http://lod.bco-dmo.org/id/dataset/866995
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2021-12-22
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Oceanographic data from 12 monthly cruises off the Israeli coast in the east Mediterranean conducted between Feb 2018 and Jan 2019 at a continental shelf station (~140m depth) and an open-deep water station.
2021-01-07
publication
2021-01-07
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2022-01-07
publication
https://doi.org/10.26008/1912/bco-dmo.866995.1
Eyal Rahav
Israel Oceanographic and Limnological Research
principalInvestigator
Daniel Sher
University of Haifa
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: Rahav, E., Sher, D. (2022) Oceanographic data from 12 monthly cruises off the Israeli coast in the east Mediterranean conducted between Feb 2018 and Jan 2019 at a continental shelf station (~140m depth) and an open-deep water station. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2021-01-07 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.866995.1 [access date]
Southeastern Mediterranean Monthly cruise Series Dataset Description: <p>The Levantine basin of the Eastern Mediterranean Sea (EMS) is one of the most oligotrophic regions of the world ocean, yet supports relatively diverse populations of organisms from microbes to fish. In this ecosystem, processes involving both seasonal bottom up control (nutrient limitation) and biotic interactions (such as coupling of primary productivity to heterotrophic growth and grazing) likely control community structure and function. The EMS, despite being an inland sea, has many of the characteristics of a major ocean gyre, while being highly accessible - only a few hours by ship from shore. Thus, the EMS is an accessible natural laboratory to study biotic and a-biotic processes affecting oligotrophic seas.</p> Methods and Sampling: <p><strong>Cruises and sample collection</strong></p>
<p>Water samples were collected as part of the SoMMoS project during twelve cruises, from February 2018 until January 2019. Each cruise took samples at two THEMO (Texas-Haifa Eastern Mediterranean Observatory) stations.</p>
<p>THEMO2, an open ocean station at a depth of ~1500 m (~50 Km from the coast, 32.820 N, 34.380 E), and THEMO1 which is positioned at the edge of the continental shelf at ~125m depth (~10 Km from the coast, 33.040 N, 34.950 E). THEMO2 was sampled from 12:00-22:00 (local time), while THEMO1 was sampled during the night, typically 00:00-02:00 (local time). Here, we will present information from data collected at the offshore THEMO2 station.</p>
<p>Start and end data of the cruises and sampling research vessel (no specific cruise IDs):</p>
<p>07/02/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 08/02/2018: R/V Bat-Galim<br />
05/03/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 06/03/2018: R/V Mediterranean Explorer<br />
09/04/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 10/04/2018: R/V Mediterranean Explorer<br />
14/05/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 15/05/2018: R/V Bat-Galim<br />
18/06/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 19/06/2018: R/V Mediterranean Explorer<br />
09/07/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 10/07/2018: R/V Mediterranean Explorer<br />
06/08/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 07/08/2018: R/V Bat-Galim<br />
05/09/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 06/09/2018: R/V Mediterranean Explorer<br />
08/10/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 09/10/2018: R/V Mediterranean Explorer<br />
05/11/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 06/11/2018: R/V Bat-Galim<br />
03/12/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 04/12/2018: R/V Mediterranean Explorer<br />
21/01/2019&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 22/01/2019: R/V Mediterranean Explorer</p>
<p>Samples were collected using a 12-bottle rosette with 8 L Niskin bottles. Samples were collected at 20-24 depths across the entire water column (11-12 bottles between the surface and 200 m, which we define here as the photic zone). Sampling depths were selected based on real-time data of Conductivity, Temperature, Depth (CTD) profiler (Seabird 19 Plus) from the down-cast before each sample collection in the up-cast, an oxygen optode (on some cruises) and a fluorescence meter (Turner designs, Cyclops-7). The continuous data was processed using the Sea-Bird data conversion software, and minimized using bin averaging. One bin of data lines was defined as a change of 1 decibar (db) between each bin. The first two meters of measurements were compiled together to account for sensors and CTD pump adjustment time and rosette depth while at sea surface.</p>
