ERDDAP > info > bcodmo_dataset_783500

Grid DAP Data	Sub- set	Table DAP Data	Make A Graph	W M S	Source Data Files	Acces- sible	Title	Sum- mary	FGDC, ISO, Metadata	Back- ground Info	RSS	E mail	Institution	Dataset ID
		data	graph		files	public	[Phytoplankton Growth Acclimation] - Growth rates and equivalent spherical diameters of Heterosigma akashiwo after temperature transition (Quantifying Temperature Dependence In Growth & Grazing Rates of Planktonic Herbivores)		I   M	background			BCO-DMO	bcodmo_dataset_783500

The Dataset's Variables and Attributes

Row Type	Variable Name	Attribute Name	Data Type	Value
attribute	NC_GLOBAL	access_formats	String	.htmlTable,.csv,.json,.mat,.nc,.tsv
attribute	NC_GLOBAL	acquisition_description	String	Experimental setup H. akashiwo (CCMP 3374) was isolated from Narragansett Bay June 10, 2010 when in situ water temperature was 21.2\u00b0C. After isolation the culture was maintained at 15\u00b0C. All experiments were conducted with cells that were grown in autoclaved, 0.2 \u00b5m sterile-filtered seawater (30-31 ppt) amended with F/2 media without silica (Guillard 1975). All cultures were maintained under a light intensity of 150 \u00b5mol photons m-2 s-1 and a 12:12 h light: dark cycle. Preliminary experiments to determine the characteristics of this strains\u2019 growth patterns were used to maintain cultures in exponential phase by transferring cultures as needed every 4 to 10 days (depending on growth temperature), resulting in cell densities of 500-24,000 cell mL-1.\u00a0 To avoid convolution of thermal response and effect of unconditioned media just after transfer culture transfers were restricted from 1 day prior and 1 day post change in temperature (Grabski and Tukaj 2008 ). Temperature treatments Temperature was manipulated in the experiment through a series of sequential temperature shifts. Beginning with a culture which had remained at 15 \u00b0C since collection, every four days a triplicate set of the most extreme, current temperature treatments were split with one fraction retained at its current treatment and one fraction shifted a temperature step outward (i.e. further towards the temperature extremes).\u00a0 Only the cultures growing at the highest and lowest temperatures were split and transferred to new temperatures, but all other cultures were continually maintained in exponential growth phase. Cultures maintained at 15 \u00b0C throughout the duration of the experiment served as an acclimated control, and as a reference for the temporal consistency in acclimated rates. Including all temperature steps and extrema, the nine treatments included: 6, 8, 10, 12, 18, 22, 25, 28, 31, and the control at 15\u00b0C. It took 20 days to complete the individual temperature shifts at 4-day intervals to reach the most extreme temperature treatments. Dedicated incubators were used for control (15\u00b0C, Model 2015 Low Temperature Incubator, VWR Scientific); 4, 6 (I-41LLVL, Percival Scientific); 8, 18, 22 (I-36LLVL, Percival Scientific); and 10 \u00b0C (Environ Air, Holman Engineering). Twenty-five, 28, and 31 \u00b0C treatments were accomplished with clear 10 L baths controlled by a coupled aquarium heater and thermostat (Fluval, Tru Temp), housed in an illuminated incubator. Light intensity was consistently controlled across temperature treatments. Population and growth rate measurements To quantify changes in cell size, population growth rate, and volumetric growth rate, the abundance and size (Equivalent Spherical Diameter, ESD) distribution of each culture were measured with a 100 \u00b5m aperture on a Beckman Coulter Multisizer 3 (Beckman Coulter, Brea California; Kim and