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The hydrography of the Arctic Seas is being altered by ongoing climate change, with knock-on effects to nutrient dynamics and primary production. As the major pathway of exchange between the Arctic and the Atlantic, the Fram Strait hosts two distinct water masses in the upper water column, northward flowing warm and saline Atlantic Waters in the east, and southward flowing cold and fresh Polar Surface Water in the west. Here, we assess how physical processes control nutrient dynamics in the Fram Strait using nitrogen isotope data collected during 2016 and 2018. In Atlantic Waters, a weakly stratified water column and a shallow nitracline reduce nitrogen limitation. To the west, in Polar Surface Water, nitrogen limitation is greater because stronger stratification inhibits nutrient resupply from deeper water and lateral nitrate supply from central Arctic waters is low. A historical hindcast simulation of ocean biogeochemistry from 1970 to 2019 corroborates these findings and highlights a strong link between nitrate supply to Atlantic Waters and the depth of winter mixing, which shoaled during the simulation in response to a local reduction in sea-ice formation. Overall, we find that while the eastern Fram Strait currently experiences seasonal nutrient replenishment and high primary production, the loss of winter sea ice and continued atmospheric warming has the potential to inhibit deep winter mixing and limit primary production in the future.

We present a new approach for quantifying the bioavailability of dissolved iron (dFe) to oceanic phytoplankton. Bioavailability is defined using an uptake rate constant (k

Although iron (Fe) is a key regulator of primary production over much of the ocean, many components of the marine iron cycle are poorly constrained, which undermines our understanding of climate change impacts. In recent years, a growing number of studies (often part of GEOTRACES) have used Fe isotopic signatures (δ56Fe) to disentangle different aspects of the marine Fe cycle. Characteristic δ56Fe endmembers of external sources and assumed isotopic fractionation during biological Fe uptake or recycling have been used to estimate relative source contributions and investigate internal transformations, respectively. However, different external sources and fractionation processes often overlap and act simultaneously, complicating the interpretation of oceanic Fe isotope observations. Here we investigate the driving forces behind the marine dissolved Fe isotopic signature (δ56Fediss) distribution by incorporating Fe isotopes into the global ocean biogeochemical model PISCES. We find that distinct external source endmembers acting alongside fractionation during organic complexation and phytoplankton uptake are required to reproduce δ56Fediss observations along GEOTRACES transects. δ56Fediss distributions through the water column result from regional imbalances of remineralisation and abiotic removal processes. They modify δ56Fediss directly and transfer surface ocean signals to the interior with opposing effects. Although attributing crustal compositions to sedimentary Fe sources in regions with low organic carbon fluxes improves our isotope model, δ56Fediss signals from hydrothermal or sediment sources cannot be reproduced accurately by simply adjusting δ56Fe endmember values. This highlights that additional processes must govern the exchange and/or speciation of Fe supplied by these sources to the ocean.

25 pages, 11 figures, supporting information https://doi.org/10.1029/2020GB006769.-- Data Availability Statement: The new and compiled data reported here are available at the NOAA Paleoclimatology database (https://www.ncdc.noaa.gov/paleo/study/30512), Quantitative knowledge about the burial of sedimentary components at the seafloor has wide‐ranging implications in ocean science, from global climate to continental weathering. The use of 230Th‐normalized fluxes reduces uncertainties that many prior studies faced by accounting for the effects of sediment redistribution by bottom currents and minimizing the impact of age model uncertainty. Here we employ a recently compiled global data set of 230Th‐normalized fluxes with an updated database of seafloor surface sediment composition to derive atlases of the deep‐sea burial flux of calcium carbonate, biogenic opal, total organic carbon (TOC), nonbiogenic material, iron, mercury, and excess barium (Baxs). The spatial patterns of major component burial are mainly consistent with prior work, but the new quantitative estimates allow evaluations of deep‐sea budgets. Our integrated deep‐sea burial fluxes are 136 Tg C/yr CaCO3, 153 Tg Si/yr opal, 20Tg C/yr TOC, 220 Mg Hg/yr, and 2.6 Tg Baxs/yr. This opal flux is roughly a factor of 2 increase over previous estimates, with important implications for the global Si cycle. Sedimentary Fe fluxes reflect a mixture of sources including lithogenic material, hydrothermal inputs and authigenic phases. The fluxes of some commonly used paleo‐productivity proxies (TOC, biogenic opal, and Baxs) are not well‐correlated geographically with satellite‐based productivity estimates. Our new compilation of sedimentary fluxes provides detailed regional and global information, which will help refine the understanding of sediment preservation, This study was supported by the Past Global Changes (PAGES) project, which in turn received support from the Swiss Academy of Sciences and the US‐NSF. The work grew out of a 2018 workshop in Aix‐Marseille, France, funded by PAGES, GEOTRACES, SCOR, US‐NSF, Aix Marseille Université, and John Cantle Scientific, and the authors would like to acknowledge all attendees of this meeting. [...]. Christopher T. Hayes acknowledges support from US‐NSF awards 1658445 and 1737023. Some data compilation on Arctic shelf seas was supported by the Russian Science Foundation, grant number 20‐17‐00157. This work was also supported through project CRESCENDO (grant no. 641816, European Commission). Zanna Chase acknowledges support from the Australian Research Council’s Discovery Projects funding scheme (project DP180102357). Christopher R. German acknowledges US‐NSF awards 1235248 and 1234827, With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)

