Currently, more and more lakes around the world are experiencing outbreaks of cyanobacterial blooms, and high-precision and rapid monitoring of the spatial distribution of algae in water bodies is an important task. Remote sensing technology is one of the effective means for monitoring algae in water bodies. Studies have shown that the Floating Algae Index (FAI) is superior to methods such as the Standardized Differential Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) in monitoring cyanobacterial blooms. However, compared to the NDVI method, the FAI method has difficulty in determining the threshold, and how to choose the threshold with the highest classification accuracy is challenging. In this study, FAI linear fitting model (FAI-L) is selected to solve the problem that FAI threshold is difficult to determine. Innovatively combine FAI index and NDVI index, and use NDVI index to find the threshold of FAI index. In order to analyze the applicability of FAI-L to extract cyanobacterial blooms, this paper selected multi-temporal Landsat8, HJ-1B, and Sentinel-2 remote sensing images as data sources, and took Chaohu Lake and Taihu Lake in China as research areas to extract cyanobacterial blooms. The results show that (1) the accuracy of extracting cyanobacterial bloom by FAI-L method is generally higher than that by NDVI and FAI. Under different data sources and different research areas, the average accuracy of extracting cyanobacterial blooms by FAI-L method is 95.13%, which is 6.98% and 18.43% higher than that by NDVI and FAI respectively. (2) The average accuracy of FAI-L method for extracting cyanobacterial blooms varies from 84.09 to 99.03%, with a standard deviation of 4.04, which is highly stable and applicable. (3) For simultaneous multi-source image data, the FAI-L method has the highest average accuracy in extracting cyanobacterial blooms, at 95.93%, which is 6.77% and 13.26% higher than NDVI and FAI methods, respectively. In this paper, it is found that FAI-L method shows high accuracy and stability in extracting cyanobacterial blooms, and it can extract the spatial distribution of cyanobacterial blooms well, which can provide a new method for monitoring cyanobacterial blooms.

Understanding the sensitivity of the response of chlorophyll (Chla) to nutrients (e.g., nitrogen and phosphorus) concentrations is important for predicting cyanobacterial bloom risk. However, the processes by which nutrients in lake that affect cyanobacterial growth and outbreaks are nonlinear, gradual and spatially and temporally heterogeneous, and the single response thresholds of concentrations between nutrients and the Chla proposed in current studies maybe hardly reflect these characteristics. Due to three decades of rapid regional socio-economic development, the eutrophication in Taihu Lake of China is serious and there are cyanobacterial blooms every year. In this study, we quantified the interaction effects of different forms of nitrogen and phosphorus on Chla concentrations in lake water and sediment pore water. And a refined response threshold range with continuous variation was proposed to characterize the relationship between the Chla concentration and the NH4-N, total nitrogen (TN) and total phosphorus (TP) concentrations. The results showed that TP was the dominant factor influencing the spatial variation of cyanobacteria blooms in most areas of Taihu Lake, followed by TN. TP should therefore be the highest priority for future pollution load reduction in Taihu Lake. The effects of the interactions between the pollution factors were greater than the sum of them individually. NH4-N and dissolved inorganic phosphorus (DIP) are likely to be preferentially consumed by algae for growth and should be the focus of nutrient control efforts in Taihu Lake. For cyanobacterial risk prediction, prevention and control, NH4-N, TN and TP concentrations of 0.06 mg/L, 2.89 mg/L and 0.06 mg/L, respectively, can be used to indicate the beginning of cyanobacterial blooms in Taihu Lake, and concentrations of 0.34 mg/L, 4.67 mg/L and 0.11 mg/L, respectively, can be used as reference thresholds to indicate serious cyanobacterial blooms.

Cyanobacterial blooms cause potential risk to submerged macrophytes and biofilms in eutrophic environments. This pilot-scale study investigated the growth, oxidative responses, and detoxification activity of aquatic plants in response to cyanobacterial blooms under different phosphorus concentrations. Variations of extracellular polymeric substances (EPSs) and microbial community composition were also assessed. Results showed that the biomass of Vallisneria natans increased with exposure to cyanobacterial blooms at higher phosphorous concentrations (P > 0.2 mg L-1). The amount of microcystin compounds (MC-LR) released into the water and the accumulation of MC-LR into both plant tissue and biofilms changed according to the phosphorus concentration. Furthermore, a certain degree of oxidative stress was induced in the plants, as evidenced by increased activity of superoxide dismutase, catalase, and peroxidase, as well as increased malondialdehyde concentrations; significant differences were also seen in acid phosphatase and glutathione S-transferase activities, as well as in glutathione concentrations. Together, these responses indicate potential mechanisms of MC-LR detoxification. Broader α-D-glucopyranose polysaccharides (PS) increased with increasing phosphorous and aggregated into clusters in biofilm EPS in response to the cyanobacterial blooms. In addition, alterations were seen in the abundance and structure of the microbial communities present in exposed biofilms. These results demonstrate that cyanobacterial blooms under different concentrations of phosphorus can induce differential responses, which can have a significant impact on aquatic ecosystems.

