Tan Lu, Wang Lan, Cai Qinghua
State Key Laboratory of Freshwater Ecology and Biotechnology, Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, Hubei, China.
Hubei Key Laboratory of Wetland Evolution & Ecological Restoration, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, Hubei, China.
Front Plant Sci. 2024 Apr 16;15:1390019. doi: 10.3389/fpls.2024.1390019. eCollection 2024.
Reservoirs, heavily influenced by artificial management, often harbor phytoplankton assemblages dominated by cyanobacteria or dinoflagellates, triggering significant changes in aquatic ecosystems. However, due to limited sampling frequency and insufficient attention to species composition, the bloom processes and key characteristics of phytoplankton community structure have not been systematically elucidated. During the low-water level period when blooms are most likely to occur (June to September) in a tributary bay of the Three Gorges Reservoir, daily sampling was conducted to investigate phytoplankton community composition, identify significant environmental factors, and evaluate important structure characteristics of phytoplankton community. The results showed that maintained a clear dominance for almost a month in stage 1, with low Shannon and evenness but a high dominance index. Phytoplankton total density and biomass decreased drastically in stage 2, but still accounted for some proportion. The highest Shannon and evenness but the lowest dominance index occurred in stage 3. occurred massively in stage 4, but its dominant advantages lasted only one to two days. NH-N was responsible for the dominance of , while TP and PO-P was responsible for the dominance of ; however, precipitation contributed to their drastic decrease or disappearance to some extent. The TN : TP ratio could be considered as an important indicator to determine whether or dominated the phytoplankton community. Throughout the study period, physiochemical factors explained more variation in phytoplankton data than meteorological and hydrological factors. Pairwise comparisons revealed an increase in average β diversity with stage progression, with higher β diversities based on abundance data than those based on presence/absence data. Repl had a greater effect on β diversity differences based on presence/absence data, whereas RichDiff had a greater effect on β diversity differences based on species abundance data. Co-occurrence networks for stage 1 showed the most complex structure, followed by stage 4, while the network for stage 3 was relatively sparse, although the overall community division remained compact. This study provides a useful attempt to explore the status and changes in phytoplankton community structure during the bloom process through high-resolution investigation.
受人工管理影响严重的水库,常常存在以蓝藻或甲藻为主导的浮游植物群落,这引发了水生生态系统的显著变化。然而,由于采样频率有限且对物种组成关注不足,浮游植物群落结构的水华过程和关键特征尚未得到系统阐明。在三峡水库一条支流湾最易发生水华的低水位期(6月至9月),进行了每日采样,以调查浮游植物群落组成,确定重要环境因素,并评估浮游植物群落的重要结构特征。结果表明,在第1阶段 几乎保持了近一个月的明显优势,香农指数和均匀度较低,但优势度指数较高。浮游植物总密度和生物量在第2阶段急剧下降,但 仍占一定比例。第3阶段出现了最高的香农指数和均匀度,但优势度指数最低。 在第4阶段大量出现,但其优势仅持续一到两天。NH-N导致了 的优势,而TP和PO-P导致了 的优势;然而,降水在一定程度上促使它们急剧减少或消失。TN:TP比率可被视为确定浮游植物群落是以 还是 为主导的重要指标。在整个研究期间,理化因素对浮游植物数据变化的解释比气象和水文因素更多。成对比较显示,随着阶段推进,平均β多样性增加,基于丰度数据的β多样性高于基于存在/缺失数据的β多样性。Repl对基于存在/缺失数据的β多样性差异影响更大,而RichDiff对基于物种丰度数据的β多样性差异影响更大。第1阶段的共现网络结构最为复杂,其次是第4阶段,而第3阶段的网络相对稀疏,尽管整体群落划分仍然紧密。本研究通过高分辨率调查,为探索水华过程中浮游植物群落结构的现状和变化提供了有益尝试。