Aim To test if a phytoplankton bloom is panmictic, or whether geographical and environmental factors cause spatial and temporal genetic structure.Location Baltic Sea.Method During four cruises, we isolated clonal strains of the diatom Skeletonema marinoi from 9 to 10 stations along a 1132 km transect and analysed the genetic structure using eight microsatellites. Using F-statistics and Bayesian clustering analysis we determined if samples were significantly differentiated. A seascape approach was applied to examine correlations between gene flow and oceanographic connectivity, and combined partial Mantel test and RDA based variation partitioning to investigate associations with environmental gradients. ResultsThe bloom was initiated during the second half of March in the southern and the northern-parts of the transect, and later propagated offshore. By mid-April the bloom declined in the south, whereas high phytoplankton biomass was recorded northward. We found two significantly differentiated populations along the transect. Genotypes were significantly isolated by distance and by the southnorth salinity gradient, which illustrated that the effects of distance and environment were confounded. The gene flow among the sampled stations was significantly correlated with oceanographic connectivity. The depletion of silica during the progression of the bloom was related to a temporal population genetic shift.Main conclusions A phytoplankton bloom may propagate as a continuous cascade and yet be genetically structured over both spatial and temporal scales. The Baltic Sea spring bloom displayed strong spatial structure driven by oceanographic connectivity and geographical distance, which was enhanced by the pronounced salinity gradient. Temporal transition of conditions important for growth may induce genetic shifts and different phenotypic strategies, which serve to maintain the bloom over longer periods.

In temperate systems, phytoplankton spring blooms deplete inorganic nutrients and are major sources of organic matter for the microbial loop. In response to phytoplankton exudates and environmental factors, heterotrophic microbial communities are highly dynamic and change their abundance and composition both on spatial and temporal scales. Yet, most of our understanding about these processes comes from laboratory model organism studies, mesocosm experiments or single temporal transects. Spatial-temporal studies examining interactions of phytoplankton blooms and bacterioplankton community composition and function, though being highly informative, are scarce. In this study, pelagic microbial community dynamics (bacteria and phytoplankton) and environmental variables were monitored during a spring bloom across the Baltic Proper (two cruises between North Germany to Gulf of Finland). To test to what extent bacterioplankton community composition relates to the spring bloom, we used next generation amplicon sequencing of the 16S rRNA gene, phytoplankton diversity analysis based on microscopy counts and population genotyping of the dominating diatom Skeletonema marinoi. Several phytoplankton bloom related and environmental variables were identified to influence bacterial community composition. Members of Bacteroidetes and Alphaproteobacteria dominated the bacterial community composition but the bacterial groups showed no apparent correlation with direct bloom related variables. The less abundant bacterial phyla Actinobacteria, Planctomycetes, and Verrucomicrobia, on the other hand, were strongly associated with phytoplankton biomass, diatom:dinoflagellate ratio, and colored dissolved organic matter (cDOM). Many bacterial operational taxonomic units (OTUs) showed high niche specificities. For example, particular Bacteroidetes OTUs were associated with two distinct genetic clusters of S. marinoi. Our study revealed the complexity of interactions of bacterial taxa with inter- and intraspecific genetic variation in phytoplankton. Overall, our findings imply that biotic and abiotic factors during spring bloom influence bacterial community dynamics in a hierarchical manner.

Modern equipment facilitates phenotyping of hundreds of strains of unicellular organisms by culturing and monitoring growth in microplates. However, in the field of phytoplankton ecology, automated monitoring of growth is not often done and this method has not been tested for many species. To meet the demand for a high‐throughput technique for monitoring growth of chain‐forming phytoplankton species, we have assessed and optimized a method commonly used for other microorganisms. Skeletonema marinoi is a pelagic chain‐forming diatom, and we have acquired growth patterns in four different treatments (i.e., low and high light, low and high nutrient concentrations) when cultured in multi‐well plates. Due to the unexpected heterogeneity in growth rates and maximum cell densities observed between wells (spatial) and runs (temporal), a set of models was fitted to the obtained phenotypic data to correct for these biases. Models were tested for robustness on two replicate multi‐strain experiments including 23 different strains. Using the model accounting for temporal and spatial bias, we could reliably determine changes in growth rate caused by nutrient treatments as well as differences in cell density as a response to nutrient availability and light treatment. This method can facilitate high‐throughput phenotyping of hundreds of strains, which is often a bottleneck in characterizing the ecology and capacity for adaptation of chain‐forming phytoplankton.

Studies of predator-prey systems in both aquatic and terrestrial environments have shown that grazers structure the intraspecific diversity of prey species, given that the prey populations are phenotypically variable. Populations of phytoplankton have traditionally considered comprising only low intraspecific variation, hence selective grazing as a potentially structuring factor of both genetic and phenotypic diversity has not been comprehensively studied. In this study, we compared strain specific growth rates, production of polyunsaturated aldehydes, and chain length of the marine diatom Skeletonema marinoi in both grazer and non-grazer conditions by conducting monoclonal experiments. Additionally, a mesocosm experiment was performed with multiclonal experimental S. marinoi populations exposed to grazers at different levels of copepod concentration to test effects of grazer presence on diatom diversity in close to natural conditions. Our results show that distinct genotypes of a geographically restricted population exhibit variable phenotypic traits relevant to grazing interactions such as chain length and growth rates. Grazer presence affected clonal richness and evenness of multiclonal Skeletonema populations in the mesocosms, likely in conjunction with intrinsic interactions among the diatom strains. Only the production of polyunsaturated aldehydes was not affected by grazer presence. Our findings suggest that grazing can be an important factor structuring diatom population diversity in the sea and emphasize the importance of considering clonal differences when characterizing species and their role in nature.