State Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Science, Beijing, 100012, China.
Environ Monit Assess. 2019 May 10;191(6):360. doi: 10.1007/s10661-019-7492-2.
Lake ecosystems follow convoluted trajectories impacted by climate change and human stress. In this study, we developed the filtering trajectory method (FTM), a mathematical model, to establish the empirical relationships between chlorophyll a (CHLa) and nutrient concentrations in eutrophic Dianchi Lake, China. FTM can identify cause-effect relationships over time in apparently stochastic data, and a filtering trajectory diagram is used to describe the driving forces of the complex trajectories of individual lake ecosystems. Our analysis showed that the nutrient concentrations of overlying water in Dianchi Lake have decreased to the levels recorded in the late 1980s and early 1990s, but CHLa has not declined synchronously. The ecosystem trajectories revealed the ups and downs of complex processes, which can be divided into four stages: (1) pollution stage (1988-1999): a macrophyte-to-phytoplankton transition occurred with an increase in nutrient inputs and a rise in temperature; (2) initial restoration stage (2000-2006): the response of CHLa to the nutrient load reduction presented an apparent time lag, or hysteresis effect; (3) recurrence stage (2007-2011): excessive water consumption and continuous drought in the watershed resulted in an increasing trend in CHLa, TP and TN; and (4) re-restoration stage (2012-2016): the implementation of a water-replenishment project resulted in a declining trend. Our approach can greatly improve our understanding of how lakes respond to broad changes in environmental conditions (e.g. climate warming) and improve water quality via targeted nutrient management, from "static" to "dynamic management" and from "One Standard for One Lake" to "Multiple Standards for One Lake".
湖泊生态系统遵循复杂的轨迹，受到气候变化和人类压力的影响。在这项研究中，我们开发了过滤轨迹方法（FTM），这是一种数学模型，用于建立中国富营养化滇池叶绿素 a（CHLa）与营养浓度之间的经验关系。FTM 可以识别在明显随机数据中随时间变化的因果关系，并用过滤轨迹图来描述单个湖泊生态系统复杂轨迹的驱动力。我们的分析表明，滇池表层水的营养浓度已降至 20 世纪 80 年代末和 90 年代初的水平，但 CHLa 并没有同步下降。生态系统轨迹揭示了复杂过程的起伏，可以分为四个阶段：（1）污染阶段（1988-1999 年）：随着营养输入的增加和温度的升高，发生了大型植物到浮游植物的转变；（2）初步恢复阶段（2000-2006 年）：CHLa 对营养负荷减少的响应表现出明显的时间滞后，或滞后效应；（3）复发阶段（2007-2011 年）：流域过度用水和持续干旱导致 CHLa、TP 和 TN 呈上升趋势；（4）再恢复阶段（2012-2016 年）：实施补水工程导致 CHLa 呈下降趋势。我们的方法可以极大地提高我们对湖泊如何应对环境条件（如气候变暖）的广泛变化以及通过有针对性的营养管理改善水质的理解，从“静态”到“动态管理”，从“一湖一标准”到“一湖多标准”。
