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  • 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  (1)
  • Biogeochemical data assimilation  (1)
  • Ecosystem model comparison  (1)
Document type
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  (1)
  • Biogeochemical data assimilation  (1)
  • Ecosystem model comparison  (1)
  • Forschungsbericht  (3)
  • Hochschulschrift  (2)
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Publisher
Years
  • 1
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    Unknown
    No detectable effect of CO2 on elemental stoichiometry of Emiliania huxleyi in nutrient-limited, acclimated continuous cultures (2014)
    PANGAEA
    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
    Details
    Publication Date: 2024-04-27
    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
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 2
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    Unknown
    Assessment of skill and portability in regional marine biogeochemical models : role of multiple planktonic groups (2010)
    American Geophysical Union
    Details
    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): C08001, doi:10.1029/2006JC003852.
    Description: Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical one-dimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways.
    Description: This research was supported by the U.S. National Science Foundation through the JGOFS Synthesis and Modeling Project (OCE-0097285) and the National Aeronautics and Space Agency (NAG5-11259 and NNG05GO04G), as well as numerous other grants to the various investigators who participated.
    Keywords: Ecosystem model comparison ; Biogeochemical data assimilation ; Phytoplankton functional groups
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
    Format: text/plain
    Format: image/tiff
    Location Call Number Limitation Availability
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    PAPER (OA)
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