High Frequency Multi-Year Variability in Baltic Sea Microbial Plankton Stocks and Activities.

Marine bacterioplankton are essential in global nutrient cycling and organic matter turnover. Time-series analyses, often at monthly sampling frequencies, have established the paramount role of abiotic and biotic variables in structuring bacterioplankton communities and productivities. However, fine-scale seasonal microbial activities, and underlying biological principles, are not fully understood. We report results from four consecutive years of high-frequency time-series sampling in the Baltic Proper. Pronounced temporal dynamics in most investigated microbial variables were observed, including bacterial heterotrophic production, plankton biomass, extracellular enzyme activities, substrate uptake rate constants of glucose, pyruvate, acetate, amino acids, and leucine, as well as nutrient limitation bioassays. Spring blooms consisting of diatoms and dinoflagellates were followed by elevated bacterial heterotrophic production and abundances. During summer, bacterial productivity estimates increased even further, coinciding with an initial cyanobacterial bloom in early July. However, bacterial abundances only increased following a second cyanobacterial bloom, peaking in August. Uptake rate constants for the different measured carbon compounds varied seasonally and inter-annually and were highly correlated to bacterial productivity estimates, temperature, and cyanobacterial abundances. Further, we detected nutrient limitation in response to environmental conditions in a multitude of microbial variables, such as elevated productivities in nutrient bioassays, changes in enzymatic activities, or substrate preferences. Variations among biotic variables often occurred on time scales of days to a few weeks, yet often spanning several sampling occasions. Such dynamics might not have been captured by sampling at monthly intervals, as compared to more predictable transitions in abiotic variables such as temperature or nutrient concentrations. Our study indicates that high resolution analyses of microbial biomass and productivity parameters can help out in the development of biogeochemical and food web models disentangling the microbial black box.