<p><strong>Nutrients</strong></p>
<p>Nutrient samples were collected in acid-washed 500 ml plastic containers and immediately filtered through 0.22 μm Nalgene rapid-flow filter units. The first two filtrates were discarded, and the final sub- samples collected in new 50 ml falcon tubes and stored in the dark at 4 ◦C in racks. The samples were transported to the analytical lab at the marine station at Sdot-Yam within 12–15 h of sampling and dissolved nutrients determined using a SEAL AA-3 autoanalyzer system (SEAL, 2011). To minimize crosscontamination in the laboratory, ammonium was analyzed first alone using an automated ophthalaldehyde (OPA) fluorescence method. Samples were placed in the sample trays and only opened immediately before the sample probe took the sample. The baseline water used for ammonium determination was freshly prepared Milli-Q (MQ) water. The next parameters to be determined were dissolved nitrate and silicate. The methods used were Cd reduction and diazo dye for nitrate &amp; nitrite (hereafter referred to as Nox), and molybdate blue in the presence of oxalic acid for Silicate. The baseline water used for these determinations was also MQ water. For the August cruise nitrite was also determined by carrying out a run also using coloured diazo dye but without Cd reduction. Finally, a 3rd run was carried out using an ultra-low level phosphate (DIP) method involving using a 100 cm long flow cell (LWCC) and molybdate blue determination derived from Murphy and Riley (1962). The blank used for phosphate determination was surface seawater, whose DIP value was determined in a previous experiment in which we determined a refractive index correction by removing the ascorbic acid reagent. It was not possible to use MQ as the baseline, as has been used elsewhere because the MQ water in our lab (derived from desalinated water) contains ~20 nM DIP.</p>
<p>40 ml subsamples for Total Dissolved Phosphorus (TDP) were taken from the filtered samples on-board, acidified with 0.2 ml of 2M sulfuric acid and frozen immediately in racks. The samples were transported to the laboratory at the Sdot Yam marine station and stored at −4 ◦C until later analysis. After thawing the samples, 4 ml of acidified potassium persulphate was added to each sample in a glass autoclavable bottle. The closed bottles were autoclaved for at least 30 min and allowed to cool overnight. The samples were then transferred to 50 ml Falcon tubes and analyzed using the same procedure as described for DIP. In order to determine the reagent blank, a similar procedure was used substituting MQ (and 50 nM and 100 nM phosphate) for the sample, adding 4 ml of acidified potassium persulphate into glass autoclave bottles. The reagent blank was treated the same way as the seawater samples.</p>
<p><strong>Bacterial and primary productivity</strong></p>
<p>Heterotrophic prokaryotic productivity (hereafter referred to as bacterial productivity, BP) was estimated using the <sup>3</sup>H-leucine incorporation method (Simon and Azam, 1989; Smith and Azam, 1992). Triplicate 1.7 ml of ocean water were taken from each sampled depth and incubated with a 7:1 mixture of ‘cold’ leucine and ‘hot’ <sup>3</sup>H-leucine, respectively (final concentration 100 nmol leucine L<sup>-1</sup>) for 4 h at room temperature in the dark immediately after sampling. Preliminary experiments show that this was the saturating level of leucine in the offshore water of the SE Mediterranean Sea. After incubation, incorporation was terminated by adding 100 μl trichloroacetic acid (TCA). As a negative control for non-specific binding, another set of triplicates were sampled from a surface layer and treated with TCA immediately after the addition of the radioactive tracer. At the end of each cruise, the samples were processes using the micro-centrifugation protocol and 1ml scintillation cocktail (ULTIMA-GOLD) was added to all samples before counted using TRI-CARB 2100 TR (PACKARD) scintillation counter. A conversion factor of 3 kg C per mole of leucine incorporated and an isotopic dilution of 2.0 were used to calculate the C incorporated (Simon and Azam, 1989).</p>
