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  • European Marine Science
  • 2018-2022
  • UK Research and Innovation
  • US
  • BE
  • Biogeosciences (BG)

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: J. P. J. Ward; K. R. Hendry; K. R. Hendry; S. Arndt; +11 Authors

    Over recent decades the highest rates of water column warming and sea ice loss across the Arctic Ocean have been observed in the Barents Sea. These physical changes have resulted in rapid ecosystem adjustments, manifesting as a northward migration of temperate phytoplankton species at the expense of silica-based diatoms. These changes will potentially alter the composition of phytodetritus deposited at the seafloor, which acts as a biogeochemical reactor and is pivotal in the recycling of key nutrients, such as silicon (Si). To appreciate the sensitivity of the Barents Sea benthic system to the observed changes in surface primary production, there is a need to better understand this benthic–pelagic coupling. Stable Si isotopic compositions of sediment pore waters and the solid phase from three stations in the Barents Sea reveal a coupling of the iron (Fe) and Si cycles, the contemporaneous dissolution of lithogenic silicate minerals (LSi) alongside biogenic silica (BSi), and the potential for the reprecipitation of dissolved silicic acid (DSi) as authigenic clay minerals (AuSi). However, as reaction rates cannot be quantified from observational data alone, a mechanistic understanding of which factors control these processes is missing. Here, we employ reaction–transport modelling together with observational data to disentangle the reaction pathways controlling the cycling of Si within the seafloor. Processes such as the dissolution of BSi are active on multiple timescales, ranging from weeks to hundreds of years, which we are able to examine through steady state and transient model runs. Steady state simulations show that 60 % to 98 % of the sediment pore water DSi pool may be sourced from the dissolution of LSi, while the isotopic composition is also strongly influenced by the desorption of Si from metal oxides, most likely Fe (oxyhydr)oxides (FeSi), as they reductively dissolve. Further, our model simulations indicate that between 2.9 % and 37 % of the DSi released into sediment pore waters is subsequently removed by a process that has a fractionation factor of approximately −2 ‰, most likely representing reprecipitation as AuSi. These observations are significant as the dissolution of LSi represents a source of new Si to the ocean DSi pool and precipitation of AuSi an additional sink, which could address imbalances in the current regional ocean Si budget. Lastly, transient modelling suggests that at least one-third of the total annual benthic DSi flux could be sourced from the dissolution of more reactive, diatom-derived BSi deposited after the surface water bloom at the marginal ice zone. This benthic–pelagic coupling will be subject to change with the continued northward migration of Atlantic phytoplankton species, the northward retreat of the marginal ice zone and the observed decline in the DSi inventory of the subpolar North Atlantic Ocean over the last 3 decades.

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    Biogeosciences
    Article . 2022
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    Biogeosciences (BG)
    Other literature type . 2022
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    Biogeosciences
    Article . 2022 . Peer-reviewed
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    https://doi.org/10.5194/bg-202...
    Preprint . 2022 . Peer-reviewed
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      Biogeosciences
      Article . 2022
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      Biogeosciences (BG)
      Other literature type . 2022
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      Biogeosciences
      Article . 2022 . Peer-reviewed
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      https://doi.org/10.5194/bg-202...
      Preprint . 2022 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Viviana Otero; Steven Pint; Klaas Deneudt; Maarten De Rijcke; +7 Authors

