Contributors | Affiliation | Role |
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Passow, Uta | University of California-Santa Barbara (UCSB-MSI) | Principal Investigator |
Laws, Edward | Louisiana State University (LSU-CC&E [formerly SC&E]) | Co-Principal Investigator |
D'Souza, Nigel | University of California-Santa Barbara (UCSB-MSI) | Scientist, Contact |
Copley, Nancy | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
The experiments in Series 3A were designed to test the combined effects of three CO2 concentrations, four temperatures, and three light intensities on growth and photophysiology of the diatom T. pseudonana CCMP1014 in a multifactorial design. This dataset reports the macronutrient (phosphate, silicate, and nitrate plus nitrite) concentrations measured during the experiments.
Three CO2 concentrations were tested: 410 ppm, 750 ppm, and 1000 ppm respectively. For each CO2 concentration, four temperatures were tested: 15 degrees-C, 20 degrees-C, 25 degrees-C, and 30 degrees-C. Within each temperature, three light levels were tested: a sub-optimum light (SOL) intensity of 60 umol photons · m-2 · s-1, an optimum light (OL) intensity of 400 umol photons · m-2 · s-1 and an extreme light (EL) intensity of 800 umol photons · m-2 · s-1. All lights were set at a 12 h day: 12 h dark cycle. For logistical reasons, experiments were partially conducted in series, with all light treatments at two temperatures (either 15 degrees-C and 25 degrees-C or 20 degrees-C and 30 degrees-C) running simultaneously. This was repeated for each CO2 concentration.
Experiments were conducted in Multicultivator MC-1000 OD units (Photon Systems Instruments, Drasov, Czech Republic). Each unit consists of eight 85 ml test-tubes immersed in a thermostated water bath, each independently illuminated by an array of cool white LEDs set at specific intensity and timing. A 0.2um filtered CO2-air mix (Praxair Distribution Inc.) was bubbled through sterile artificial seawater, and the humidified gas mix was supplied to each tube via gentle sparging through a 2um stainless steel diffuser. Flow rates were gradually increased over the course of the incubation to compensate for the DIC uptake of actively growing cells, and ranged from <0.04 Liters per minute (LPM) at the start of the incubations to 0.08 LPM in each tube after 2 days. For each CO2 and temperature level, replication was achieved by incubating three tubes at sub-optimum light intensities, two tubes at optimum light intensity, and three tubes at extreme light intensities. Each experiment was split into two phases: An acclimation phase spanning 4 days, was used to acclimate cultures to their new environment. Pre-acclimated, exponentially-growing cultures were then inoculated into fresh media and incubated through a 3-day experimental phase during which assessments of growth, photophysiology, and nutrient cycling were carried out daily. All sampling started 5 hours into the daily light cycle to minimize the effects of diurnal cycles.
Experiments were conducted with artificial seawater (ASW) prepared using previously described methods (Kester et. al 1967), and enriched with nitrate (NO3), phosphate (PO4), silicic acid (Si[OH]4), at levels ensuring that the cultures would remain nutrient-replete over the course of the experiment. Trace metals and vitamins were added as in f/2 (Guillard 1975). The expected DIC concentration and pH of the growth media was determined for the different pCO2 and temperatures using the CO2SYS calculator (Pierrot et al. 2006), with constants from Mehrbach et al. (1973, refit by Dickson & Millero 1987), and inputs of temperature, salinity, total alkalinity (2376.5 umol · kg-1), pCO2, phosphate, and silicic acid. DIC levels in ASW at the start of each phase of the experiments were manipulated by the addition of NaHCO3, and was then maintained by bubbling a CO2-Air mix through the cultures over the course of the experiments. The pH of the growth media was measured spectrophometrically using the m-cresol purple method (Dickson 1993), and adjusted using 0.1N HCl or 0.1M NaOH. The media was distributed into 75 ml aliquots and each aliquot was inoculated with 5 ml of the T. pseudonana CCMP 1014 (TP1014) stock culture at the start of the experiments.
Macronutrient concentrations:
Media was filtered through 0.2 um filters into clean (plastic) bottles and stored at -20 degrees-C until analyses for nutrients. During the experiment, subsamples were filtered through 0.2 micron filters for Chl-a analyses, and through GF/F filters for particulate carbon (POC) analyses. The filterate from these filtrations was pooled into acid-washed HDPE containers, and stored at -20 degrees-C until analyses. Phosphate (PO4), Nitrate (NO3) + Nitrite (NO2), and Silicic Acid (Si(OH)4) were measured by Flow injection analysis (FIA) using a QuikChem 8500 Series 2 AutoAnalyzer (Lachat Instruments, Zellweger Analytics, Inc.).
Nutrient detection limits are reported in the last record of the data table.
