Concentrations of phycocyanin, a pigment of Cyanobacteria, were measured at 1‐min intervals during the ice‐free seasons of 2008–2018 by automated sensors suspended from a buoy at a central station in Lake Mendota, Wisconsin, U.S.A. In each year, stochastic‐dynamic models fitted to time series of log‐transformed phycocyanin concentration revealed two alternative stable states and random factors that were much larger than the difference between the alternate stable states. Transitions between low and high states were abrupt and apparently driven by stochasticity. Variation in annual magnitudes of the alternate states and the stochastic factors were not correlated with annual phosphorus input to the lake. At daily time scales, however, phycocyanin concentration was correlated with phosphorus input, precipitation, and wind velocity for time lags of 1–15 d. Multiple years of high‐frequency data were needed to discern these patterns in the noise‐dominated dynamics of Cyanobacteria.

中文翻译：

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蓝藻细菌在富营养化湖泊的长期高频观测中的随机动力学

在美国威斯康星州门多塔湖中心站的浮标上悬挂的自动传感器，在2008–2018年的无冰季节中，以1分钟的间隔测量蓝藻色素的藻蓝蛋白浓度。对数转换后的藻蓝蛋白浓度的时间序列拟合的动力学模型揭示了两个替代的稳态和随机因素，其远大于替代的稳态之间的差异。高低状态之间的转换是突然的，并且显然是由随机性驱动的。交替状态的年级变化和随机因素与每年向湖中输入的磷无关。然而，在每天的时间尺度上，藻蓝蛋白的浓度与磷的输入，降水，风速为1-15 d。需要多年的高频数据才能在蓝细菌的噪声主导的动力学中识别这些模式。