Phytoplankton diversity and community characteristics are closely associated with aquatic environmental factors. Understanding these dynamics can provide insights into the ecological health of water bodies. We investigate the spatial and temporal characteristics of phytoplankton communities in 27 drinking water source reservoirs in Shenzhen, China. As a method, we collected samples during the dry season in 2021 and the wet season in 2022, analyzed the alpha and beta diversities of phytoplankton communities, and correlated these with the environmental factors. The results reveal that Cyanobacteria dominate the phytoplankton communities in the Shenzhen reservoirs. Phytoplankton diversity is greater during the dry season. The algal composition varies spatially, and the phytoplankton diversity tends to decrease with increasing eutrophication. A co-occurrence network analysis indicates denser and stronger correlations among phytoplankton nodes during the wet season than dry season. Reservoirs with moderate eutrophication levels exhibit denser nodes and stronger correlations compared to those with low or high eutrophication levels. The chemical oxygen demand, water temperature, pH, and total nitrogen are identified as key influencers of the phytoplankton community structure. Our results contribute to the enhanced understanding of the spatial and temporal dynamics of phytoplankton communities in reservoirs in South China and provides insights into the management and conservation of these drinking water reservoirs.

Environmental DNA (eDNA) has become a promising tool for phytoplankton surveys. However, the accuracy of eDNA-based detection is related to primer selection across diverse environments, and optimal primer pairs selection on phytoplankton community in human impacted ecosystems is still lacking. The aim of this study is to evaluate how primer selection shapes phytoplankton community profiles by eDNA biomonitoring diverse anthropogenically disturbed aquatic systems (rivers, reservoirs, and seas). Four primer pairs targeting the 18S rRNA (V9-1 and V9-2), chloroplast rbcL, and ITS regions, were explored and our results revealed that primer choice critically governed the accuracy of phytoplankton profiling. Significant variations in annotated phytoplankton eDNA sequences in different groups of primer pairs were observed, where the primers 18SV9-1 and rbcL demonstrated superior specificity, amplifying >90% of phytoplankton OTUs. 18S-targeted primers detected the highest species richness, while the ITS primer showed the lowest. Alpha diversity was highest and most consistent for 18S primers. Beta diversity ordination (nMDS/Bray–Curtis) further highlighted primer-dependent community structuring in which 18S primers effectively clustered reservoir and marine samples separately, whereas primer rbcL discriminated habitat-specific signatures across three ecosystems. The primer ITS failed to distinguish among different habitats. Overall, our data demonstrated the critical role of primer optimization in eDNA-based phytoplankton studies, and could provide methodological guidelines for the design of effective monitoring protocols in rapidly urbanizing aquatic systems.