Bloom-forming toxic cyanobacterium Microcystis: Quantification and monitoring with a high-frequency echosounder

Assessment of in-situ monitoring and tracking the vertical migration of cyanobacterial blooms using LISST-HAB

Cyanobacterial harmful algal blooms (cyanoHABs) are becoming increasingly common in aquatic ecosystems worldwide. However, their heterogeneous distributions make it difficult to accurately estimate the total algae biomass and forecast the occurrence of surface cyanoHABs by using traditional monitoring methods. Although various optical instruments and remote sensing methods have been employed to monitor the dynamics of cyanoHABs at the water surface (i.e., bloom area, chlorophyll a), there is no effective in-situ methodology to monitor the dynamic change of cell density and integrated biovolume of algae throughout the water column. In this study, we propose a quantitative protocol for simultaneously measurements of multiple indicators (i.e., biovolume concentration, size distribution, cell density, and column-integrated biovolume) of cyanoHABs in water bodies by using the laser in-situ scattering and transmissometry (LISST) instrument. The accuracy of measurements of the biovolume and colony size of algae was evaluated and exceeded 95% when the water bloom was dominated by cyanobacteria. Furthermore, the cell density of cyanobacteria was well estimated based on total biovolume and mean cell volume measured by the instrument. Therefore, this methodology has the potential to be used for broader applications, not only to monitor the spatial and temporal distribution of algal biovolume concentration but also monitor the vertical distribution of cell density, biomass and their relationship with size distribution patterns. This provides new technical means for the monitoring and analysis of algae migration and early warning of the formation of cyanoHABs in lakes and reservoirs.

Rapid in situ assessment of high-resolution spatial and temporal distribution of cyanobacterial blooms using fishery echosounder

Cyanobacterial blooms are increasing in frequency, magnitude, and duration globally because of enhanced eutrophication and climate change. Thus, comprehensive investigation and systematic monitoring of the spatial and temporal distribution of cyanobacteria in aquatic environments are urgently needed to better understand bloom development and complex interactions within a dynamic environment. Various methods have been used to investigate the distribution of cyanobacteria, however, none of them can provide high-resolution data for the three-dimensional spatial structure of the bloom and its dynamics in real time. In the present study, we investigated the applicability of a high-frequency (200 kHz) fishery echosounder, a type widely used in fisheries acoustics, to detect and estimate the cyanobacterial genus Microcystis bloom distribution and biomass in a shallow lake (Sulejów Reservoir, Poland). Verification of the usefulness of in situ acoustic quantification of bloom-forming cyanobacteria was based on a comparison of acoustic estimates of cyanobacterial biomass with the ground truth-that is, fluorometric measurements and chlorophyll a concentrations. We compared the acoustic estimates with other methods for continuous measurements along 10 predetermined parallel transects and point samples at 14 stations situated on the transects. In vertical hydroacoustic measurements at night, we observed that cyanobacterial biomass was highest in the uppermost layer and diminished continuously with depth. For both horizontal and vertical continuous measurements, we found significant positive correlations between acoustic and fluorometric estimates of cyanobacterial biomass. The traditional point samples measurements, however, did not agree equally well with the acoustic estimates, especially for vertical beam. We argue that the point measurements have more stochastic character and less adequately describe dynamic changes in the cyanobacteria distribution than continuous acoustic estimates. More studies are required to explore the cyanobacteria distribution patterns under different biological, physical, and meteorological conditions.

Laser Remote Sensing of Lake Kinneret by Compact Fluorescence LiDAR

Harmful algal blooms in freshwater reservoirs became a steady phenomenon in recent decades, so instruments for monitoring water quality in real time are of high importance. Modern satellite remote sensing is a powerful technique for mapping large areas but cannot provide depth-resolved data on algal concentrations. As an alternative to satellite techniques, laser remote sensing is a perspective technique for depth-resolved studies of fresh or seawater. Recent progress in lasers and electronics makes it possible to construct compact and lightweight LiDARs (Light Detection and Ranging) that can be installed on small boats or drones. LiDAR sensing is an established technique; however, it is more common in studies of seas rather than freshwater reservoirs. In this study, we present an experimental verification of a compact LiDAR as an instrument for the shipborne depth profiling of chlorophyll concentration across the freshwater Lake Kinneret (Israel). Chlorophyll depth profiles of 3 m with a 1.5 m resolution were measured in situ, under sunlight conditions. A good correlation (R² = 0.89) has been established between LiDAR signals and commercial algae profiler data. A non-monotonic algae depth distribution was observed along the boat route during daytime (Tiberias city-Jordan River mouth-Tiberias city). The impact of high algal concentration on water temperature laser remote sensing has been studied in detail to estimate the LiDAR capability of in situ simultaneous measurements of temperature and chlorophyll concentration.

