BCO-DMO ERDDAP
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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 Chaetoceros simplex cultures, were obtained from population strain CCMP 200\n(National Center for Marine Algae and Microbiota, NCMA).\n \nThermal performance curve (TPC) assays:  \n We assayed the TPCs of our populations twice during the evolution\nexperiment. This involved pre\\u2010acclimating sub\\u2010cultures from each\npopulation to 28 \\u00b0C (in\\u2010between the 25 \\u00b0C control and 31\n\\u00b0C experimental treatment) in N\\u2010replete medium for 20 days\n(20\\u201325 generations) to remove any effects of acclimation to previous\ntemperatures (31 or 25 \\u00b0C) and N levels. Subsequently, separate flasks\ncontaining N\\u2010replete medium were placed at each assay temperature,\ninoculated with pre\\u2010acclimated populations, and allowed to acclimate for\nsix more days.\n \nAfter ~ 100 generations of evolution (102\\u2013114 days, corresponding to\n90\\u2013134 generations depending on the populations), we assessed the TPCs of\nall evolved populations and the control population. Assay temperatures were\n12, 20, 25, 29, 31, 32 and 34 \\u00b0C. Four replicate populations were\nestablished at each temperature in 12\\u2010well plates\\u00a0by combining four\n0.5 mL aliquots from the acclimated flasks with 4.5 mL of N\\u2010replete\nmedium. These plates were then maintained at each temperature. We measured in\nvivo chlorophyll\\u2010a fluorescence (excitation wavelength: 436 nm, emission\nwavelength: 680 nm) daily using a SpectraMax M5 microplate reader (Molecular\nDevices, Sunnyvale, CA, USA) to estimate the growth rate (252 estimates).\n \nGrowth rate calculations:  \n From the daily biomass estimations (in vivo chlorophyll\\u2010a fluorescence\n), we calculated population growth rates (day\\u22121), as the slope of the\nlinear regression of ln(biomass) vs. time (days).  \n ---  \n Also see data for 200 generations:\\u00a0[https://www.bco-\ndmo.org/dataset/778779](\\\\\"https://www.bco-dmo.org/dataset/778779\\\\\")  \n More details in Aranguren-Gassis et al. 2019, Ecology Letters.
attribute NC_GLOBAL awards_0_award_nid String 712786
attribute NC_GLOBAL awards_0_award_number String OCE-1638958
attribute NC_GLOBAL awards_0_data_url String http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1638958 (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 Michael E. Sieracki
attribute NC_GLOBAL awards_0_program_manager_nid String 50446
attribute NC_GLOBAL awards_1_award_nid String 712792
attribute NC_GLOBAL awards_1_award_number String OCE-1638804
attribute NC_GLOBAL awards_1_data_url String http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1638804 (external link)
attribute NC_GLOBAL awards_1_funder_name String NSF Division of Ocean Sciences
attribute NC_GLOBAL awards_1_funding_acronym String NSF OCE
attribute NC_GLOBAL awards_1_funding_source_nid String 355
attribute NC_GLOBAL awards_1_program_manager String Michael E. Sieracki
attribute NC_GLOBAL awards_1_program_manager_nid String 50446
attribute NC_GLOBAL awards_2_award_nid String 712795
attribute NC_GLOBAL awards_2_award_number String OCE-1638834
attribute NC_GLOBAL awards_2_data_url String http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1638834 (external link)
attribute NC_GLOBAL awards_2_funder_name String NSF Division of Ocean Sciences
attribute NC_GLOBAL awards_2_funding_acronym String NSF OCE
attribute NC_GLOBAL awards_2_funding_source_nid String 355
attribute NC_GLOBAL awards_2_program_manager String Michael E. Sieracki
attribute NC_GLOBAL awards_2_program_manager_nid String 50446
attribute NC_GLOBAL cdm_data_type String Other
attribute NC_GLOBAL comment String TPC Growth rates: 100 generations \n   Daily growth rates for Thermal Performance Curve (TPC) of Chaetoceros simplex  \n    after about 100 generations of evolution at seven temperatures, 12-34 degrees C. \n   P.I.'s: M. Aranguren-Gassis (U. Vigo), E. Litchman (MSU), C. Klausmeier (MSU) \n   version date: 2019-10-07
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 2019-10-07T20:31:11Z
attribute NC_GLOBAL date_modified String 2019-10-30T17:28:25Z
attribute NC_GLOBAL defaultDataQuery String &time<now
attribute NC_GLOBAL doi String 10.1575/1912/bco-dmo.778749.1
attribute NC_GLOBAL infoUrl String https://www.bco-dmo.org/dataset/778749 (external link)
attribute NC_GLOBAL institution String BCO-DMO
attribute NC_GLOBAL instruments_0_dataset_instrument_nid String 779427
attribute NC_GLOBAL instruments_0_description String Plate readers (also known as microplate readers) are laboratory instruments designed to detect biological, chemical or physical events of samples in microtiter plates. They are widely used in research, drug discovery, bioassay validation, quality control and manufacturing processes in the pharmaceutical and biotechnological industry and academic organizations. Sample reactions can be assayed in 6-1536 well format microtiter plates. The most common microplate format used in academic research laboratories or clinical diagnostic laboratories is 96-well (8 by 12 matrix) with a typical reaction volume between 100 and 200 uL per well. Higher density microplates (384- or 1536-well microplates) are typically used for screening applications, when throughput (number of samples per day processed) and assay cost per sample become critical parameters, with a typical assay volume between 5 and 50 µL per well. Common detection modes for microplate assays are absorbance, fluorescence intensity, luminescence, time-resolved fluorescence, and fluorescence polarization. From: https://en.wikipedia.org/wiki/Plate_reader, 2014-09-0-23.
