Determining the probability of cyanobacterial blooms: the application of Bayesian networks in multiple lake systems

A Bayesian network model was developed to assess the combined influence of nutrient conditions and climate on the occurrence of cyanobacterial blooms within lakes of diverse hydrology and nutrient supply. Physicochemical, biological, and meteorological observations were collated from 20 lakes located at different latitudes and characterized by a range of sizes and trophic states. Using these data, we built a Bayesian network to (1) analyze the sensitivity of cyanobacterial bloom development to different environmental factors and (2) determine the probability that cyanobacterial blooms would occur. Blooms were classified in three categories of hazard (low, moderate, and high) based on cell abundances. The most important factors determining cyanobacterial bloom occurrence were water temperature, nutrient availability, and the ratio of mixing depth to euphotic depth. The probability of cyanobacterial blooms was evaluated under different combinations of total phosphorus and water temperature. The Bayesian network was then applied to quantify the probability of blooms under a future climate warming scenario. The probability of the "high hazardous" category of cyanobacterial blooms increased 5% in response to either an increase in water temperature of 0.8°C (initial water temperature above 24°C) or an increase in total phosphorus from 0.01 mg/L to 0.02 mg/L. Mesotrophic lakes were particularly vulnerable to warming. Reducing nutrient concentrations counteracts the increased cyanobacterial risk associated with higher temperatures

New Zealand Guidelines for cyanobacteria in recreational fresh waters: Interim Guidelines

This document is divided into four main sections, plus 14 appendices. Section 1. Introduction provides an overview of the purpose and status of the document as well as advice on who should use it. Section 2. Framework provides a background to the overall guidelines approach, recommendations on agency roles and responsibilities, and information on the condition of use of this document. Section 3. Guidelines describes the recommended three-tier monitoring and action sequence for planktonic and benthic cyanobacteria. Section 4. Sampling provides advice on sampling planktonic and benthic cyanobacteria. The appendices give further background information and include templates for data collection and reporting, including: • background information on known cyanotoxins and their distribution in New Zealand • information on the derivation of guideline values • photographs of typical bloom events • a list of biovolumes for common New Zealand cyanobacteria • templates for field assessments • suggested media releases and warning sign templates. A glossary provides definitions for abbreviations and terms used in these guidelines

Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes

The growth of mass populations of toxin-producing cyanobacteria is a serious concern for the ecological status of inland waterbodies and for human and animal health. In this study we examined the performance of four semi-analytical algorithms for the retrieval of chlorophyll a (Chl a) and phycocyanin (C-PC) from data acquired by the Compact Airborne Spectrographic Imager-2 (CASI-2) and the Airborne Imaging Spectrometer for Applications (AISA) Eagle sensor. The retrieval accuracies of the semi-analytical models were compared to those returned by optimally calibrated empirical band-ratio algorithms. The best-performing algorithm for the retrieval of Chl a was an empirical band-ratio model based on a quadratic function of the ratio of re!ectance at 710 and 670 nm (R2=0.832; RMSE=29.8%). However, this model only provided a marginally better retrieval than the best semi-analytical algorithm. The best-performing model for the retrieval of C-PC was a semi-analytical nested band-ratio model (R2=0.984; RMSE=3.98 mg m−3). The concentrations of C-PC retrieved using the semi-analytical model were correlated with cyanobacterial cell numbers (R2=0.380) and the particulate and total (particulate plus dissolved) pools of microcystins (R2=0.858 and 0.896 respectively). Importantly, both the empirical and semi-analytical algorithms were able to retrieve the concentration of C-PC at cyanobacterial cell concentrations below current warning thresholds for cyanobacteria in waterbodies. This demonstrates the potential of remote sensing to contribute to early-warning detection and monitoring of cyanobacterial blooms for human health protection at regional and global scales

Analysis of bacterial communities in a municipal duck pond during a phytoplankton bloom and isolation of Anatilimnocola aggregata gen. nov., sp. nov., Lacipirellula limnantheis sp. nov. and Urbifossiella limnaea gen. nov., sp. nov. belonging to the phylum Planctomycetes