Numerical models of ocean biogeochemistry are relied upon to make projections about the impact of climate change on marine resources and test hypotheses regarding the drivers of past changes in climate and ecosystems. In large areas of the ocean, iron availability regulates the functioning of marine ecosystems and hence the ocean carbon cycle. Accordingly, our ability to quantify the drivers and impacts of fluctuations in ocean ecosystems and carbon cycling in space and time relies on first achieving an appropriate representation of the modern marine iron cycle in models. When the iron distributions from 13 global ocean biogeochemistry models are compared against the latest oceanic sections from the GEOTRACES program, we find that all models struggle to reproduce many aspects of the observed spatial patterns. Models that reflect the emerging evidence for multiple iron sources or subtleties of its internal cycling perform much better in capturing observed features than their simpler contemporaries, particularly in the ocean interior. We show that the substantial uncertainty in the input fluxes of iron results in a very wide range of residence times across models, which has implications for the response of ecosystems and global carbon cycling to perturbations. Given this large uncertainty, iron fertilization experiments based on any single current generation model should be interpreted with caution. Improvements to how such models represent iron scavenging and also biological cycling are needed to raise confidence in their projections of global biogeochemical change in the ocean.

[1] Alongside climate change, anthropogenic emissions of CO2 will cause ocean acidification (OA), which will impact upon key biogeochemical processes in the ocean such as net primary production (NPP), carbon export (CEX), N2 fixation (NFIX), denitrification (DENIT), and ocean suboxia (SOX). However, appraising the impact of OA on marine biogeochemical cycles requires ocean general circulation and biogeochemistry models (OGCBMs) that necessitate a number of assumptions regarding the response of phytoplankton physiological processes to OA. Of particular importance are changes in C:N:P stoichiometry, which cannot be accounted for in current generation OGCBMs that rely on fixed Redfield C:N:P ratios. We developed a new version of the PISCES OGCBM that resolves the cycles of C, N, and P independently to investigate the impact of assumptions that OA (1) enhances NPP, (2) enhances losses of fixed carbon in dissolved organic forms, and (3) modifies the uptake of nutrients by phytoplankton. In total, six simulations were performed over the period 1860–2100. We find that while the prescribed “CO2 sensitivity” of rate processes explains the NPP response, there are large uncertainties in the response of CEX, NFIX, DENIT, and SOX related to assumptions regarding the fate of fixed carbon and nutrient uptake. The overall responses of NPP and CEX are opposite and of similar magnitude to those predicted to occur from climate change alone, suggesting that changes in stoichiometry and NPP in response to OA (and probably also climate change) need to be evaluated in non-Redfield coupled-climate OGCBMs. Using a recent synthesis of OA experiments, it was not possible to evaluate whether one or more of our scenarios was most likely. Future coupled experimental modeling approaches are necessary to better understand the impact of OA on ocean biogeochemistry.

Iron regulates net primary production (NPP) in a number of ocean regions and exists in a variety of different forms in seawater, not all of which are bioavailable. We used a relatively complex iron cycle model to examine variability in iron speciation as a function of irradiance/temperature and parameterize its first-order impact in a global ocean biogeochemistry model (OBM), which necessitated certain assumptions regarding the representation of iron chemistry. Overall, we find that higher irradiance (typical of shallower mixed layers) promotes the conversion of dissolved iron (dFe) into bioavailable forms (bFe) and increases bFe concentration by 5-53%, depending on parameter values. Temperature plays a secondary role in controlling bFe, with cold mixed layers increasing bFe concentrations. For a given irradiance and temperature, the presence of bioavailable Fe ligands increases bFe/dFe. When bioavailable Fe ligands are present, then reducing the photolability, increasing the log conditional stability, or increasing the concentration of such ligands all act to increase bFe/dFe. Such processes are currently not represented in global OBMs, where iron is typically parameterized as one pool, and we find that NPP can vary by >±20% regionally if the impact of temperature and irradiance on bFe is included, even under a constant circulation. Additionally, iron chemistry is important in controlling the depth over which phytoplankton iron limitation can be alleviated and the subsequent efficiency of iron-based NPP. We also suggest organically complexed dFe must be bioavailable if distributions of phytoplankton biomass and macronutrients are to be reconciled with observations. Our results are important in understanding the role of the irradiance/mixing regime in governing the supply of iron to phytoplankton under a changing climate. New data sets on iron speciation and rate processes will aid in refining our model.

