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.

Phytoplankton is the basis for aquatic food webs and mirrors the water quality. Conventionally, phytoplankton analysis has been done using time consuming and partly subjective microscopic observations, but next generation sequencing (NGS) technologies provide promising potential for rapid automated examination of environmental samples. Because many phytoplankton species have tough cell walls, methods for cell lysis and DNA or RNA isolation need to be efficient to allow unbiased nucleic acid retrieval. Here, we analyzed how two phytoplankton preservation methods, three commercial DNA extraction kits and their improvements, three RNA extraction methods, and two data analysis procedures affected the results of the NGS analysis. A mock community was pooled from phytoplankton species with variation in nucleus size and cell wall hardness. Although the study showed potential for studying Lugol-preserved sample collections, it demonstrated critical challenges in the DNA-based phytoplankton analysis in overall. The 18S rRNA gene sequencing output was highly affected by the variation in the rRNA gene copy numbers per cell, while sample preservation and nucleic acid extraction methods formed another source of variation. At the top, sequence-specific variation in the data quality introduced unexpected bioinformatics bias when the sliding-window method was used for the quality trimming of the Ion Torrent data. While DNA-based analyses did not correlate with biomasses or cell numbers of the mock community, rRNA-based analyses were less affected by different RNA extraction procedures and had better match with the biomasses, dry weight and carbon contents, and are therefore recommended for quantitative phytoplankton analyses.

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.

A small range (, 1uC) of under-ice water temperature is shown to result in remarkably different circulation regimes under spring ice in a deep, oligotrophic boreal lake. With the water column at , 4uC, melting of snow led to deepening vertical convection before ice break and a final depth of convection inversely correlated with earlier deep-water temperature. We attribute that to the nonlinear dependence of water density on temperature, albeit further affected by stochastic weather factors. In four of nine study years, convection led to complete under-ice overturn of the lake, indicating that this may not be uncommon in similar lakes with steep topography. River inflow and more intensive warming of water in the littoral zone also created a horizontal density differential, convection that involved flow down the sloping bottom and a lateral intrusion of this sinking water at a depth between the vertical convection and the quiescent deep-water layers. The vertical and horizontal convection together produced a profile of temperature slightly increasing from the surface to the bottom of the convection layer. The contribution of horizontal convection to under-ice mixing was interannually variable, and in one of the study years it eventually dominated under-ice mixing. A thermal bar circulation regime developed occasionally and only in the open water between ice and shoreline. We identified five different under-ice mixing regimes that form an interannually variable continuum of behavior during the ice melting period. The dependence on a narrow temperature range likely makes the circulation regime sensitive to a warming climate.