Abstract The Hindu Kush Himalayan (HKH) region sustains the headwaters of major Asian rivers and harbors unique alpine biodiversity, and yet, it is highly sensitive to climate change. Biodiversity organization and community assembly processes across trophic levels within its river ecosystems remain poorly understood. Here, we used multi‐marker environmental DNA (eDNA) metabarcoding targeting four biological groups (cyanobacteria, diatoms, invertebrates, and vertebrates) to assess multi‐trophic biodiversity patterns in two alpine rivers of the region: the Yellow River source region (YR) and the middle–upper Nujiang River (NJ). These two systems differ markedly in geography, hydroclimate, vegetation, and human disturbance intensity. We identified 1695 operational taxonomic units and revealed pronounced differences in biodiversity pattern and community composition between rivers. Phototrophs and invertebrates showed higher α diversity in NJ, whereas vertebrates were richer in YR. β diversity was mainly driven by species turnover in both rivers, with a stronger distance–decay pattern in YR. Correlations between environmental variables and α and β diversity varied across groups and rivers, with geographic and climatic factors exerting stronger effects in NJ. iCAMP and pNST analyses revealed that stochastic processes dominated community assembly in both rivers, whereas deterministic processes were relatively stronger in YR compared to NJ. Accordingly, co‐occurrence networks revealed cohesive communities in YR but more modular ones in NJ, indicating contrasting ecological stability regimes. Overall, our study provides an integrated, multi‐trophic perspective on how environmental gradients shape riverine biodiversity and ecological interactions, informing adaptive conservation strategies under accelerating environmental change in the HKH region.
Lu et al. (Mon,) studied this question.