[1] We include a prognostic parameterization of carbon-13 into a global ocean-biogeochemistry model to investigate the spatiotemporal variability in ocean carbon-13 between 1860 and 2000. Carbon-13 was included in all 10 existing carbon pools, with dynamic fractionations occurring during photosynthesis, gas exchange and carbonate chemistry. We find that ocean distributions of δ13CDIC at any point in time are controlled by the interplay between biological fractionation, gas exchange, and ocean mixing. In particular, the deep ocean δ13CDIC is sensitive (by > 0.5‰) to the degree of ocean ventilation. On interannual timescales, although the variability in δ13CDIC is a first order function of the atmospheric δ13CO2 and overall carbon flux, the spatial distributions are controlled by the degree to which surface waters are exposed to the atmosphere. The δ13CPOC is highly sensitive to the species of inorganic carbon assimilated during photosynthesis (by 10 to 17‰), as well as the intrinsic growth rate and in situ [CO2(aq)], suggesting that phytoplankton utilize both HCO3− and CO2(aq). The relationship between Δδ13CDIC and anthropogenic carbon (Cant) varies by ±70% regionally and circulation and biotic effects can influence estimates of Cant that are based on Δδ13CDIC.

Cobalt is an important micronutrient for ocean microbes as it is present in vitamin B12 and is a co-factor in various metalloenzymes that catalyze cellular processes. Moreover, when seawater availability of cobalt is compared to biological demands, cobalt emerges as being depleted in seawater, pointing to a potentially important limiting role. To properly account for the potential biological role for cobalt, there is therefore a need to understand the processes driving the biogeochemical cycling of cobalt and, in particular, the balance between external inputs and internal cycling. To do so, we developed the first cobalt model within a state-of-the-art three-dimensional global ocean biogeochemical model. Overall, our model does a good job in reproducing measurements with a correlation coefficient of >0.7 in the surface and >0.5 at depth. We find that continental margins are the dominant source of cobalt, with a crucial role played by supply under low bottom-water oxygen conditions. The basin-scale distribution of cobalt supplied from margins is facilitated by the activity of manganese-oxidizing bacteria being suppressed under low oxygen and low temperatures, which extends the residence time of cobalt. Overall, we find a residence time of 7 and 250 years in the upper 250 m and global ocean, respectively. Importantly, we find that the dominant internal resupply process switches from regeneration and recycling of particulate cobalt to dissolution of scavenged cobalt between the upper ocean and the ocean interior. Our model highlights key regions of the ocean where biological activity may be most sensitive to cobalt availability.

Copper (Cu) is an unusual micronutrient as it can limit primary production but can also become toxic for growth and cellular functioning under high concentrations. Cu also displays an atypical linear profile, which will modulate its availability to marine microbes across the ocean. Multiple chemical forms of Cu coexist in seawater as dissolved species and understanding the main processes shaping the Cu biogeochemical cycling is hampered by key knowledge gaps. For instance, the drivers of its specific linear profile in seawater are unknown, and the bioavailable form of Cu for marine phytoplankton is debated. Here we developed a global 3‐D biogeochemical model of oceanic Cu within the NEMO/PISCES global model, which represents the global distribution of dissolved copper well. Using our model, we find that reversible scavenging of Cu by organic particles drives the dissolved Cu vertical profile and its distribution in the deep ocean. The low modeled inorganic copper (Cu') in the surface ocean means that Cu' cannot maintain phytoplankton cellular copper requirements within observed ranges. The global budget of oceanic Cu from our model suggests that its residence time may be shorter than previously estimated and provides a global perspective on Cu cycling and the main drivers of Cu biogeochemistry in different regions. Cu scavenging within particle microenvironments and uptake by denitrifying bacteria could be a significant component of Cu cycling in oxygen minimum zones., Key Points Phytoplankton uptake of ligand‐bound copper is necessary to meet phytoplankton copper requirementsReversible scavenging is responsible for the linear profile of dissolved copperLigands are important drivers of the surface Cu cycling