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  • 1
    Keywords: Hochschulschrift
    Type of Medium: Online Resource
    Pages: 1 Online-Ressource (77 Seiten = 5 MB) , Illustrationen, Graphen
    Edition: 2021
    Language: German
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  • 2
    Keywords: Forschungsbericht
    Type of Medium: Online Resource
    Pages: 1 Online-Ressource (29 Seiten, 6,77 MB) , Illustrationen, Diagramme, Karten
    Language: German
    Note: Förderkennzeichen BMBF 03F0802A , Verbundnummer 01183326 , Literaturangaben
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  • 3
    Keywords: Forschungsbericht
    Type of Medium: Online Resource
    Pages: 1 Online-Ressource (19 Seiten, 2,35 MB) , Illustrationen, Diagramme, Karten
    Language: German
    Note: Förderkennzeichen BMBF 03F0802A+B , Verbundnummer 01183326
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  • 4
    Keywords: Hochschulschrift
    Description / Table of Contents: Zs.-Fassung ; Abstract
    Type of Medium: Online Resource
    Pages: Online-Ressource (VI, 127 S. = 6.22 MB, Text) , Ill., graph. Darst.
    Edition: [Electronic ed.]
    Language: English
    Note: Kiel, Univ., Diss., 2001
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  • 5
    Online Resource
    Online Resource
    Kiel : [GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel]
    Keywords: Forschungsbericht ; Pleistozän ; Paläoklima ; Modell ; Simulation ; Meer ; Biogeochemie
    Type of Medium: Online Resource
    Pages: 1 Online-Ressource (13 Seiten, 2,37 MB) , Diagramme
    Language: German
    Note: Förderkennzeichen BMBF 01LP1512A+B , Verbundnummer 01162224 , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden
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  • 6
    Publication Date: 2023-05-12
    Description: Here we provide optimised vertical eddy diffusivity estimates for the PeECE III and KOSMOS 2013 mesocosm experiment, obtained from a model-based reanalysis. These diffusivities are derived from the observed temperature and salinity profiles that have been published in Schulz et al., 2008. Furthermore, we make our model code available, providing an adjustable tool to simulate vertical mixing in any other pelagic mesocosm. We also provide the interpolated and regridded temperature and salinity profiles of the PeECE III experiment as well as the density profiles which we calculated from the temperature and salinity profiles using the R package seacarb (Lavigne et al., 2011). These data files are required as input to run simulations of the PeECE III experiment with the 1D mesocosm mixing model. The columns of the environmental files (required input files for the model) from left to right are: Experiment year, month, day, Julian day, photosynthetically active radiation (PAR) [W/m^2], temperature [C], salinity [PSU], CO2 concentration [ppm], wind speed [m/s]. The rows list the respective value of each hour of the experiment. Temperature and salinity in this table are hourly interpolated values of the daily measurements published by the PeECE III team (2005). PAR has been calculated from global radiation data of Bergen provided by Olseth et al., 2005. In the temperature, salinity and density files, the rows indicate the depth (0.5 m resolution, the first row is the surface, the last row is the bottom), whereas the columns indicate the experiment time at an hourly resolution.
    Keywords: File content; File format; File name; File size; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 20 data points
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  • 7
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    In:  Supplement to: Engel, Anja; Cisternas Novoa, Carolina; Wurst, Mascha; Endres, Sonja; Tang, Tiantian; Schartau, Markus; Lee, Cindy (2014): No detectable effect of CO2 on elemental stoichiometry of Emiliania huxleyi in nutrient-limited, acclimated continuous cultures. Marine Ecology Progress Series, 507, 15-30, https://doi.org/10.3354/meps10824
    Publication Date: 2024-03-15
    Description: Effects of CO2 concentration on elemental composition of the coccolithophore Emiliania huxleyi were studied in phosphorus-limited, continuous cultures that were acclimated to experimental conditions for 30 d prior to the first sampling. We determined phytoplankton and bacterial cell numbers, nutrients, particulate components like organic carbon (POC), inorganic carbon (PIC), nitrogen (PN), organic phosphorus (POP), transparent exopolymer particles (TEP), as well as dissolved organic carbon (DOC) and nitrogen (DON), in addition to carbonate system parameters at CO2 levels of 180, 380 and 750 µatm. No significant difference between treatments was observed for any of the measured variables during repeated sampling over a 14 d period. We considered several factors that might lead to these results, i.e. light, nutrients, carbon overconsumption and transient versus steady-state growth. We suggest that the absence of a clear CO2 effect during this study does not necessarily imply the absence of an effect in nature. Instead, the sensitivity of the cell towards environmental stressors such as CO2 may vary depending on whether growth conditions are transient or sufficiently stable to allow for optimal allocation of energy and resources. We tested this idea on previously published data sets where PIC and POC divided by the corresponding cell abundance of E. huxleyi at various pCO2 levels and growth rates were available.