    Marine phytoplankton biomass dynamics are affected by eutrophication, ocean warming, and ocean acidification. These changing abiotic conditions may impact phytoplankton biomass and its spatiotemporal dynamics. In this study, we used a nutrient–phytoplankton–zooplankton (NPZ) model to quantify the relative importance of the bottom-up and top-down determinants of phytoplankton biomass dynamics in the Belgian part of the North Sea (BPNS). Using four years (2014–2017) of monthly observations of nutrients, solar irradiance, sea surface temperature, chlorophyll-a, and zooplankton biomass at ten locations, we disentangled the monthly, seasonal, and yearly variation in phytoplankton biomass dynamics. To quantify how the relative importance of determinants changed along a near–offshore gradient, the analysis was performed for three spatial regions, i.e., the nearshore region (<10 km to the coastline), the midshore region (10–30 km), and the offshore region (>30 km). We found that, from year 2014 to 2017, the phytoplankton biomass dynamics ranged from 1.4 to 23.1 mg Chla m−3. Phytoplankton biomass dynamics follow a general seasonal cycle, as is the case in other temperate regional seas, with a distinct spring bloom (5.3–23.1 mg Chla m−3) and a modest autumn bloom (2.9–5.4 mg Chla m−3). This classic bimodal bloom pattern was not observed between 2003 and 2010 in the BPNS. The seasonal pattern was most expressed in the nearshore region. The relative contribution of factors determining phytoplankton biomass dynamics varied spatially and temporally. Throughout a calendar year, solar irradiance and zooplankton grazing were the most influential determinants in all regions, i.e., they jointly explained 38–65% of the variation in the offshore region, 45–71% in the midshore region, and 56–77% in the nearshore region. In the near- and midshore regions, nutrients were the greatest limit on phytoplankton production in the month following the spring bloom (44–55%). Nutrients were a determinant throughout the year in the offshore region (27–62%). During winter, sea surface temperature was a determinant in all regions (15–17%). By the high-resolution spatiotemporal analysis of the relative contributions of different determinants, this study contributes to a better mechanistic understanding of the spatiotemporal dynamics of phytoplankton biomass in the southern North Sea. This detailed understanding is anticipated to contribute to the definition of targeted management strategies for the BPNS and to support sustainable development in Belgium’s blue economy.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Journal of Marine Sc...arrow_drop_down
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    https://doi.org/10.5194/bg-202...
    Preprint . 2022 . Peer-reviewed
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Journal of Marine Sc...arrow_drop_down
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      https://doi.org/10.5194/bg-202...
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    Authors: Rödenbeck, Christian; DeVries, Tim; Hauck, Judith; Quéré, Corinne; +1 Authors

    This study considers year-to-year and decadal variations in as well as secular trends of the sea–air CO2 flux over the 1957–2020 period, as constrained by the pCO2 measurements from the SOCATv2021 database. In a first step, we relate interannual anomalies in ocean-internal carbon sources and sinks to local interannual anomalies in sea surface temperature (SST), the temporal changes in SST (dSST/dt), and squared wind speed (u2), employing a multi-linear regression. In the tropical Pacific, we find interannual variability to be dominated by dSST/dt, as arising from variations in the upwelling of colder and more carbon-rich waters into the mixed layer. In the eastern upwelling zones as well as in circumpolar bands in the high latitudes of both hemispheres, we find sensitivity to wind speed, compatible with the entrainment of carbon-rich water during wind-driven deepening of the mixed layer and wind-driven upwelling. In the Southern Ocean, the secular increase in wind speed leads to a secular increase in the carbon source into the mixed layer, with an estimated reduction in the sink trend in the range of 17 % to 42 %. In a second step, we combined the result of the multi-linear regression and an explicitly interannual pCO2-based additive correction into a “hybrid” estimate of the sea–air CO2 flux over the period 1957–2020. As a pCO2 mapping method, it combines (a) the ability of a regression to bridge data gaps and extrapolate into the early decades almost void of pCO2 data based on process-related observables and (b) the ability of an auto-regressive interpolation to follow signals even if not represented in the chosen set of explanatory variables. The “hybrid” estimate can be applied as an ocean flux prior for atmospheric CO2 inversions covering the whole period of atmospheric CO2 data since 1957.

