Contributors | Affiliation | Role |
---|---|---|
Olson, M Brady | Western Washington University (WWU) | Principal Investigator |
Love, Brooke | Western Washington University (WWU) | Co-Principal Investigator |
Strom, Suzanne | Western Washington University (WWU) | Co-Principal Investigator |
Still, Kelly Ann | Western Washington University (WWU) | Student |
Copley, Nancy | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Related Reference:
Still, Kelly Ann, Microzooplankton grazing, growth and gross growth efficiency are affected by pCO2 induced changes in phytoplankton biology. (Masters Thesis) Western Washington University. http://cedar.wwu.edu/cgi/viewcontent.cgi?article=1490&context=wwuet
The phytoplankton Rhodomonas sp. CCMP 755 was grown semi-continuously in atmosphere controlled chambers at three different CO2 treatment concentrations; Ambient (400ppmv), Moderate (750ppmv), and High (1000ppmv). Cultures were started and allowed to grow four days to reach a density of approximately 50,000 cells per ml. Cultures were then diluted daily with pre-equilibrated media containing f/50 nutrients. Each morning of dilution the cultures were gently mixed prior to a small sample being taken for cell counts. Cells were counted live on a Z2 Coulter Particle Counter. The dilution volume was then calculated to achieve a cell density of approximately 25,000 cells per ml which was the density determined in preliminary experiments to be adequate to maintain pCO2 near target concentrations.
These data are unprocessed cell counts.
BCO-DMO Processing Notes:
- added conventional header with dataset name, PI name, version date
- modified parameter names to conform with BCO-DMO naming conventions
File |
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expt5_cell_count_daily.csv (Comma Separated Values (.csv), 2.30 KB) MD5:578cbc077c724d31b58c4e790192ef53 Primary data file for dataset ID 669572 |
Parameter | Description | Units |
treatment_replicate | sample identifier: individual grazer analyzed | unitless |
target_density_day_1 | Target count for day 1 morning cell count | cells/milliliter |
count_day_2 | Count for day 2 morning cell count | cells/milliliter |
day_2_post_dilution | Count for day 2 post-dilution; for the predicted cell count after dilution | cells/milliliter |
count_day_3 | Count for day 3 morning cell count | cells/milliliter |
day_3_post_dilution | Count for day 3 post-dilution; for the predicted cell count after dilution | cells/milliliter |
count_day_4 | Count for day 4 morning cell count | cells/milliliter |
day_4_post_dilution | Count for day 4 post-dilution; for the predicted cell count after dilution | cells/milliliter |
count_day_5 | Count for day 5 morning cell count | cells/milliliter |
day_5_post_dilution | Count for day 5 post-dilution; for the predicted cell count after dilution | cells/milliliter |
count_day_6 | Count for day 6 morning cell count | cells/milliliter |
day_6_post_dilution | Count for day 6 post-dilution; for the predicted cell count after dilution | cells/milliliter |
count_day_7 | Count for day 7 morning cell count | cells/milliliter |
day_7_post_dilution | Count for day 7 post-dilution; for the predicted cell count after dilution | cells/milliliter |
count_day_8 | Count for day 8 morning cell count | cells/milliliter |
day_8_post_dilution | Count for day 8 post-dilution; for the predicted cell count after dilution | cells/milliliter |
count_day_9 | Count for day 9 morning cell count | cells/milliliter |
day_9_post_dilution | Count for day 9 post-dilution; for the predicted cell count after dilution | cells/milliliter |
count_day_10 | Count for day 10 morning cell count | cells/milliliter |
day_10_post_dilution | Count for day 10 post-dilution; for the predicted cell count after dilution | cells/milliliter |
count_day_11 | Count for day 11 morning cell count | cells/milliliter |
day_11_post_dilution | Count for day 11 post-dilution; for the predicted cell count after dilution | cells/milliliter |
count_day_12 | Count for day 12 morning cell count | cells/milliliter |
day_12_post_dilution | Count for day 12 post-dilution; for the predicted cell count after dilution | cells/milliliter |
count_day_13 | Count for day 13 morning cell count | cells/milliliter |
day_13_post_dilution | Count for day 13 post-dilution; for the predicted cell count after dilution | cells/milliliter |
count_day_14 | Count for day 14 morning cell count | cells/milliliter |
day_14_post_dilution | Count for day 14 post-dilution; for the predicted cell count after dilution | cells/milliliter |
count_day_15 | Count for day 15 morning cell count | cells/milliliter |
day_15_post_dilution | Count for day 15 post-dilution; for the predicted cell count after dilution | cells/milliliter |
count_day_16 | Count for day 16 morning cell count | cells/milliliter |
day_16_post_dilution | Count for day 16 post-dilution; for the predicted cell count after dilution | cells/milliliter |
count_day_17 | Count for day 17 morning cell count | cells/milliliter |
Dataset-specific Instrument Name | Z2 Coulter Particle Counter |
Generic Instrument Name | Coulter Counter |
Dataset-specific Description | Used to count cells |
Generic Instrument Description | An apparatus for counting and sizing particles suspended in electrolytes. It is used for cells, bacteria, prokaryotic cells and virus particles. A typical Coulter counter has one or more microchannels that separate two chambers containing electrolyte solutions.
from https://en.wikipedia.org/wiki/Coulter_counter |
Website | |
Platform | WWU |
Start Date | 2011-03-31 |
End Date | 2016-09-15 |
Description | laboratory experiments |
Description from NSF award abstract:
The calcifying Haptophyte Emiliania huxleyi appears to be acutely sensitive to the rising concentration of ocean pCO2. Documented responses by E. huxleyi to elevated pCO2 include modifications to their calcification rate and cell size, malformation of coccoliths, elevated growth rates, increased organic carbon production, lowering of PIC:POC ratios, and elevated production of the active climate gas DMS. Changes in these parameters are mechanisms known to elicit alterations in grazing behavior by microzooplankton, the oceans dominant grazer functional group. The investigators hypothesize that modifications to the physiology and biochemistry of calcifying and non-calcifying Haptophyte Emiliania huxleyi in response to elevated pCO2 will precipitate alterations in microzooplankton grazing dynamics. To test this hypothesis, they will conduct controlled laboratory experiments where several strains of E. huxleyi are grown at several CO2 concentrations. After careful characterization of the biochemical and physiological responses of the E. huxleyi strains to elevated pCO2, they will provide these strains as food to several ecologically-important microzooplankton and document grazing dynamics. E. huxleyi is an ideal organism for the study of phytoplankton and microzooplankton responses to rising anthropogenic CO2, the effects of which in the marine environment are called ocean acidification; E. huxleyi is biogeochemically important, is well studied, numerous strains are in culture that exhibit variation in the parameters described above, and they are readily fed upon by ecologically important microzooplankton.
The implications of changes in microzooplankton grazing for carbon cycling, specifically CaCO3 export, DMS production, nutrient regeneration in surface waters, and carbon transfer between trophic levels are profound, as this grazing, to a large degree, regulates all these processes. E. huxleyi is a model prey organism because it is one of the most biogeochemically influential global phytoplankton. It forms massive seasonal blooms, contributes significantly to marine inorganic and organic carbon cycles, is a large producer of the climatically active gas DMS, and is a source of organic matter for trophic levels both above and below itself. The planned controlled study will increase our knowledge of the mechanisms that drive patterns of change between trophic levels, thus providing a wider array of tools necessary to understand the complex nature of ocean acidification field studies, where competing variables can confound precise interpretation.
Funding Source | Award |
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NSF Division of Ocean Sciences (NSF OCE) |