Excessive phytoplankton concentrations in rivers can result in the loss of plant and invertebrate communities, and threaten drinking water supplies. Whilst the physicochemical controls on algal blooms have been identified previously, how these factors combine to control the initiation, size, and cessation of blooms in rivers is not well understood. We applied flow cytometry to quantify diatom, chlorophyte, and cyanobacterial group abundances in the River Thames (UK) at weekly intervals from 2011 to 2022, alongside physicochemical data. A niche modeling approach was used to identify thresholds in water temperature, flow, solar radiation, and soluble reactive phosphorus (SRP) concentrations required to produce periods of phytoplankton growth, with blooms only occurring when all thresholds were met. The thresholds derived from the 2011 to 2018 dataset were applied to a test data set (2019–2022), which predicted the timing and duration of blooms at accuracies of > 80%. Diatoms and nano‐chlorophyte blooms were initiated by flow and water temperature, and usually terminated due to temperature and flow going out of the threshold range, or SRP and Si becoming limiting. Cyanobacterial bloom dynamics were primarily controlled by water temperature and solar radiation. This simple methodology provides a key understanding of phytoplankton community succession and inter‐annual variation and can be applied to any river with similar water quality and phytoplankton data. It provides early warnings of algal and cyanobacterial bloom timings, which support future catchment management decisions to safeguard water resources, and provides a basis for modeling changing phytoplankton bloom risk due to future climate change.

中文翻译：

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使用生态位模型预测河流浮游植物的繁殖和群落演替

河流中浮游植物浓度过高会导致植物和无脊椎动物群落的丧失，并威胁饮用水供应。虽然之前已经确定了对藻华的物理化学控制，但这些因素如何结合起来控制河流中藻华的发生、大小和停止尚不清楚。从 2011 年到 2022 年，我们应用流式细胞术每周对泰晤士河（英国）中的硅藻、叶绿藻和蓝藻群丰度进行量化，并提供理化数据。使用生态位建模方法来确定产生浮游植物生长周期所需的水温、流量、太阳辐射和可溶性活性磷（SRP）浓度的阈值，只有在满足所有阈值时才会出现水华。将 2011 年至 2018 年数据集得出的阈值应用于测试数据集（2019 年至 2022 年），该数据集以 > 80% 的准确度预测开花时间和持续时间。硅藻和纳米叶绿藻水华是由水流和水温引发的，通常由于温度和水流超出阈值范围或 SRP 和 Si 受到限制而终止。蓝藻水华动态主要受水温和太阳辐射控制。这种简单的方法提供了对浮游植物群落演替和年际变化的关键理解，并且可以应用于具有相似水质和浮游植物数据的任何河流。它提供藻类和蓝藻水华时间的早期预警，支持未来流域管理决策以保护水资源，并为模拟因未来气候变化而变化的浮游植物水华风险提供基础。