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Updated: Jun 23, 2026

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
Published on: February 25, 2021
Weather variability, sunspots, and the blooms of cyanobacteria
Wenbiao Hu1, Des Connell, Kerrie Mengersen
1School of Public Health and Institute of Biomedical Innovation, Queensland University of Technology, Victoria Park Road, Kelvin Grove, Brisbane, QLD, Australia.
Abstract:
The roles of weather variability and sunspots in the occurrence of cyanobacteria blooms, were investigated using cyanobacteria cell data collected from the Fred Haigh Dam, Queensland, Australia. Time series generalized linear model and classification and regression tree (CART) model were used in the analysis. Data on notified cell numbers of cyanobacteria and weather variables over the periods 2001 and 2005 were provided by the Australian Department of Natural Resources and Water, and Australian Bureau of Meteorology, respectively. The results indicate that monthly minimum temperature (relative risk [RR]: 1.13, 95% confidence interval [CI]: 1.02-1.25) and rainfall (RR: 1.11; 95% CI: 1.03-1.20) had a positive association, but relative humidity (RR: 0.94; 95% CI: 0.91-0.98) and wind speed (RR: 0.90; 95% CI: 0.82-0.98) were negatively associated with the cyanobacterial numbers, after adjustment for seasonality and auto-correlation. The CART model showed that the cyanobacteria numbers were best described by an interaction between minimum temperature, relative humidity, and sunspot numbers. When minimum temperature exceeded 18 degrees C and relative humidity was under 66%, the number of cyanobacterial cells rose by 2.15-fold. We conclude that weather variability and sunspot activity may affect cyanobacteria blooms in dams.
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