Using cyanobacteria and other phytoplankton to assess trophic conditions: A qPCR-based, multi-year study in twelve large rivers across the United States

Zhang, Chiqian; McIntosh, Kyle; Sienkiewicz, Nathan; Stelzer, Erin A.; Graham, Jennifer L.; Lu, Jingrang

doi:10.1016/j.watres.2023.119679

Cited by 2 publications

(2 citation statements)

References 167 publications

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“…The qPCR-based method has been used to assess the trophic conditions of large rivers across the United States by detecting cyanobacteria and other phytoplankton. 21 Seven phyla of common algae in freshwater were also quantified by qPCR to evaluate the bloom intensity. 22 Recently, a novel DNA microarray tool was developed to target nearly all cyanobacteria strains by implementing 43,666 genome-wide, strain-specific probes.…”

Section: ■ Introductionmentioning

confidence: 99%

“…Additionally, qPCR can be seamlessly integrated with high-throughput sequencing, allowing for highly accurate assessment of phytoplankton communities. The qPCR-based method has been used to assess the trophic conditions of large rivers across the United States by detecting cyanobacteria and other phytoplankton . Seven phyla of common algae in freshwater were also quantified by qPCR to evaluate the bloom intensity .…”

Section: Introductionmentioning

confidence: 99%

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

Yin,

Lin,

et al. 2024

ACS EST Water

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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.

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Section: ■ Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Yin,

Lin,

et al. 2024

ACS EST Water

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Biological resources of Lake Kroshnozero (North-West of Russia)

Syarki,

Sidorova,

Georgiev

et al. 2023

E3S Web Conf.

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A comprehensive analysis of plankton and benthic communities, composition, structure and quantitative characteristics indicate that the ecosystem of Lake Kroshnozero has a eutrophic status or a transitional one between the β-mesotrophic and α-eutrophic. Plankton communities are in a stable state and provide a sustainable food base for planktivores fishes. A slight decrease in the quantitative indicators of benthos is possibly due to the methodological features of sampling and the underestimation of littoral communities. The composition and structure of benthic communities have been preserved since previous studies in the 50-90s of the last century. The ichthyofauna of Kroshnozero includes 13 fish species. Whitefish, zander, and vendace are fish of commercial importance. Fish of secondary importance are bream, perch, ruff, roach, and pike. Fish such as bleak, grayling sculpin, and burbot are relatively rare and do not serve as objects of fishing. Model calculations of fish productivity of planktivores, benthophages and predatory fish, taking into account losses to 2.3 kcal/m2 per season or 22.6 kg/ha. The average modelled ichthyomass is 4.6 kg/ha. Possible catches are one third of fish productivity equal to 7.5 kg/ha. To improve the quality and quantity of commercial stocks, recommendations are given to preserve the conditions for the reproduction and growth of valuable fish.

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Using cyanobacteria and other phytoplankton to assess trophic conditions: A qPCR-based, multi-year study in twelve large rivers across the United States

Cited by 2 publications

References 167 publications

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

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

Biological resources of Lake Kroshnozero (North-West of Russia)

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