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The importance of dissolved Fe (dFe) in regulating ocean primary production and the carbon cycle is well established. However, the large-scale distribution and temporal dynamics of dFe remain poorly constrained in part due to incomplete observational coverage. In this study, we use a compilation of published dFe observations (n=32,344) with paired environmental predictors from contemporaneous satellite observations and reanalysis products to build a data-driven surface-to-seafloor dFe climatology with 1°×1° resolution using three machine-learning approaches (random forest, supper vector machine and artificial neural network). Among the three approaches, random forest achieves the highest accuracy with overall R 2 and root mean standard error of 0.8 and 0.3 nmol L -1 , respectively. Using this data-driven climatology, we explore the possible mechanisms governing the dFe distribution at various depth horizons using statistical metrics such as Pearson correlation coefficients and the rank of predictors importance in the model construction. Our results are consistent with the critical role of aeolian iron supply in enriching surface dFe in the low latitude regions and suggest a far-reaching impact of this source at depth. Away from the surface layer, the strong correlation between dFe and apparent oxygen utilization implies that a combination of regeneration, scavenging and large-scale ocean circulation are controlling the interior distribution of dFe, with hydrothermal inputs important in some regions. Finally, our data-driven dFe climatology can be used as an alternative reference to evaluate the performance of ocean biogeochemical models. Overall, the new global scale climatology of dFe achieved in our study is an important step toward improved representation of dFe in the contemporary ocean and may also be used to guide future sampling strategies. 

The global air‐sea CO₂flux (F) impacts and is impacted by a plethora of climate‐related processes operating at multiple time scales. In bulk mass transfer formulations, F is driven by physico‐ and bio‐chemical factors such as the air‐sea partial pressure difference (∆pCO₂), gas transfer velocity, sea surface temperature, and salinity–all varying at multiple time scales. To de‐convolve the impact of these factors on variability in F at different time scales, time‐resolved estimates of F were computed using a global data set assembled between 1988 and 2015. The F anomalies were defined as temporal deviations from the 28‐year time‐averaged value. Spectral analysis revealed four dominant timescales of variability in F–subseasonal, seasonal, interannual, and decadal with relative amplitude differences varying across regions. A second‐order Taylor series expansion was then conducted along these four timescales to separate drivers across differing regions. The analysis showed that on subseasonal timescales, wind speed variability explains some 66% of the global F anomaly and is the dominant driver. On seasonal, interannual, and decadal timescales, the ∆pCO₂effect controlled by the ∆pCO₂anomaly, explained much of the F anomaly. On decadal timescales, the F anomaly was almost entirely governed by the ∆pCO₂effect with large contributions from high latitudes. The main drivers across timescales also dominate the regional F anomaly, particularly in the mid‐high latitude regions. Finally, the driver of the ∆pCO₂effect was closely connected with the relative strength of atmospheric pCO₂and the nonthermal component of oceanic pCO₂anomaly associated with dissolved inorganic carbon and alkalinity.

 

Understanding the interplay of ocean physics and biology at the submesoscale and below (<30 km) is an ongoing challenge in oceanography. While poorly constrained, these scales may be of critical importance for understanding how changing ocean dynamics will impact marine ecosystems. Fronts in the ocean, regions where two disparate water masses meet and isopycnals become tilted toward vertical, are considered hotspots for biophysical interaction, but there is limited observational evidence at the appropriate scales to assess their importance. Fronts around western boundary currents like the Gulf Stream are of particular interest as these dynamic physical regions are thought to influence both productivity and composition of primary producers; however, how exactly this plays out is not well known. Using satellite data and 2 years of in situ observations across the Gulf Stream front near Cape Hatteras, North Carolina, we investigate how submesoscale frontal dynamics could affect biological communities and generate hotspots of productivity and export. We assess the seasonality and phenology of the region, generalize the kilometer‐scale structure of the front, and analyze 69 transects to assess two physical processes of potential biogeochemical importance: cold shelf filament subduction and high salinity Sargasso Sea obduction. We link these processes observationally to meanders in the Gulf Stream and discuss how cold filament subduction could be exporting carbon and how obduction of high salinity water from depth is connected with high chlorophyll‐a. Finally, we report on phytoplankton community composition in each of these features and integrate these observations into our understanding of frontal submesoscale dynamics.