<p>Net daily photosynthetic carbon fixation rates were estimated using the <sup>14</sup>C incorporation method (Nielsen, 1952), with several modifications (Hazan et al., 2018). Triplicate 50 ml samples were taken from each depth within the photic zone and from one aphotic depth using sterile vials and kept at surface light and temperature conditions. The ‘dark’ sample served as blank and was kept under the same temperature as the ‘light’ samples. Radioactive spiking was done at ~08:00 AM the day following of the cruise in order to start a 24h incubation for all samples (including those collected at THEMO-1 station, not shown) at the same time. Early work by Letelier and colleagues (1996) at station HOT showed that prolonged on-deck incubations, similarly to the protocol used in this study, may result in underestimated PP rates as it cannot precisely mimic the temperature and illumination levels in-situ. Our preliminary tests concur with this conclusion and found that ashore incubations underestimate PP rates by up to ~20% compared to incubations onto a mooring rope tied to the ship (Figure S2). Samples were spiked with 50μl (5 μCi) of NaH<sup>14</sup>CO<sub>3</sub> tracer and were incubated for 24 h under 3 light regimes: surface illumination (samples from the upper mixing depths), 50% illumination (samples from below the mixing depth to the DCM) and ~1% illumination (samples from the DCM and below). Shading was performed using neutral density nets, thus changing light intensity but not spectral properties. Water samples were then filtered through GF/F filters (0.7 μm nominal pore size, 25 mm diameter) using low vacuum pressure (&lt; 50 mmHg) and rinsed 3 times with filtered sea water. Filters from each sample were then put in scintillation vials where 50 μl of 32%HCl solution was immediately added in order to remove excess <sup>14</sup>C-bicarbonate and kept overnight for incubation. After incubation 5 mL scintillation cocktail (ULTIMA-GOLD) was added to the samples and counted using TRI-CARB 2100 TR (PACKARD) scintillation counter. Three random aliquots were counted immediately after the addition of the radiotracer (without incubation) with ethanolamine to serve as added activity measurements.</p>
<p><strong>Picophytoplankton abundance using flow-cytometry</strong></p>
<p>Triplicates water samples (1.5 ml) were collected from each sampling depth, put in cryo-vials (Nunc), and supplemented with 7.5 µl 25% glutaraldehyde (Sigma). Vials were incubated in the dark for 10 min, flash-frozen in liquid nitrogen, and stored in -80 <sup>o</sup>C freezer. Before analysis, samples were thawed in the dark at room temperature. Each sample was run twice on a BD Canto II flow-cytometer with 2 μm diameter fluorescent beads (Polysciences, Warminster, PA, USA) as a size and fluorescence standard. In the first run three types of phytoplankton cells were identified based on their natural auto-fluorescence: <em>Prochlorococcus</em>, <em>Synechococcus</em> and picoeukaryotes. Cells were differentiated based on cell chlorophyll (Ex482nm/Em676nm, PerCP channel) and phycoerythrin fluorescence (Ex564nm/Em574nm), and by the size of cell (forward scatter). Before the second FCM, run samples were stained with SYBR Green I (Molecular Probes/ ThermoFisher) to enable counting followed by detection at Ex494nm/Em520nm (FITC channel). This provided counts of the total bacterial population (phytoplankton + heterotrophic bacteria and archaea) as well as a distinction between cells with High or Low DNA content (not shown). Data were processed using FlowJo software. Flow rates were determined several times during each running session by weighing tubes with double-distilled water, and counts of the standard beads were used to verify a consistent flow rate.</p>
<p><strong>Algal pigment markers</strong></p>
<p>Eight litters of seawater were collected from all photic sample depths and one from a dark depth (depth varies between cruises). Water was filtered onto GF/F filters (0.7 μm nominal pore size, 47mm diameter, Waters) using a peristaltic pump until either all 8 L were filtered or the filter became blocked, in which case the volume filtered was recorded. Filters were placed in cryo-vials and flash frozen in liquid nitrogen until they could be stored in a -80 <sup>o</sup>C freezer. Pigments were extracted in 1ml 100% methanol for 3 h at room temperature and clarified using syringe filters (Acrodisc CR, 13 mm, 0.2 μm PTFE membranes, Pall Life Sciences). Total chlorophyll was