Contributors | Affiliation | Role |
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Tobin, Elizabeth D. | University of Alaska Fairbanks (UAF-Juneau) | Principal Investigator |
Ake, Hannah | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Biddle, Mathew | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Summary CTD data collected approximately weekly from two phytoplankton monitoring sites in Juneau, AK from 2015-2016.
Dock-based CTD casts were completed at approximately weekly intervals at two phytoplankton sampling stations, Auke Bay and Amalga Harbor, in Juneau, AK using a SBE-25 Sealogger CTD equipped with a SBE-3 temperature sensor, SBE-4C conductivity sensor, SBE-29 external pressure sensor, and a WETLabs Fluorometer. The CTD was deployed down to ~1 meter above the seafloor. Local date and time were recorded at the start of each sampling event.
The CTD instrument package was last serviced and calibrated by Sea-Bird Electronics, Inc. in June 2015.
CTD casts were uploaded as .hex files and converted to .cnv files using the Seasoft V2 software. The .cnv files were processed in batch (R programming) to calculate summary water column parameters: cast depth (m), sea surface temperature (degrees celsius), surface salinity (psu), bottom salinity (psu), surface density (kg/m3), bottom density (kg/m3) and maximum fluorescence (mg/m3). Sea Surface temperature, surface salinity and surface density were averaged over 0.5 – 2 meters of the water column. Bottom salinity and density are data values recorded at the maximum cast depth. Maximum fluorescence is the peak of the fluorescence signal.
All summary data was referenced with water column profiles plotting using the SeaSoft V2 software.
BCO-DMO Data Processing Notes:
-Reformatted column names to comply with BCO-DMO standards
-Removed spaces from data values and replaced with underscores
-Filled in blank cells with "nd"
-2017-07-25: Updated with data from 2016.
File |
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CTD_data.csv (Comma Separated Values (.csv), 18.14 KB) MD5:3b1d98dd9784b17643b87384790952d5 Primary data file for dataset ID 660308 |
Parameter | Description | Units |
sampling_event | Sampling event ID | unitless |
date | Date sample was taken; YYYYmmdd | unitless |
time_zone | Time zone where sample was taken | unitless |
time_local | Local time when sampling occurred; HH:MM | unitless |
station | Station where sample was taken | unitless |
lon | Longitude | decimal degrees |
lat | Latitude | decimal degrees |
instrument | Instrument used to collect sample | unitless |
investigator | Investigator responsible for collecting sample | unitless |
cast_depth | Bottom depth of cast | meters |
surface_temp | Sea surface temperature | celsius |
s_salinity | Surface salinity | practical salinity units (PSU) |
b_salinity | Bottom salinity | practical salinity units (PSU) |
s_density | Surface density | kilogram per meter cubed (kg/m3) |
b_density | Botton density | kilogram per meter cubed (kg/m3) |
max_fluor | Maximum fluorescence | milligram per meter cubed (mg/m3) |
data_quality | Codes providing information about missing or flagged data | unitless |
ISO_DateTime_Local | DateTime local; YYYY-mm-dd HH:MM | unitless |
year | Four digit year sample was taken; YYYY | unitless |
Dataset-specific Instrument Name | SBE-25 Sealogger CTD |
Generic Instrument Name | CTD - profiler |
Dataset-specific Description | Dock based CTD casts were used in this survey |
Generic Instrument Description | The Conductivity, Temperature, Depth (CTD) unit is an integrated instrument package designed to measure the conductivity, temperature, and pressure (depth) of the water column. The instrument is lowered via cable through the water column. It permits scientists to observe the physical properties in real-time via a conducting cable, which is typically connected to a CTD to a deck unit and computer on a ship. The CTD is often configured with additional optional sensors including fluorometers, transmissometers and/or radiometers. It is often combined with a Rosette of water sampling bottles (e.g. Niskin, GO-FLO) for collecting discrete water samples during the cast.
