How effectively do combined otolith shape descriptors and morphometric parameters differentiate Cirrhinus reba (Hamilton, 1822) stocks inhabiting the River Ganga?

Population structure assessment is crucial for effective management and conservation of freshwater fish species facing anthropogenic pressures. Despite its ecological and economic significance, Cirrhinus reba , a commercially important minor carp species in the River Ganga, has not been adequately studied using otolith-based approaches for stock discrimination. This study employed otolith shape analysis to discriminate C. reba stocks across four selected sampling locations along the River Ganga. We examined 100 otoliths using Discrete Wavelet descriptors, Elliptic Fourier descriptors, and morphometric parameters. PERMANOVA, canonical analysis of principal coordinates, linear discriminant analysis, and Random Forest classification were used for stock discrimination. Three distinct stocks were identified: Narora-Kanpur (combined), Varanasi, and Bhagalpur. Wavelet descriptors demonstrated superior discriminatory power (78% accuracy) compared to Fourier descriptors (68%) and morphometric parameters (56%), with combined approaches achieving maximum accuracy (81%). Bhagalpur exhibited the most distinctive otolith morphology with lowest within-group variation, while Narora and Kanpur showed morphological similarity. Stock structure patterns reflected cumulative effects of tributary confluences, barrages, and environmental heterogeneity. The identified three-stock structure necessitates site-specific management and conservation strategies, providing scientific foundation for sustainable fisheries management practices and targeted conservation measures for populations experiencing different environmental conditions.