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  • Alkalinity, total; Alkalinity, total, standard deviation; Aragonite saturation state; Bicarbonate ion; Biomass/Abundance/Elemental composition; Bottles or small containers/Aquaria (〈20 L); Calcite saturation state; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, inorganic, dissolved, standard deviation; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Carbon dioxide, partial pressure, standard deviation; Chromista; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Laboratory experiment; Laboratory strains; Macro-nutrients; Nitrogen/Carbon ratio; Nitrogen/Carbon ratio, standard deviation; Nitrogen/Phosphorus ratio; Nitrogen cellular quota; Not applicable; OA-ICC; Ocean Acidification International Coordination Centre; Ochrophyta; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Pelagos; pH; Phaeodactylum tricornutum; Phosphorus/Carbon ratio; Phosphorus/Carbon ratio, standard deviation; Phytoplankton; Polyunsaturated fatty acids; Polyunsaturated fatty acids, standard deviation; Ratio; Registration number of species; Rhodomonas sp.; Salinity; Salinity, standard deviation; Single species; Species; Temperature, water; Type; Uniform resource locator/link to reference  (1)
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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Oecologia 77 (1988), S. 464-467 
    ISSN: 1432-1939
    Keywords: Antarctic phytoplankton ; Competition ; Resource ratios ; Nutrients
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Summary An attempt was made, to test for the impact of resource competition on Antarctic marine phytoplankton. According to theory, species composition near competitive equilibrium should be determined by the ratios of limiting resources. Enrichment bioassays identified silicon and nitrogen as limiting nutrients for some of the most important phytoplankton species during early austral summer in the region near the Antarctic Peninsula. Together with the generally acknowledged limiting resource light, this gave three meaningful ratios of essential resources (Si:N, Si:light, N:light) and one ratio of substitutable resources (NO3:NH4). Phytoplankton species assemblages were found to be well separated by the ratios of the essential resources and by mixing depth. Nine out of 12 individual species were found to be separated along at least one of the gradients of resource ratios. Where comparison with competition experiments was available, predicted and realized distributions of species were compatible.
    Type of Medium: Electronic Resource
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  • 2
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    PANGAEA
    In:  Supplement to: Bi, Rong; Ismar, Stefanie M; Sommer, Ulrich; Zhao, Meixun (2017): Environmental dependence of the correlations between stoichiometric and fatty acid-based indicators of phytoplankton nutritional quality. Limnology and Oceanography, 62(1), 334-347, https://doi.org/10.1002/lno.10429
    Publication Date: 2024-03-15
    Description: Marine phytoplankton is simultaneously affected by multiple environmental drivers. To-date integrative assessments of multiple combined effects are rare on the relationship between elemental stoichiometry and biochemicals in marine phytoplankton. We investigated responses of stoichiometric (N:C and P:C ratios) and fatty acid-based (polyunsaturated fatty acid, PUFA) indicators of nutritional quality to three N:P supply ratios (10:1, 24:1, and 63:1 mol/mol), three temperatures (12, 18, and 24°C) and two pCO2 levels (560 and 2400 µatm) in the marine phytoplankters Rhodomonas sp. and Phaeodactylum tricornutum. Overall, warming and nutrient deficiency showed dramatic effects, but increased pCO2 had modest effects on the two indicators of nutritional quality. Specifically, warming showed strong positive effects on N:C and P:C ratios in Rhodomonas sp. but negative effects on PUFAs in both species. The low N- and low P-media led to low contents of both nutrients but high contents of PUFAs in the biomass of Rhodomonas sp., while the response of P. tricornutum was more complex: N:C ratios were lowest at the intermediate N:P supply but P:C ratios responded negatively to P deficiency and positively to N deficiency. Large variations in the two indicators of nutritional quality can be attributed to species-specific physiological optima and interactions between the three manipulated variables. Our results suggest that stoichiometric and FA-based indicators of nutritional quality may change differentially in response to warming and nutrient deficiency in marine phytoplankton, highlighting the relevance of simultaneous considerations of the two indicators of nutritional quality, when assessing food web dynamics under future ocean scenarios.
    Keywords: Alkalinity, total; Alkalinity, total, standard deviation; Aragonite saturation state; Bicarbonate ion; Biomass/Abundance/Elemental composition; Bottles or small containers/Aquaria (〈20 L); Calcite saturation state; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, inorganic, dissolved, standard deviation; Carbonate ion; Carbonate system computation flag; Carbon dioxide; Carbon dioxide, partial pressure, standard deviation; Chromista; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Laboratory experiment; Laboratory strains; Macro-nutrients; Nitrogen/Carbon ratio; Nitrogen/Carbon ratio, standard deviation; Nitrogen/Phosphorus ratio; Nitrogen cellular quota; Not applicable; OA-ICC; Ocean Acidification International Coordination Centre; Ochrophyta; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Pelagos; pH; Phaeodactylum tricornutum; Phosphorus/Carbon ratio; Phosphorus/Carbon ratio, standard deviation; Phytoplankton; Polyunsaturated fatty acids; Polyunsaturated fatty acids, standard deviation; Ratio; Registration number of species; Rhodomonas sp.; Salinity; Salinity, standard deviation; Single species; Species; Temperature, water; Type; Uniform resource locator/link to reference
    Type: Dataset
    Format: text/tab-separated-values, 4633 data points
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