Weekly dynamics of abundance and size structure of specific nanophytoplankton lineages in coastal waters (Baltic Sea)

Abstract

Nanophytoplankton, the key component of algal communities, remains understudied, thus there is a substantial knowledge gap about dynamics of abundance, biovolume, and cell size of specific algae. Here, I studied weekly changes in abundance, biovolume, cell volume, and cell surface to volume (SV) ratio (> 11,700 cells measured) of specific nanophytoplankton groups using amplicon sequencing and catalyzed reported deposition‐fluorescence in situ hybridization. I applied oligonucleotide probes to study major nanophytoplankton groups: chlorophytes, chrysophytes, pelagophytes, cryptophytes, pedinellids, and haptophytes. I designed three novel probes, two for pedinellid species Apedinella radians and Pseudopedinella elastica, and for a haptophyte genus Haptolina. Chlorophytes were the most abundant group, followed by haptophytes and cryptophytes. Abundance and biovolume of specific groups showed distinct seasonal dynamics and fluctuated up to 100‐fold within a week. Different groups contributed to nanophytoplankton peaks over the season, and this pattern was consistent down to a genus/species level, as shown for cryptophytes, pedinellids, and haptophytes. Inorganic nutrients were the best explanatory variables for abundance and biovolume, but their importance varied for specific groups. Thus, the differences in seasonal dynamics of different algal groups can be explained by temporal niche separation between them. Changes in nanophytoplankton size structure were substantial, and cell volume varied over 104‐fold. However, the size dynamics (variability in cell volume and SV ratio) was lower at genus/species level, indicating changes in nanophytoplankton size structure likely resulted from changes in community composition. Temperature and nutrients best explained the size dynamics, but their explanatory power differed for specific nanophytoplankton groups.

Bacterial and Eukaryotic Small-Subunit Amplicon Data Do Not Provide a Quantitative Picture of Microbial Communities, but They Are Reliable in the Context of Ecological Interpretations

“…The agreement was very good for the eukaryotic data set, as in both cases DistML pointed to soluble reactive phosphorus (SRP) as the only explanatory variable ( Table 2). However, this result was largely driven by a single outlier sample, for which we observed elevated SRP concentrations and a massive bloom of the dinoflagellate Heterocapsa triquetra (46). The abundance of nanophytoplankton was substantially lower in this sample, and the sequencing library was dominated by reads from the dinoflagellate.…”

“…The CARD-FISH procedure was performed with Alexa 488-labeled tyramides (Molecular Probes, Thermo Fisher Scientific, Waltham, MA, USA), as previously described (56), and analyzed manually using 10 to 20 microphotographs randomly taken by epifluorescence microscopy at ϫ1,000 magnification (AxioVision.M1; Carl Zeiss, Jena, Germany). Biovolume was estimated by multiplying cell abundance by average cell volume, which was calculated based on manual measurements of cell width and length and assuming the cell shape to be prolate spheroid, as described by Piwosz in 2019 (46). The relative abundance of an individual lineage was calculated as the proportion of cells hybridized with the specific probe to that of cells hybridized with the general eukaryotic probe.…”

“…Interestingly, this agreed with the CARD-FISH biovolume data, for which a significant model was not found in both cases ( Table 2). This imperfect agreement between the models can be partially attributed to the fact that eukaryotic abundance and biovolume may respond differently to changing conditions (46). In general, it seems that statistical models calculated from HTS and CARD-FISH data may identify the same environmental drivers affecting eukaryotic microbial communities, but it is advisable to combine and calibrate HTS with microscopic methods during experiments aimed to test hypotheses derived from statistical models on observational data.…”

Cascading effects in freshwater microbial food webs by predatory Cercozoa, Katablepharidacea and ciliates feeding on aplastidic bacterivorous cryptophytes

“… 2009 ; Grujčić et al . 2018 , Piwosz 2019 ). Thus, taxa with otherwise poor morphological distinguishability can be identified by a strong fluorescence signal and prevailing food items in their food vacuoles can be examined.…”

Seasonal and Spatial Changes of Primary Production in the Baltic Sea (Europe) Based on in situ Measurements in the Period of 1993–2018

“…Phytoplankton taxa forming blooms have different specific of both photosynthesis and growth rates. The highest ones was observed for nanoplankton (2-20 µm) (Maranon et al, 2013;Piwosz, 2019).…”