Seasonal mixed layer depth shapes phytoplankton physiology, viral production, and accumulation in the North Atlantic.

Seasonal shifts in phytoplankton accumulation and loss largely follow changes in mixed layer depth, but the impact of mixed layer depth on cell physiology remains unexplored. Here, we investigate the physiological state of phytoplankton populations associated with distinct bloom phases and mixing regimes in the North Atlantic. Stratification and deep mixing alter community physiology and viral production, effectively shaping accumulation rates. Communities in relatively deep, early-spring mixed layers are characterized by low levels of stress and high accumulation rates, while those in the recently shallowed mixed layers in late-spring have high levels of oxidative stress. Prolonged stratification into early autumn manifests in negative accumulation rates, along with pronounced signatures of compromised membranes, death-related protease activity, virus production, nutrient drawdown, and lipid markers indicative of nutrient stress. Positive accumulation renews during mixed layer deepening with transition into winter, concomitant with enhanced nutrient supply and lessened viral pressure.

Seasonal modulation of phytoplankton biomass in the Southern Ocean.

Over the last ten years, satellite and geographically constrained in situ observations largely focused on the northern hemisphere have suggested that annual phytoplankton biomass cycles cannot be fully understood from environmental properties controlling phytoplankton division rates (e.g., nutrients and light), as they omit the role of ecological and environmental loss processes (e.g., grazing, viruses, sinking). Here, we use multi-year observations from a very large array of robotic drifting floats in the Southern Ocean to determine key factors governing phytoplankton biomass dynamics over the annual cycle. Our analysis reveals seasonal phytoplankton accumulation ('blooming') events occurring during periods of declining modeled division rates, an observation that highlights the importance of loss processes in dictating the evolution of the seasonal cycle in biomass. In the open Southern Ocean, the spring bloom magnitude is found to be greatest in areas with high dissolved iron concentrations, consistent with iron being a well-established primary limiting nutrient in this region. Under ice observations show that biomass starts increasing in early winter, well before sea ice begins to retreat. The average theoretical sensitivity of the Southern Ocean to potential changes in seasonal nutrient and light availability suggests that a 10% change in phytoplankton division rate may be associated with a 50% reduction in mean bloom magnitude and annual primary productivity, assuming simple changes in the seasonal magnitude of phytoplankton division rates. Overall, our results highlight the importance of quantifying and accounting for both division and loss processes when modeling future changes in phytoplankton biomass cycles.

Temperate infection in a virus-host system previously known for virulent dynamics.

The blooming cosmopolitan coccolithophore Emiliania huxleyi and its viruses (EhVs) are a model for density-dependent virulent dynamics. EhVs commonly exhibit rapid viral reproduction and drive host death in high-density laboratory cultures and mesocosms that simulate blooms. Here we show that this system exhibits physiology-dependent temperate dynamics at environmentally relevant E. huxleyi host densities rather than virulent dynamics, with viruses switching from a long-term non-lethal temperate phase in healthy hosts to a lethal lytic stage as host cells become physiologically stressed. Using this system as a model for temperate infection dynamics, we present a template to diagnose temperate infection in other virus-host systems by integrating experimental, theoretical, and environmental approaches. Finding temperate dynamics in such an established virulent host-virus model system indicates that temperateness may be more pervasive than previously considered, and that the role of viruses in bloom formation and decline may be governed by host physiology rather than by host-virus densities.

Small phytoplankton dominate western North Atlantic biomass.

The North Atlantic phytoplankton spring bloom is the pinnacle in an annual cycle that is driven by physical, chemical, and biological seasonality. Despite its important contributions to the global carbon cycle, transitions in plankton community composition between the winter and spring have been scarcely examined in the North Atlantic. Phytoplankton composition in early winter was compared with latitudinal transects that captured the subsequent spring bloom climax. Amplicon sequence variants (ASVs), imaging flow cytometry, and flow-cytometry provided a synoptic view of phytoplankton diversity. Phytoplankton communities were not uniform across the sites studied, but rather mapped with apparent fidelity onto subpolar- and subtropical-influenced water masses of the North Atlantic. At most stations, cells < 20-µm diameter were the main contributors to phytoplankton biomass. Winter phytoplankton communities were dominated by cyanobacteria and pico-phytoeukaryotes. These transitioned to more diverse and dynamic spring communities in which pico- and nano-phytoeukaryotes, including many prasinophyte algae, dominated. Diatoms, which are often assumed to be the dominant phytoplankton in blooms, were contributors but not the major component of biomass. We show that diverse, small phytoplankton taxa are unexpectedly common in the western North Atlantic and that regional influences play a large role in modulating community transitions during the seasonal progression of blooms.

