Accessing BCO-DMO data
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| Dataset Title: | [Neuse River Estuary YSI Profile] - YSI data from the Neuse River from 2008- 2013 (Collaborative Research: Regulation of Phytoplankton Dynamics in Mid- Atlantic Estuaries Subject to Climatic Perturbations) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_767641) |
| Range: | longitude = -77.1222 to -76.52602°E, latitude = 34.94888 to 35.2106°N, depth = 0.1 to 7.817m |
| Information: | Summary
| License
| FGDC
| ISO 19115
| Metadata
| Background
| Subset
| Data Access Form
| Files
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Zoom: ![[The graph you specified. Please be patient.]](https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_767641.png?longitude,latitude,Station&.draw=markers&.marker=5%7C5&.color=0x000000&.colorBar=%7C%7C%7C%7C%7C&.bgColor=0xffccccff)
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Attributes {
s {
Zlevel1 {
String bcodmo_name "unknown";
String description "Column used to determine surface or near bottom designation (closest reading to 0.5 m from bottom or last reading)";
String long_name "Zlevel1";
String units "unitless";
}
Zlevel2 {
String bcodmo_name "unknown";
String description "Column used to determine surface or near bottom designation (closest reading to 0.5 m from bottom or last reading)";
String long_name "Zlevel2";
String units "unitless";
}
Date {
String bcodmo_name "date";
String description "Date of water sample collection; filtration; and in situ measurements.";
String long_name "Date";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
String time_precision "1970-01-01";
String units "unitless";
}
Station {
Int16 _FillValue 32767;
Int16 actual_range 0, 180;
String bcodmo_name "station";
String description "The name of the fixed sampling station.";
String long_name "Station";
String units "unitless";
}
time2 {
String bcodmo_name "time";
String description "Exact time (hours:minutes:seconds) when the in situ measurements were made. This time is an approximate water sampling time.";
String long_name "Time";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/AHMSAA01/";
String units "unitless";
}
depth {
String _CoordinateAxisType "Height";
String _CoordinateZisPositive "down";
Float64 _FillValue NaN;
Float64 actual_range 0.1, 7.817;
String axis "Z";
String bcodmo_name "depth";
Float64 colorBarMaximum 8000.0;
Float64 colorBarMinimum -8000.0;
String colorBarPalette "TopographyDepth";
String description "Exact depth (meters) where the in situ measurements were made.";
String ioos_category "Location";
String long_name "Depth";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
String positive "down";
String standard_name "depth";
String units "m";
}
Temp {
Float32 _FillValue NaN;
Float32 actual_range 2.04, 33.69;
String bcodmo_name "temperature";
String description "In situ water temperature";
String long_name "Temperature";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
String units "degrees Celsius";
}
SpCond {
Float32 _FillValue NaN;
Float32 actual_range 0.081, 48.08;
String bcodmo_name "conductivity";
String description "In situ specific conductivity";
String long_name "Sp Cond";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/CNDC/";
String units "milli Siemens per centimeter";
}
Salinity {
Float32 _FillValue NaN;
Float32 actual_range 0.04, 31.23;
String bcodmo_name "sal";
Float64 colorBarMaximum 37.0;
Float64 colorBarMinimum 32.0;
String description "In situ salinity";
String long_name "Sea Water Practical Salinity";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
String units "parts per thousand";
}
DOsat {
Float32 _FillValue NaN;
Float32 actual_range 0.2, 165.2;
String bcodmo_name "O2sat";
String description "In situ dissolved oxygen saturation";
String long_name "DOsat";
String units "percent";
}
DOconc {
Float32 _FillValue NaN;
Float32 actual_range 0.02, 16.17;
String bcodmo_name "dissolved Oxygen";
String description "In situ dissolved oxygen concentration";
String long_name "DOconc";
String units "milligrams per liter";
}
pH {
Float32 _FillValue NaN;
Float32 actual_range 5.83, 9.23;
String bcodmo_name "pH";
Float64 colorBarMaximum 9.0;
Float64 colorBarMinimum 7.0;
String description "In situ pH.";
String long_name "Sea Water Ph Reported On Total Scale";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PHXXZZXX/";
String units "unitless";
}
Turbidity {
Float32 _FillValue NaN;
Float32 actual_range -1.0, 1071.2;
String bcodmo_name "turbidity";
String description "In situ turbidity";
String long_name "Turbidity";