Menden-Deuer 2013). The default bin size was the instrument standard of 0.2 \u00b5m. Each treatment set was measured daily for 15 days following the initial transfer to the target temperature. Experiments were terminated after 15 days because the objective of these experiments was to establish the response to relatively short-term temperature fluctuations. Statistical analysis Mean and standard deviation of size distribution and cell counts as measured by the Coulter Counter were estimated from the raw data by a gaussian distribution, fit with maximum likelihood estimation to the frequency of particles greater than 8 \u00b5m. Measurements that immediately followed culture inoculation and those from the growth were omitted. Cell volumes were estimated with equivalent spherical diameter (ESD) and spherical shape approximation. Cell biomass was calculated using ESD measured with the coulter counter and calculated cell volume with the relationship of pg C cell-1=0.288x volume0.811 (Menden-Deuer and Lessard 2000). Total biomass was approximate using a culture and time specific mean ESD and cell count. Specific growth rate was calculated by linear regression of natural log transformed abundance. Production rates were calculated by linear regression of natural log transformed total estimated biomass for each culture. Specific growth rates were used to fit a thermal reaction norm modified from Norberg (2004), where a, b, and z are shape parameters, w the thermal niche width, T \u00a0a given temperature, and k(T) the specific growth rate at that temperature. k(T) = a * e^bT [1-(T-z)/w/2)^2] To quantify the effect of time (acclimation) on growth rate the initial growth rates, measured in the first three days (\u00b50; \u0394 time<3 days), as well as final rates (\u00b5f, 7< \u0394 time<15 days) were calculated for each temperature treatment. These experiments were conducted at the University of Rhode Island, Graduate School of Oceanography in the laboratory of Dr. Susanne Menden-Deuer
attribute	NC_GLOBAL	awards_0_award_nid	String	739231
attribute	NC_GLOBAL	awards_0_award_number	String	OCE-1736635
attribute	NC_GLOBAL	awards_0_data_url	String	http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1736635
attribute	NC_GLOBAL	awards_0_funder_name	String	NSF Division of Ocean Sciences
attribute	NC_GLOBAL	awards_0_funding_acronym	String	NSF OCE
attribute	NC_GLOBAL	awards_0_funding_source_nid	String	355
attribute	NC_GLOBAL	awards_0_program_manager	String	David L. Garrison
attribute	NC_GLOBAL	awards_0_program_manager_nid	String	50534
attribute	NC_GLOBAL	cdm_data_type	String	Other
attribute	NC_GLOBAL	comment	String	Growth rates and ESD Growth rates and equivalent spherical diameters of Heterosigma akashiwo after temperature transition PI: S. Menden-Deuer (URI) version date: 2020-01-06 replaces version 2019-12-04
attribute	NC_GLOBAL	Conventions	String	COARDS, CF-1.6, ACDD-1.3
attribute	NC_GLOBAL	creator_email	String	info at bco-dmo.org
attribute	NC_GLOBAL	creator_name	String	BCO-DMO
attribute	NC_GLOBAL	creator_type	String	institution
attribute	NC_GLOBAL	creator_url	String	https://www.bco-dmo.org/
attribute	NC_GLOBAL	data_source	String	extract_data_as_tsv version 2.3 19 Dec 2019
attribute	NC_GLOBAL	date_created	String	2019-12-04T19:30:11Z
attribute	NC_GLOBAL	date_modified	String	2020-01-09T14:54:34Z
attribute	NC_GLOBAL	defaultDataQuery	String	&amp;time&lt;now
attribute	NC_GLOBAL	doi	String	10.1575/1912/bco-dmo.783500.2
attribute	NC_GLOBAL	infoUrl	String	https://www.bco-dmo.org/dataset/783500
attribute	NC_GLOBAL	institution	String	BCO-DMO
attribute	NC_GLOBAL	instruments_0_dataset_instrument_description	String	Used to count cells.