Severe cyanobacterial blooms in an Australian lake; causes and factors controlling succession patterns

Cyanobacterial blooms have major impacts on the ecological integrity and anthropogenic value of freshwater systems. Chrysosporum ovalisporum, a potentially toxic cyanobacteria has been rare in Australian waters until recently when is has bloomed in a number of lake and river systems. The aim of this study was to determine drivers of its growth and growing dominance. We performed regular monitoring of Mannus Lake, a small freshwater reservoir in South-Eastern Australia that has recently undergone extremely dense bloom events. Blooms of the diazotrophic Chrysosporum ovalisporum occurred in both summers of the 19 month study during periods of persistent thermal stratification. Following the C. ovalisporum blooms, non-diazotrophic taxa (Microcystis aeruginosa and Woronichinia sp.) dominated the phytoplankton community under less stratified conditions. Thermal stratification and nitrogen availability appeared to be the primary drivers of changes in cyanobacterial community structure. We propose that the observed transition from C. ovalisporum to M. aeruginosa and/or Woronichinia sp. may be a result of nitrogen limitation in early summer, which combined with persistent thermal stratification led to an ecological advantage for the nitrogen-fixing C. ovalisporum. Mixing events caused the senescence of the C. ovalisporum bloom, likely supplementing the nutrient budget of the lake with atmospherically derived N and alleviating N limitation to non-diazotrophic taxa. Non-diazotrophic cyanobacterial growth then increased, albeit at much lower biovolumes compared to the initial bloom. Overall, the results demonstrate the role of thermal stratification and nutrient cycling in structuring the cyanobacterial community and provide insights into the environmental factors driving the proliferation of the relatively new, potentially toxic cyanobacterium C. ovalisporum in Australian waters.

Simultaneously Acquiring Optical and Acoustic Properties of Individual Microalgae Cells Suspended in Water

Microalgae play a vital role in aquatic ecological research, but the fine classification of these tiny and various microalgae cells is still challenging for the community. In this paper, we propose a multimodality technique to simultaneously acquire the polarized light scattering, fluorescence and laser-induced acoustic wave signals originated from individual microalgae cells in water. Experiments of different species of Spirulina and different states of Microcystis have been conducted to test our experiment setup, and the results demonstrate that this method can well discriminate microalgae cells with pigment or microstructural differences. Moreover, with these modalities, the consumption of absorbed energy is evaluated quantitively, and a possible way to assess photosynthesis on a single-cell level is presented. This work is expected to be a powerful technique to probe the biophysical states of microalgae in the aquatic ecosystem.

Cyanobacterial pigment concentrations in inland waters: Novel semi-analytical algorithms for multi- and hyperspectral remote sensing data

Cyanobacteria are notorious for producing harmful algal blooms that present an ever-increasing serious threat to aquatic ecosystems worldwide, impacting the quality of drinking water and disrupting the recreational use of many water bodies. Remote sensing techniques for the detection and quantification of cyanobacterial blooms are required to monitor their initiation and spatiotemporal variability. In this study, we developed a novel semi-analytical approach to estimate the concentration of cyanobacteria-specific pigment phycocyanin (PC) and common phytoplankton pigment chlorophyll a (Chl a) from hyperspectral remote sensing data. The PC algorithm was derived from absorbance-concentration relationship, and the Chl a algorithm was devised based on a conceptual three-band structure model. The developed algorithms were applied to satellite imageries obtained by the Hyperspectral Imager for the Coastal Ocean (HICO™) sensor and tested in Lake Kinneret (Israel) during strong cyanobacterium Microcystis sp. bloom and out-of-bloom times. The sensitivity of the algorithms to errors was evaluated. The Chl a and PC concentrations were estimated with a mean absolute percentage difference (MAPD) of 16% and 28%, respectively. Sensitivity analysis shows that the influences of backscattering and other water constituents do not affect the estimation accuracy of PC (~2% MAPD). The reliable PC/Chl a ratios can be obtained at PC concentrations above 10 mg m^-3. The computed PC/Chl a ratio depicts the contribution of cyanobacteria to the total phytoplankton biomass and permits investigating the role of ambient factors in the formation of a complex planktonic community. The novel algorithms have extensive practical applicability and should be suitable for the quantification of PC and Chl a in aquatic ecosystems using hyperspectral remote sensing data as well as data from future multispectral remote sensing satellites, if the respective bands are featured in the sensor.

