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Teleconnection between phytoplankton dynamics in north temperate lakes and global climatic oscillation by time-frequency analysis

Xiao, Xi, He, Junyu, Yu, Yan, Cazelles, Bernard, Li, Ming, Jiang, Qutu, Xu, Caicai
Water research 2019
El Nino, La Nina, algal blooms, chlorophyll, climate, data collection, lakes, periodicity, phytoplankton, time series analysis, water quality, wavelet
We are still facing the knowledge gap of how the water-quality extremes (i.e. phytoplankton blooms), their causes, severity or occurrence could be directly related to the climatic oscillation. Considering that the climatic and phytoplankton concentration time series are highly non-stationary, we applied the advanced time-frequency analysis - Ensemble Empirical Mode Decomposition (EEMD), Hilbert-Huang Spectrum (HHS) and Wavelet Analysis (WA) - to examine the variability of long term phytoplankton dynamics from 1986 to 2014 in five North Temperate Lakes (NTLs). These analysis techniques isolated five separate time series for the surface Chlorophyll a concentrations (CHL) of the five NTLs and a time series for the global climate oscillation (denoted by multivariate ENSO index, MEI), and showed that these time series generally operated at similar time scales. The long-term residual trends of decreasing were found in three lakes (i.e., BM, SP and TR lakes), which are the same to global climate dynamics (MEI). The wavelet analysis reveals strong coherency between MEI and CHL data sets for all lakes, with a periodicity of 64-months. Intuitive associations between the CHL and MEI data set showed that two types of ENSO (El Nino and La Nina) differ in their influences to CHL. Potential mechanisms relating the phytoplankton dynamics in NTLs to climatic oscillation (ENSO) were also discussed.