abstract
Climate change has been causing the increase in frequency, severity, and duration of harmful algal blooms, which makes the establishment of water management strategies indispensable. For cyanobacteria, several methods are currently used in monitoring programs. However, these methods are time-consuming and require specialists, and results are usually not provided within an adequate timeframe for taking timely mitigation actions. This work proposes a strategy for a faster, easier, and more cost-effective monitoring of cyanobacterial blooms, using a stepwise approach based on fluorometric determination of phycocyanin at an early stage. Complementary parameters (chlorophyll a, enumeration of dominant cyanobacterial species and cyanotoxin potential and quantification) are determined when necessary, thus progressively allocating human and financial resources within the monitoring program. This strategy was applied and validated using nine lentic eutrophic freshwater bodies prone to the occurrence of cyanobacterial blooms. Samples were sequentially evaluated, and the study ended up with two samples that showed high health risks. However, according to WHO guidelines, eight of the nine samples would be classified as having "moderate risk of adverse health effects" and could lead to preventive measures that would have an important regional economic impact. Therefore, the present approach proved to be a promising alternative to increase the effectiveness and accuracy of the risk assessment process in water bodies where cyanobacterial blooms occur.
keywords
HARMFUL ALGAL BLOOMS; CYLINDROSPERMOPSIS-RACIBORSKII; RIBOSOMAL-RNA; PHYCOCYANIN; MICROCYSTIS; STRAINS; GROWTH; PCR; ESTABLISHMENT; VARIABILITY
subject category
Environmental Sciences & Ecology
authors
Macario, IPE; Castro, BB; Nunes, IMS; Pizarro, C; Coelho, C; Goncalves, F; de Figueiredo, DR
our authors
Inês Adriana Patrunilho Efe Macário
PhD Studentacknowledgements
This work was supported by European Funds through COMPETE and by National Funds through the Portuguese Science Foundation (FCT) within project PEst-C/MAR/LA0017/2013 and UID/AMB/50017/2013. Daniela de Figueiredo was supported by FCT, by means of a post-doctoral grant (SFRH/BPD/74184/2010).