String units "NTU";
}
Fluorescence {
Float32 _FillValue NaN;
Float32 actual_range -0.5, 36.6;
String bcodmo_name "fluorescence";
String description "In situ chlorophyll fluorescence";
String long_name "Fluorescence";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLPM01/";
String units "relative fluorescence units";
}
Chlorophyll {
Float32 _FillValue NaN;
Float32 actual_range -1.9, 128.3;
String bcodmo_name "chlorophyll a";
Float64 colorBarMaximum 30.0;
Float64 colorBarMinimum 0.03;
String colorBarScale "Log";
String description "In situ chlorophyll concentration from fluorescence";
String long_name "Concentration Of Chlorophyll In Sea Water";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLHPP1/";
String units "micrograms per liter";
}
PARdepth {
Float32 _FillValue NaN;
Float32 actual_range -0.06, 7.657;
String bcodmo_name "depth";
String description "Depth where PAR measurements were taken";
String long_name "PARdepth";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
String units "meters (m)";
}
PAR1 {
Float32 _FillValue NaN;
Float32 actual_range -0.8, 2643.0;
String bcodmo_name "PAR";
String description "Photosynthetically active radiation";
String long_name "PAR1";
String units "Einsteins/m2/s";
}
PAR2 {
Float32 _FillValue NaN;
Float32 actual_range -0.1, 2010.0;
String bcodmo_name "PAR";
String description "Photosynthetically active radiation";
String long_name "PAR2";
String units "Einsteins/m2/s";
}
BarPress {
Int16 _FillValue 32767;
Int16 actual_range 753, 780;
String bcodmo_name "press_bar";
String description "Surface barometric pressure";
String long_name "Bar Press";
String units "millimeters of mercury";
}
ODO {
String bcodmo_name "unknown";
String description "Whether optical DO sensor used (Y or N)";
String long_name "ODO";
String units "unitless";
}
DOsat_calc {
String bcodmo_name "unknown";
String description "Whether DO saturation value calculated in spreadsheet (Y or N)";
String long_name "DOsat Calc";
String units "unitless";
}
DOconc_calc {
String bcodmo_name "unknown";
String description "Whether DO concentration value calculated in spreadsheet(Y or N)";
String long_name "DOconc Calc";
String units "unitless";
}
Notes {
String bcodmo_name "unknown";
String description "notes";
String long_name "Notes";
String units "unitless";
}
ISO_DateTime {
String bcodmo_name "DateTime";
String description "Date and time combined into ISO8601 format";
String long_name "ISO Date Time";
String source_name "ISO_DateTime";
String time_precision "1970-01-01T00:00:00Z";
String units "unitless";
}
Station_Description {
String bcodmo_name "station";
String description "The physical location of the sampling station such as at or near a particular river marker; buoy; road or bridge. Lists other names that may also be used to refer to this station.";
String long_name "Station Description";
String units "unitless";
}
km0 {
Float64 _FillValue NaN;
Float64 actual_range 0.0, 72.92813623908513;
String bcodmo_name "length";
String description "The distance (in kilometers) of the sampling station from station 0.";
String long_name "KM0";
String units "kilometers (km)";
}
latitude {
String _CoordinateAxisType "Lat";
Float64 _FillValue NaN;
Float64 actual_range 34.94888, 35.2106;
String axis "Y";
String bcodmo_name "latitude";
Float64 colorBarMaximum 90.0;
Float64 colorBarMinimum -90.0;
String description "North latitude of station in decimal degrees";
String ioos_category "Location";
String long_name "Latitude";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
String standard_name "latitude";
String units "degrees_north";
}
longitude {
String _CoordinateAxisType "Lon";
Float64 _FillValue NaN;
Float64 actual_range -77.1222, -76.52602;
String axis "X";
String bcodmo_name "longitude";
Float64 colorBarMaximum 180.0;
Float64 colorBarMinimum -180.0;
String description "West longitude of station in decimal degrees";
String ioos_category "Location";
String long_name "Longitude";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
String standard_name "longitude";
String units "degrees_east";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
String acquisition_description
"Bi-weekly water sampling and in situ measurements were performed at fixed
sampling stations.\\u00a0 In situ measurements were\\u00a0performed throughout
the water column in 0.5 meter depth increments.\\u00a0 Parameters measured
include: temperature, salinity, specific conductivity, dissolved oxygen (DO),
pH, chlorophyll fluorescence, photosynthetically active radiation (PAR),
turbidity, and barometric pressure.
