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  • 1
    Keywords: Hochschulschrift ; Eisenverbindungen ; Spurenmetall ; Biogeochemie
    Type of Medium: Online Resource
    Pages: 1 Online-Ressource (xi, 103 Seiten) , Illustrationen, Diagramme
    DDC: 579.8
    Language: English
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  • 2
    Publication Date: 2022-06-17
    Description: Biological nitrogen fixation is an important oceanic nitrogen source, potentially stabilizing marine fertility in an increasingly stratified and nutrient‐depleted ocean. Iron limitation of low latitude primary producers has been previously demonstrated to affect simulated regional ecosystem responses to climate warming or nitrogen cycle perturbation. Here we use three biogeochemical models that vary in their representation of the iron cycle to estimate change in the marine nitrogen cycle under a high CO2 emissions future scenario (RCP8.5). The first model neglects explicit iron effects on biology (NoFe), the second utilizes prescribed, seasonally cyclic iron concentrations and associated limitation factors (FeMask), and the third contains a fully dynamic iron cycle (FeDyn). Models were calibrated using observed fields to produce near‐equivalent nutrient and oxygen fits, with productivity ranging from 49 to 75 Pg C yr−1. Global marine nitrogen fixation increases by 71.1% with respect to the preindustrial value by the year 2100 in NoFe, while it remains stable (0.7% decrease in FeMask and 0.3% increase in FeDyn) in explicit iron models. The mitigation of global nitrogen fixation trend in the models that include a representation of iron originates in the Eastern boundary upwelling zones, where the bottom‐up control of iron limitation reduces export production with warming, which shrinks the oxygen deficient volume, and reduces denitrification. Warming‐induced trends in the oxygen deficient volume in the upwelling zones have a cascading effect on the global nitrogen cycle, just as they have previously been shown to affect tropical net primary production.
    Description: Plain Language Summary: Phytoplankton need nutrients to grow. Two of those nutrients are nitrogen and iron. Climate change projections suggest that in the future there could be less nitrogen supplied to the surface ocean, which might reduce phytoplankton growth. Less phytoplankton growth could impact a wide range of ocean services, like fishing and fossil carbon draw‐down. However, some phytoplankton have the ability to add “new” nitrogen to the surface ocean directly from the atmosphere. In this study, we explore how this biological fixation of new nitrogen might change into the future using three models. These models differ in how iron is represented, but all do equally well in representing the observed nutrient and oxygen distribution. Biological nitrogen fixation slightly decreases with climate change in the very complex iron model and the moderately complex iron model, but it increases strongly (by more than 70% by the year 2100) in the model that does not include iron effects on biology. Our study addresses the importance of iron models and how they can change our view of how the ocean responds to climate change.
    Description: Key Points: Models performing similarly with respect to global NO3, PO4, and O2 distributions yield diverse responses in marine N2 fixation to warming. Marine N2 fixation trends are sensitive to whether iron limits primary production in upwelling regions, for example, the Eastern Tropical Pacific.
    Description: Helmholtz Research School for Ocean System Science and Technology
    Description: New Zealand Ministry of Business, Innovation and Employment
    Description: https://data.geomar.de/downloads/20.500.12085/673e7de0-20ab-4dd3-afe9-c4bfb00b1faf/
    Keywords: ddc:551.9
    Language: English
    Type: doc-type:article
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  • 3
    Publication Date: 2022-01-31
    Description: Iron is represented in biogeochemical ocean models by a variety of structurally different approaches employing generally poorly constrained empirical parameterizations. Increasing the structural complexity of iron modules also increases computational costs and introduces additional uncertainties, with as yet unclear benefits. In order to demonstrate the benefits of explicitly representing iron, we calibrate a hierarchy of iron modules and evaluate the remaining model-data misfit. The first module includes a complex iron cycle with major processes resolved explicitly, the second module applies iron limitation in primary production using prescribed monthly iron concentration fields, and the third module does not explicitly include iron effects at all. All three modules are embedded into the same circulation model. Models are calibrated against global data sets of NO3, PO4 and O2 applying a state-of-the-art multi-variable constraint parameter optimization. The model with fully resolved iron cycle is marginally (up to 4.8%) better at representing global distributions of NO3, PO4 and O2 compared to models with implicit or absent parameterizations of iron. We also found a slow down of global surface nutrient cycling by about 30% and a shift of productivity from the tropics to temperate regions for the explicit iron module. The explicit iron model also reduces the otherwise overestimated volume of suboxic waters, yielding results closer to observations.
