Thesis (M.Sc. Biology)--University of Waikato, 2009. / Title from PDF cover (viewed Apr. 22, 2010). Includes bibliographical references (p. 35-47, 104-120)

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Cyanobacteria, also known as blue-green algae for a long time, are the most ancient and problematic bloom-forming phylum on earth. An alert levels framework has been established by World Health Organization(WHO) to prevent the potential harmful cyanobacterial blooms. Normally, low cyanobacteria levels are found in surface water. 2000 cyanobacterial cells/mL and 100,000 cyanobacterial cells/mL are established for WHO Alert Level 1 and 2, respectively. However, eutrophication, climate change and other factors may promote the spread of cyanobacteria and increase the occurrence of harmful cyanobacterial blooms in water on a global scale. Hence, a rapid real time cyanobacteiral monitoring system is required to protect public health from the cyanotoxins produced by toxic cyanobacterial species. Current methods to control or prevent the development of harmful cyanobacterial blooms are either expensive, time consuming or not effective in the long term. The best method to control the blooms is to prevent the formation of the blooms at the very beginning. Although emerging advanced autofluorescence-based sensors, imaging flow cytometry applications, and remote sensing have been utilized for rapid real-time enumeration and classification of cyanobacteria, the need to accurately monitor low-level cyanobacterial species in water remains unsolved. Microflow cytometry has been employed as a functional cell analysis technique in past decades, and it can provide real-time, accurate results. The autofluorescence of cyanobacterial pigments can be used for determination and counting of cyanobacterial density in water. A pre-concentration system of an automated cyanobacterial concentration and recovery system (ACCRS) based on tangential flow filtration and back-flushing technique was applied to reduce the sample assay volume and increase the concentration of target cells for further cell capture and detection. In this project, a microflow cytometry platform with a microfluidic device and an automated pre-concentration system was established to monitor cyanobacteria and provide early warning alerts for potential harmful blooms. In this work, quantification of low-level cyanobacterial samples (∼ 5 cyanobacterial cells/mL) in water has been achieved by using a microflow cytometer together with a pre-concentration system (ACCRS). Meanwhile, this platform can also provide early warning alerts for potential harmful cyanobacterial blooms at least 15 days earlier before reaching WHO Alert Level 1. Results have shown that this platform can be applied for rapid determination of cyanobacteria and early warning alerts can be triggered for authorities to protect the public and the environment. / Thesis / Doctor of Engineering (DEng) / Harmful cyanobacterial blooms have been a rising risk to the public heath across the world in recent decades. Alert levels of cyanobacteria in water has also been established. In this case, a rapid on-side monitoring system for cyanobacteria is required. In this thesis, a microflow cytometer platform combined with a bacterial concentration and recovery system was built to quickly monitor the relatively low level of cyanobacteria for early warning alerts. A pre-enrichment system based on tangential flow filtration and back-flushing technique was applied to increase the concentration levels of microbial samples and a microfluidic device capable of collecting phycocyanin fluorescence was designed to count cyanobacterial cells. The limit of quantification for cyanobacterial concentration based on the microflow cytometry platform was as low as ∼ 5 cells/mL. We can claim that the microflow cytometry platform can provide useful early warning alerts for the decision-makers to control the potential harmful cyanobacterial blooms at the very early stage and protect the aquatic animals and public health.

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Thesis (S.M. in Biology)--Joint Program in Biological Oceanography (Massachusetts Institute of Technology, Dept. of Biology; and the Woods Hole Oceanographic Institution), 1999. / Includes bibliographical references (leaves 23-30). / Phytoplankton mortality (herbivory) and bacterivory were examined experimentally in West Neck Bay and Coecles Harbor, Long Island, NY from April through September, 1998. Small algae (<5 [tm diameter) dominated phytoplankton communities in both ecosystems throughout the summer, and zooplankton were also small (mostly <40 tm). Generally, plankton abundances were indicative of eutrophic ecosystems. Oscillations in standing stocks and mortality of prey indicated tight coupling of growth and grazing mortality in both bays. Phytoplankton mortality rates accounted for the removal of 14% to 65% of total phytoplankton standing stocks daily, while bacterivory accounted for the removal of 14% to 88% of total bacterial standing stocks daily. Estimates of carbon consumption revealed high energy flux through the nano- and microzooplankton assemblages of these estuarine environments. / by Katie Rose Boissonneault Cellineri. / S.M.in Biology