 

The significance of the water-side gas transfer velocity for air–sea CO2 gas exchange (k) and its non-linear dependence on wind speed (U) is well accepted. What remains a subject of inquiry are biases associated with the form of the non-linear relation linking k to U (hereafter labeled as f(U), where f(.) stands for an arbitrary function of U), the distributional properties of U (treated as a random variable) along with other external factors influencing k, and the time-averaging period used to determine k from U. To address the latter issue, a Taylor series expansion is applied to separate f(U) into a term derived from time-averaging wind speed (labeled as ⟨U⟩, where ⟨.⟩ indicates averaging over a monthly time scale) as currently employed in climate models and additive bias corrections that vary with the statistics of U. The method was explored for nine widely used f(U) parameterizations based on remotely-sensed 6-hourly global wind products at 10 m above the sea-surface. The bias in k of monthly estimates compared to the reference 6-hourly product was shown to be mainly associated with wind variability captured by the standard deviation σσU around ⟨U⟩ or, more preferably, a dimensionless coefficient of variation Iu= σσU/⟨U⟩. The proposed correction outperforms previous methodologies that adjusted k when using ⟨U⟩ only. An unexpected outcome was that upon setting Iu2 = 0.15 to correct biases when using monthly wind speed averages, the new model produced superior results at the global and regional scale compared to prior correction methodologies. Finally, an equation relating Iu2 to the time-averaging interval (spanning from 6 h to a month) is presented to enable other sub-monthly averaging periods to be used. While the focus here is on CO2, the theoretical tactic employed can be applied to other slightly soluble gases. As monthly and climatological wind data are often used in climate models for gas transfer estimates, the proposed approach provides a robust scheme that can be readily implemented in current climate models. 

Since the middle of the past century, the Western Antarctic Peninsula has warmed rapidly with a significant loss of sea ice but the impacts on plankton biodiversity and carbon cycling remain an open question. Here, using a 5-year dataset of eukaryotic plankton DNA metabarcoding, we assess changes in biodiversity and net community production in this region. Our results show that sea-ice extent is a dominant factor influencing eukaryotic plankton community composition, biodiversity, and net community production. Species richness and evenness decline with an increase in sea surface temperature (SST). In regions with low SST and shallow mixed layers, the community was dominated by a diverse assemblage of diatoms and dinoflagellates. Conversely, less diverse plankton assemblages were observed in waters with higher SST and/or deep mixed layers when sea ice extent was lower. A genetic programming machine-learning model explained up to 80% of the net community production variability at the Western Antarctic Peninsula. Among the biological explanatory variables, the sea-ice environment associated plankton assemblage is the best predictor of net community production. We conclude that eukaryotic plankton diversity and carbon cycling at the Western Antarctic Peninsula are strongly linked to sea-ice conditions.

 

Mixed‐layer dynamics exert a first order control on nutrient and light availability for phytoplankton. In this study, we examine the influence of mixed‐layer dynamics on net community production (NCP) in the Southern Ocean on intra‐seasonal, seasonal, interannual, and decadal timescales, using biogeochemical Argo floats and satellite‐derived NCP estimates during the period from 1997 to 2020. On intraseasonal timescales, the shoaling of the mixed layer is more likely to enhance NCP in austral spring and winter, suggesting an alleviation of light limitation. As expected, NCP generally increases with light availability on seasonal timescales. On interannual timescales, NCP is correlated with mixed layer depth (MLD) and mixed‐layer‐averaged photosynthetically active radiation (PAR) in austral spring and winter, especially in regions with deeper mixed layers. Though recent studies have argued that winter MLD controls the subsequent growing season's iron and light availability, the limited number of Argo float observations contemporaneous with our satellite observations do not show a significant correlation between NCP and the previous‐winter's MLD on interannual timescales. Over the 1997–2020 period, we observe regional trends in NCP (e.g., increasing around S. America), but no trend for the entire Southern Ocean. Overall, our results show that the dependence of NCP on MLD is a complex function of timescales.