    Type: Article , PeerReviewed
    Format: text
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  • 4
    Publication Date: 2021-12-16
    Description: We describe and test a new model of biological marine silicate cycling, implemented in the Kiel Marine Biogeochemical Model version 3 (KMBM3), embedded in the University of Victoria Earth System Climate Model (UVic ESCM) version 2.9. This new model adds diatoms, which are a key component of the biological carbon pump, to an existing ecosystem model. This new model combines previously published parameterizations of a diatom functional type, opal production and export with a novel, temperature-dependent dissolution scheme. Modelled steady-state biogeochemical rates, carbon and nutrient distributions are similar to those found in previous model versions. The new model performs well against independent ocean biogeochemical indicators and captures the large-scale features of the marine silica cycle to a degree comparable to similar Earth system models. Furthermore, it is computationally efficient, allowing both fully coupled, long-timescale transient simulations and “offline” transport matrix spinups. We assess the fully coupled model against modern ocean observations, the historical record starting from 1960 and a business-as-usual atmospheric CO2 forcing to the year 2300. The model simulates a global decline in net primary production (NPP) of 1.4 % having occurred since the 1960s, with the strongest declines in the tropics, northern midlatitudes and Southern Ocean. The simulated global decline in NPP reverses after the year 2100 (forced by the extended RCP8.5 CO2 concentration scenario), and NPP returns to 98 % of the pre-industrial rate by 2300. This recovery is dominated by increasing primary production in the Southern Ocean, mostly by calcifying phytoplankton. Large increases in calcifying phytoplankton in the Southern Ocean offset a decline in the low latitudes, producing a global net calcite export in 2300 that varies only slightly from pre-industrial rates. Diatom distribution moves southward in our simulations, following the receding Antarctic ice front, but diatoms are outcompeted by calcifiers across most of their pre-industrial Southern Ocean habitat. Global opal export production thus drops to 75 % of its pre-industrial value by 2300. Model nutrients such as phosphate, silicate and nitrate build up along the Southern Ocean particle export pathway, but dissolved iron (for which ocean sources are held constant) increases in the upper ocean. This different behaviour of iron is attributed to a reduction of low-latitude NPP (and consequently, a reduction in both uptake and export and particle, including calcite scavenging), an increase in seawater temperatures (raising the solubility of particulate iron) and stratification that “traps” the iron near the surface. These results are meant to serve as a baseline for sensitivity assessments to be undertaken with this model in the future.
    Type: Article , PeerReviewed
    Format: text
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  • 5
    Publication Date: 2024-01-19
    Description: The marine biological carbon pump (BCP) stores carbon in the ocean interior, isolating it from exchange with the atmosphere and thereby coregulating atmospheric carbon dioxide (CO 2 ). As the BCP commonly is equated with the flux of organic material to the ocean interior, termed “export flux,” a change in export flux is perceived to directly impact atmospheric CO 2 , and thus climate. Here, we recap how this perception contrasts with current understanding of the BCP, emphasizing the lack of a direct relationship between global export flux and atmospheric CO 2 . We argue for the use of the storage of carbon of biological origin in the ocean interior as a diagnostic that directly relates to atmospheric CO 2 , as a way forward to quantify the changes in the BCP in a changing climate. The diagnostic is conveniently applicable to both climate model data and increasingly available observational data. It can explain a seemingly paradoxical response under anthropogenic climate change: Despite a decrease in export flux, the BCP intensifies due to a longer reemergence time of biogenically stored carbon back to the ocean surface and thereby provides a negative feedback to increasing atmospheric CO 2 . This feedback is notably small compared with anthropogenic CO 2 emissions and other carbon‐climate feedbacks. In this Opinion paper, we advocate for a comprehensive view of the BCP's impact on atmospheric CO 2 , providing a prerequisite for assessing the effectiveness of marine CO 2 removal approaches that target marine biology.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
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  • 6
    Publication Date: 2024-02-07