Cyanobacterial blooms in lakes impact human health, the economy, and ecosystem health. It is predicted that climate change will promote and increase the frequency and intensity of cyanobacterial blooms due to unique physiological adaptions that allow cyanobacteria to exploit warm stable water bodies. Key cyanobacteria physiological adaptions include nitrogen fixation, buoyancy regulation and higher optimum growth temperatures. The largest uncertainty of predicting the effect of climate change is in understanding how the interactions among species will change. Adding to the ambiguity, cyanobacteria physiological adaptions can vary based on lakespecific ecotypes and can have different sensitivities to temperature. It is critical to understand how cyanobacterial physiological adaptions impact species interactions in order to improve and devise adaptable, short‐term management methods for bloom control. This study investigated how weather patterns and algal buoyancy regulation influence the competition and accumulation of two bloom‐forming buoyant cyanobacteria species (Aphanizomenon flos‐aquae (APFA) and toxin‐forming Microcystis aeruginosa (MSAE)) in Upper Klamath Lake (UKL), Oregon. The focus was confirming the buoyancy rate of the APFA in Upper Klamath Lake and exploring whether short‐term weather conditions could lead to dangerous accumulations of APFA or MSAE. A sensitivity analysis was conducted on the model's buoyancy terms and growth curves to see if the outcome of competition was influenced by these parameters. UKL specific buoyancy rates were measured on APFA from samples taken directly from the lake in the summer of 2015. Tracking software was used to measure APFA movement through water, and individual colony movement was averaged to obtain a single buoyancy rate. There was a high degree of agreement between the calculated APFA buoyancy rate in UKL (0.89 ± 0.34 m hr-1) with the rate published by Walsby (1995; 0.9 ± 0.5 m hr-1). This study investigated how weather patterns and buoyancy regulation influenced the outcome of competition between APFA and MSAE. Weather and water column temperature data were collected from UKL in the summer of 2016. A onedimensional hydrodynamic model was used to calculate the lake's thermal and turbulence structure on days with contrasting weather patterns (hot/cool and windy/calm). A competition model was used to calculate the accumulation of APFA and MSAE cells in regular intervals through the water column under the various weather scenarios. MSAE accumulation was significantly influenced by the thermal and turbulence regimes, but APFA maintained high accumulations under every regime and was the better competitor under every thermal and turbulence regime. MSAE was more negatively impacted by high turbulence than low temperatures. APFA's optimum temperature growth curve was found to be important in determining the outcome of competition between APFA and MSAE. Surprisingly, competition was not sensitive to changes in buoyancy rates. Buoyancy was not found to be a function of algal accumulation under any thermal and turbulence regime. The impacts of climate change and human‐induced enrichment has the potential to change existing patterns of species interactions in lentic systems. Restoration and management efforts should consider the significance of cascading ecological responses to climate change. Understanding how key physiological adaptions operate is the first step to assessing the scope of this impact. While buoyancy might not play a large role in competition in UKL, it might be possible to use mixing to suppress MSAE because it is negatively impacted by high turbulence. If MSAE hot spots become a reoccurring problem in UKL, lakes managers might be able to use localized mixing to suppress MSAE blooms in these problem areas.

Thesis (M.A.)--University of Wisconsin, 1949. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 157-159).

Animals living in marine sediments (the second largest habitat on earth) play a major role in global biogeochemical cycling. By feeding on organic matter from settled phytoplankton blooms they produce food for higher trophic levels and nutrients that can fuel primary production. In the Baltic Sea, anthropogenic stresses, such as eutrophication and introductions of invasive species, have altered phytoplankton dynamics and benthic communities. This thesis discusses the effects of different types of phytoplankton on the deposit-feeding community and the importance of benthic biodiversity for fate of the phytoplankton bloom-derived organic matter. Deposit-feeders survived and fed on settled cyanobacterial bloom material and in doing so accumulated the cyanobacterial toxin nodularin. Their growth after feeding on cyanobacteria was much slower than on a diet of spring bloom diatoms. The results show that settling blooms of cyanobacteria are used as food without obvious toxic effects, although they do not sustain rapid growth of the fauna. Since all tested species accumulated the cyanotoxin, negative effects higher up in the food web can not be ruled out. Both species composition and richness of deposit-feeding macrofauna influenced how much of the phytoplankton bloom material that was incorporated in fauna or retained in the sediment. The mechanism behind the positive effect of species richness was mainly niche differentiation among functionally different species, resulting in a more efficient utilization of resources at greater biodiversity. This was observed even after addition of an invasive polychaete species. Hence, species loss can be expected to affect benthic productivity negatively. In conclusion, efficiency in organic matter processing depends both on pelagic phytoplankton quality and benthic community composition and species richness. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Manuscript. Paper 4: In press. Paper 5: Manuscript.</p>

M.Sc. (Environmental Management) / In South Africa, there are practically no freshwater lakes. Therefore, exploitable water supplies are confined to rivers, artificial lakes behind dams, and groundwater. The many demands for water, and the erratic flow of most South African rivers, have led to the creation of artificial lakes and dams, i.e. impoundments on all the major rivers, in order to stabilise flow and therefore guarantee annual water supply. Cyanobacterial bloom formation in freshwater sources, such as rivers, lakes, dams and reservoirs are known to occur throughout the world. In South Africa, the occurrence of cyanobacteria has also been recorded with the best known being the bloom of the hyper-eutrophic Hartbeespoort Dam. In South Africa specifically, cyanobacteria are mostly seasonally driven. Species that are known to cause bloom formation are Microcystis sp., Anabaena sp., Oscillatoria sp. and Cylindrospermopsis sp. These species are known to produce cyanotoxins that cause health problems in animals and humans, but also produce taste and odour problems in drinking water, if not treated effectively. In most cases where cyanobacteria blooms have been known to occur, it also enters source water for drinking water purification plants. Because source water containing cyanobacteria and the effect it has on the consumer, environment and animals, it is thus important to identify the dominant algae species. Cyanotoxin drinking water guidelines must be developed and implemented and a management plan for the Water Treatment Plant must be produced, to ensure that the risk of human exposure to the cyanotoxins are minimised. The present study focuses on the Vaalkop Dam from which raw water is abstracted and treated by the Magalies Water Vaalkop Water Treatment Plant (MWVWTP) to produce potable water. The source water abstracted from the Vaalkop Dam can contain high numbers of cyanobacteria as well as cyanotoxins that must be removed by the MWVWTP during potable water purification to ensure compliance to water quality standards. The overall objective of the study is to investigate the occurrence of cyanobacteria and cyanotoxins in the Vaalkop Dam at the point where the source water is abstracted for drinking water purification.

