Factors influencing the pigment composition and dynamics of photoautotrophic picoplankton in shallow eutrophic lakes.

Photoautotrophic picoplankton (0.2-2 µm) can be a major contributor to primary production and play a significant part in the ecosystem carbon flow. However, the understanding about the dynamics of both eukaryotic and prokaryotic components of picoplankton in shallow eutrophic freshwater environments is still poor. Very few studies in these ecosystems reveal the taxonomic composition of picoeukaryotes. The main objective of this study was to investigate the seasonal dynamics of phototrophic picoplankton with the emphasis on the eukaryote community composition in a large shallow, eutrophic lake of the northern temperate zone (Lake Võrtsjärv). Phytoplankton pigments were employed to determine the taxonomic composition of photoautotrophic picoplankton. We found out that photoautotrophic picoplankton constitutes an important part of the phytoplankton community in Lake Võrtsjärv and its contribution can be highly variable (from ~9.3% to ~39%) in different years. The eukaryotic photoautotrophic picoplankton was dominated by diatoms followed by chrysophytes and other minor groups. Picoeukaryotes were prevailing in low-light conditions and low temperatures as their predominance in the picoplankton community was tightly linked to the presence or absence of ice cover. Ice cover strongly suppressed the growth of picocyanobacteria. Total phosphorus, turbidity and metazooplankton abundance had a clear relationship with photoautotrophic picoplankton chlorophyll a.

Using Microcystin Gene Copies to Determine Potentially-Toxic Blooms, Example from a Shallow Eutrophic Lake Peipsi.

Global warming, paired with eutrophication processes, is shifting phytoplankton communities towards the dominance of bloom-forming and potentially toxic cyanobacteria. The ecosystems of shallow lakes are especially vulnerable to these changes. Traditional monitoring via microscopy is not able to quantify the dynamics of toxin-producing cyanobacteria on a proper spatio-temporal scale. Molecular tools are highly sensitive and can be useful as an early warning tool for lake managers. We quantified the potential microcystin (MC) producers in Lake Peipsi using microscopy and quantitative polymerase chain reaction (qPCR) and analysed the relationship between the abundance of the mcyE genes, MC concentration, MC variants and toxin quota per mcyE gene. We also linked environmental factors to the cyanobacteria community composition. In Lake Peipsi, we found rather moderate MC concentrations, but microcystins and microcystin-producing cyanobacteria were widespread across the lake. Nitrate (NO3-) was a main driver behind the cyanobacterial community at the beginning of the growing season, while in late summer it was primarily associated with the soluble reactive phosphorus (SRP) concentration. A positive relationship was found between the MC quota per mcyE gene and water temperature. The most abundant variant-MC-RR-was associated with MC quota per mcyE gene, while other MC variants did not show any significant impact.

Parallel assessment of marine autotrophic picoplankton using flow cytometry and chemotaxonomy.

Autotrophic picoplankton (0.2-2µm) can be a significant contributor to primary production and hence play an important role in carbon flow. The phytoplankton community structure in the Baltic Sea is very region specific and the understanding of the composition and dynamics of pico-size phytoplankton is generally poor. The main objective of this study was to determine the contribution of picoeukaryotic algae and their taxonomic composition in late summer phytoplankton community of the West-Estonian Archipelago Sea. We found that about 20% of total chlorophyll a (Chl a) in this area belongs to autotrophic picoplankton. With increasing total Chl a, the Chl a of autotrophic picoplankton increased while its contribution in total Chl a decreased. Picoeukaryotes play an important role in the coastal area of the Baltic Sea where they constituted around 50% of the total autotrophic picoplankton biomass. The most abundant groups of picoeukaryotic algae were cryptophytes (16%), chlorophytes (13%) and diatoms (9%). Picocyanobacteria were clearly dominated by phycoerythrin containing Synechococcus. The parallel use of different assessment methods (CHEMTAX and flow cytometry) revealed the share of eukaryotic and prokaryotic part of autotrophic picoplankton.

Pigment-based chemotaxonomy--a quick alternative to determine algal assemblages in large shallow eutrophic lake?

Pigment-based chemotaxonomy and CHEMTAX software have proven to be a valuable phytoplankton monitoring tool in marine environments, but are yet underdeveloped to determine algal assemblages in freshwater ecosystems. The main objectives of this study were (1) to compare the results of direct microscopy and CHEMTAX in describing phytoplankton community composition dynamics in a large, shallow and eutrophic lake; (2) to analyze the efficiency of the pigment-based method to detect changes in phytoplankton seasonal dynamics and during rapid bloom periods; (3) to assess the suitability of specific marker pigments and available marker pigment:chlorophyll a ratios to follow seasonal changes in eutrophic freshwater environment. A 5-year (2009-2013) parallel phytoplankton assessment by direct microscopy and by CHEMTAX was conducted using published marker pigment:chlorophyll a ratios. Despite displaying some differences from microscopy results, the pigment-based method successfully described the overall pattern of phytoplankton community dynamics during seasonal cycle in a eutrophic lake. Good agreement between the methods was achieved for most phytoplankton groups - cyanobacteria, chlorophytes, diatoms and cryptophytes. The agreement was poor in case of chrysophytes and dinoflagellates. Our study shows clearly that published marker pigment:chlorophyll a ratios can be used to describe algal class abundances, but they need to be calibrated for specific freshwater environment. Broader use of this method would enable to expand monitoring networks and increase measurement frequencies of freshwater ecosystems to meet the goals of the Water Framework Directive.