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    Other literature type . 2021
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    Authors: C. Wohl; C. Wohl; C. Wohl; C. Wohl; +9 Authors

    The marginal sea ice zone has been identified as a source of different climate-active gases to the atmosphere due to its unique biogeochemistry. However, it remains highly undersampled, and the impact of summertime changes in sea ice concentration on the distributions of these gases is poorly understood. To address this, we present measurements of dissolved methanol, acetone, acetaldehyde, dimethyl sulfide, and isoprene in the sea ice zone of the Canadian Arctic from the surface down to 60 m. The measurements were made using a segmented flow coil equilibrator coupled to a proton-transfer-reaction mass spectrometer. These gases varied in concentrations with depth, with the highest concentrations generally observed near the surface. Underway (3–4 m) measurements showed higher concentrations in partial sea ice cover compared to ice-free waters for most compounds. The large number of depth profiles at different sea ice concentrations enables the proposition of the likely dominant production processes of these compounds in this area. Methanol concentrations appear to be controlled by specific biological consumption processes. Acetone and acetaldehyde concentrations are influenced by the penetration depth of light and stratification, implying dominant photochemical sources in this area. Dimethyl sulfide and isoprene both display higher surface concentrations in partial sea ice cover compared to ice-free waters due to ice edge blooms. Differences in underway concentrations based on sampling region suggest that water masses moving away from the ice edge influences dissolved gas concentrations. Dimethyl sulfide concentrations sometimes display a subsurface maximum in ice -free conditions, while isoprene more reliably displays a subsurface maximum. Surface gas concentrations were used to estimate their air–sea fluxes. Despite obvious in situ production, we estimate that the sea ice zone is absorbing methanol and acetone from the atmosphere. In contrast, dimethyl sulfide and isoprene are consistently emitted from the ocean, with marked episodes of high emissions during ice-free conditions, suggesting that these gases are produced in ice-covered areas and emitted once the ice has melted. Our measurements show that the seawater concentrations and air–sea fluxes of these gases are clearly impacted by sea ice concentration. These novel measurements and insights will allow us to better constrain the cycling of these gases in the polar regions and their effect on the oxidative capacity and aerosol budget in the Arctic atmosphere This work was supported by the Natural Environment Research Council through the EnvEast Doctoral Training Partnership (grant no. NE/L002582/1) and by the UK Department for Business, Energy and Industrial Strategy (United Kingdom & Canada Arctic Partnership: 2017 Bursaries Programme awarded to MY). Financial support was provided to Brent Else by the National Sciences and Engineering Research Council of Canada. This work is a contribution to ArcticNet, a Network of Centres of Excellence Canada 25 pages, 11 figures, supplement https://doi.org/10.5194/bg-19-1021-2022-supplement.-- Data availability: Data have been submitted to Polar Data Catalogue (https://www.polardata.ca/pdcsearch/), where the CCIN Reference number is 13249 and the DOI is https://doi.org/10.21963/13249 With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S) Peer reviewed

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    https://doi.org/10.5194/bg-202...
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    Biogeosciences
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    Biogeosciences; Rothamsted Repository
    Article . 2022 . Peer-reviewed
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    Authors: Clare Woulds; James B. Bell; Adrian G. Glover; Steven Bouillon; +1 Authors

    ispartof: BIOGEOSCIENCES vol:17 issue:1 pages:1-12 status: published

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    Authors: Guillermic, Maxence; Misra, Sambuddha; Eagle, Robert; Villa, Alexandra; +2 Authors

    Boron isotope systematics of planktonic foraminifera from core-top sediments and culture experiments have been studied to investigate the sensitivity of δ11B of calcite tests to seawater pH. However, our knowledge of the relationship between δ11B and pH remains incomplete for many taxa. Thus, to expand the potential scope of application of this proxy, we report δ11B data for seven different species of planktonic foraminifera from sediment core tops. We utilize a method for the measurement of small samples of foraminifera and calculate the δ11B-calcite sensitivity to pH for Globigerinoides ruber, Trilobus sacculifer (sacc or without sacc), Orbulina universa, Pulleniatina obliquiloculata, Neogloboquadrina dutertrei, Globorotalia menardii, and Globorotalia tumida, including for unstudied core tops and species. These taxa have diverse ecological preferences and are from sites that span a range of oceanographic regimes, including some that are in regions of air–sea equilibrium and others that are out of equilibrium with the atmosphere. The sensitivity of δ11Bcarbonate to δ11Bborate (e.g., Δδ11Bcarbonate∕Δδ11Bborate) in core tops is consistent with previous studies for T. sacculifer and G. ruber and close to unity for N. dutertrei, O. universa, and combined deep-dwelling species. Deep-dwelling species closely follow the core-top calibration for O. universa, which is attributed to respiration-driven microenvironments likely caused by light limitation and/or symbiont–host interactions. Our data support the premise that utilizing boron isotope measurements of multiple species within a sediment core can be utilized to constrain vertical profiles of pH and pCO2 at sites spanning different oceanic regimes, thereby constraining changes in vertical pH gradients and yielding insights into the past behavior of the oceanic carbon pumps.

