Physical and chemical processes promoting dominance of the toxic cyanobacterium Cylindrospermopsis raciborskii |
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Authors: | Michele A Burford Timothy W Davis |
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Institution: | Michele A. BURFORD*,Timothy W. DAVIS Australian Rivers Institute,Griffith University,Nathan Qld. 4111,Australia |
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Abstract: | The freshwater cyanobacterium, Cylindrospermopsis raciborskii (Wo’oszyńska) Seenayya and Subba Raju is a common species in lakes and reservoirs globally. In some areas of the world it
can produce cyto- and hepatotoxins (cylindrospermopsins, saxitoxins), making blooms of this species a serious health concern
for humans. In the last 10–15 years, there has been a considerable body of research conducted on the ecology, physiology and
toxin production of this species and this paper reviews these studies with a focus on the cylindrospermopsin (CYN)-producing
strains. C. raciborskii has low light requirements, close to neutral buoyancy, and a wide temperature tolerance, giving it the capacity to grow in
many lentic waterbodies. It also has a flexible strategy with respect to nitrogen (N) utilisation; being able to switch between
utilising fixed and atmospheric N as sources of N fluctuate. Additionally this species has a high phosphate (DIP) affinity
and storage capacity. Like many cyanobacteria, it also has the capacity to use dissolved organic phosphorus (DOP). Changes
in nutrient concentrations, light levels and temperature have also been found to affect production of the toxin CYN by this
species. However, optimal toxin production does not necessarily occur when growth rates are optimal. Additionally, different
strains of C. raciborskii vary in their cell quota of CYN, making it difficult to predict toxin concentrations, based on C. raciborskii cell densities. In summary, the ecological flexibility of this organism means that controlling blooms of C. raciborskii is a difficult undertaking. However, improved understanding of factors promoting the species and toxin production by genetically
capable strains will lead to improved predictive models of blooms. |
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Keywords: | cyanobacteria freshwater algal toxins nutrients light temperature |
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