attribute NC_GLOBAL instruments_0_instrument_name String plate reader
attribute NC_GLOBAL instruments_0_instrument_nid String 528693
attribute NC_GLOBAL instruments_0_supplied_name String SpectraMax M5 microplate reader (Molecular Devices, Sunnyvale, CA, USA)
attribute NC_GLOBAL keywords String bco, bco-dmo, biological, chemical, data, dataset, dmo, erddap, evol, Evol_strain, growth, Growth_rate, management, oceanography, office, preliminary, rate, replicate, strain, temperature, well, Well_replicate
attribute NC_GLOBAL license String https://www.bco-dmo.org/dataset/778749/license (external link)
attribute NC_GLOBAL metadata_source String https://www.bco-dmo.org/api/dataset/778749 (external link)
attribute NC_GLOBAL param_mapping String {'778749': {}}
attribute NC_GLOBAL parameter_source String https://www.bco-dmo.org/mapserver/dataset/778749/parameters (external link)
attribute NC_GLOBAL people_0_affiliation String Michigan State University
attribute NC_GLOBAL people_0_affiliation_acronym String MSU
attribute NC_GLOBAL people_0_person_name String Elena Litchman
attribute NC_GLOBAL people_0_person_nid String 543190
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 Michigan State University
attribute NC_GLOBAL people_1_affiliation_acronym String MSU
attribute NC_GLOBAL people_1_person_name String Christopher Klausmeier
attribute NC_GLOBAL people_1_person_nid String 543192
attribute NC_GLOBAL people_1_role String Co-Principal Investigator
attribute NC_GLOBAL people_1_role_type String originator
attribute NC_GLOBAL people_2_affiliation String Michigan State University
attribute NC_GLOBAL people_2_affiliation_acronym String MSU
attribute NC_GLOBAL people_2_person_name String Colin T. Kremer
attribute NC_GLOBAL people_2_person_nid String 779889
attribute NC_GLOBAL people_2_role String Scientist
attribute NC_GLOBAL people_2_role_type String originator
attribute NC_GLOBAL people_3_affiliation String Universidad de Vigo
attribute NC_GLOBAL people_3_person_name String Maria Aranguren-Gassis
attribute NC_GLOBAL people_3_person_nid String 778758
attribute NC_GLOBAL people_3_role String Contact
attribute NC_GLOBAL people_3_role_type String related
attribute NC_GLOBAL people_4_affiliation String Woods Hole Oceanographic Institution
attribute NC_GLOBAL people_4_affiliation_acronym String WHOI BCO-DMO
attribute NC_GLOBAL people_4_person_name String Nancy Copley
attribute NC_GLOBAL people_4_person_nid String 50396
attribute NC_GLOBAL people_4_role String BCO-DMO Data Manager
attribute NC_GLOBAL people_4_role_type String related
attribute NC_GLOBAL project String Phytoplankton Community Responses
attribute NC_GLOBAL projects_0_acronym String Phytoplankton Community Responses
attribute NC_GLOBAL projects_0_description String NSF Award Abstract:\nPhotosynthetic marine microbes, phytoplankton, contribute half of global primary production, form the base of most aquatic food webs and are major players in global biogeochemical cycles. Understanding their community composition is important because it affects higher trophic levels, the cycling of energy and elements and is sensitive to global environmental change. This project will investigate how phytoplankton communities respond to two major global change stressors in aquatic systems: warming and changes in nutrient availability. The researchers will work in two marine systems with a long history of environmental monitoring, the temperate Narragansett Bay estuary in Rhode Island and a subtropical North Atlantic site near Bermuda. They will use field sampling and laboratory experiments with multiple species and varieties of phytoplankton to assess the diversity in their responses to different temperatures under high and low nutrient concentrations. If the diversity of responses is high within species, then that species may have a better chance to adapt to rising temperatures and persist in the future. Some species may already be able to grow at high temperatures; consequently, they may become more abundant as the ocean warms. The researchers will incorporate this response information in mathematical models to predict how phytoplankton assemblages would reorganize under future climate scenarios. Graduate students and postdoctoral associates will be trained in diverse scientific approaches and techniques such as shipboard sampling, laboratory experiments, genomic analyses and mathematical modeling. The results of the project will be incorporated into K-12 teaching, including an advanced placement environmental science class for underrepresented minorities in Los Angeles, data exercises for rural schools in Michigan and disseminated to the public through an environmental journalism institute based in Rhode Island.