Cyanobacterial blooms at Lake Atitlán in Guatemala threaten and compromise the livelihood and health of local residents. Indigenous Tz\'utujil, Kaqchikel, and K\'iche\' rely directly on lake water for drinking, bathing, cleaning, cooking, and fishing. Nonpoint source runoff and untreated wastewater pumped directly into the lake contribute to high fecal pathogen loads into source waters. Concurrent nutrient loading results in cyanobacterial blooms further compromising water quality. A lakeside municipality facing high rates of childhood gastrointestinal illness volunteered to engage in community-based participatory research (CBPR) to evaluate efficacy, utility, and longevity of filters in households. The filters consistently reduced the risk of coliforms and E. coli in household water drawn from the lake based on World Health Organization guidelines. Household surveys were simultaneously administered through a student leadership group regarding water usage, water quality, and community health. Filters demonstrated ability to reduce high loads of fecal indicators from source waters and ability to remove a cyanobacterial toxin (microcystin) at 10 μg/L in deionized water. Further studies are imperative to determine longevity of use in households and CBPR provides a powerful avenue to test efficacy of a possible intervention while engaging stakeholders and empowering community members with sustainable solutions.

Cyanobacterial blooms are worldwide issues of societal concern and scientific interest. Lake Taihu and Lake Dianchi, two of the largest lakes in China, have been suffering from annual Microcystis-based blooms over the past two decades. These two eutrophic lakes differ in both nutrient load and environmental parameters, where Microcystis microbiota consisting of different Microcystis morphospecies and associated bacteria (epibionts) have dominated. We conducted a comprehensive metagenomic study that analyzed species diversity, community structure, functional components, metabolic pathways and networks to investigate functional interactions among the members of six Microcystis-epibiont communities in these two lakes. Our integrated metagenomic pipeline consisted of efficient assembly, binning, annotation, and quality assurance methods that ensured high-quality genome reconstruction. This study provides a total of 68 reconstructed genomes including six complete Microcystis genomes and 28 high quality bacterial genomes of epibionts belonging to 14 distinct taxa. This metagenomic dataset constitutes the largest reference genome catalog available for genome-centric studies of the Microcystis microbiome. Epibiont community composition appears to be dynamic rather than fixed, and the functional profiles of communities were related to the environment of origin. This study demonstrates mutualistic interactions between Microcystis and epibionts at genetic and metabolic levels. Metabolic pathway reconstruction provided evidence for functional complementation in nitrogen and sulfur cycles, fatty acid catabolism, vitamin synthesis, and aromatic compound degradation among community members. Thus, bacterial social interactions within Microcystis-epibiont communities not only shape species composition, but also stabilize the communities functional profiles. These interactions appear to play an important role in environmental adaptation of Microcystis colonies.

Harmful cyanobacterial blooms are exemplified as a major environmental concern due to producing toxin, and have generated a serious threat to public health. Knowledge on the spatial-temporal distribution of cyanobacterial blooms is therefore crucial for public health organizations and environmental agencies. In this study, field data and charge coupled device (CCD) image were collected in Lakes Gaoyang and Hanfeng of the Three Gorges Reservoir (TGR), China. We conducted the risky grade index (RGI) and coverage area index to develop a feasible estimation framework of cyanobacterial blooms. First, the close relationships between CCD reflectance spectral indices and water quality parameters were constructed based on water optical classification. Then, a regional algorithm for the RGI classification was established by density peaks. Finally, our proposed algorithm was applied to investigate dynamics of cyanobacterial blooms in the two lakes from 6-year series of CCD images. Encouraging results demonstrated that satellite remote sensing in conjunction with field observation can aid in the estimation of cyanobacterial blooms in the TGR.