BCO-DMO Processing Notes:
- added conventional header with dataset name, PI name, version date
- modified parameter names to conform with BCO-DMO naming conventions
- changed "- NA -" to "NA" ("not applicable")
File |
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3A_nuts.csv (Comma Separated Values (.csv), 6.91 KB) MD5:66293751cede4595c7137bdb310fc4ff Primary data file for dataset ID 771370 |
Parameter | Description | Units |
Phase | Indicates whether the sample was collected during the acclimation phase or the experiment phase of the experiment. The last record gives the instrument detection limits. Note that some concentrations in some treatments were below detection limits. | unitless |
CO2 | Indicates the concentration of CO2 in the CO2-Air mix that was bubbled through the samples over the course of the experiment | parts per million (ppm) |
Temperature | Indicates the temperature at which the samples were incubated. | degrees Celsius |
Day | Indicates the timepoint (day) of sampling. D0 = day 0; D1 = day 1; etc. | unitless |
Replicate | Indicates replication within a treatment. "NA" indicates "not applicable" | unitless |
SOL_PO4 | Phosphate concentrations in samples incubated at sub optimum light (SOL) | microMol |
OL_PO4 | Phosphate concentrations in samples incubated at optimum light (OL) | microMol |
EL_PO4 | Phosphate concentrations in samples incubated at extreme light (EL) | microMol |
SOL_SiO4 | Silicate concentrations in samples incubated at sub optimum light (SOL) | microMol |
OL_SiO4 | Silicate concentrations in samples incubated at optimum light (OL) | microMol |
EL_SiO4 | Silicate concentrations in samples incubated at extreme light (EL) | microMol |
SOL_NO3_NO2 | Nitrate + Nitrite concentrations in samples incubated at sub optimum light (SOL) | microMol |
OL_NO3_NO2 | Nitrate + Nitrite concentrations in samples incubated at optimum light (OL) | microMol |
EL_NO3_NO2 | Nitrate + Nitrite concentrations in samples incubated at extreme light (E | microMol |
Dataset-specific Instrument Name | Multicultivator MC-1000 OD (Photon Systems Instruments, Drasov, Czech Republic) |
Generic Instrument Name | Cell Cultivator |
Dataset-specific Description | Used for incubation of TP1014 cultures. |
Generic Instrument Description | An instrument used for the purpose of culturing small cells such as algae or bacteria. May provide temperature and light control and bubbled gas introduction. |
Dataset-specific Instrument Name | • QuikChem 8500 Series 2 AutoAnalyzer (Lachat Instruments, Zellweger Analytics, Inc.) |
Generic Instrument Name | Nutrient Autoanalyzer |
Dataset-specific Description | Used for analysis of nutrient (N, P, Si) concentrations. |
Generic Instrument Description | Nutrient Autoanalyzer is a generic term used when specific type, make and model were not specified. In general, a Nutrient Autoanalyzer is an automated flow-thru system for doing nutrient analysis (nitrate, ammonium, orthophosphate, and silicate) on seawater samples. |
The overarching goal of this project is to develop a framework for understanding the response of phytoplankton to multiple environmental stresses. Marine phytoplankton, which are tiny algae, produce as much oxygen as terrestrial plants and provide food, directly or indirectly, to all marine animals. Their productivity is thus important both for global elemental cycles of oxygen and carbon, as well as for the productivity of the ocean. Globally the productivity of marine phytoplankton appears to be changing, but while we have some understanding of the response of phytoplankton to shifts in one environmental parameter at a time, like temperature, there is very little knowledge of their response to simultaneous changes in several parameters. Increased atmospheric carbon dioxide concentrations result in both ocean acidification and increased surface water temperatures. The latter in turn leads to greater ocean stratification and associated changes in light exposure and nutrient availability for the plankton. Recently it has become apparent that the response of phytoplankton to simultaneous changes in these growth parameters is not additive. For example, the effect of ocean acidification may be severe at one temperature-light combination and negligible at another. The researchers of this project will carry out experiments that will provide a theoretical understanding of the relevant interactions so that the impact of climate change on marine phytoplankton can be predicted in an informed way. This project will engage high schools students through training of a teacher and the development of a teaching unit. Undergraduate and graduate students will work directly on the research. A cartoon journalist will create a cartoon story on the research results to translate the findings to a broader general public audience.
Each phytoplankton species has the capability to acclimatize to changes in temperature, light, pCO2, and nutrient availability - at least within a finite range. However, the response of phytoplankton to multiple simultaneous stressors is frequently complex, because the effects on physiological responses are interactive. To date, no datasets exist for even a single species that could fully test the assumptions and implications of existing models of phytoplankton acclimation to multiple environmental stressors. The investigators will combine modeling analysis with laboratory experiments to investigate the combined influences of changes in pCO2, temperature, light, and nitrate availability on phytoplankton growth using cultures of open ocean and coastal diatom strains (Thalassiosira pseudonana) and an open ocean cyanobacteria species (Synechococcus sp.). The planned experiments represent ideal case studies of the complex and interactive effects of environmental conditions on organisms, and results will provide the basis for predictive modeling of the response of phytoplankton taxa to multiple environmental stresses.
Funding Source | Award |
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NSF Division of Ocean Sciences (NSF OCE) |