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IntroductionAnalyzing the correlation between planktonic eukaryotic communities (PECs) and aquatic physicochemical parameters (APPs) provides important references for predicting the impact of climate change and human activities on aquatic ecosystems.MethodsTo assess the influence of seasons and APPs on PEC structures in lakes and rivers, we utilized high-throughput sequencing of the 18S rRNA gene to analyze PEC structures in a lake and seven rivers in the Chaohu Lake Basin and analyzed their correlations with APPs.ResultsOur results revealed that PEC structure was significantly affected by season, with the highest α-diversity observed in summer. Furthermore, we identified several APPs, including water temperature, conductivity, dissolved oxygen, pH, phosphate, total phosphorus, trophic level index (TLI), nitrate, ammonia nitrogen, and total nitrogen, that significantly influenced PEC structures. Specifically, we found that Stephanodiscus hantzschii, Simocephalus serrulatus, Cryptomonas sp. CCAC_0109, Pedospumella encystans, Actinochloris sphaerica, Chlamydomonas angulosa, Gonyostomum semen, Skeletonema potamos, Chlamydomonas klinobasis, Pedospumella sp., and Neochlorosarcina negevensis were significantly correlated to TLI, while Limnoithona tetraspina, Theileria sp., and Pseudophyllomitus vesiculosus were significantly correlated to the water quality index (WQI). However, our random forest regression analysis using the top 100 species was unable to accurately predict the WQI and TLI.DiscussionThese results provide valuable data for evaluating the impact of APPs on PEC and for protecting water resource in the Chaohu Lake Basin. |