\nPredicting how ecological communities will respond to a changing environment requires knowledge of genetic, phylogenetic and functional diversity within and across species. This project will investigate how the interaction of phylogenetic, genetic and functional diversity in thermal traits within and across a broad range of species determines the responses of marine phytoplankton communities to rising temperature and changing nutrient regimes. High genetic and functional diversity within a species may allow evolutionary adaptation of that species to warming. If the phylogenetic and functional diversity is higher across species, species sorting and ecological community reorganization is likely. Different marine sites may have a different balance of genetic and functional diversity within and across species and, thus, different contribution of evolutionary and ecological responses to changing climate. The research will be conducted at two long-term time series sites in the Atlantic Ocean, the Narragansett Bay Long-Term Plankton Time Series and the Bermuda Atlantic Time Series (BATS) station. The goal is to assess intra- and inter-specific genetic and functional diversity in thermal responses at contrasting nutrient concentrations for a representative range of species in communities at the two sites in different seasons, and use this information to parameterize eco-evolutionary models embedded into biogeochemical ocean models to predict responses of phytoplankton communities to projected rising temperatures under realistic nutrient conditions. Model predictions will be informed by and tested with field data, including the long-term data series available for both sites and in community temperature manipulation experiments. This project will provide novel information on existing intraspecific genetic and functional thermal diversity for many ecologically and biogeochemically important phytoplankton species, estimate generation of new genetic and functional diversity in evolution experiments, and develop and parameterize novel eco-evolutionary models interfaced with ocean biogeochemical models to predict future phytoplankton community structure. The project will also characterize the interaction of two major global change stressors, warming and changing nutrient concentrations, as they affect phytoplankton diversity at functional, genetic, and phylogenetic levels. In addition, the project will develop novel modeling methodology that will be broadly applicable to understanding how other types of complex ecological communities may adapt to a rapidly warming world.
attribute NC_GLOBAL projects_0_end_date String 2020-09
attribute NC_GLOBAL projects_0_geolocation String Narragansett Bay, RI and Bermuda, Bermuda Atlantic Time-series Study (BATS)
attribute NC_GLOBAL projects_0_name String Dimensions: Collaborative Research: Genetic, functional and phylogenetic diversity determines marine phytoplankton community responses to changing temperature and nutrients
attribute NC_GLOBAL projects_0_project_nid String 712787
attribute NC_GLOBAL projects_0_start_date String 2016-10
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 Daily growth rates for Thermal Performance Curve (TPC) of Chaetoceros simplex after about 100 generations of evolution at seven temperatures, 12-34 degrees C.
attribute NC_GLOBAL title String [TPC Growth rates: 100 generations] - Daily growth rates for Thermal Performance Curve (TPC) of Chaetoceros simplex after about 100 generations of evolution at seven temperatures, 12-34 degrees C. (Dimensions: Collaborative Research: Genetic, functional and phylogenetic diversity determines marine phytoplankton community responses to changing temperature and nutrients)
attribute NC_GLOBAL version String 1
attribute NC_GLOBAL xml_source String osprey2erddap.update_xml() v1.3
variable Evol_strain String
attribute Evol_strain bcodmo_name String sample
attribute Evol_strain description String evolved population identifier; L1 signifies strains raised in 'regular' medium at 884 micromoles nitrate; 5 signifies medium with reduced nitrate at 5 micromoles. Control refers to the population maintained at 25ºC during the evolution experiment as a temperature control population.
attribute Evol_strain long_name String Evol Strain
attribute Evol_strain nerc_identifier String https://vocab.nerc.ac.uk/collection/P02/current/ACYC/ (external link)
attribute Evol_strain units String none
variable Temperature byte
attribute Temperature _FillValue byte 127
attribute Temperature actual_range byte 12, 34
attribute Temperature bcodmo_name String temperature
attribute Temperature description String Culture maintenance temperature
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 Celsius degrees
variable Well_replicate byte
attribute Well_replicate _FillValue byte 127
attribute Well_replicate actual_range byte 1, 4
attribute Well_replicate bcodmo_name String replicate
attribute Well_replicate description String Replicate number
attribute Well_replicate long_name String Well Replicate
attribute Well_replicate units String unitless
variable Growth_rate float
attribute Growth_rate _FillValue float NaN
attribute Growth_rate actual_range float -0.4, 1.2
attribute Growth_rate bcodmo_name String growth
attribute Growth_rate description String Growth rate calculated from biomass
attribute Growth_rate long_name String Growth Rate
attribute Growth_rate units String day-1

 
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