attribute	NC_GLOBAL	instruments_0_dataset_instrument_nid	String	783507
attribute	NC_GLOBAL	instruments_0_description	String	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
attribute	NC_GLOBAL	instruments_0_instrument_name	String	Coulter Counter
attribute	NC_GLOBAL	instruments_0_instrument_nid	String	668847
attribute	NC_GLOBAL	instruments_0_supplied_name	String	Beckman Coulter Multisizer III Counter
attribute	NC_GLOBAL	keywords	String	bco, bco-dmo, bio, biological, BioRate, chemical, culture, data, dataset, dmo, erddap, esd, growth, GrowthRate, management, mean, MeanESD_t, oceanography, office, preliminary, rate, temperature, time, time2
attribute	NC_GLOBAL	license	String	https://www.bco-dmo.org/dataset/783500/license
attribute	NC_GLOBAL	metadata_source	String	https://www.bco-dmo.org/api/dataset/783500
attribute	NC_GLOBAL	param_mapping	String	{'783500': {}}
attribute	NC_GLOBAL	parameter_source	String	https://www.bco-dmo.org/mapserver/dataset/783500/parameters
attribute	NC_GLOBAL	people_0_affiliation	String	University of Rhode Island
attribute	NC_GLOBAL	people_0_affiliation_acronym	String	URI-GSO
attribute	NC_GLOBAL	people_0_person_name	String	Susanne Menden-Deuer
attribute	NC_GLOBAL	people_0_person_nid	String	739234
attribute	NC_GLOBAL	people_0_role	String	Principal Investigator
attribute	NC_GLOBAL	people_0_role_type	String	originator
attribute	NC_GLOBAL	people_1_affiliation	String	Woods Hole Oceanographic Institution
attribute	NC_GLOBAL	people_1_affiliation_acronym	String	WHOI BCO-DMO
attribute	NC_GLOBAL	people_1_person_name	String	Nancy Copley
attribute	NC_GLOBAL	people_1_person_nid	String	50396
attribute	NC_GLOBAL	people_1_role	String	BCO-DMO Data Manager
attribute	NC_GLOBAL	people_1_role_type	String	related
attribute	NC_GLOBAL	project	String	Planktonic Herbivore Temp Dependence
attribute	NC_GLOBAL	projects_0_acronym	String	Planktonic Herbivore Temp Dependence
attribute	NC_GLOBAL	projects_0_description	String	NSF Award Abstract: Plankton, single-celled organisms that inhabit the world's oceans are responsible for the generation of oxygen, cycling energy and matter between the atmosphere and the deep ocean and are the basis for virtually all seafood harvested. These life-giving functions critically depend on the relative rates at which plankton grow and get eaten. How temperature influences those rates is essential to understand plankton responses to environmental changes and ocean dynamics. It is well established that plankton grow faster when temperatures are higher however, whether feeding has a similar temperature dependence is unknown. That means oceanographers are missing key data required to build global predictive models. This project will fill essential knowledge gaps and measure physiological rates of singled celled zooplankton across temperature gradients representing the global ocean, from polar to tropical regions and throughout the seasonal cycle. Researchers will combine laboratory experiments with specimens taken from the coastal ocean (Narragansett Bay), which is exemplary in its strong seasonal temperature variations. These data will provide a clear picture of the production capacity and activity of plankton in a global and dynamic ocean. The project supports an early career scientist, as well as graduate and undergraduate students. Scientists will continue communicating their research to the public through large-scale outreach events, education at the high-school level, and engagement through online and other media. Moreover, researchers will continue collaborating with the Metcalf Institute for Marine & Environmental Reporting to support their Annual Science Immersion Workshop for Journalists and their ongoing work to disseminate research findings through web-based seminars. Grazing is the single largest loss factor of marine primary production and thus affects a key transfer rate between global organic and inorganic matter pools. Remarkably, data for herbivorous protist growth and grazing rates at temperatures representative of the vast polar regions and during winter and spring periods are extremely sparse. By combining laboratory experiments with ground truthing fieldwork, this project alleviates a central knowledge gap in oceanography and delivers the empirical measurements necessary to derive algorithms to incorporate temperature dependence of heterotrophic protist growth and grazing rates into biogeochemical models. The extraordinary seasonal temperature fluctuations in a temperate coastal estuary (Narragansett Bay) are exploited to measure rates of heterotrophic protists isolated from different temperatures and seasons and to quantify the temperature and acclimation responses of these ecotypes. This project delivers data urgently needed to solve the conundrum of whether herbivorous growth and predation is depressed at low temperatures, implying low trophic transfer rates and high carbon export, or if predation proceeds at rates comparable to temperate systems with primary production largely lost to predation. Large temperature gradients in the global ocean mean that cross-biome and biogeochemical models are particularly sensitive to assumptions about the temperature dependence in modeled rate processes. Establishment of the dependence of heterotrophic plankton physiological rates (growth and grazing) to gradients of temperature, mimicking realistic conditions experienced by plankton in a changing ocean, is a key step towards integrating much needed biological information in biogeochemical modeling efforts. This project makes a significant contribution to linking ecological research with ecosystem models by providing empirically rooted algorithms of the temperature dependence of protistan herbivory and growth rates, key processes in the transformation of organic matter in global biogeochemical cycles and tools critically missing in ecosystem models.