measured spectrophotometrically using a NanoDrop 2000c (Thermo Sciences) at 632, 652, 665 and 695 nm, and the concentration of chlorophyll a was calculated (Ritchie 2008). Ultra high-pressure Liquid Chromatography (UPLC) was performed on an ACQUITY UPLC system (Waters) equipped with a photodiode array detector. A C8 column (1.7 μm particle size, 2.1 mm internal diameter, 50 mm column length, ACQUITY UPLC BEH, 186002877) was used. The chromatography method was adapted for UPLC from the LOV method (Hooker et al., 2005). Samples were preheated to 30 °C and column to 50 °C before each run. Running buffers were a 70:30 mixture of methanol and 0.5M ammonium acetate (buffer A) and 100% methanol (buffer B). The program consisted of an isocratic run using a 80:20 mixture of buffers A:B for 2min, followed by a linear gradient to 50:50 for 7 minutes and an increase to 100% solvent B. The flow rate was 0.5ml/min. Pigment standards from DHI (Denmark) were used to identify the UPLC peaks (chlorophyll a, divinyl-chlorophyll a, chlorophyll b,&nbsp; zeaxanthin,&nbsp; diatoxanthin, fucoxanthin, peridinin, 19’- butanoyloxyfucoxanthin and 19’- hexanoyloxyfucoxanthin). Due to potential degradation of the pigment standards, we present the total chlorophyll measured spectrophotometrically and the pigment ratios within each UPLC run.</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1635070 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1635070
completed
Eyal Rahav
Israel Oceanographic and Limnological Research
+972(0)524712010
Tel- Shikmona, P.O.B. 9753
Haifa
3109701
Israel
eyalrahav@gmail.com
pointOfContact
Daniel Sher
University of Haifa
+972(4)8249349
199 Aba Koushy Ave.
Mount Carmel
Haifa
3498838
Israel
dsher@univ.haifa.ac.il
pointOfContact
asNeeded
Dataset Version: 1
Unknown
Cruise
Station
Type
YYYY_MM_DD
hhmm
Longitude
Latitude
Bot_Depth
Depth
time_ISO8601
Cruise_nr
Cast
ID
Altimeter
Density
Fluorescence
Oxygen_Sat
Oxygen
Pressure
Salinity
Temperature
Par
Turbidity
PicoEukaryotes
Prochloroccocus
Synechococcus
PicoEuk_SD
Pro_SD
Syn_SD
HNA
LNA
HNA_SD
LNA_SD
Cell_Count
Cell_Count_SD
Primary_production
Primary_production_SD
Bacterial_production
Bacterial_production_SD
Tchla
Total_Chlorophylla
DVChlTa_TotalChla
Total_19Hex_19But
Per_Total
Total_19But
Fuco_Total
Total_19Hex
Diato_Total
Zea_Total
chlB_Total
Phosphate
TOxN
Si
Ammonia
NO2
N_P_ratio
TDP
DOP
CTD profiler Seabird 19 Plus
BD Canto II flow-cytometer
JASCO fluorometer
TRI-CARB 2100 TR (PACKARD) scintillation counter
100 cm long flow cell (LWCC)
NanoDrop 2000c (Thermo Sciences)
ACQUITY UPLC system (Waters)
theme
None, User defined
Cruise identfier
station
sample type
date
sample time
longitude
latitude
depth_bottom
depth
time of day
cast
sample identification
height
density
fluorescence
dissolved Oxygen
water pressure
salinity from CTD
water temperature at measurement depth
PAR
turbidity
pico_euks
prochlorococcus abundance
synechococcus abundance
standard deviation
amino acid concentration
cell_concentration
primary production
Bacterial production in the water column
chlorophyll a
pigment concentration
phosphate
Nitrogen
silica
Ammonia
Nitrite
ratio
Phosphorus
Dissolved Organic Phosphorus
featureType
BCO-DMO Standard Parameters
CTD Sea-Bird SBE SEACAT 19plus
Flow Cytometer
Fluorometer
Liquid Scintillation Counter
Liquid Waveguide Capillary Cells
Spectrophotometer
Ultra-high-performance liquid chromatography
instrument
BCO-DMO Standard Instruments
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
Microbial ecosystems in silico, in the lab and in the field: understanding interactions between abundant marine bacterial taxa
https://osprey.bco-dmo.org/project/650767
Microbial ecosystems in silico, in the lab and in the field: understanding interactions between abundant marine bacterial taxa
<p>Every drop of seawater contains around one million microorganisms (bacteria, small algae and other organisms such as ciliates and diatoms). These marine microbes feed the entire marine ecosystem, modulate global cycles of carbon and other elements, and impact climate. With the advances in genome-sequencing technology, we can now identify the microbes and assess their genetic and metabolic capacities, yet we still cannot deduce from the genomes of these organisms how they will grow - and interact - in nature. The proposed project will tackle this challenge through a tightly integrated combination of mathematical modeling, laboratory experiments and field work in the Eastern