Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.

Microplastics (MPs) from households, stormwater, and various industries are transported to wastewater treatment plants (WWTPs), where a high proportion of them are captured before discharging their residuals to watersheds. Although recent studies have indicated that the removed MPs are mainly retained in wastewater sludge, sludge treatment processes have gained less attention in MP research than water streams at primary, secondary, and tertiary treatments. In this study, we sampled 12 different process steps in a tertiary-level municipal WWTP in central Finland. Our results showed that, compared to the plant influent load, three times more MPs circulated via reject water from the sludge centrifugation back to the beginning of the treatment process. Fibrous MPs were especially abundant in the dewatered sludge, whereas fragment-like MPs were observed in an aqueous stream. We concluded that, compared to the tertiary effluent, sludge treatment is the major exit route for MPs into the environment, but sludge treatment is also a return loop to the beginning of the process. Our sampling campaign also demonstrated that WWTPs with varying hydraulic conditions (such as the one studied here) benefit from disc filter-based tertiary treatments in MP removal.

The development of phytoplankton biomass and composition in a eutrophic boreal lake was studied during the evolution of under-ice convection in spring. The results from 8 yr showed that, within a few weeks before ice-break, phytoplankton biomass regularly increased by up to two or three orders of magnitude, reaching or exceeding the biomass in summer. Accordingly, this may be the most significant single annual phytoplankton episode in the lake. The development of phytoplankton was closely coupled with that of convection created by solar radiation at water temperatures < 4°C. In addition to vertical convection which keeps phytoplankton suspended, there was also horizontal convection which transported water with likely higher abundance of phytoplankton from the shallow lake margins. The effect of mechanical mixing, which was meant to prevent anoxia in the deep water layers of the study basin, was overridden by natural convection. Stochastic variations in weather played a key role controlling light penetration into the lake and hence the abundance and composition of under-ice phytoplankton. After snow melt the proportion of motile algae was at first higher, sometimes with a maximum nearest to the ice, but later diatoms flourished throughout the convection layer. Only in the years of the shortest convection period did the proportion of motile algae remain high until the end of ice cover. More detailed information about the interaction between littoral and pelagial water masses under different mixing regimes is needed for a more profound understanding of the development of phytoplankton under-ice.

Phytoplankton synthesizes essential ω-3 and ω-6 polyunsaturated fatty acids (PUFA) for consumers in the aquatic food webs. Only certain phytoplankton taxa can synthesize eicosapentaenoic (EPA; 20:5ω3) and docosahexaenoic acid (DHA; 22:6ω3), whereas all phytoplankton taxa can synthesize shorter-chain ω-3 and ω-6 PUFA. Here, we experimentally studied how the proportion, concentration (per DW and cell-specific), and production (µg FA L⁻¹ day⁻¹) of ω-3 and ω-6 PUFA varied among six different phytoplankton main groups (16 freshwater strains) and between exponential and stationary growth phase. EPA and DHA concentrations, as dry weight, were similar among cryptophytes and diatoms. However, Cryptomonas erosa had two–27 times higher EPA and DHA content per cell than the other tested cryptophytes, diatoms, or golden algae. The growth was fastest with diatoms, green algae, and cyanobacteria, resulting in high production of medium chain ω-3 and ω-6 PUFA. Even though the dinoflagellate Peridinium cinctum grew slowly, the content of EPA and DHA per cell was high, resulting in a three- and 40-times higher production rate of EPA and DHA than in cryptophytes or diatoms. However, the production of EPA and DHA was 40 and three times higher in cryptophytes and diatoms than in golden algae (chrysophytes and synyrophytes), respectively. Our results show that phytoplankton taxon explains 56–84% and growth phase explains ~1% of variation in the cell-specific concentration and production of ω-3 and ω-6 PUFA, supporting understanding that certain phytoplankton taxa play major roles in the synthesis of essential fatty acids. Based on the average proportion of PUFA of dry weight during growth, we extrapolated the seasonal availability of PUFA during phytoplankton succession in a clear water lake. This extrapolation demonstrated notable seasonal and interannual variation, the availability of EPA and DHA being prominent in early and late summer, when dinoflagellates or diatoms increased.

Effective monitoring of microalgae growth is crucial for environmental observation, while the applications of this monitoring could also be expanded to commercial and research-focused microalgae cultivation. Currently, the distinctive optical properties of different microalgae groups are targeted for monitoring. Since different microalgae can grow together, their spectral signals are mixed with ambient properties, making estimations of species biomasses a challenging task. In this study, we cultured five different microalgae and monitored their growth with a mobile spectral imager in three separate experiments. We trained and validated a one-dimensional convolution neural network by introducing absorbance spectra of the cultured microalgae and simulated pairwise mixtures of them. We then tested the model with samples of microalgae (monocultures and their pairwise mixtures) that were not part of the training or validation data. The convolution neural network classified microalgae accurately in the monocultures (test accuracy = 95%, SD = 4) and in the pairwise mixtures (test accuracy = 100%, SD = 0). Median prediction errors for biomasses were 17% (mean = 22%, SD = 18) for the monocultures and 17% (mean 24%, SD = 28) for the pairwise mixtures. As the spectral camera produced spatial information of the imaged target, we also demonstrated here the spatial distribution of microalgae biomass by applying the model across 5 × 5 pixel areas of the spectral images. The results of this study encourage the application of a one-dimensional convolution neural network to solve classification, regression, and distribution problems related to microalgae observation, simultaneously.

Spectral cameras are traditionally used in remote sensing of microalgae, but increasingly also in laboratory-scale applications, to study and monitor algae biomass in cultures. Practical and cost-efficient protocols for collecting and analyzing hyperspectral data are currently needed. The purpose of this study was to test a commercial, easy-to-use hyperspectral camera to monitor the growth of different algae strains in liquid samples. Indices calculated from wavebands from transmission imaging were compared against algae abundance and wet biomass obtained from an electronic cell counter, chlorophyll a concentration, and chlorophyll fluorescence. A ratio of selected wavebands containing near-infrared and red turned out to be a powerful index because it was simple to calculate and interpret, yet it yielded strong correlations to abundances strain-specifically (0.85 < r < 0.96, p < 0.001). When all the indices formulated as A/B, A/(A + B) or (A − B)/(A + B), where A and B were wavebands of the spectral camera, were scrutinized, good correlations were found amongst them for biomass of each strain (0.66 < r < 0.98, p < 0.001). Comparison of near-infrared/red index to chlorophyll a concentration demonstrated that small-celled strains had higher chlorophyll absorbance compared to strains with larger cells. The comparison of spectral imaging to chlorophyll fluorescence was done for one strain of green algae and yielded strong correlations (near-infrared/red, r = 0.97, p < 0.001). Consequently, we described a simple imaging setup and information extraction based on vegetation indices that could be used to monitor algae cultures.