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    Authors: Clare Woulds; James B. Bell; Adrian G. Glover; Steven Bouillon; +1 Authors

    Sedimented hydrothermal vents are likely to be widespread compared to hard substrate hot vents. They host chemosynthetic microbial communities which fix inorganic C at the seafloor, as well as a wide range of macroinfauna, including vent-obligate and background non-vent taxa. There are no previous direct observations of Carbon cycling at a sedimented hydrothermal vent. We conducted 13C isotope tracing experiments at 3 sedimented sites in the Bransfield Strait, Antarctica, which showed different degrees of hydrothermalism. Two experimental treatments were applied, with 13C added as either algal detritus (photosynthetic C), or as bicarbonate (substrate for benthic C fixation). Algal 13C was taken up by both bacteria and metazoan macrofaunal, but its dominant fate was respiration, as observed at deeper and more food limited sites elsewhere. Rates of 13C uptake and respiration suggested that the diffuse hydrothermal site was not the hotspot of benthic C-cycling that we hypothesised it would be. Fixation of inorganic C into bacterial biomass was observed at all, and was measurable at 2 out of 3 sites. At all sites, newly fixed C was transferred to metazoan macrofauna. Fixation rates were relatively low compared to similar experiments elsewhere, thus C fixed at the seafloor was a minor C source for the benthic ecosystem. However, as the greatest amount of benthic C fixation occurred at the off vent (non-hydrothermal) site (0.077 ± 0.034 mg C m−2 fixed during 60 h), we suggest that benthic fixation of inorganic C is more widespread than previously thought, and warrants further study.

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    https://doi.org/10.5194/bg-201...
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      Biogeosciences (BG)
      Other literature type . 2019
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      https://doi.org/10.5194/bg-201...
      Preprint . 2019
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Wilson, Jamie D.; Barker, Stephen; Edwards, Neil R.; Holden, Philip B.; +1 Authors

    The concentration of CO2 in the atmosphere is sensitive to changes in the depth at which sinking particulate organic matter is remineralized: often described as a change in the exponent “b” of the Martin curve. Sediment trap observations from deep and intermediate depths suggest there is a spatially heterogeneous pattern of b, particularly varying with latitude, but disagree over the exact spatial patterns. Here we use a biogeochemical model of the phosphorus cycle coupled with a steady-state representation of ocean circulation to explore the sensitivity of preformed phosphate and atmospheric CO2 to spatial variability in remineralization depths. A Latin hypercube sampling method is used to simultaneously vary the Martin curve independently within 15 different regions, as a basis for a regression-based analysis used to derive a quantitative measure of sensitivity. Approximately 30 % of the sensitivity of atmospheric CO2 to changes in remineralization depths is driven by changes in the subantarctic region (36 to 60∘ S) similar in magnitude to the Pacific basin despite the much smaller area and lower export production. Overall, the absolute magnitude of sensitivity is controlled by export production, but the relative spatial patterns in sensitivity are predominantly constrained by ocean circulation pathways. The high sensitivity in the subantarctic regions is driven by a combination of high export production and the high connectivity of these regions to regions important for the export of preformed nutrients such as the Southern Ocean and North Atlantic. Overall, regionally varying remineralization depths contribute to variability in CO2 of between around 5 and 15 ppm, relative to a global mean change in remineralization depth. Future changes in the environmental and ecological drivers of remineralization, such as temperature and ocean acidification, are expected to be most significant in the high latitudes where CO2 sensitivity to remineralization is also highest. The importance of ocean circulation pathways to the high sensitivity in subantarctic regions also has significance for past climates given the importance of circulation changes in the Southern Ocean.

