Projected climate change impact on cyanobacterial bloom phenology in temperate rivers based on temperature dependency

Abstract

Climate warming is linked to earlier onset and extended duration of cyanobacterial blooms in temperate rivers. This causes an unpredictable extent of harm to the functioning of the ecosystem and public health. We used Microcystis spp. cell density data monitored for seven years (2016-2022) in ten sites across four temperate rivers of the Republic of Korea to define the phenology of cyanobacterial blooms and elucidate the climatic effect on their pattern. The day of year marking the onset, peak, and end of Microcystis growth were estimated using a Weibull function, and linear mixed-effect models were employed to analyze their relationships with environmental variables. These models identified river-specific temperatures at the beginning and end dates of cyanobacterial blooms. Furthermore, the most realistic models were employed to project future Microcystis bloom phenology, considering downscaled and quantile-mapped regional air temperatures from a general circulation model. Daily minimum and daily maximum air temperatures (mintemp and maxtemp) primarily drove the timing of the beginning and end of the bloom, respectively. The models successfully captured the spatiotemporal variations of the beginning and end dates, with mintemp and maxtemp predicted to be 24℃ (R² = 0.68) and 16℃ (R² = 0.35), respectively. The beginning and end dates were projected to advance considerably in the future under the Representative Concentration Pathway 2.6, 4.5, and 8.5. The simulations suggested that the largest uncertainty lies in the timing of when the bloom ends, whereas the timing of when blooming begins has less variation. Our study highlights the dependency of cyanobacterial bloom phenology on temperatures and earlier and prolonged bloom development.

Keywords: Cyanobacteria; Cyanobacterial bloom; Global warming; Microcystis; Mixed effect modeling; Phenology.