker techniques, enhancing taxonomic research.
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