BCO-DMO ERDDAP
Accessing BCO-DMO data 		log in    
Brought to you by BCO-DMO    
 
 
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\n \nH. akashiwo (CCMP 3374) was isolated from Narragansett Bay June 10, 2010 when\nin situ water temperature was 21.2\\u00b0C. After isolation the culture was\nmaintained at 15\\u00b0C. All experiments were conducted with cells that were\ngrown in autoclaved, 0.2 \\u00b5m sterile-filtered seawater (30-31 ppt) amended\nwith F/2 media without silica (Guillard 1975). All cultures were maintained\nunder a light intensity of 150 \\u00b5mol photons m-2 s-1 and a 12:12 h light:\ndark cycle. Preliminary experiments to determine the characteristics of this\nstrains\\u2019 growth patterns were used to maintain cultures in exponential\nphase by transferring cultures as needed every 4 to 10 days (depending on\ngrowth temperature), resulting in cell densities of 500-24,000 cell\nmL-1.\\u00a0 To avoid convolution of thermal response and effect of\nunconditioned media just after transfer culture transfers were restricted from\n1 day prior and 1 day post change in temperature (Grabski and Tukaj 2008 ).\n \nTemperature treatments\n \nTemperature was manipulated in the experiment through a series of sequential\ntemperature shifts. Beginning with a culture which had remained at 15 \\u00b0C\nsince collection, every four days a triplicate set of the most extreme,\ncurrent temperature treatments were split with one fraction retained at its\ncurrent treatment and one fraction shifted a temperature step outward (i.e.\nfurther towards the temperature extremes).\\u00a0 Only the cultures growing at\nthe highest and lowest temperatures were split and transferred to new\ntemperatures, but all other cultures were continually maintained in\nexponential growth phase. Cultures maintained at 15 \\u00b0C throughout the\nduration of the experiment served as an acclimated control, and as a reference\nfor the temporal consistency in acclimated rates. Including all temperature\nsteps and extrema, the nine treatments included: 6, 8, 10, 12, 18, 22, 25, 28,\n31, and the control at 15\\u00b0C. It took 20 days to complete the individual\ntemperature shifts at 4-day intervals to reach the most extreme temperature\ntreatments.\n \nDedicated incubators were used for control (15\\u00b0C, Model 2015 Low\nTemperature Incubator, VWR Scientific); 4, 6 (I-41LLVL, Percival Scientific);\n8, 18, 22 (I-36LLVL, Percival Scientific); and 10 \\u00b0C (Environ Air, Holman\nEngineering). Twenty-five, 28, and 31 \\u00b0C treatments were accomplished\nwith clear 10 L baths controlled by a coupled aquarium heater and thermostat\n(Fluval, Tru Temp), housed in an illuminated incubator. Light intensity was\nconsistently controlled across temperature treatments.\n \nPopulation and growth rate measurements\n \nTo quantify changes in cell size, population growth rate, and volumetric\ngrowth rate, the abundance and size (Equivalent Spherical Diameter, ESD)\ndistribution of each culture were measured with a 100 \\u00b5m aperture on a\nBeckman Coulter Multisizer 3 (Beckman Coulter, Brea California; Kim and\nMenden-Deuer 2013). The default bin size was the instrument standard of 0.2\n\\u00b5m. Each treatment set was measured daily for 15 days following the\ninitial transfer to the target temperature. Experiments were terminated after\n15 days because the objective of these experiments was to establish the\nresponse to relatively short-term temperature fluctuations.\n \nStatistical analysis\n \nMean and standard deviation of size distribution and cell counts as measured\nby the Coulter Counter were estimated from the raw data by a gaussian\ndistribution, fit with maximum likelihood estimation to the frequency of\nparticles greater than 8 \\u00b5m. Measurements that immediately followed\nculture inoculation and those from the growth were omitted. Cell volumes were\nestimated with equivalent spherical diameter (ESD) and spherical shape\napproximation. Cell biomass was calculated using ESD measured with the coulter\ncounter and calculated cell volume with the relationship of pg C cell-1=0.288x\nvolume0.811 (Menden-Deuer and Lessard 2000). Total biomass was approximate\nusing a culture and time specific mean ESD and cell count.\n \nSpecific growth rate was calculated by linear regression of natural log\ntransformed abundance. Production rates were calculated by linear regression\nof natural log transformed total estimated biomass for each culture. Specific\ngrowth rates were used to fit a thermal reaction norm modified from Norberg\n(2004), where a, b, and z are shape parameters, w the thermal niche width, T\n\\u00a0a given temperature, and k(T) the specific growth rate at that\ntemperature.\n \nk(T) = a * e^bT [1-(T-z)/w/2)^2]\n \nTo quantify the effect of time (acclimation) on growth rate the initial growth\nrates, measured in the first three days (\\u00b50; \\u0394 time<3 days), as well\nas final rates (\\u00b5f, 7< \\u0394 time<15 days) were calculated for each\ntemperature treatment.\n \nThese experiments were conducted at the University of Rhode Island, Graduate\nSchool 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 (external link)
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 \n   Growth rates and equivalent spherical diameters of Heterosigma akashiwo after temperature transition \n   PI: S. Menden-Deuer (URI) \n   version date: 2020-01-06 \n \treplaces 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/ (external link)
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 (external link)
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.\n\nfrom 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 (external link)
attribute NC_GLOBAL metadata_source String https://www.bco-dmo.org/api/dataset/783500 (external link)
attribute NC_GLOBAL param_mapping String {'783500': {}}
attribute NC_GLOBAL parameter_source String https://www.bco-dmo.org/mapserver/dataset/783500/parameters (external link)
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:\nPlankton, 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.\nGrazing 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/ (external link)
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/ (external link)
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

 
ERDDAP, Version 2.22
Disclaimers | Privacy Policy | Contact