Validation of the particle size distribution obtained with the laser in-situ scattering and transmission (LISST) meter in flow-through mode.

High spatial and temporal resolution estimates of the particle size distribution (PSD) in the surface ocean can enable improved understanding of biogeochemistry and ecosystem dynamics. Oceanic PSD measurements remain rare due to the time-consuming, manual sampling methods of common particle sizing instruments. Here, we evaluate the utility of measuring particle size data at high spatial resolution with a commercially-available submersible laser diffraction particle sizer (LISST-100X, Sequoia Scientific), operating in an automated mode with continuously flowing seawater. The LISST PSD agreed reasonably well with discrete PSD measurements obtained with a Coulter Counter and data from the flow-through sampling Imaging Flow-Cytobot, validating our methodology. Total particulate area and Volume derived from the LISST PSD agreed well with beam-attenuation and particulate organic carbon respectively, further validating the LISST PSD. Furthermore, When compared to the measured spectral characteristics of particulate beam attenuation, we find a significant correlation. However, no significant relationship between the PSD and spectral particulate backscattering was found.

An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models.

We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters.

Influence of Raman scattering on ocean color inversion models.

Raman scattering can be a significant contributor to the emergent radiance spectrum from the surface ocean. Here, we present an analytical approach to directly estimate the Raman contribution to remote sensing reflectance, and evaluate its effects on optical properties estimated from two common semianalytical inversion models. For application of the method to ocean color remote sensing, spectral irradiance products in the ultraviolet from the OMI instrument are merged with MODerate-resolution Imaging Spectroradiometer (MODIS) data in the visible. The resulting global fields of Raman-corrected optical properties show significant differences from standard retrievals, particularly for the particulate backscattering coefficient, b(bp), where average errors in clear ocean waters are ~50%. Given the interest in transforming b(bp) into biogeochemical quantities, Raman scattering must be accounted for in semianalytical inversion schemes.

The oligotrophic ocean is autotrophic.

In vitro observations of net community production (NCP) imply that the oligotrophic subtropical gyres of the open ocean are net heterotrophic; in situ observations, in contrast, consistently imply that they are net autotrophic. At least one approach must be returning an incorrect answer. We find that (a) no bias in in situ oxygen-based production estimates would give false-positive (net autotrophy) rates, (b) observed (13)C enrichment of surface water dissolved inorganic carbon (DIC) can be explained only by positive NCP (net autotrophy), (c) lateral and vertical inputs of organic carbon are insufficient to sustain net heterotrophy, and (d) atmospheric input of organic material is too small to support in vitro rates of net heterotrophy and would yield δ(13)C depletion of surface DIC, quite the opposite of what is observed in the subtropical gyres. We conclude that the in vitro observations, implying net heterotrophy, must contain a bias that is due to an underestimate of photosynthetic rate and/or an overestimate of respiration rate.

Coherence of particulate beam attenuation and backscattering coefficients in diverse open ocean environments.

We present an extensive data set of particle attenuation (c(p)), backscattering (b(bp)), and chlorophyll concentration (Chl) from a diverse set of open ocean environments. A consistent observation in the data set is the strong coherence between c(p) and b(bp) and the resulting constancy of the backscattering ratio (0.010 +/- 0.002). The strong covariability between c(p) and b(bp) must be rooted in one or both of two explanations, 1) the size distribution of particles in the ocean is remarkably conserved and particle types responsible for c(p) and b(bp) covary, 2) the same particle types exert influence on both quantities. Therefore, existing relationships between c(p) or Chl:c(p) and phytoplankton biomass and physiological indices can be conceptually extended to the use of b(bp). This finding lends support to use of satellite-derived Chl and b(bp) for investigation of phytoplankton biomass and physiology and broadens the applications of existing ocean color retrievals.