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Abstract. Supply of iron (Fe) to the surface ocean supports primary productivity, and while hydrothermal input of Fe to the deep ocean is knownto be extensive it remains poorly constrained. Global estimates of hydrothermal Fe supply rely on using dissolved Fe (dFe) toexcess He (xs3He) ratios to upscale fluxes, but observational constraints on dFe/xs3He may be sensitive toassumptions linked to sampling and interpolation. We examined the variability in dFe/xs3He using two methods of estimation, forfour vent sites with different geochemistry along the Mid-Atlantic Ridge. At both Rainbow and TAG, the plume was sampled repeatedly and the range ofdFe/xs3He was 4 to 63 and 4 to 87 nmol:fmol, respectively, primarily due to differences in plume age. To account for backgroundxs3He and shifting plume position, we calibrated He values using contemporaneous dissolved Mn (dMn). Applying thisapproach more widely, we found dFe/xs3He ratios of 12, 4–8, 4–44, and 4–86 nmol fmol−1 for the Menez Gwen, LuckyStrike, Rainbow, and TAG hydrothermal vent sites, respectively. Differences in plume dFe/xs3He across sites were not simplyrelated to the vent endmember Fe and He fluxes. Within 40 km of the vents, the dFe/xs3He ratios decreased to3–38 nmol fmol−1, due to the precipitation and subsequent settling of particulates. The ratio of colloidal Fe to dFe wasconsistently higher (0.67–0.97) than the deep N. Atlantic (0.5) throughout both the TAG and Rainbow plumes, indicative of Fe exchangebetween dissolved and particulate phases. Our comparison of TAG and Rainbow shows there is a limit to the amount of hydrothermal Fe releasedfrom vents that can form colloids in the rising plume. Higher particle loading will enhance the longevity of the Rainbow hydrothermal plume withinthe deep ocean assuming particles undergo continual dissolution/disaggregation. Future studies examining the length of plume pathways required toescape the ridge valley will be important in determining Fe supply from slow spreading mid-ocean ridges to the deep ocean, along with thefrequency of ultramafic sites such as Rainbow. Resolving the ridge valley bathymetry and accounting for variability in vent sources in globalbiogeochemical models will be key to further constraining the hydrothermal Fe flux. 

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. 

Although iron and light are understood to regulate the Southern Ocean biological carbon pump, observations have also indicated a possible role for manganese. Low concentrations in Southern Ocean surface waters suggest manganese limitation is possible, but its spatial extent remains poorly constrained and direct manganese limitation of the marine carbon cycle has been neglected by ocean models. Here, using available observations, we develop a new global biogeochemical model and find that phytoplankton in over half of the Southern Ocean cannot attain maximal growth rates because of manganese deficiency. Manganese limitation is most extensive in austral spring and depends on phytoplankton traits related to the size of photosynthetic antennae and the inhibition of manganese uptake by high zinc concentrations in Antarctic waters. Importantly, manganese limitation expands under the increased iron supply of past glacial periods, reducing the response of the biological carbon pump. Overall, these model experiments describe a mosaic of controls on Southern Ocean productivity that emerge from the interplay of light, iron, manganese and zinc, shaping the evolution of Antarctic phytoplankton since the opening of the Drake Passage.

 

Abstract. Over the past decade, the GEOTRACES and wider trace metalgeochemical community has made substantial contributions towardsconstraining the marine cobalt (Co) cycle and its major biogeochemicalprocesses. However, few Co speciation studies have been conducted in theNorth and equatorial Pacific Ocean, a vast portion of the world's oceans byvolume and an important end-member of deep thermohaline circulation.Dissolved Co (dCo) samples, including total dissolved and labile Co, weremeasured at-sea during the GEOTRACES Pacific Meridional Transect (GP15) expedition along the 152∘ W longitudinal from 56∘ N to20∘ S. Along this transect, upper-ocean dCo (σ0<26) was linearly correlated with dissolved phosphate (slope = 82±3, µmol : mol) due to phytoplankton uptake and remineralization.As depth increased, dCo concentrations became increasingly decoupled fromphosphate concentrations due to co-scavenging with manganese oxide particlesin the mesopelagic. The transect revealed an organically bound coastalsource of dCo to the Alaskan Stream associated with low-salinity waters. Anintermediate-depth hydrothermal flux of dCo was observed off the Hawaiiancoast at the Loihi Seamount, and the elevated dCo was correlated withpotential xs3He at and above the vent site; however, the Loihi Seamountlikely did not represent a major source of Co to the Pacific basin. Elevatedconcentrations of dCo within oxygen minimum zones (OMZs) in the equatorialNorth and South Pacific were consistent with the suppression of oxidativescavenging, and we estimate that future deoxygenation could increase the OMZdCo inventory by 18 % to 36 % over the next century. In Pacific Deep Water(PDW), a fraction of elevated ligand-bound dCo appeared protected fromscavenging by the high biogenic particle flux in the North Pacific basin.This finding is counter to previous expectations of low dCo concentrationsin the deep Pacific due to scavenging over thermohaline circulation.Compared to a Co global biogeochemical model, the observed transectdisplayed more extreme inventories and fluxes of dCo than predicted by themodel, suggesting a highly dynamic Pacific Co cycle. 

Micronutrients control phytoplankton growth in the ocean, influencing carbon export and fisheries. It is currently unclear how micronutrient scarcity affects cellular processes and how interdependence across micronutrients arises. We show that proximate causes of micronutrient growth limitation and interdependence are governed by cumulative cellular costs of acquiring and using micronutrients. Using a mechanistic proteomic allocation model of a polar diatom focused on iron and manganese, we demonstrate how cellular processes fundamentally underpin micronutrient limitation, and how they interact and compensate for each other to shape cellular elemental stoichiometry and resource interdependence. We coupled our model with metaproteomic and environmental data, yielding an approach for estimating biogeochemical metrics, including taxon-specific growth rates. Our results show that cumulative cellular costs govern how environmental conditions modify phytoplankton growth.