    Keywords: Abundance per volume; Alkalinity, total; Alkalinity, total, standard deviation; Aragonite saturation state; Bicarbonate ion; BIOACID; Biological Impacts of Ocean Acidification; Biomass/Abundance/Elemental composition; Bottles or small containers/Aquaria (〈20 L); Calcite saturation state; Calcite saturation state, standard deviation; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, inorganic, particulate, per cell; Carbon, organic, dissolved, per cell; Carbon, organic, dissolved/Nitrogen, organic, dissolved ratio; Carbon, organic, particulate, per cell; Carbon, organic, particulate, standard deviation; Carbon, organic, particulate/Nitrogen, particulate ratio; Carbon, organic, particulate/Nitrogen, particulate ratio, standard deviation; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Carbon dioxide, partial pressure; Chlorophyll a, standard deviation; Chlorophyll a per cell; Chromista; Day of experiment; Emiliania huxleyi; Emiliania huxleyi, standard deviation; Figure; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Haptophyta; Laboratory experiment; Laboratory strains; Nitrogen, organic, dissolved, per cell; Nitrogen, particulate, per cell; Nitrogen, total, particulate/Phosphorus, organic, particulate, ratio; Nitrogen, total, particulate/Phosphorus, organic, particulate, ratio, standard deviation; Not applicable; OA-ICC; Ocean Acidification International Coordination Centre; Partial pressure of carbon dioxide, standard deviation; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Particulate inorganic carbon/particulate organic carbon ratio; Particulate inorganic carbon/particulate organic carbon ratio, standard deviation; Pelagos; pH; pH, standard deviation; Phosphorus, organic, particulate, per cell; Phytoplankton; Salinity; Single species; Species; Standard deviation; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 3723 data points
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  • 8
    Publication Date: 2022-06-17
    Description: We applied a 1-D plankton ecosystem-biogeochemical model to assess the impacts of ocean alkalinity enhancement (OAE) on seasonal changes in biogeochemistry and plankton dynamics. Depending on deployment scenarios, OAE should theoretically have variable effects on pH and seawater pCO2, which might in turn affect (a) plankton growth conditions and (b) the efficiency of carbon dioxide removal (CDR) via OAE. Thus, a major focus of our work is how different magnitudes and temporal frequencies of OAE might affect seasonal response patterns of net primary productivity (NPP), ecosystem functioning and biogeochemical cycling. With our study we aimed at identifying a parameterization of how magnitude and frequency of OAE affect net growth rates, so that these effects could be employed for Earth System Modell applications. So far we learned that a meaningful response parameterization has to resolve positive and negative anomalies that covary with temporal shifts. As to the intricacy of the response patterns, the derivation of such parameterization is work in progress. However, our study readily provides valuable insights to how OAE can alter plankton dynamics and biogeochemistry. Our modelling study first focuses at a local site where time series data are available (European Station for Time series in the Ocean Canary Islands ESTOC), including measurements of pH, concentrations of total alkalinity, dissolved inorganic carbon (DIC), chlorophyll-a and dissolved inorganic nitrogen (DIN). These observational data were made available by Andres Cianca (personal communication, PLOCAN, Spain), Melchor Gonzalez and Magdalena Santana Casiano (personal communication, Universidad de Las Palmas de Gran Canaria). The choice of this location was underpinned by the fact that the first OAE mesocosm experiment was conducted on the Canary Island Gran Canaria, which will facilitate synthesizing our modelling approach with experimental findings. For our simulations at the ESTOC site in the Subtropical North Atlantic we found distinct, non-linear responses of NPP to different temporal modes of alkalinity deployment. In particular, phytoplankton bloom patterns displayed pronounced temporal phase shifts and changes in their amplitude. Notably, our simulations suggest that OAE can have a slightly stimulating effect on NPP, which is however variable, depending on the magnitude of OAE and the temporal mode of alkalinity addition. Furthermore, we find that increasing alkalinity perturbations can lead to a shift in phytoplankton community composition (towards coccolithophores), which even persists after OAE has stopped. In terms of CDR, we found that a decrease in efficiency with increasing magnitude of alkalinity addition, as well as substantial differences related to the timing of addition. Altogether, our results suggest that annual OAE during the right season (i.e. physical and biological conditions), could be a reasonable compromise in terms of logistical feasibility, efficiency of CDR and side-effects on marine biota. With respect to transferability to global models, the complex, non-linear responses of biological processes to OAE identified in our simulations do not allow for simple parameterizations that can easily adapted. Dedicated future work is required to transfer the observed responses at small spatiotemporal scales to the coarser resolution of global models.
