High-resolution temporal detection of cyanobacterial blooms in a deep and oligotrophic lake by high-frequency buoy data.

ABSTRACT

Cyanobacterial blooms are increasing in magnitude, frequency, and duration worldwide. However, our knowledge of cyanobacterial blooms dynamics and driving mechanisms is still limited due to their high spatiotemporal variability. To determine the potential driving mechanisms of cyanobacterial blooms in oligotrophic lakes, we collected a high-frequency depth profile of chlorophyll fluorescence (ChlF) and synchronous water quality, hydrometeorological data in early spring 2016 in oligotrophic Lake Qiandaohu. The vertical distribution of ChlF exhibited two patterns, "aggregated" and "discrete", using Morisita's index, and the aggregated ChlF presented subsurface chlorophyll maxima during the thermal stratification period. The ChlF concentration was positively correlated with water temperature and negatively correlated with turbidity. Significantly linear relationships were observed between ChlF vertical structure parameters (e.g., Morisita's index, subsurface chlorophyll maxima depth and thickness) and thermal stratification parameters (e.g., mixing layer depth and relative water column stability). After rainstorm floods, the ChlF pattern suddenly change from "aggregated" to "discrete" and a ChlF concentration <1 µg/L was observed for 7-11 days with a significant increase in the mixing depth layer and turbidity. The results suggest that cyanobacterial blooms are robustly associated with thermal stratification and rainstorm floods in the deep and oligotrophic lake. Thermal stratification boosts surface phytoplankton accumulation by increasing water temperature, enhancing light availability and restricting phytoplankton vertical distribution. Rainstorm floods interrupt the accumulation by disrupting thermal stratification and decreasing the available light. Furthermore, wind speed and air temperature both regulate the phytoplankton dynamics by affecting thermal stratification. Our research quantifies the cyanobacterial bloom dynamics and their relationship between environmental factors, improving our knowledge of the driving mechanisms of cyanobacterial bloom for the protection of drinking water safety and aquatic organism health in lakes.