The results of empirical studies have revealed links between phytoplankton and bacterioplankton, such as the frequent correlation between chlorophyll a and bulk bacterial abundance and production. Nevertheless, little is known about possible links at the level of specific taxonomic groups. To investigate this issue, seawater microcosm experiments were performed in the northwestern Mediterranean Sea. Turbulence was used as a noninvasive means to induce phytoplankton blooms dominated by different algae. Microcosms exposed to turbulence became dominated by diatoms, while small phytoflagellates gained importance under still conditions. Denaturing gradient gel electrophoresis (DGGE) of 16S rRNA gene fragments showed that changes in phytoplankton community composition were followed by shifts in bacterioplankton community composition, both as changes in the presence or absence of distinct bacterial phylotypes and as differences in the relative abundance of ubiquitous phylotypes. Sequencing of DGGE bands showed that four Roseobacter phylotypes were present in all microcosms. The microcosms with a higher proportion of phytoflagellates were characterized by four phylotypes of the Bacteroidetes phylum: two affiliated with the family Cryomorphaceae and two with the family Flavobacteriaceae . Two other Flavobacteriaceae phylotypes were characteristic of the diatom-dominated microcosms, together with one Alphaproteobacteria phylotype ( Roseobacter ) and one Gammaproteobacteria phylotype ( Methylophaga ). Phylogenetic analyses of published Bacteroidetes 16S rRNA gene sequences confirmed that members of the Flavobacteriaceae are remarkably responsive to phytoplankton blooms, indicating these bacteria could be particularly important in the processing of organic matter during such events. Our data suggest that quantitative and qualitative differences in phytoplankton species composition may lead to pronounced differences in bacterioplankton species composition.

The searching trajectories of different animals can be described with a broad class of flight length ( l _j ) distributions with P ( l _j ) = l _j ^–μ . Theoretical studies have shown that changes in these distributions (i.e., different μ values) are key to optimizing the long-term encounter statistics under certain searcher–resource scenarios. In particular, they predict the advantage of Lévy searching (μ ≈ 2) over Brownian motion (μ ≥ 3) for low-prey-density scenarios. Here, we present experimental evidence of predicted optimal changes in the flight-time distribution of a predator's walk in response to gradual density changes of its moving prey. Flight times of the dinoflagellate Oxyrrhis marina switched from an exponential to an inverse square power-law distribution when the prey ( Rhodomonas sp.) decreased in abundance. Concomitantly, amplitude and frequency of the short-term helical path increased. The specific biological mechanisms involved in these searching behavioral changes are discussed. We suggest that, in a three-dimensional environment, a stronger helical component combined with a Lévy walk searching strategy enhances predator's encounter rates. Our results support the idea of universality of the statistical laws in optimal searching processes despite variations in the biological details of the organisms.

It is a well known fact that stirring keeps particles suspended in fluids. This is apparent, for instance, when shaking medicine flasks, when agitating tea deposits in a mug, or when heavy winds fill the air with dust particles. The commonplace nature of such observations makes it easy to accept that this feature will apply to any natural phenomenon as long as the flow is turbulent enough. This has been the case for phytoplankton in the surface mixed layers of lakes and oceans. The traditional view assumes that an increase in turbulence bears ecological advantages for nonmotile groups like diatoms that, otherwise, would settle in deep and unlit waters. However, this assumption has no theoretical ground, and the experimental results we present here point in the opposite direction. Phytoplankton settling velocity increases when turbulence intensifies from the low to the higher values recorded in the upper mixed layers of lakes and oceans. Consequently, turbulence does not favor phytoplankton remaining in lit waters but is rather an environmental stress that can only be avoided through morphological and/or physiological adaptations.

In the vast Low Nutrient Low‐Chlorophyll (LNLC) Ocean, the vertical nutrient supply from the subsurface to the sunlit surface waters is low, and atmospheric contribution of nutrients may be one order of magnitude greater over short timescales. The short turnover time of atmospheric Fe and N supply (<1 month for nitrate) further supports deposition being an important source of nutrients in LNLC regions. Yet, the extent to which atmospheric inputs are impacting biological activity and modifying the carbon balance in oligotrophic environments has not been constrained. Here, we quantify and compare the biogeochemical impacts of atmospheric deposition in LNLC regions using both a compilation of experimental data and model outputs. A metadata‐analysis of recently conducted field and laboratory bioassay experiments reveals complex responses, and the overall impact is not a simple “fertilization effect of increasing phytoplankton biomass” as observed in HNLC regions. Although phytoplankton growth may be enhanced, increases in bacterial activity and respiration result in weakening of biological carbon sequestration. The application of models using climatological or time‐averaged non‐synoptic deposition rates produced responses that were generally much lower than observed in the bioassay experiments. We demonstrate that experimental data and model outputs show better agreement on short timescale (days to weeks) when strong synoptic pulse of aerosols deposition, similar in magnitude to those observed in the field and introduced in bioassay experiments, is superimposed over the mean atmospheric deposition fields. These results suggest that atmospheric impacts in LNLC regions have been underestimated by models, at least at daily to weekly timescales, as they typically overlook large synoptic variations in atmospheric deposition and associated nutrient and particle inputs. Inclusion of the large synoptic variability of atmospheric input, and improved representation and parameterization of key processes that respond to atmospheric deposition, is required to better constrain impacts in ocean biogeochemical models. This is critical for understanding and prediction of current and future functioning of LNLC regions and their contribution to the global carbon cycle.