Acoustic scattering by gas-bearing cyanobacterium Microcystis: Modeling and in situ biomass assessment

Cyanobacterial harmful algal blooms (HABs) are increasing in a growing number of aquatic ecosystems around the world due to eutrophication and climatic change over the past few decades. Quantitative monitoring of HABs remains a challenge because their distributions are spatially heterogeneous and temporally variable. Most of the standard biological sampling methods are labor intensive and time consuming. In this paper, we present an efficient acoustic method to assess the biomass (biovolume) concentration of the cyanobacterium Microcystis in aquatic ecosystems. Acoustic backscattering vertical profiles from a gas-bearing Microcystis population were measured with echosounders at three frequencies (70, 120, and 333 kHz) in Lake Kinneret (case study). Concurrently, the volume concentration of Microcystis colonies and cyanobacteria-related Chlorophyll a were evaluated. We developed a partially coherent acoustic scattering model to quantify the cyanobacterium biomass based on depth-dependent acoustic backscattering signals. We also evaluated empirical regression models to obtain the Microcystis biomass from acoustically measured volume backscattering strength, S_v. It is demonstrated that both methods can convert the S_v to Microcystis biovolume concentrations reasonably well. Pro and cons of these methods are discussed. The results suggest that the presented methods may have a potential to be used for broader applications to monitor and quantify the gas-containing plankton in large aquatic ecosystems.

Individual-based modelling of cyanobacteria blooms: Physical and physiological processes

Lakes and reservoirs throughout the world are increasingly adversely affected by cyanobacterial harmful algal blooms (CyanoHABs). The development and spatiotemporal distributions of blooms are governed by complex physical mixing and transport processes that interact with physiological processes affecting the growth and loss of bloom-forming species. Individual-based models (IBMs) can provide a valuable tool for exploring and integrating some of these processes. Here we contend that the advantages of IBMs have not been fully exploited. The main reasons for the lack of progress in mainstreaming IBMs in numerical modelling are their complexity and high computational demand. In this review, we identify gaps and challenges in the use of IBMs for modelling CyanoHABs and provide an overview of the processes that should be considered for simulating the spatial and temporal distributions of cyanobacteria. Notably, important processes affecting cyanobacteria distributions, in particular their vertical passive movement, have not been considered in many existing lake ecosystem models. We identify the following research gaps that should be addressed in future studies that use IBMs: 1) effects of vertical movement and physiological processes relevant to cyanobacteria growth and accumulations, 2) effects and feedbacks of CyanoHABs on their environment; 3) inter and intra-specific competition of cyanobacteria species for nutrients and light; 4) use of high resolved temporal-spatial data for calibration and verification targets for IBMs; and 5) climate change impacts on the frequency, intensity and duration of CyanoHABs. IBMs are well adapted to incorporate these processes and should be considered as the next generation of models for simulating CyanoHABs.

Sensitivity Analysis and Optimization of a Radiative Transfer Numerical Model for Turbid Lake Water

Remote sensing can detect and map algal blooms. The HydroLight (Sequoia Scientific Inc., Bellevue, Washington, DC, USA) model generates the reflectance profiles of various water bodies. However, the influence of model parameters has rarely been investigated for inland water. Moreover, the simulation time of the HydroLight model increases as the amount of input data increases, which limits the practicality of the HydroLight model. This study developed a graphical user interface (GUI) software for the sensitivity analysis of the HydroLight model through multiple executions. The GUI software stably performed parameter sensitivity analysis and substantially reduced the simulation time by up to 92%. The GUI software results for lake water show that the backscattering ratio was the most important parameter for estimating vertical reflectance profiles. Based on the sensitivity analysis results, parameter calibration of the HydroLight model was performed. The reflectance profiles obtained using the optimized parameters agreed with observed profiles, with R2 values of over 0.98. Thus, a strong relationship between the backscattering coefficient and the observed cyanobacteria genera cells was identified.