 

Despite generally low primary productivity and diatom abundances in oligotrophic subtropical gyres, the North Atlantic Subtropical Gyre (NASG) exhibits significant diatom-driven carbon export on an annual basis. Subsurface pulses of nutrients likely fuel brief episodes of diatom growth, but the exact mechanisms utilized by diatoms in response to these nutrient injections remain understudied within near-natural settings. Here we simulated delivery of subsurface nutrients and compare the response among eukaryotic phytoplankton using a combination of physiological techniques and metatranscriptomics. We show that eukaryotic phytoplankton groups exhibit differing levels of transcriptional responsiveness and expression of orthologous genes in response to release from nutrient limitation. In particular, strategies for use of newly delivered nutrients are distinct among phytoplankton groups. Diatoms channel new nitrate to growth-related strategies while physiological measurements and gene expression patterns of other groups suggest alternative strategies. The gene expression patterns displayed here provide insights into the cellular mechanisms that underlie diatom subsistence during chronic nitrogen-depleted conditions and growth upon nutrient delivery that can enhance carbon export from the surface ocean.

 

Nitrogen availability limits marine productivity across large ocean regions. Diazotrophs can supply new nitrogen to the marine environment via nitrogen (N2) fixation, relieving nitrogen limitation. The distributions of diazotrophs and N2 fixation have been hypothesized to be generally controlled by temperature, phosphorus, and iron availability in the global ocean. However, even in the North Atlantic where most research on diazotrophs and N2 fixation has taken place, environmental controls remain contentious. Here we measure diazotroph composition, abundance, and activity at high resolution using newly developed underway sampling and sensing techniques. We capture a diazotrophic community shift from Trichodesmium to UCYN-A between the oligotrophic, warm (25–29 °C) Sargasso Sea and relatively nutrient-enriched, cold (13–24 °C) subpolar and eastern American coastal waters. Meanwhile, N2 fixation rates measured in this study are among the highest ever recorded globally and show significant increase with phosphorus availability across the transition from the Gulf Stream into subpolar and coastal waters despite colder temperatures and higher nitrate concentrations. Transcriptional patterns in both Trichodesmium and UCYN-A indicate phosphorus stress in the subtropical gyre. Over this iron-replete transect spanning the western North Atlantic, our results suggest that temperature is the major factor controlling the diazotrophic community structure while phosphorous drives N2 fixation rates. Overall, the occurrence of record-high UCYN-A abundance and peak N2 fixation rates in the cold coastal region where nitrate concentrations are highest (~200 nM) challenges current paradigms on what drives the distribution of diazotrophs and N2 fixation.

 

Nitrogen (N) is a limiting nutrient in vast regions of the world’s oceans, yet the sources of N available to various phytoplankton groups remain poorly understood. In this study, we investigated inorganic carbon (C) fixation rates and nitrate (NO3−), ammonium (NH4+) and urea uptake rates at the single cell level in photosynthetic pico-eukaryotes (PPE) and the cyanobacteria Prochlorococcus and Synechococcus. To that end, we used dual 15N and 13C-labeled incubation assays coupled to flow cytometry cell sorting and nanoSIMS analysis on samples collected in the North Pacific Subtropical Gyre (NPSG) and in the California Current System (CCS). Based on these analyses, we found that photosynthetic growth rates (based on C fixation) of PPE were higher in the CCS than in the NSPG, while the opposite was observed for Prochlorococcus. Reduced forms of N (NH4+ and urea) accounted for the majority of N acquisition for all the groups studied. NO3− represented a reduced fraction of total N uptake in all groups but was higher in PPE (17.4 ± 11.2% on average) than in Prochlorococcus and Synechococcus (4.5 ± 6.5 and 2.9 ± 2.1% on average, respectively). This may in part explain the contrasting biogeography of these picoplankton groups. Moreover, single cell analyses reveal that cell-to-cell heterogeneity within picoplankton groups was significantly greater for NO3− uptake than for C fixation and NH4+ uptake. We hypothesize that cellular heterogeneity in NO3− uptake within groups facilitates adaptation to the fluctuating availability of NO3− in the environment.