Methods
Water sampling was conducted bi-weekly. When collection was split over two
days, a single date was used based on the upstream or majority stations.
Stations were selected to cover the entire length of the Neuse River Estuary
from Streets Ferry Bridge (Station 0) to the mouth of the estuary where it
flows into Pamlico Sound.\\u00a0 When possible, efforts were made to select
locations with key stationary features (channel markers, buoys and land
markers) to allow easy station identification in the field.
Surface water samples were collected by submerging 10 liter high-density
polyethylene containers just below the water surface or by filling the
containers with surface water collected from bucket casts.\\u00a0 Bottom water
samples were collected with a horizontal plastic Van Dorn sampler. Starting
December 2007, all samples collected with diaphragm pump and a weighted,
marked hose. All containers were kept in dark coolers at ambient temperature
during transport to the laboratory.\\u00a0 All filtration was done within a few
hours of collection and when conditions permitted, on board the research
vessel.
Prior to the 09/13/2000 sampling date, in situ measurements were performed at
discrete depths using a Hydrolab Data Sonde 3 equipped with a multiprobe and
SVR3 display logger.\\u00a0 Beginning on the 09/13/2000 sampling date, in situ
measurements were performed at discrete depths on the sunlit side of the
research vessel using a Yellow Springs Instruments (YSI Incoporated, Ohio)
multiparameter sonde (Model 6600 or 6600 EDS-S Extended Deployment System)
equipped with a YSI conductivity/temperature probe (Model 6560), a YSI
chlorophyll probe (Model 6025), a YSI pH probe (Model 6561 or 6566), a YSI
pulsed dissolved oxygen probe (Model 6562), a self cleaning YSI turbidity
probe (Model 6026 or 6136), and beginning on the 07/30/2003 sampling date, a
flat Li-Cor sensor (UWQ-PAR 6067).\\u00a0 The YSI sonde was coupled to a either
a YSI 610 DM datalogger or a YSI 650 MDS Multi-parameter Display System
datalogger.\\u00a0 In situ measurements were performed at the surface
(approximately 0.2 meters) and at the bottom of the water column
(approximately 0.5 meters from the sediment layer).\\u00a0 These data are
included in the worksheet titled \\\"NRE Dataset.\\\"\\u00a0 In situ measurements
were also performed throughout the water column in 0.5 meter depth
increments.\\u00a0 These data are included in the worksheet titled \\\"NRE YSI
Profiles.\\\"\\u00a0 The data were stored on the datalogger and downloaded to
Ecowin software upon return to the laboratory.
Distance (in river kilometers) was calculated using ESRI ArcGIS
software.\\u00a0 Distances were calculated using projected station locations
(North Carolina State Plane 1983 meters projection).\\u00a0 Distances from
station 0 through 30 (upper river stations) were measured along the main
channel of the river. Distances from stations 30 to 180 were measured as
straight lines between stations";
String awards_0_award_nid "762165";
String awards_0_award_number "OCE-0825466";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0825466";
String awards_0_funder_name "NSF Division of Ocean Sciences";
String awards_0_funding_acronym "NSF OCE";
String awards_0_funding_source_nid "355";
String awards_0_program_manager "David L. Garrison";
String awards_0_program_manager_nid "50534";
String cdm_data_type "Other";
String comment
"YSI data from the Neuse River.