attribute	NC_GLOBAL	projects_0_end_date	String	2020-08
attribute	NC_GLOBAL	projects_0_geolocation	String	Narragansett Bay
attribute	NC_GLOBAL	projects_0_name	String	Quantifying Temperature Dependence In Growth & Grazing Rates of Planktonic Herbivores
attribute	NC_GLOBAL	projects_0_project_nid	String	739232
attribute	NC_GLOBAL	projects_0_start_date	String	2017-09
attribute	NC_GLOBAL	publisher_name	String	Biological and Chemical Oceanographic Data Management Office (BCO-DMO)
attribute	NC_GLOBAL	publisher_type	String	institution
attribute	NC_GLOBAL	sourceUrl	String	(local files)
attribute	NC_GLOBAL	standard_name_vocabulary	String	CF Standard Name Table v55
attribute	NC_GLOBAL	summary	String	Quantifying phytoplankton growth as a function of environmental conditions such as temperature is critical for understanding and predicting production in the ocean. Typically, thermal response is described as the steady state growth rates under static conditions. However, here, with a clonal culture of Heterosigma akashiwo, temperature was manipulated in the laboratory with the goal of describing how growth rates may change over time through the acclimation process. Growth rates and equivalent spherical diameter of Heterosigma akashiwo after temperature transition are reported.
attribute	NC_GLOBAL	title	String	[Phytoplankton Growth Acclimation] - Growth rates and equivalent spherical diameters of Heterosigma akashiwo after temperature transition (Quantifying Temperature Dependence In Growth & Grazing Rates of Planktonic Herbivores)
attribute	NC_GLOBAL	version	String	2
attribute	NC_GLOBAL	xml_source	String	osprey2erddap.update_xml() v1.3
variable	Culture		String
attribute	Culture	bcodmo_name	String	sample
attribute	Culture	description	String	culture identifier
attribute	Culture	long_name	String	Culture
attribute	Culture	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P02/current/ACYC/
attribute	Culture	units	String	unitless
variable	time2		String
attribute	time2	bcodmo_name	String	flag
attribute	time2	description	String	either growth rate immediately after temperature change (t1) or growth rate after 1 week to acclimate (tf)
attribute	time2	long_name	String	Time
attribute	time2	units	String	unitless
variable	Temperature		byte
attribute	Temperature	_FillValue	byte	127
attribute	Temperature	actual_range	byte	6, 31
attribute	Temperature	bcodmo_name	String	temperature
attribute	Temperature	description	String	temperature treatment
attribute	Temperature	long_name	String	Temperature
attribute	Temperature	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/
attribute	Temperature	units	String	degrees Celsius
variable	GrowthRate		float
attribute	GrowthRate	_FillValue	float	NaN
attribute	GrowthRate	actual_range	float	-0.16, 0.73
attribute	GrowthRate	bcodmo_name	String	growth
attribute	GrowthRate	description	String	divison-based growth rate
attribute	GrowthRate	long_name	String	Growth Rate
attribute	GrowthRate	units	String	per day
variable	BioRate		float
attribute	BioRate	_FillValue	float	NaN
attribute	BioRate	actual_range	float	-0.05, 0.93
attribute	BioRate	bcodmo_name	String	growth
attribute	BioRate	description	String	biovolume-based growth rate
attribute	BioRate	long_name	String	Bio Rate
attribute	BioRate	units	String	per day
variable	MeanESD_t		float
attribute	MeanESD_t	_FillValue	float	NaN
attribute	MeanESD_t	actual_range	float	10.0, 18.0
attribute	MeanESD_t	bcodmo_name	String	diameter
attribute	MeanESD_t	description	String	Mean Equivalent Spherical Diameter for a culture during the period of growth rate calculation
attribute	MeanESD_t	long_name	String	Mean ESD T
attribute	MeanESD_t	units	String	micrometers

The information in the table above is also available in other file formats (.csv, .htmlTable, .itx, .json, .jsonlCSV1, .jsonlCSV, .jsonlKVP, .mat, .nc, .nccsv, .tsv, .xhtml) via a RESTful web service.