Discriminatory Potential of Otolith Contour Morphometry for Population Identification of Semaprochilodus insignis Across Amazonian Rivers

Otolith morphometry has been widely used as an effective tool for discriminating fish populations. Three sets of morphometric descriptors are employed in otolith shape analysis: shape indices (Si) calculated from area, perimeter, length, and width; elliptic Fourier descriptors (EFd), which capture global shape differences; and Discrete Wavelet descriptors (DWd) sensitive to local variations along the contour. This study evaluates the discriminatory potential of these descriptors for identifying populations of Semaprochilodus insignis, a migratory species of great commercial importance to the Amazon basin that moves across rivers with distinct limnological characteristics. A total of 118 individuals were collected from five rivers—Negro, Tapajós, Curuá-Una, Tefé, and Mataurá—each representing one population. Differences among populations were tested by Permutational Multivariate Analysis of Variance (PERMANOVA), group separation was visualized through Canonical Analysis of Principal Coordinates (CAP), and classificatory performance was assessed using Random Forest with k-fold cross-validation. PERMANOVA revealed significant morphological differentiation among populations (p < 0.001). CAP ordination showed broad morphological overlap among the Negro, Tapajós, and Mataurá river populations, whereas the Curuá-Una population displayed greater separation across all three descriptors. Random Forest indicated low classification accuracy: Si (40.43%), EFd (45.41%), and DWd (53.92%). The low discriminatory capacity does not reflect a methodological limitation, but rather the biological nature of a migratory species embedded in a highly connected hydrological system, suggesting continuous genetic flow among populations—a pattern consistent with a metapopulation structure. These results reinforce the importance of managing S. insignis as an interconnected stock throughout the Amazon basin. This study was funded by the Fundação de Amparo à Pesquisa do Estado do Amazonas (FAPEAM).