College of Science, University of Shanghai for Science and Technology, Shanghai 200093, China.
Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta T6G 2G1, Canada.
Chaos. 2022 Apr;32(4):043116. doi: 10.1063/5.0085560.
Disturbances related to extreme weather events, such as hurricanes, heavy precipitation events, and droughts, are important drivers of evolution processes of a shallow lake ecosystem. A non-Gaussian α-stable Lévy process is esteemed to be the most suitable model to describe such extreme events. This paper incorporates extreme weather via α-stable Lévy noise into a parameterized lake model for phosphorus dynamics. We obtain the stationary probability density function of phosphorus concentration and examine the pivotal roles of α-stable Lévy noise on phosphorus dynamics. The switches between the oligotrophic state and the eutrophic state can be induced by the noise intensity σ, skewness parameter β, or stability index α. We calculate the mean first passage time, also referred to as the mean switching time, from the oligotrophic state to the eutrophic state. We observe that the increased noise intensity, skewness parameter, or stability index makes the mean switching time shorter and thus accelerates the switching process and facilitates lake eutrophication. When the frequency of extreme weather events exceeds a critical value, the intensity of extreme events becomes the most key factor for promoting lake eutrophication. As an application, we analyze the available data of Lake Taihu (2014-2018) for monthly precipitation, phosphorus, and chlorophyll-a concentrations and quantify the linkage among them using the Lévy-stable distribution. This study provides a fundamental framework to uncover the impact of any extreme climate event on aquatic nutrient status.
与极端天气事件（如飓风、强降水事件和干旱）相关的干扰是浅水湖生态系统演化过程的重要驱动因素。非高斯 α-稳定 Lévy 过程被认为是描述此类极端事件的最合适模型。本文通过 α-稳定 Lévy 噪声将极端天气纳入磷动力的参数化湖泊模型中。我们得到了磷浓度的平稳概率密度函数，并检验了 α-稳定 Lévy 噪声对磷动力的关键作用。噪声强度 σ、偏度参数 β 或稳定性指数 α 可以诱导贫营养状态和富营养状态之间的转换。我们计算了从贫营养状态到富营养状态的平均首次通过时间，也称为平均切换时间。我们发现，噪声强度、偏度参数或稳定性指数的增加会使平均切换时间变短，从而加速切换过程并促进湖泊富营养化。当极端天气事件的频率超过某个临界值时，极端事件的强度就成为促进湖泊富营养化的最关键因素。作为应用，我们分析了太湖（2014-2018 年）的月降水、磷和叶绿素-a 浓度的可用数据，并使用 Lévy-稳定分布量化了它们之间的联系。这项研究提供了一个基本框架，可以揭示任何极端气候事件对水生营养状况的影响。
