Yunfei Wang, Yang Zhou, Liuxuan Qiao, Haoran Zhang, Lijing Long, Jian Su, Chaowei Zhou, Zhaofang Han, Haiping Liu
Schizothoracinae represent an endemic and dominant teleost group in the Qinghai-Xizang Plateau and adjacent regions. Despite their rich species diversity, closely related Schizothoracinae species exhibit remarkable external morphological similarity, which hinders traditional morphological discrimination. In this study, lapillus otoliths from 360 individuals representing 12 Schizothoracinae species collected across major Tibetan water systems were systematically examined. We evaluated and compared the performance of traditional scalar-based shape indices and Elliptic Fourier Analysis (EFA, 60 normalized harmonic coefficients following size-allometry correction) in otolith contour quantification and species identification. Statistical analyses including one-way ANOVA, principal component analysis (PCA), non-linear manifold learning (t-SNE and UMAP), and linear discriminant analysis (LDA) were executed. One-way ANOVA revealed highly significant differences among all 12 species across all shape indices and Fourier coefficients. The overall LDA classification accuracy was 35.3% for the shape index method, whereas EFA achieved a higher overall accuracy of 68.3%, representing a 33.0 percentage point improvement. Under EFA, Schizothorax lhasaensis (93.3%) and Schizothorax nukiangensis (90.0%) demonstrated the highest single-species discrimination success. Interspecific otolith morphological divergence was substantially higher in the riverine genus Schizothorax than in lacustrine genera (Gymnocypris and Schizopygopsis), the latter two of which show extensive morphological overlap consistent with their low genomic differentiation. Fishes of Gymnocypris displayed significantly higher otolith roundness (p < 0.05), which correlates with their adaptation to lacustrine or sluggish water habitats. Our findings demonstrate that EFA effectively captures multi-scale otolith contour harmonics, serving as a valuable morphometric approach for Schizothoracinae species identification and morphological discrimination, although challenges remain for species with incomplete lineage sorting. The morphometric database established herein provides valuable morphological baselines for the conservation and management of endemic QXP fish resources.