    Type: Report , NonPeerReviewed , info:eu-repo/semantics/book
    Format: text
    Format: text
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  • 9
    Publication Date: 2020-02-06
    Description: Estuary-type circulation is a residual circulation in coastal systems with horizontal density gradients. It drives the accumulation of suspended particulate matter in coastal embayments where density gradients are sustained by some freshwater inflow from rivers. Ebenhöh et al. (Ecol Model 174(3):241–252, 2004) found that shallow water depth can explain nutrient gradients becoming established towards the coast even in the absence of river inflow. The present study follows their concept and investigates the characteristic transport of organic matter towards the coast based on idealised scenarios whereby an estuary-type circulation is maintained by surface freshwater fluxes and pronounced shoaling towards the coast. A coupled hydrodynamical and biogeochemical model is used to simulate the dynamics of nutrient gradients and to derive budgets of organic matter flux for a coastal transect. Horizontal nutrient gradients are considered only in terms of tidal asymmetries of suspended matter transport. The results show that the accumulation of organic matter near the coast is not only highly sensitive to variations in the sinking velocity of suspended matter but is also noticeably enhanced by an increase in precipitation. This scenario is comparable with North Sea conditions. By contrast, horizontal nutrient gradients would be reversed in the case of evaporation-dominated inverse estuaries (cf. reverse gradients of nutrient and organic matter concentrations). Credible coastal nutrient budget calculations are required for resolving trends in eutrophication. For tidal systems, the present results suggest that these calculations require an explicit consideration of freshwater flux and asymmetries in tidal mixing. In the present case, the nutrient budget for the vertically mixed zone also indicates carbon pumping from the shelf sea towards the coast from as far offshore as 25 km.
    Type: Article , PeerReviewed
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  • 10
    Publication Date: 2020-07-30
    Description: In this paper, we review the state of the art and major challenges in current efforts to incorporate biogeochemical functional groups into models that can be applied on basin-wide and global scales, with an emphasis on models that might ultimately be used to predict how biogeochemical cycles in the ocean will respond to global warming. We define the term “biogeochemical functional group” to refer to groups of organisms that mediate specific chemical reactions in the ocean. Thus, according to this definition, “functional groups” have no phylogenetic meaning—these are composed of many different species with common biogeochemical functions. Substantial progress has been made in the last decade toward quantifying the rates of these various functions and understanding the factors that control them. For some of these groups, we have developed fairly sophisticated models that incorporate this understanding, e.g. for diazotrophs (e.g. Trichodesmium), silica producers (diatoms) and calcifiers (e.g. coccolithophorids and specifically Emiliania huxleyi). However, current representations of nitrogen fixation and calcification are incomplete, i.e., based primarily upon models of Trichodesmium and E. huxleyi, respectively, and many important functional groups have not yet been considered in open-ocean biogeochemical models. Progress has been made over the last decade in efforts to simulate dimethylsulfide (DMS) production and cycling (i.e., by dinoflagellates and prymnesiophytes) and denitrification, but these efforts are still in their infancy, and many significant problems remain. One obvious gap is that virtually all functional group modeling efforts have focused on autotrophic microbes, while higher trophic levels have been completely ignored. It appears that in some cases (e.g., calcification), incorporating higher trophic levels may be essential not only for representing a particular biogeochemical reaction, but also for modeling export. Another serious problem is our tendency to model the organisms for which we have the most validation data (e.g., E. huxleyi and Trichodesmium) even when they may represent only a fraction of the biogeochemical functional group we are trying to represent. When we step back and look at the paleo-oceanographic record, it suggests that oxygen concentrations have played a central role in the evolution and emergence of many of the key functional groups that influence biogeochemical cycles in the present-day ocean. However, more subtle effects are likely to be important over the next century like changes in silicate supply or turbulence that can influence the relative success of diatoms versus dinoflagellates, coccolithophorids and diazotrophs. In general, inferences drawn from the paleo-oceanographic record and theoretical work suggest that global warming will tend to favor the latter because it will give rise to increased stratification. However, decreases in pH and Fe supply could adversely impact coccolithophorids and diazotrophs in the future. It may be necessary to include explicit dynamic representations of nitrogen fixation, denitrification, silicification and calcification in our models if our goal is predicting the oceanic carbon cycle in the future, because these processes appear to play a very significant role in the carbon cycle of the present-day ocean and they are sensitive to climate change. Observations and models suggest that it may also be necessary to include the DMS cycle to predict future climate, though the effects are still highly uncertain. We have learned a tremendous amount about the distributions and biogeochemical impact of bacteria in the ocean in recent years, yet this improved understanding has not yet been incorporated into many of our models. All of these considerations lead us toward the development of increasingly complex models. However, recent quantitative model intercomparison studies suggest that continuing to add complexity and more functional groups to our ecosystem models may lead to decreases in predictive ability if the models are not properly constrained with available data. We also caution that capturing the present-day variability tells us little about how well a particular model can predict the future. If our goal is to develop models that can be used to predict how the oceans will respond to global warming, then we need to make more rigorous assessments of predictive skill using the available data.
    Type: Article , PeerReviewed
    Format: text
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