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  • Nature Research  (3)
  • National Academy of Sciences  (2)
  • 1
    Publication Date: 2015-02-23
    Description: No records exist to evaluate long-term pH dynamics in high-latitude oceans, which have the greatest probability of rapid acidification from anthropogenic CO2 emissions. We reconstructed both seasonal variability and anthropogenic change in seawater pH and temperature by using laser ablation high-resolution 2D images of stable boron isotopes (δ11B) on a long-lived coralline alga that grew continuously through the 20th century. Analyses focused on four multiannual growth segments. We show a long-term decline of 0.08 ± 0.01 pH units between the end of the 19th and 20th century, which is consistent with atmospheric CO2 records. Additionally, a strong seasonal cycle (∼0.22 pH units) is observed and interpreted as episodic annual pH increases caused by the consumption of CO2 during strong algal (kelp) growth in spring and summer. The rate of acidification intensifies from –0.006 ± 0.007 pH units per decade (between 1920s and 1960s) to –0.019 ± 0.009 pH units per decade (between 1960s and 1990s), and the episodic pH increases show a continuous shift to earlier times of the year throughout the centennial record. This is indicative of ecosystem shifts in shallow water algal productivity in this high-latitude habitat resulting from warming and acidification.
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
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  • 2
    Publication Date: 2022-09-20
    Description: No records exist to evaluate long-term pH dynamics in high-latitude oceans, which have the greatest probability of rapid acidification from anthropogenic CO2 emissions. We reconstructed both seasonal variability and anthropogenic change in seawater pH and temperature by using laser ablation high-resolution 2D images of stable boron isotopes (δ11B) on a long-lived coralline alga that grew continuously through the 20th century. Analyses focused on four multiannual growth segments. We show a long-term decline of 0.08 ± 0.01 pH units between the end of the 19th and 20th century, which is consistent with atmospheric CO2 records. Additionally, a strong seasonal cycle (∼0.22 pH units) is observed and interpreted as episodic annual pH increases caused by the consumption of CO2 during strong algal (kelp) growth in spring and summer. The rate of acidification intensifies from –0.006 ± 0.007 pH units per decade (between 1920s and 1960s) to –0.019 ± 0.009 pH units per decade (between 1960s and 1990s), and the episodic pH increases show a continuous shift to earlier times of the year throughout the centennial record. This is indicative of ecosystem shifts in shallow water algal productivity in this high-latitude habitat resulting from warming and acidification.
    Type: Article , PeerReviewed
    Format: text
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  • 3
    Publication Date: 2024-02-07
    Description: Nitrogen fixers, or diazotrophs, play a key role in the nitrogen and carbon cycle of the world oceans. Diazotrophs are capable of utilising atmospheric dinitrogen which is a competitive advantage over generally faster growing ordinary phytoplankton in nitrogen-depleted conditions in the sun-lit surface ocean. In this study we argue that additional competitive advantages must be at play in order to explain the dynamics and distribution of diazotrophs in the global oceans. Backed by growing published evidence we test the effects of preferential grazing (where zooplankton partly avoids diazotrophs) and high-affinity diazotrophic phosphorus uptake in an Earth System Model of intermediate complexity. Our results illustrate that these fundamentally different model assumptions result in a very similar match to observation-based estimates of nitrogen fixation while, at the same time, they imply very different trajectories into our warming future. The latter applies to biomass, fixation rates as well as to the ratio of the two. We conclude that a more comprehensive understanding of the competition between ordinary and diazotrophic phytoplankton will reduce uncertainties in model-based projections of the oceanic N cycle.
    Type: Article , PeerReviewed
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  • 4
    Publication Date: 2024-02-07
    Description: In late summer, massive blooms and surface scums of cyanobacteria emerge regularly in the Baltic Sea. The bacteria can produce toxins and add bioavailable nitrogen fixed from atmospheric nitrogen to an already over-fertilized system. This counteracts management efforts targeted at improving water quality. Despite their critical role, the controls on cyanobacteria blooms are not comprehensively understood yet. This limits the usability of models-based bloom forecasts and projections into our warming future. Here we add to the discussion by combining, for the first time, satellite estimates of cyanobacteria blooms with output of a high-resolution general ocean circulation model and in-situ nutrient observations. We retrace bloom origins and conditions by calculating the trajectories of respective water parcels backwards in time. In an attempt to identify drivers of bloom development, we find that blooms originate and manifest themselves predominantly offshore where conditions are more nutrient-depleted compared to more coastal environments.
    Type: Article , PeerReviewed
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  • 5
    Publication Date: 2024-02-07
    Description: Pelagic biogeochemical models (BGCMs) have matured into generic components of Earth System Models. BGCMs mimic the effects of marine biota on oceanic nutrient, carbon and oxygen cycles. They rely on parameters that are adjusted to match observed conditions. Such parameters are key to determining the models’ responses to changing environmental conditions. However, many of these parameters are difficult to constrain and constitute a major source of uncertainty in BGCM projections. Here we use, for the first time, variance-based sensitivity analyses to map BGCM parameter uncertainties onto their respective local manifestation in model entities (such as oceanic oxygen concentrations) for both contemporary climate and climate projections. The mapping effectively relates local uncertainties of projections to the uncertainty of specific parameters. Further, it identifies contemporary benchmarking regions, where the uncertainties of specific parameters manifest themselves, thereby facilitating an effective parameter refinement and a reduction of the associated uncertainty. Our results demonstrate that the parameters that are linked to uncertainties in projections may differ from those parameters that facilitate model conformity with present-day observations. In summary, we present a practical approach to the general question of where present-day model fidelity may be indicative for reliable projections.
    Type: Article , PeerReviewed
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