Series 3A: Multiple stressor experiments on T. pseudonana (CCMP1014) - Chlorophyll, particulate organic carbon and particulate organic nitrogen.

Website: https://www.bco-dmo.org/dataset/771594
Version: 1
Version Date: 2019-06-17

Project
» Collaborative Research: Effects of multiple stressors on Marine Phytoplankton (Stressors on Marine Phytoplankton)
ContributorsAffiliationRole
Passow, UtaUniversity of California-Santa Barbara (UCSB-MSI)Principal Investigator
Laws, EdwardLouisiana State University (LSU-SC&E)Co-Principal Investigator
D'Souza, NigelUniversity of California-Santa Barbara (UCSB-MSI)Scientist, Contact
Copley, NancyWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager

Abstract
The experiments were designed to test the combined effects of CO2, temperatures, and light on growth and photophysiology of the diatom T. pseudonana CCMP1014 in a multifactorial design. This dataset contains measurements of extracted chlorophyll, particulate organic carbon (POC), and particulate organic nitrogen (PON) made over the course of the experiments.


Coverage

Temporal Extent: 2018-07 - 2018-12

Dataset Description

The experiments were designed to test the combined effects of CO2, temperatures, and light on growth and photophysiology of the diatom T. pseudonana CCMP1014 in a multifactorial design. This dataset contains measurements of extracted chlorophyll, particulate organic carbon (POC), and particulate organic nitrogen (PON) made over the course of the experiments.


Acquisition Description

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.

Organic Carbon and Nitrogen concentrations:
Samples were filtered onto pre-combusted GF/F filters, dried at 60 degrees C, and stored at room temperature until analyses of particulate organic carbon (POC), and particulate organic nitrogen (PON). Between 3 and > 10 mL were filtered, with larger filtration volumes used on the final day of the experiment. Samples were analyzed using an elemental analyzer (CEC 44OHA; Control Equipment). Samples where C or N concentrations were below instrument detection limits were flagged.

Chlorophyll:
Daily subsamples from each treatment were filtered onto 0.45 µm polycarbonate filters and stored at -20 degrees C. Filters were placed in 90% acetone (v/v) overnight at -20 degrees C, and the extracted chlorophyll was measured fluorometrically on a Turner 700 fluorometer (Strickland 1972). Chlorophyll-a liquid standards in 90% acetone (Turner Designs Inc.), and adjustable solid secondary standards (Turner Designs Inc. P/N 8000-952) were used for calibrations, and to calculate the chlorophyll content of the samples (Column O)


Processing Description

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"
- changed "<" to "BDL" (below detection limit)

 


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Related Publications

Dickson, A. G. (1993). The measurement of sea water pH. Marine Chemistry, 44(2-4), 131–142. doi:10.1016/0304-4203(93)90198-W
Dickson, A. G., & Millero, F. J. (1987). A comparison of the equilibrium constants for the dissociation of carbonic acid in seawater media. Deep Sea Research Part A. Oceanographic Research Papers, 34(10), 1733–1743. doi:10.1016/0198-0149(87)90021-5
Dickson, A.G., Sabine, C.L. and Christian, J.R. (Eds.) 2007. Guide to best practices for ocean CO2 measurements. PICES Special Publication 3, 191 pp. ISBN: 1-897176-07-4. Handle: http://hdl.handle.net/11329/249. URL: https://www.nodc.noaa.gov/ocads/oceans/Handbook_2007.html
Guillard, R. R. L. (1975). Culture of Phytoplankton for Feeding Marine Invertebrates. Culture of Marine Invertebrate Animals, 29–60. doi:10.1007/978-1-4615-8714-9_3
KESTER, D. R., DUEDALL, I. W., CONNORS, D. N., & PYTKOWICZ, R. M. (1967). PREPARATION OF ARTIFICIAL SEAWATER1. Limnology and Oceanography, 12(1), 176–179. doi:10.4319/lo.1967.12.1.0176
Mehrbach, C., Culberson, C. H., Hawley, J. E., & Pytkowicx, R. M. (1973). MEASUREMENT OF THE APPARENT DISSOCIATION CONSTANTS OF CARBONIC ACID IN SEAWATER AT ATMOSPHERIC PRESSURE1. Limnology and Oceanography, 18(6), 897–907. doi:10.4319/lo.1973.18.6.0897
Pierrot, D. E. Lewis,and D. W. R. Wallace. 2006. MS Excel Program Developed for CO2 System Calculations. ORNL/CDIAC-105a. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee. doi: 10.3334/CDIAC/otg.CO2SYS_XLS_CDIAC105a.

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Parameters

Parameters for this dataset have not yet been identified


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Instruments

Dataset-specific Instrument Name
Turner 700 fluorometer
Generic Instrument Name
Fluorometer
Dataset-specific Description
Used for fluorometric analyses of extracted chlorophyll.
Generic Instrument Description
A fluorometer or fluorimeter is a device used to measure parameters of fluorescence: its intensity and wavelength distribution of emission spectrum after excitation by a certain spectrum of light. The instrument is designed to measure the amount of stimulated electromagnetic radiation produced by pulses of electromagnetic radiation emitted into a water sample or in situ.

Dataset-specific Instrument Name
Elemental analyzer (CEC 44OHA; Control Equipment)
Generic Instrument Name
CHN Elemental Analyzer
Dataset-specific Description
Used for analysis of total organic carbon content.
Generic Instrument Description
A CHN Elemental Analyzer is used for the determination of carbon, hydrogen, and nitrogen content in organic and other types of materials, including solids, liquids, volatile, and viscous samples.

Dataset-specific Instrument Name
Multicultivator MC-1000 OD (Qubit Systems)
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.


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Project Information

Collaborative Research: Effects of multiple stressors on Marine Phytoplankton (Stressors on Marine Phytoplankton)


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.


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Funding

Funding SourceAward
NSF Division of Ocean Sciences (NSF OCE)

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