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Recent studies have clearly shown the importance of omega-3 (ω-3) and omega-6 (ω-6) polyunsaturated fatty acids (PUFAs) for human and animal health. The long-chain eicosapentaenoic acid (EPA; 20:5ω-3) and docosahexaenoic acid (DHA; 22:6ω-3) are especially recognized for their nutritional value, and ability to alleviate many diseases in humans. So far, fish oil has been the main human source of EPA and DHA, but alternative sources are needed to satisfy the growing need for them. Therefore, we compared a fatty acid profile and content of 10 diatoms and seven dinoflagellates originating from marine, brackish and freshwater habitats. These two phytoplankton groups were chosen since they are excellent producers of EPA and DHA in aquatic food webs. Multivariate analysis revealed that, whereas the phytoplankton group (46%) explained most of the differences in the fatty acid profiles, habitat (31%) together with phytoplankton group (24%) explained differences in the fatty acid contents. In both diatoms and dinoflagellates, the total fatty acid concentrations and the ω-3 and ω-6 PUFAs were markedly higher in freshwater than in brackish or marine strains. Our results show that, even though the fatty acid profiles are genetically ordered, the fatty acid contents may vary greatly by habitat and affect the ω-3 and ω-6 availability in food webs.

Monitoring data facilitate the basic understanding of changes taking place in nature and provide information for making management decisions, but environmental monitoring is often considered expensive. Here, we apply the concept of value of information to evaluate the value of marine monitoring in the EU Marine Strategy Framework Directive context. We estimated the costs of the Finnish marine monitoring program and used the costs and economic benefits estimates of the Finnish marine strategy to assess the value of environmental monitoring. The numbers were applied to scenarios with different levels of information available prior to management decision-making. Monitoring costs were related to the value of perfect information prior to the management decision, assuming that managers will choose the management option that maximizes the benefits. The underlying assumptions of the conceptual model are that more accurate information about the status facilitates the selection of an optimal set of measures to achieve the environmental objectives and the related welfare gains from the improved environmental status. Our results emphasize the fact that monitoring is an essential part of effective marine management. Importantly, our study show that the value of marine monitoring data is an order of magnitude greater than the resources currently spent on monitoring and that an improved knowledge base can facilitate the planning of more cost-effective measures.

Cyanobacteria are an important part of phytoplankton communities, however, they are also known for forming massive blooms with potentially deleterious effects on recreational use, human and animal health, and ecosystem functioning. Emerging high-frequency imaging flow cytometry applications, such as Imaging FlowCytobot (IFCB), are crucial in furthering our understanding of the factors driving bloom dynamics, since these applications provide community composition information at frequencies impossible to attain using conventional monitoring methods. However, the proof of applicability of automated imaging applications for studying dynamics of filamentous cyanobacteria is still scarce. In this study we present the first results of IFCB applied to a Baltic Sea cyanobacterial bloom community using a continuous flow-through setup. Our main aim was to demonstrate the pros and cons of the IFCB in identifying filamentous cyanobacterial taxa and in estimating their biomass. Selected environmental parameters (water temperature, wind speed and salinity) were included, in order to demonstrate the dynamics of the system the cyanobacteria occur in and the possibilities for analyzing high-frequency phytoplankton observations against changes in the environment. In order to compare the IFCB results with conventional monitoring methods, filamentous cyanobacteria were enumerated from water samples using light microscopical analysis. Two common bloom forming filamentous cyanobacteria in the Baltic Sea, Aphanizomenon flosaquae and Dolichospermum spp. dominated the bloom, followed by an increase in Oscillatoriales abundance. The IFCB results compared well with the results of the light microscopical analysis, especially in the case of Dolichospermum. Aphanizomenon biomass varied slightly between the methods and the Oscillatoriales results deviated the most. Bloom formation was initiated as water temperature increased to over 15°C and terminated as the wind speed increased, dispersing the bloom. Community shifts were closely related to movements of the water mass. We demonstrate how using a high-frequency imaging flow cytometry application can help understand the development of cyanobacteria summer blooms.

Uusitalo, L., Fleming-Lehtinen, V., Hällfors, H., Jaanus A., Hällfors, S., and London, L. 2013. A novel approach for estimating phytoplankton biodiversity – ICES Journal of Marine Science, 70: 408–417. Maintaining biodiversity is one of the main priorities in environmental protection. The biodiversity of phytoplankton, the key primary producers in the marine ecosystem, is, however, often very difficult to estimate, since the phytoplankton assemblage includes a vast number of taxa, many of which occur in such small quantities that they may not be recorded in routine sampling. Moreover, many taxa cannot be identified to species level by routine methods such as light microscopy of preserved samples, even by a skilled taxonomist. This means that, in general, we cannot assume to have a complete list of species in the ecosystem at any given point in time. In this paper, we present an approach for evaluating phytoplankton biodiversity in spite of this challenge. Since eutrophication, which increases phytoplankton biomass, has been identified as the most important factor causing degradation of the Baltic Sea ecosystem, the proposed approach was evaluated against total phytoplankton biomass. When phytoplankton biomass was low, both low and high biodiversity values were observed, and, as the phytoplankton biomass increased, the high biodiversity values disappeared. These results were consistent both using data based on individual samples and using yearly sampling station averages.