PI: Hans Paerl
Version: 2019-05-13";
String Conventions "COARDS, CF-1.6, ACDD-1.3";
String creator_email "info@bco-dmo.org";
String creator_name "BCO-DMO";
String creator_type "institution";
String creator_url "https://www.bco-dmo.org/";
String data_source "extract_data_as_tsv version 2.3 19 Dec 2019";
String date_created "2019-05-13T19:24:04Z";
String date_modified "2019-05-15T16:30:34Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.767641.1";
Float64 Easternmost_Easting -76.52602;
Float64 geospatial_lat_max 35.2106;
Float64 geospatial_lat_min 34.94888;
String geospatial_lat_units "degrees_north";
Float64 geospatial_lon_max -76.52602;
Float64 geospatial_lon_min -77.1222;
String geospatial_lon_units "degrees_east";
Float64 geospatial_vertical_max 7.817;
Float64 geospatial_vertical_min 0.1;
String geospatial_vertical_positive "down";
String geospatial_vertical_units "m";
String history
"2024-11-14T17:57:02Z (local files)
2024-11-14T17:57:02Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_767641.das";
String infoUrl "https://www.bco-dmo.org/dataset/767641";
String institution "BCO-DMO";
String instruments_0_acronym "YSI Sonde 6-Series";
String instruments_0_dataset_instrument_description "Beginning on the 09/13/2000 sampling date, in situ measurements were performed at discrete depths on the sunlit side of the research vessel using a Yellow Springs Instruments (YSI Incoporated, Ohio) multiparameter sonde (Model 6600 or 6600 EDS-S Extended Deployment System) equipped with a YSI conductivity/temperature probe (Model 6560), a YSI chlorophyll probe (Model 6025), a YSI pH probe (Model 6561 or 6566), a YSI pulsed dissolved oxygen probe (Model 6562), a self cleaning YSI turbidity probe (Model 6026 or 6136), and beginning on the 07/30/2003 sampling date, a flat Li-Cor sensor (UWQ-PAR 6067).";
String instruments_0_dataset_instrument_nid "767648";
String instruments_0_description "YSI 6-Series water quality sondes and sensors are instruments for environmental monitoring and long-term deployments. YSI datasondes accept multiple water quality sensors (i.e., they are multiparameter sondes). Sondes can measure temperature, conductivity, dissolved oxygen, depth, turbidity, and other water quality parameters. The 6-Series includes several models. More from YSI.";
String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0737/";
String instruments_0_instrument_name "YSI Sonde 6-Series";
String instruments_0_instrument_nid "663";
String instruments_0_supplied_name "Yellow Springs Instruments (YSI Incoporated, Ohio) multiparameter sonde (Model 6600 or 6600 EDS-S Extended Deployment System)";
String keywords "bar, BarPress, bco, bco-dmo, biological, calc, chemical, chemistry, chlorophyll, concentration, concentration_of_chlorophyll_in_sea_water, cond, data, dataset, date, density, depth, description, dmo, doconc, DOconc_calc, dosat, DOsat_calc, earth, Earth Science > Oceans > Ocean Chemistry > Chlorophyll, Earth Science > Oceans > Ocean Chemistry > pH, Earth Science > Oceans > Salinity/Density > Salinity, erddap, fluorescence, iso, km0, latitude, longitude, management, notes, ocean, oceanography, oceans, odo, office, par1, par2, pardepth, practical, preliminary, press, reported, salinity, scale, science, sea, sea_water_ph_reported_on_total_scale, sea_water_practical_salinity, seawater, SpCond, station, Station_Description, Temp, temperature, time, time2, total, turbidity, water, zlevel1, zlevel2";
String keywords_vocabulary "GCMD Science Keywords";
String license "https://www.bco-dmo.org/dataset/767641/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/767641";
Float64 Northernmost_Northing 35.2106;
String param_mapping "{'767641': {'Lat': 'flag - latitude', 'Depth': 'flag - depth', 'Lon': 'flag - longitude'}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/767641/parameters";
String people_0_affiliation "University of North Carolina at Chapel Hill";
String people_0_affiliation_acronym "UNC-Chapel Hill";
String people_0_person_name "Hans Paerl";
String people_0_person_nid "734605";
String people_0_role "Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "Woods Hole Oceanographic Institution";
String people_1_affiliation_acronym "WHOI BCO-DMO";
String people_1_person_name "Mathew Biddle";
String people_1_person_nid "708682";
String people_1_role "BCO-DMO Data Manager";
String people_1_role_type "related";
String project "climate_phyto_estuaries";
String projects_0_acronym "climate_phyto_estuaries";
String projects_0_description
"NSF Award Abstract:
Climatic perturbations by drought-flood cycles, tropical storms, and hurricanes are increasingly important in Mid-Atlantic estuaries, leading to ecosystem-scale responses of the plankton system with significant trophic implications. Recent observations support an emerging paradigm that climate dominates nutrient enrichment in these ecosystems, explaining seasonal and interannual variability of phytoplankton floral composition, biomass (chl-a), and primary production (PP). This project will evaluate this paradigm in the two largest estuaries in the United States, Chesapeake Bay (CB) and Albemarle-Pamlico Sound-Neuse River Estuary (APS-NRE) by quantifying responses to climatic perturbations. This project will: (1) resolve long-term trends of plankton biomass/production from high variability driven by climatic forcing, such as drought-flood cycles that generate significant departures from the norm; (2) quantify the role of episodic wind and precipitation events, such as those associated with frontal passages, tropical storms, and hurricanes, that evoke consequential spikes of biomass/production outside the resolution of traditional methods. The field program will focus on event-scale forcing of phytoplankton dynamics by collecting shipboard, aircraft remote sensing, and satellite (SeaWiFS, MODIS-A) data, analyzing extensive monitoring data for CB and APS-NRE to develop context, and quantifying effects of climatic perturbations on phytoplankton dynamics as departures from long-term averages. The rapid-response sampling will be paired with numerical simulations using coupled hydrodynamic biogeochemical models based on the Regional Ocean Modeling System (ROMS). This combination of observations and modeling will be used to explore mechanistic links and test empirical relationships obtained from field data.