This term applies to profiling CTDs. For fixed CTDs, see https://www.bco-dmo.org/instrument/869934. |
Dataset-specific Instrument Name | WETLabs fluorometer |
Generic Instrument Name | CTD-fluorometer |
Dataset-specific Description | Equipped on CTD |
Generic Instrument Description | A CTD-fluorometer is an instrument package designed to measure hydrographic information (pressure, temperature and conductivity) and chlorophyll fluorescence. |
Dataset-specific Instrument Name | SBE-29 external pressure sensor |
Generic Instrument Name | Pressure Sensor |
Dataset-specific Description | Equipped on CTD |
Generic Instrument Description | A pressure sensor is a device used to measure absolute, differential, or gauge pressures. It is used only when detailed instrument documentation is not available. |
Dataset-specific Instrument Name | SBE-4C conductivity sensor |
Generic Instrument Name | Sea-Bird SBE-4 Conductivity Sensor |
Dataset-specific Description | Equipped on CTD |
Generic Instrument Description | The Sea-Bird SBE-4 conductivity sensor is a modular, self-contained instrument that measures conductivity from 0 to 7 Siemens/meter. The sensors (Version 2; S/N 2000 and higher) have electrically isolated power circuits and optically coupled outputs to eliminate any possibility of noise and corrosion caused by ground loops. The sensing element is a cylindrical, flow-through, borosilicate glass cell with three internal platinum electrodes. Because the outer electrodes are connected together, electric fields are confined inside the cell, making the measured resistance (and instrument calibration) independent of calibration bath size or proximity to protective cages or other objects. |
Dataset-specific Instrument Name | SBE-3 temperature sensor |
Generic Instrument Name | Water Temperature Sensor |
Dataset-specific Description | Equipped on CTD |
Generic Instrument Description | General term for an instrument that measures the temperature of the water with which it is in contact (thermometer). |
Website | |
Platform | shoreside Juneau_Alaska |
Start Date | 2015-03-10 |
End Date | 2016-12-15 |
Description | Phytoplankton and CTD sampling was performed here in 2015 and 2016 by E. Tobin. |
Description from NSF award abstract:
The project is supported under the NSF Science, Engineering and Education for Sustainability Fellows (SEES Fellows) program, with the goal of helping to enable discoveries needed to inform actions that lead to environmental, energy and societal sustainability while creating the necessary workforce to address these challenges.
This project focuses on the sustainability of shelfish harvesting in Alaska. In Alaska, paralytic shellfish poisoning caused by the marine alga Alexandrium is a severe and persistent problem that significantly impacts human health and the availability of shellfish resources. This project aims to enhance sustainability of commercial, recreational and subsistence shellfish harvest in Southeast Alaska by addressing the ecology of Alexandrium harmful algal blooms and their sociocultural impacts. Despite the recognized impacts of paralytic shellfish poisoning, little research has been done on the causative organism, Alexandrium, and the sociocultural impacts of toxic Alexandrium blooms in the Southeast Alaska region. This study is a three-pronged effort. First, the project bolsters understanding of the ecological mechanisms that promote Alexandrium blooms by mapping cyst seedbeds (i.e., bloom initiation sites), monitoring cyst emergence, and identifying environmental conditions under which blooms form. This information adds to the body of scientific knowledge about Alexandrium bloom dynamics in coastal, fjord systems, provide early-warning information about toxic bloom development and help focus future paralytic shellfish poisoning testing and harmful algal bloom monitoring efforts in Southeast Alaska. Second, the application of novel in situ sensors will overcome previous benthic emergence monitoring challenges and has the potential to improve harmful algal bloom forecasting capabilities. Third, human dimensions research will generate critical information about how social systems can reduce vulnerability to harmful algal blooms and how local/traditional knowledge can support scientific efforts by establishing strong community partnerships.
The SEES Fellow, Dr. Elizabeth Tobin, works with host mentor Dr. Ginny Eckert at the University of Alaska Fairbanks, and with partner mentor Dr. Thomas Leschine at the University of Washington.
Funding Source | Award |
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NSF Divsion of Integrative and Collaborative Education and Research (NSF ICER) |