Meteorological and hydrological conditions driving the formation and disappearance of black blooms, an ecological disaster phenomena of eutrophication and algal blooms

Distinguishing two phenotypes of blooms using the normalised difference peak-valley index (NDPI) and Cyano-Chlorophyta index (CCI)

Harmful algal blooms are now widely recognised as a severe threat to freshwater ecosystems, particularly in semi-fluvial environments created by river damming. Given the high spatial and temporal variability of cyanobacterial blooms, remote sensing is more suitable than conventional field surveys in monitoring blooms. However, the majority of existing algorithms cannot distinguish cyanobacterial blooms from eukaryotic algal blooms by extracting spectral features in the remote-sensing reflectance (R_rs). In this study, in situ R_rs spectra of cyanobacterial and green algal blooms in Lakes Gaoyang, Hanfeng and Changshou of the Three Gorges Reservoir (TGR) in China were recorded. Characteristic spectral indices, namely, the normalised difference peak-valley index and Cyano-Chlorophyta index, were used to develop an algorithm that can effectively distinguish cyanobacterial and green algal blooms. The proposed algorithm was also used to investigate the spatio-temporal dynamics of the two phenotypes of blooms derived from Huan Jing 1 charge-coupled device images. The resulting accuracy of 93.5% demonstrated that remote sensing technology, in conjunction with field observation, could efficiently differentiate bloom-forming species and assess the water quality in the TGR.

Spatiotemporal Changes of Cyanobacterial Bloom in Large Shallow Eutrophic Lake Taihu, China

Lake Taihu is a large shallow eutrophic lake with frequent recurrence of cyanobacterial bloom which has high variable distribution in space and time. Based on the field observations and remote sensing monitoring of cyanobacterial bloom occurrence, in conjunction with laboratory controlled experiments of mixing effects on large colony formation and colonies upward moving velocity measurements, it is found that the small or moderate wind-induced disturbance would increase the colonies size and enable it more easily to overcome the mixing and float to water surface rapidly during post-disturbance. The proposed mechanism of wind induced mixing on cyanobacterial colony enlargement is associated with the presence of the extracellular polysaccharide (EPS) which increased the size and buoyancy of cyanobacteria colonies and promote the colonies aggregate at the water surface to form bloom. Both the vertical movement and horizontal migration of cyanobacterial colonies were controlled by the wind induced hydrodynamics. Because of the high variation of wind and current coupling with the large cyanobacterial colony formation make the bloom occurrence as highly mutable in space and time. This physical factor determining cyanobacterial bloom formation in the large shallow lake differ from the previously documented light-mediated bloom formation dynamics.

Fungal community dynamics during a marine dinoflagellate (Noctiluca scintillans) bloom

Contamination and eutrophication have caused serious ecological events (such as algal bloom) in coastal area. During this ecological process, microbial community structure is critical for algal bloom succession. The diversity and composition of bacteria and archaea communities in algal blooms have been widely investigated; however, those of fungi are poorly understood. To fill this gap, we used pyrosequencing and correlation approaches to assess fungal patterns and associations during a dinoflagellate (Noctiluca scintillans) bloom. Phylum level fungal types were predominated by Ascomycota, Chytridiomycota, Mucoromycotina, and Basidiomycota. At the genus level drastic changes were observed with Hysteropatella, Malassezia and Saitoella dominating during the initial bloom stage, while Malassezia was most abundant (>50%) during onset and peak-bloom stages. Saitoella and Lipomyces gradually became more abundant and, in the decline stage, contributed almost 70% of sequences. In the terminal stage of the bloom, Rozella increased rapidly to a maximum of 50-60%. Fungal population structure was significantly influenced by temperature and substrate (N and P) availability (P < 0.05). Inter-specific network analyses demonstrated that Rozella and Saitoella fungi strongly impacted the ecological trajectory of N. scintillans. The functional prediction show that symbiotrophic fungi was dominated in the onset stage; saprotroph type was the primary member present during the exponential growth period; whereas pathogentroph type fungi enriched in decline phase. Overall, fungal communities and functions correlated significantly with N. scintillans processes, suggesting that they may regulate dinoflagellate bloom fates. Our results will facilitate deeper understanding of the ecological importance of marine fungi and their roles in algal bloom formation and collapse.

Disturbance-induced phytoplankton regime shifts and recovery of cyanobacteria dominance in two subtropical reservoirs

Many countries in the world still suffer from high toxic cyanobacterial blooms in inland waters used for human consumption. Regional climate change and human activities within watersheds exert a complex and diverse influence on aquatic ecosystem structure and function across space and time. However, the degree to which these factors may contribute to the long-term dynamics of plankton communities is still not well understood. Here, we explore the impacts of multiple disturbance events (e.g. human-resettlement, temperature change, rainfall, water level fluctuations), including six combined disturbances, on phytoplankton and cyanobacteria in two subtropical reservoirs over six years. Our data showed that combined environmental disturbances triggered two apparent and abrupt switches between cyanobacteria-dominated state and non-cyanobacterial taxa-dominated state. In late 2010, the combined effect of human-resettlement (emigration) and natural disturbances (e.g. cooling, rainfall, water level fluctuations) lead to a 60-90% decrease in cyanobacteria biomass accompanied by the disappearance of cyanobacterial blooms, in tandem with an abrupt and persistent shift in phytoplankton community. After summer 2014, however, combined weather and hydrological disturbances (e.g. warming, rainfall, water level fluctuations) occurred leading to an abrupt and marked increase of cyanobacteria biomass, associated with a return to cyanobacteria dominance. These changes in phytoplankton community were strongly related to the nutrient concentrations and water level fluctuations, as well as water temperature and rainfall. As both extreme weather events and human disturbances are predicted to become more frequent and severe during the twenty-first century, prudent sustainable management will require consideration of the background limnologic conditions and the frequency of disturbance events when assessing the potential impacts on reservoir biodiversity and ecosystem functioning and services.

Remote estimation of cyanobacterial blooms using the risky grade index (RGI) and coverage area index (CAI): a case study in the Three Gorges Reservoir, China

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.

A new approach for the estimation of phytoplankton cell counts associated with algal blooms

This study proposes a method for estimating phytoplankton cell counts associated with an algal bloom, using satellite images coincident with in situ and meteorological parameters. Satellite images from Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), Operational Land Imager (OLI) and HJ-1 A/B Charge Couple Device (CCD) sensors were integrated with the meteorological observations to provide an estimate of phytoplankton cell counts. All images were atmospherically corrected using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) atmospheric correction method with a possible error of 1.2%, 2.6%, 1.4% and 2.3% for blue (450-520nm), green (520-600nm), red (630-690nm) and near infrared (NIR 760-900nm) wavelengths, respectively. Results showed that the developed Artificial Neural Network (ANN) model yields a correlation coefficient (R) of 0.95 with the in situ validation data with Sum of Squared Error (SSE) of 0.34cell/ml, Mean Relative Error (MRE) of 0.154cells/ml and a bias of -504.87. The integration of the meteorological parameters with remote sensing observations provided a promising estimation of the algal scum as compared to previous studies. The applicability of the ANN model was tested over Hong Kong as well as over Lake Kasumigaura, Japan and Lake Okeechobee, Florida USA, where algal blooms were also reported. Further, a 40-year (1975-2014) red tide occurrence map was developed and revealed that the eastern and southern waters of Hong Kong are more vulnerable to red tides. Over the 40 years, 66% of red tide incidents were associated with the Dinoflagellates group, while the remainder were associated with the Diatom group (14%) and several other minor groups (20%). The developed technology can be applied to other similar environments in an efficient and cost-saving manner.