Intellectual Merit. Drought-flood cycles, tropical storms, and hurricanes are occurring at increasing severity and frequency, exerting significant pressures on land margin ecosystems. Research and monitoring in these ecosystems has focused singularly on eutrophication for nearly five decades. Recognition of climatic perturbations as the underlying cause of phytoplankton variability represents a significant departure from this singular focus. This project will combine observations and modeling to significantly extend our knowledge of how climate regulates phytoplankton dynamics in estuaries. Progress in calibrating and validating hydrodynamic biogeochemical models with data collected in CB and APS-NRE by this project will lead to predictive capabilities thus far unattained, allowing us to evaluate the paradigm that climatic perturbations regulate phytoplankton dynamics in estuaries.
Broader Impacts: Addressing the effects of climatic perturbations on phytoplankton dynamics in estuaries with a combination of data collection, analysis, and mechanistic modeling has societal benefits for scientists and resource managers. Applications in addition to ?basic? science include the consideration of climatic forcing in designing effective nutrient management strategies. Specific impacts include: (1) quantifying the effects of climatic perturbations on planktonic processes for important estuarine-coastal ecosystems; (2) extending empirically-based water quality criteria forward by enabling predictions of floral composition, chl-a, and PP in changing climate conditions; (3) combining observations and mechanistic models to support scenario analysis, allowing us to distinguish long-term trends from variability imposed by climate. This project will offer a graduate course in physical transport processes and plankton productivity that will benefit from this research, support two Ph.D. students, and train undergraduates in NSF REU and minority outreach programs at HPL-UMCES and IMS-UNC. The main products will be peer-reviewed publications and presentations at scientific meetings. The three PIs maintain active web sites that will be used to distribute results and data.
NOTE:
Dr. Harding was the original Lead PI. Dr. Michael R. Roman was named as substitute PI when Dr. Harding served as a Program Director in the NSF Biological Oceanography Program for two years, and through his move to UCLA thereafter. Dr. Harding is responsible for the data holdings on this project and for coordinating their submittal to BCO-DMO.";
String projects_0_end_date "2013-09";
String projects_0_geolocation "The two largest estuaries in the United States, Chesapeake Bay (CB) and Albemarle-Pamlico Sound- Neuse River Estuary (APS-NRE).";
String projects_0_name "Collaborative Research: Regulation of Phytoplankton Dynamics in Mid-Atlantic Estuaries Subject to Climatic Perturbations";
String projects_0_project_nid "491333";
String projects_0_project_website "http://paerllab.web.unc.edu/projects/modmon/";
String projects_0_start_date "2008-10";
String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
String publisher_type "institution";
String sourceUrl "(local files)";
Float64 Southernmost_Northing 34.94888;
String standard_name_vocabulary "CF Standard Name Table v55";
String subsetVariables "DOsat_calc,DOconc_calc";
String summary "The Neuse River Estuary Water Quality Dataset is a compilation of the biological, chemical and physical water quality data that was collected along the length of the Neuse River Estuary, NC from March 14, 1985 to February 15, 1989 and from January 24, 1994 to the present. The primary purpose of this dataset was to provide long-term environmental information to supplement experimental, process-based research, including the Atlantic Coast Environmental Indicators Consortium (ACE-INC) project as well as other laboratory studies.";
String title "[Neuse River Estuary YSI Profile] - YSI data from the Neuse River from 2008-2013 (Collaborative Research: Regulation of Phytoplankton Dynamics in Mid-Atlantic Estuaries Subject to Climatic Perturbations)";
String version "1";
Float64 Westernmost_Easting -77.1222;
String xml_source "osprey2erddap.update_xml() v1.3";
}
}
Data Access Protocol (DAP) and its
selection constraints.
The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.
Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names,
followed by a collection of
constraints (e.g., variable<value),
each preceded by '&' (which is interpreted as "AND").
For details, see the tabledap Documentation.