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      Other ORP type . 2019
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ödalen, M; Nycander, J; Oliver, KIC; Brodeau, L; +1 Authors

    During the four most recent glacial cycles atmospheric CO2 during glacial maxima has been lowered by about 90-100gm with respect to interglacials. There is widespread consensus that most of this carbon was partitioned in the ocean. It is, however, still debated which processes were dominant in achieving this increased carbon storage. In this paper, we use an Earth system model of intermediate complexity to explore the sensitivity of ocean carbon storage to ocean circulation state. We carry out a set of simulations in which we run the model to pre-industrial equilibrium, but in which we achieve different states of ocean circulation by changing forcing parameters such as wind stress, ocean diffusivity and atmospheric heat diffusivity. As a consequence, the ensemble members also have different ocean carbon reservoirs, global ocean average temperatures, biological pump efficiencies and conditions for air-sea CO2 disequilibrium. We analyse changes in total ocean carbon storage and separate it into contributions by the solubility pump, the biological pump and the CO2 disequilibrium component. We also relate these contributions to differences in the strength of the ocean overturning circulation. Depending on which ocean forcing parameter is tuned, the origin of the change in carbon storage is different. When wind stress or ocean diapycnal diffusivity is changed, the response of the biological pump gives the most important effect on ocean carbon storage, whereas when atmospheric heat diffusivity or ocean isopycnal diffusivity is changed, the solubility pump and the disequilibrium component are also important and sometimes dominant. Despite this complexity, we obtain a negative linear relationship between total ocean carbon and the combined strength of the northern and southern overturning cells. This relationship is robust to different reservoirs dominating the response to different forcing mechanisms. Finally, we conduct a drawdown experiment in which we investigate the capacity for increased carbon storage by artificially maximising the efficiency of the biological pump in our ensemble members. We conclude that different initial states for an ocean model result in different capacities for ocean carbon storage due to differences in the ocean circulation state and the origin of the carbon in the initial ocean carbon reservoir. This could explain why it is difficult to achieve comparable responses of the ocean carbon pumps in model inter-comparison studies in which the initial states vary between models. We show that this effect of the initial state is quantifiable. The drawdown experiment highlights the importance of the strength of the biological pump in the control state for model studies of increased biological efficiency.

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    Biogeosciences (BG)
    Other literature type . 2018
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: J. P. J. Ward; K. R. Hendry; K. R. Hendry; S. Arndt; +11 Authors

    Over recent decades the highest rates of water column warming and sea ice loss across the Arctic Ocean have been observed in the Barents Sea. These physical changes have resulted in rapid ecosystem adjustments, manifesting as a northward migration of temperate phytoplankton species at the expense of silica-based diatoms. These changes will potentially alter the composition of phytodetritus deposited at the seafloor, which acts as a biogeochemical reactor and is pivotal in the recycling of key nutrients, such as silicon (Si). To appreciate the sensitivity of the Barents Sea benthic system to the observed changes in surface primary production, there is a need to better understand this benthic–pelagic coupling. Stable Si isotopic compositions of sediment pore waters and the solid phase from three stations in the Barents Sea reveal a coupling of the iron (Fe) and Si cycles, the contemporaneous dissolution of lithogenic silicate minerals (LSi) alongside biogenic silica (BSi), and the potential for the reprecipitation of dissolved silicic acid (DSi) as authigenic clay minerals (AuSi). However, as reaction rates cannot be quantified from observational data alone, a mechanistic understanding of which factors control these processes is missing. Here, we employ reaction–transport modelling together with observational data to disentangle the reaction pathways controlling the cycling of Si within the seafloor. Processes such as the dissolution of BSi are active on multiple timescales, ranging from weeks to hundreds of years, which we are able to examine through steady state and transient model runs. Steady state simulations show that 60 % to 98 % of the sediment pore water DSi pool may be sourced from the dissolution of LSi, while the isotopic composition is also strongly influenced by the desorption of Si from metal oxides, most likely Fe (oxyhydr)oxides (FeSi), as they reductively dissolve. Further, our model simulations indicate that between 2.9 % and 37 % of the DSi released into sediment pore waters is subsequently removed by a process that has a fractionation factor of approximately −2 ‰, most likely representing reprecipitation as AuSi. These observations are significant as the dissolution of LSi represents a source of new Si to the ocean DSi pool and precipitation of AuSi an additional sink, which could address imbalances in the current regional ocean Si budget. Lastly, transient modelling suggests that at least one-third of the total annual benthic DSi flux could be sourced from the dissolution of more reactive, diatom-derived BSi deposited after the surface water bloom at the marginal ice zone. This benthic–pelagic coupling will be subject to change with the continued northward migration of Atlantic phytoplankton species, the northward retreat of the marginal ice zone and the observed decline in the DSi inventory of the subpolar North Atlantic Ocean over the last 3 decades.