    Description: We describe and test a new model of biological marine silicate cycling, implemented in the Kiel Marine Biogeochemical Model version 3 (KMBM3), embedded in the University of Victoria Earth System Climate Model (UVic ESCM) version 2.9. This new model adds diatoms, which are a key component of the biological carbon pump, to an existing ecosystem model. This new model combines previously published parameterizations of a diatom functional type, opal production and export with a novel, temperature-dependent dissolution scheme. Modelled steady-state biogeochemical rates, carbon and nutrient distributions are similar to those found in previous model versions. The new model performs well against independent ocean biogeochemical indicators and captures the large-scale features of the marine silica cycle to a degree comparable to similar Earth system models. Furthermore, it is computationally efficient, allowing both fully coupled, long-timescale transient simulations and “offline” transport matrix spinups. We assess the fully coupled model against modern ocean observations, the historical record starting from 1960 and a business-as-usual atmospheric CO2 forcing to the year 2300. The model simulates a global decline in net primary production (NPP) of 1.4 % having occurred since the 1960s, with the strongest declines in the tropics, northern midlatitudes and Southern Ocean. The simulated global decline in NPP reverses after the year 2100 (forced by the extended RCP8.5 CO2 concentration scenario), and NPP returns to 98 % of the pre-industrial rate by 2300. This recovery is dominated by increasing primary production in the Southern Ocean, mostly by calcifying phytoplankton. Large increases in calcifying phytoplankton in the Southern Ocean offset a decline in the low latitudes, producing a global net calcite export in 2300 that varies only slightly from pre-industrial rates. Diatom distribution moves southward in our simulations, following the receding Antarctic ice front, but diatoms are outcompeted by calcifiers across most of their pre-industrial Southern Ocean habitat. Global opal export production thus drops to 75 % of its pre-industrial value by 2300. Model nutrients such as phosphate, silicate and nitrate build up along the Southern Ocean particle export pathway, but dissolved iron (for which ocean sources are held constant) increases in the upper ocean. This different behaviour of iron is attributed to a reduction of low-latitude NPP (and consequently, a reduction in both uptake and export and particle, including calcite scavenging), an increase in seawater temperatures (raising the solubility of particulate iron) and stratification that “traps” the iron near the surface. These results are meant to serve as a baseline for sensitivity assessments to be undertaken with this model in the future.
    Type: Article , PeerReviewed
    Format: text
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  • 7
    Publication Date: 2024-02-07
    Description: Iron is a key micronutrient controlling phytoplankton growth in vast regions of the global ocean. Despite its importance, uncertainties remain high regarding external iron source fluxes and internal cycling on a global scale. In this study, we used a global dissolved iron dataset, including GEOTRACES measurements, to constrain source and scavenging fluxes in the marine iron component of a global ocean biogeochemical model. Our model simulations tested three key uncertainties: source inputs of atmospheric soluble iron deposition (varying from 1.4–3.4 Gmol/yr), reductive sedimentary iron release (14–117 Gmol/yr), and compared a variable ligand parameterization to a constant distribution. In each simulation, scavenging rates were tuned to reproduce the observed global mean iron inventory for consistency. The variable ligand parameterization improved the global model-data misfit the most, suggesting that heterotrophic bacteria are an important source of ligands to the ocean. Model simulations containing high source fluxes of atmospheric soluble iron deposition (3.4 Gmol/yr) and reductive sedimentary iron release (114 Gmol/yr) further improved the model most notably in the surface ocean. High scavenging rates were then required to maintain the iron inventory resulting in relatively short surface and global ocean residence times of 0.83 and 7.5 years, respectively. The model simulates a tight spatial coupling between source inputs and scavenging rates, which may be too strong due to underrepresented ligands near source inputs, contributing to large uncertainties when constraining individual fluxes with dissolved iron concentrations. Model biases remain high and are discussed to help improve global marine iron cycle models.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: other
    Format: text
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  • 8
    Publication Date: 2024-02-07
    Description: The trace metal iron is considered to be the nutrient that limits marine primary production in one third of the global surface ocean (Martin, 1990; Boyd et al., 2007; Moore et al., 2013). It is also the nutrient that maintains future ocean fertility due to its irreplaceable role in the process of nitrogen fixation, which adds “new” nitrogen (another nutrient for phytoplankton) to the surface ocean (Raven, 1988; Kustka et al., 2003b; Zehr and Capone, 2020). Due to iron’s importance, it is not surprising that the demand for incorporating iron into global biogeochemical models is high. However, including iron in an earth system model has been shown to have no clear benefits with respect to model misfit against observational data (Nickelsen et al., 2015) . How smart is it then to introduce iron models into global biogeochemical