Description: Numerical simulations of ocean biogeochemical cycles need to adequately represent particle sinking velocities (SV). For decades, Stokes' Law estimating particle SV from density and size has been widely used. But while Stokes' Law holds for small, smooth, and rigid spheres settling at low Reynolds number, it fails when applied to marine aggregates complex in shape, structure, and composition. Minerals and zooplankton can alter phytoplankton aggregates in ways that change their SV, potentially improving the applicability of Stokes' models. Using rolling cylinders, we experimentally produced diatom aggregates in the presence and absence of minerals and/or microzooplankton. Minerals and to a lesser extent microzooplankton decreased aggregate size and roughness and increased their sphericity and compactness. Stokes' Law parameterized with a fractal porosity modeled adequately size‐SV relationships for mineral‐loaded aggregates. Phytoplankton‐only aggregates and those exposed to microzooplankton followed the general Navier‐Stokes drag equation suggesting an indiscernible effect of microzooplankton and a drag coefficient too complex to be calculated with a Stokes' assumption. We compared our results with a larger data set of ballasted and nonballasted marine aggregates. This confirmed that the size‐SV relationships for ballasted aggregates can be simulated by Stokes' models with an adequate fractal porosity parameterization. Given the importance of mineral ballasting in the ocean, our findings could ease biogeochemical model parameterization for a significant pool of particles in the ocean and especially in the mesopelagic zone where the particulate organic matter : mineral ratio decreases. Our results also reinforce the importance of accounting for porosity as a decisive predictor of marine aggregate SV.

Description: Microalgae produce copious amounts of structurally diverse polysaccharides, some are bound within cells and cell walls, while others are secreted into the surrounding seawater. A fraction of the secreted polysaccharides assembles into particles promoting aggregation and in turn formation of aggregates increases the export of carbon into the deep ocean via sinking. However, specific polysaccharides contributing to particle formation and carbon export remain unknown. Here, we studied microalgae polysaccharide composition in a system of reduced complexity consisting of lab grown monospecific cultures of the centric diatom species Thalassiosira weissflogii and Chaetoceros socialis. We followed the abundance and dynamics of five specific polysaccharide types in the dissolved and particulate organic matter (DOM and POM) for two weeks. Polysaccharides were detected using monoclonal antibodies (mAbs) specific for β-1,4-mannan, β-1,4-xylan, arabinogalactan, and two fucose-containing sulfated polysaccharide (FCSP) epitopes. Additionally, glycan composition of all samples was analyzed by monosaccharide analysis. The time series revealed polysaccharides partition differently between the dissolved and particulate carbon pools. β-1,4-xylan and β-1,4-mannan were mainly present in POM, possibly as cell wall polymers, while FCSPs were found in both DOM and POM. The data showed that the main glycan component secreted by diatoms was fucose-containing polysaccharide, which accumulated in DOM over time. Roller tank experiments were used to induce aggregate formation finding FCSP transitioned from DOM to POM under aggregating conditions. These results suggest that diatom-secreted FCSPs are involved in the formation of aggregates, which promote the formation of particles, and potentially carbon export.

Description: Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.

Description: Diatom aggregates constitute a significant fraction of the particle flux from the euphotic zone into the mesopelagic ocean as part of the ocean's biological carbon pump. Modeling studies of their exchange processes with the surrounding water usually assume spherical shape and that aggregates are impermeable to flow. Using particle image velocimetry, we examined flow distributions around individual aggregates of various irregular shapes formed from two different diatom species: (1) Skeletonema marinoi, known for its cell–cell stickiness, and (2) Chaetoceros affinis, exhibiting cell-TEP (transparent exopolymeric particles) stickiness. Chaetoceros aggregates formed porous, highly irregularly shaped aggregates as compared to the more compact and near-spherical Skeletonema aggregates, yet flow distributions around both types of aggregates were relatively similar at a millimeter scale. At a micrometer scale, the irregular shape of diatom aggregates caused velocity gradients and vorticity close to the surface to locally vary more than for spherical model aggregates (agar-yeast spheres). Water was deflected from the surface of all aggregate types and we found no direct evidence that flow occurred within aggregates. Digital holographic imaging and Alcian blue staining revealed a substantial presence of TEP likely clogging the interstitial pore spaces in Chaetoceros aggregates. Radial oxygen concentration distributions measured by O2 microsensors within the aggregates were similar to those modeled for aggregates and spheres impermeable to flow. Thus, transport of gases, nutrients, and solutes likely occurs by diffusion, even within large, irregularly shaped diatom aggregates during sinking.

Description: The collection of zooplankton swimmers and sinkers in time-series sediment traps provides unique insight into year-round and interannual trends in zooplankton population dynamics. These samples are particularly valuable in remote and difficult to access areas such as the Arctic Ocean, where samples from the ice-covered season are rare. In the present study, we investigated zooplankton composition based on swimmers and sinkers collected by sediment traps at water depths of 180–280, 800–1320, and 2320–2550 m, over a period of 16 yr (2000–2016) at the Long-Term Ecological Research observatory HAUSGARTEN located in the eastern Fram Strait (79°N, 4°E). The time-series data showed seasonal and interannual trends within the dominant zooplankton groups including copepoda, foraminifera, ostracoda, amphipoda, pteropoda, and chaetognatha. Amphipoda and copepoda dominated the abundance of swimmers while pteropoda and foraminifera were the most important sinkers. Although the seasonal occurrence of these groups was relatively consistent between years, there were notable interannual variations in abundance, suggesting the influence of various environmental condi- tions such as sea-ice dynamic and lateral advection of water masses, for example, meltwater and Atlantic water. Statistical analyses revealed a correlation between the Arctic dipole climatic index and sea-ice dynamics (i.e., ice coverage and concentration), as well as the importance of the distance from the ice edge on swimmer composition patterns and carbon export.