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    Biogeosciences
    Article . 2022
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    Biogeosciences
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    https://doi.org/10.5194/bg-202...
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      https://doi.org/10.5194/bg-202...
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    Authors: Viviana Otero; Steven Pint; Klaas Deneudt; Maarten De Rijcke; +7 Authors

    Marine phytoplankton biomass dynamics are affected by eutrophication, ocean warming, and ocean acidification. These changing abiotic conditions may impact phytoplankton biomass and its spatiotemporal dynamics. In this study, we used a nutrient–phytoplankton–zooplankton (NPZ) model to quantify the relative importance of the bottom-up and top-down determinants of phytoplankton biomass dynamics in the Belgian part of the North Sea (BPNS). Using four years (2014–2017) of monthly observations of nutrients, solar irradiance, sea surface temperature, chlorophyll-a, and zooplankton biomass at ten locations, we disentangled the monthly, seasonal, and yearly variation in phytoplankton biomass dynamics. To quantify how the relative importance of determinants changed along a near–offshore gradient, the analysis was performed for three spatial regions, i.e., the nearshore region (<10 km to the coastline), the midshore region (10–30 km), and the offshore region (>30 km). We found that, from year 2014 to 2017, the phytoplankton biomass dynamics ranged from 1.4 to 23.1 mg Chla m−3. Phytoplankton biomass dynamics follow a general seasonal cycle, as is the case in other temperate regional seas, with a distinct spring bloom (5.3–23.1 mg Chla m−3) and a modest autumn bloom (2.9–5.4 mg Chla m−3). This classic bimodal bloom pattern was not observed between 2003 and 2010 in the BPNS. The seasonal pattern was most expressed in the nearshore region. The relative contribution of factors determining phytoplankton biomass dynamics varied spatially and temporally. Throughout a calendar year, solar irradiance and zooplankton grazing were the most influential determinants in all regions, i.e., they jointly explained 38–65% of the variation in the offshore region, 45–71% in the midshore region, and 56–77% in the nearshore region. In the near- and midshore regions, nutrients were the greatest limit on phytoplankton production in the month following the spring bloom (44–55%). Nutrients were a determinant throughout the year in the offshore region (27–62%). During winter, sea surface temperature was a determinant in all regions (15–17%). By the high-resolution spatiotemporal analysis of the relative contributions of different determinants, this study contributes to a better mechanistic understanding of the spatiotemporal dynamics of phytoplankton biomass in the southern North Sea. This detailed understanding is anticipated to contribute to the definition of targeted management strategies for the BPNS and to support sustainable development in Belgium’s blue economy.

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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Journal of Marine Sc...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      https://doi.org/10.5194/bg-202...
      Preprint . 2022 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      https://bg.copernicus.org/prep...
      Preprint
      License: CC BY
      Data sources: UnpayWall
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/