Unveiling the Dominant Influence of Reservoir Characteristics over Water Quality on Algal Concentrations Revealed by qPCR Detection

Abstract

This study develops a quantitative polymerase chain reaction (qPCR) method to detect four prevalent algal genera, Pseudanabaena, Cylindrospermopsis, Cryptomonas, and Limnothrixin nine drinking water reservoirs in Zhuhai, China. We examined the correlation between algal abundance and both water quality parameters and reservoir characteristics. Cryptomonas was the most abundant, with average levels at 6.76 ± 2.20 log10 copies/L, while Pseudanabaena showed the lowest at 4.93 ± 2.50 log10 copies/L. Although nutrient substances showed minimal impact, algal abundances exhibited active and substantial responses to reservoir characteristics including reservoir scale, water retention time, water supply source, and hydrological seasons. High algal abundances were significantly associated with large-scale reservoirs, long water retention time, river-fed reservoirs, and wet seasons (p < 0.05). Redundancy analysis indicated that reservoir characteristics account for 51.5% of the variation in algal abundance. This study demonstrates the effectiveness of qPCR in monitoring algal dynamics and highlights the significant role of reservoir characteristics in influencing algal blooms.