4.0 Article

Physical and chemical processes promoting dominance of the toxic cyanobacterium Cylindrospermopsis raciborskii

Journal

CHINESE JOURNAL OF OCEANOLOGY AND LIMNOLOGY
Volume 29, Issue 4, Pages 883-891

Publisher

SCIENCE PRESS
DOI: 10.1007/s00343-011-0517-5

Keywords

cyanobacteria; freshwater; algal toxins; nutrients; light; temperature

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The freshwater cyanobacterium, Cylindrospermopsis raciborskii (Wo'oszyAska) 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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