The gut microbiome is thought to play vital roles in host fitness and local adaptation to new environments, thereby facilitating the invasion of the host species. The Nile tilapia (Oreochromis niloticus) (NT) is an aggressive and omnivorous species that competes with native fishes for food resources, and it has successfully invaded much of the Pearl River basin in China. Here, we investigated the gut microbiomes of invasive Nile tilapia and indigenous black Amur bream (BA) in the same river section using high-throughput 16S rRNA gene sequencing. The results indicated that the gut microbiome of NT had several special characteristics, e.g., higher alpha diversity and greater niche breadth, compared with the bream. The gut microbiota of the small size of Nile tilapia (NTS) and small size of black Amur bream (BAS) groups were dominated by Proteobacteria, while those of the NTS and large size of Nile tilapia (NTL) and BAS and large size of black Amur bream (BAL). BAL and NTL were characterized by Firmicutes and Fusobacteriota, respectively. We found that Pseudomonas, Cetobacterium, Ralstonia, and Romboutsia were biomarkers of the NTS, NTL, BAS, and BAL groups, respectively. Moreover, the results collectively suggested that the clustering coefficients of BAL and NTL networks were greater than those of BAS and NTS networks, and BAS had the smallest network among the four groups. Positive interactions between two ASVs dominated the BAS, NTS, and NTL networks, while the proportion of negative interactions between two ASVs in the BAL network was remarkably increased. Low levels of interspecies competition in the NT gut microbiome would contribute to high diversity in the dietary niches and would also benefit the survival and local adaptation of the host. Our results identified specific biomarkers of gut microbial species in invasive Nile tilapia and provided useful information concerning how to monitor and manage invasive Nile tilapia populations.

Determining the temporal community composition of fish eggs in particular regions and understanding the reproductive times of regional fish taxa are key aspects of the management and regulation of regional fish stocks. However, it is extremely difficult to accurately identify fish eggs due to the absence of diagnostic morphological characters. We sampled fish eggs in the lower Hongshuihe River (an upper mainstem of the Pearl River) between May and September 2020. We then used DNA barcoding to determine the species composition of the egg pool and to predict the spawning periods of the identified species. A total of 641 eggs and 17 larvae were chosen for molecular identification; 397 eggs and 17 larvae yielded high‐quality barcoding sequences. The high failure rate (~38%) was most likely due to long‐term storage in low concentrations of ethanol prior to molecular analysis. We successfully classified 392 eggs into 10 species and 13 larvae into four species using public databases. Most of the species identified in the egg pool were small and/or benthic, and migratory species were rare. This may partially reflect the adverse effects of hydropower cascade development in this river section. We also found that spawning periods tended to be species‐specific. Our study provides a reference for the conservation and management of regional fishery stocks.