Cyanobacteria are a unique organism, a bacterium that develop photosynthesis, thus it contains chlorophyll, a pigment commonly associated to algae. For this reason, cyanobacteria are also known as blue-green algae. One of the secondary metabolites of cyanobacteria is cyanotoxin, a substance which is hepatoxic, neurotoxic, and dermatoxic. The frequency and intensity of cyanobacterial blooms have been of increasing concern in the last decades for drinking water supply. There is a need to improve monitoring of cyanobacteria content at source water for drinking water supply and its indicators and correlation with other chemical, physical and biological parameters. This study aims to identify the potential cyanobacterial bloom risk in Lake Mälaren by determining the influential chemical and physical parameters using Random Forest in classification mode. The classification was done using the WHO Alert Level Frameworks and study cases for lakes in Sweden. The data used to model was downloaded from the website of the Swedish University of Agricultural Science. It comprises 33 monitoring stations from 1964 to 2020, 21 chemical parameters, including cyanobacteria biovolume and chlorophyll content. Given the heterogeneity of data, the monitoring stations were grouped into Clusters. Using the data, statistical, correlation, time series, and principal component analysis were performed. Through these methods, spatial, distribution and temporal analysis were obtained. Afterwards, several models were determined using Random Forest. However, the mean values of cyanobacteria distributed over time indicated a medium risk, the maximum values suggested high risk in several areas of the Lake. Maximum concentrations were present at the west and northeast of the Lake, where the major inflows from the Watershed are discharged. As the water flows through the basin, the concentration of cyanobacteria reduces by half, which suggested that the large and deep bays act as sedimentation ponds. A very high correlation was found between the Cluster 5 and 6, east and middle northeast of the Lake, respectively. Finally, the contributing factors identified after modelling cyanobacteria as target factor were chlorophyll, month, water temperature, oxygen content, transparency, NO2NO3N, TN/TP, Ca, Mg and Cl. / Cyanobakterier är unika organismer, bakterier som utvecklar fotosyntes, så de innehåller klorofyll, ett pigment som vanligtvis förknippas med alger. Av denna anledning är cyanobakterier också kända som blågröna alger. En av de sekundära metaboliterna av cyanobakterier är cyanotoxin, ett ämne som är hepatoxiskt, neurotoxiskt och dermatoxiskt. Frekvensen och intensiteten av cyanobakterieblomningar har varit ett ökande problem under de senaste decennierna för dricksvattenförsörjningen. Många vattenreningsverk mäter inte innehållet av cyanobakterier i vatten; medan andra kemiska, fysikaliska och biologiska parametrar mäts. Denna studie syftar till att identifiera den potentiella risken för cyanobakteriell blomning i Mälaren genom att bestämma de mest inflytelserika kemiska och fysikaliska parametrarna med hjälp av metoden Random Forest i klassificeringsläge. Klassificeringen gjordes med hjälp av WHO Alert Level Frameworks och olika studier av sjöar i Sverige. Data som användes för att modellera laddades ner från Sveriges Lantbruksuniversitets webbplats. Den omfattar 33 övervakningsstationer från 1964 till 2020, med 21 kemiska parametrar, inklusive cyanobakteriers biovolym och klorofyllhalt. Med tanke på heterogeniteten i data grupperades övervakningsstationerna i kluster. Med hjälp av data utfördes statistisk analys, korrelation, tidsserier och huvudkomponentanalys. Genom dessa metoder erhölls rumslig, distribution och tidsanalys. Efteråt bestämdes flera modeller med hjälp av Random Forest. Medelvärdena för cyanobakterier fördelade över tiden indikerade en medelrisk, medan maximivärdena antydde något annat. Maximala koncentrationer fanns i väster och nordost om Mälaren, där de stora inflödena från vattendelaren släpps ut. När vattnet rinner genom bassängen minskar koncentrationen av cyanobakterier till hälften, vilket tyder på att de stora och djupa vikarna fungerar som sedimentationsdammar. En mycket hög korrelation hittades mellan kluster 5 och 6, öster respektive mellan nordost om sjön. Slutligen var de viktigaste faktorerna som identifierades efter modellering av cyanobakterier som målfaktor klorofyll, månad, vattentemperatur, syrehalt, transparens, NO2NO3N, TN/TP, Ca, Mg och Cl.