models, when the benefits are not clearly identifiable? Especially, when the iron models perform poorly at reproducing observed iron patterns in the ocean (Tagliabue et al., 2016). The poor performance of iron models, coupled with their failure to improve biogeochemical tracer representation of the ocean, inspired this additional effort to identify the advantages of including iron in a global biogeochemical model, both for the preindustrial state and under conditions of a changing climate. The working hypothesis was that the relatively poor performance of iron models might come from inadequate model calibration. A first sensitivity study on biogeochemical model parameter values was conducted in order to identify key parameters for model calibration. It was found that while some of the parameters influence simulated nitrogen, phosphorus, and oxygen concentrations, few parameters influence simulated iron concentrations. This suggests that our modelling skill of the iron cycle is still limited and/or that the observational data base is insufficient for comprehensive model calibration so far. Thus it was decided not to include iron data in further model calibration. A model calibration framework (Kriest et al., 2017) was next applied to a hierarchy of global models with different implementations of iron; one without iron, one with prescribed iron concentrations, and another one with a dynamic iron cycle. Using calibration against global data sets of nitrogen, phosphorus, and oxygen, the misfit of each model was pushed to its minimum. It was found that under an assumed preindustrial steady state, the calibrated model with a full dynamic iron cycle has the lowest model misfit against observations (thus confirming the working hypothesis). It was also found that the calibrated model with a fully dynamic iron cycle has 50% less net primary production (which is closer to empirical estimations) compared to the calibrated model without iron. Finally, transient simulations for all calibrated models were integrated from their pre- industrial state until the end of the 21st century using an atmospheric CO2 concentration pathway consistent with a ’business-as-usual’ CO2 emission scenario. It was found that nitrogen fixation trends diverge among models. This divergence is caused by whether iron limits the productivity of the upwelling regions, e.g. in the eastern tropical Pacific. The export production in the eastern tropical Pacific (and other tropical upwelling regions) reacts differently to warming, depending on whether iron is a limiting nutrient. These different responses trigger a divergent chain of downstream responses that affect nitrogen fixation across the tropical oligotrophic regions in the model. Through the comparison between calibrated models, this thesis quantifies the advantages of including iron in a global biogeochemistry model and reveals how important iron is for future nitrogen fixation trends. It furthermore illustrates the interconnection between tropical upwelling and oligotrophic regions.
    Type: Thesis , NonPeerReviewed
    Format: text
    Format: text
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  • 9
    Publication Date: 2024-02-07
    Description: Key points: Models performing similarly with respect to global NO3, PO4, and O2 distributions yield diverse responses in marine N2 fixation to warming • Marine N2 fixation trends are sensitive to whether iron limits primary production in upwelling regions, for example, the Eastern Tropical Pacific Biological nitrogen fixation is an important oceanic nitrogen source, potentially stabilizing marine fertility in an increasingly stratified and nutrient-depleted ocean. Iron limitation of low latitude primary producers has been previously demonstrated to affect simulated regional ecosystem responses to climate warming or nitrogen cycle perturbation. Here we use three biogeochemical models that vary in their representation of the iron cycle to estimate change in the marine nitrogen cycle under a high CO2 emissions future scenario (RCP8.5). The first model neglects explicit iron effects on biology (NoFe), the second utilizes prescribed, seasonally-cyclic iron concentrations and associated limitation factors (FeMask), and the third contains a fully dynamic iron cycle (FeDyn). Models were calibrated using observed fields to produce near-equivalent nutrient and oxygen fits, with productivity ranging from 49 to 75 Pg C yr−1. Global marine nitrogen fixation increases by 71.1% with respect to the preindustrial value by the year 2100 in NoFe, while it remains stable (0.7% decrease in FeMask and 0.3% increase in FeDyn) in explicit iron models. The mitigation of global nitrogen fixation trend in the models that include a representation of iron originates in the Eastern boundary upwelling zones, where the bottom-up control of iron limitation reduces export production with warming, which shrinks the oxygen deficient volume, and reduces denitrification. Warming-induced trends in the oxygen deficient volume in the upwelling zones have a cascading effect on the global nitrogen cycle, just as they have previously been shown to affect tropical net primary production.
    Type: Article , PeerReviewed
    Format: text
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