Waterbodies such as lakes and ponds are fragile environments affected by human influences. Suitable conditions can result in massive growth of phototrophs, commonly referred to as phytoplankton blooms. Such events benefit heterotrophic bacteria able to use compounds secreted by phototrophs or their biomass as major nutrient source. One example of such bacteria are Planctomycetes, which are abundant on the surfaces of marine macroscopic phototrophs; however, less data are available on their ecological roles in limnic environments. In this study, we followed a cultivation-independent deep sequencing approach to study the bacterial community composition during a cyanobacterial bloom event in a municipal duck pond. In addition to cyanobacteria, which caused the bloom event, members of the phylum Planctomycetes were significantly enriched in the cyanobacteria-attached fraction compared to the free-living fraction. Separate datasets based on isolated DNA and RNA point towards considerable differences in the abundance and activity of planctomycetal families, indicating different activity peaks of these families during the cyanobacterial bloom. Motivated by the finding that the sampling location harbours untapped bacterial diversity, we included a complementary cultivation-dependent approach and isolated and characterized three novel limnic strains belonging to the phylum Planctomycetes

Persistent cyanobacteria blooms in artificial water bodies : an effect of environmental conditions or the result of anthropogenic change

Algal blooms are an emerging problem. The massive development of phytoplankton is driven partly by the anthropogenic eutrophication of aquatic ecosystems and the expansion of toxic cyanobacteria in planktonic communities in temperate climate zones by the continual increase in global temperature. Cyanobacterial harmful algal blooms (CyanoHABs) not only disturb the ecological balance of the ecosystem, but they also prevent the use of waterbodies by humans. This study examines the cause of an unusual, persistent bloom in a recreational, flow-through reservoir; the findings emphasize the role played by the river supplying the reservoir in the formation of its massive cyanobacterial bloom. Comprehensive ecosystem-based environmental studies were performed, including climate change investigation, hydrochemical analysis, and bio-assessment of the ecological state of the river/reservoir, together with monitoring the cyanobacteria content of phytoplankton. Our findings show that the persistent and dominant biomass of Microcystis was related to the N/P ratio, while the presence of Aphanizomenon and Dolichospermum was associated with the high-temperature end electric conductivity of water. Together with the increase in global temperature, the massive and persistent cyanobacterial bloom appears to be maintained by the inflow of biogenic compounds carried by the river and the high electric conductivity of water. Even at the beginning of the phenomenon, the reservoir water already contained cyanobacterial toxins, which excluded its recreational use for about half the year

The Use of Sentinel-3 Imagery to Monitor Cyanobacterial Blooms

Cyanobacterial harmful algal blooms (CHABs) have been a concern for aquatic systems, especially those used for water supply and recreation. Thus, the monitoring of CHABs is essential for the establishment of water governance policies. Recently, remote sensing has been used as a tool to monitor CHABs worldwide. Remote monitoring of CHABs relies on the optical properties of pigments, especially the phycocyanin (PC) and chlorophyll-a (chl-a). The goal of this study is to evaluate the potential of recent launch the Ocean and Land Color Instrument (OLCI) on-board the Sentinel-3 satellite to identify PC and chl-a. To do this, OLCI images were collected over the Western part of Lake Erie (U.S.A.) during the summer of 2016, 2017, and 2018. When comparing the use of traditional remote sensing algorithms to estimate PC and chl-a, none was able to accurately estimate both pigments. However, when single and band ratios were used to estimate these pigments, stronger correlations were found. These results indicate that spectral band selection should be re-evaluated for the development of new algorithms for OLCI images. Overall, Sentinel 3/OLCI has the potential to be used to identify PC and chl-a. However, algorithm development is needed

Cyanobacteria Monitoring in the Charles River Lower Basin: Water Quality Assessment and Implications for Future Practice 2006-2014

The resurgence of cyanobacterial blooms in the Lower Charles River basin is of great concern to public and ecosystem health due to the potential hazard of cyanotoxins produced by these colonial cyanobacteria. In response to public concern about the condition of the river, Charles River Watershed Association (CRWA) is conducting cyanobacteria monitoring program to improve the water quality since 2006 and developing a solutions to watershed problems. This report is a concise overview of the cyanobacterial bloom monitoring results, its relationship to trophic state and temporal dynamics and potential solutions for future monitoring to serve recreational users of the Lower Charles River