Mediterranean, to identify genes and pathways dictating how environmentally-relevant microbes grow and interact in the sea. We will produce genome-scale mathematical models of the metabolism of <em>Prochlorococus</em>, the numerically-dominant photosynthetic bacteria in large swaths of the ocean, and of <em>Alteromonas</em>, abundant marine bacteria which make their living by consuming and respiring organic molecules produced by <em>Prochlorococcus</em> and other photosynthetic microbes. We will test these models using laboratory cultures of these organisms grown alone and together, and determine to what extent the models and laboratory cultures represent the growth and death of these organisms in the Eastern Mediterranean. This study will be useful for scientists of many disciplines, including not only marine biology, oceanography and ecology but also genetics, medicine and agriculture. Our results will shed light on the dynamics of some of the most common organisms in the world, responsible for the production of up to 20% of the oxygen we breathe. Our collaborative study will foster the development and training of the next generation of marine scientists, and will be used in outreach activities designed to share with high-school students and the general public the excitement of marine research and the need to responsibly utilize and sustain the oceans for the sake of future generations.</p>
<p>The proposed project will tackle the challenge of understanding microbial interactions from the underlying genetic data through a tightly integrated combination of genome scale modeling, laboratory experiments and field work in the Eastern Mediterranean. We aim to identify genomic traits dictating how environmentally-relevant primary producers and heterotrophic bacteria interact. Genome-scale (dynamic flux balance analysis, dFBA) models of <em>Prochlorococus</em> MED4 and of <em>Alteromonas</em> HOT1A3 will be produced and calibrated using high-throughput measurements of growth and physiological parameters in laboratory batch cultures, combined with detailed analysis of specific metabolites; The dFBA models will be combined <em>in-silico</em> and the results compared to laboratory co-cultures. Model-data discrepancies will provide opportunities to revisit the models, suggesting the mediation of alternative processes such as allelopathy or other types of chemical signaling. Finally, time-series data on the community composition and function during the summer/fall <em>Prochlorococcus</em> bloom in the hyper-oligotrophic Eastern Mediterranean, combined with field experiments (microcosms), will provide a test of hypotheses generated in the lab. This study will provide the first detailed "roadmap" linking genomic traits (genes and metabolic pathways) and rate measurements with species interactions in environmentally-relevant marine microbes. Genome-scale models will likely be embedded in a not-so-distant future in global-scale models of the Earth System, and the proposed study will provide a critical stepping-stone towards predicting how marine microbial systems will evolve in a changing world. The strong human impact on marine ecosystems, and the need for quantitative and predictive understanding of how they will respond to a changing environment, calls for interdisciplinary research and training for the next generation of scientists and decision makers. Models and data generated by our work will be integrated into a novel educational exploration-focused, web- and field-based educational module. This module will introduce key concepts in microbiology, environmental sciences and oceanography to intermediate- and high-school students.</p>
<p>(Note: acronym HADFBA = Heterotroph-Autotroph Dynamic Flux Balance Analysis)</p>
HADFBA
largerWorkCitation
project
eng; USA
oceans
34.38
34.95
32.82
33.04
2018-02-07
2019-01-22
Eastern Mediterranean Sea
0
BCO-DMO catalogue of parameters from Oceanographic data from 12 monthly cruises off the Israeli coast in the east Mediterranean conducted between Feb 2018 and Jan 2019 at a continental shelf station (~140m depth) and an open-deep water station.
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/867555.rdf
Name: Cruise
Units: unitless
Description: <p>THEMO: Texas-Haifa Eastern Mediterranean Observatory</p>
http://lod.bco-dmo.org/id/dataset-parameter/867556.rdf
Name: Station
Units: unitless
Description: <p>THEMO station 1 or 2</p>
http://lod.bco-dmo.org/id/dataset-parameter/867557.rdf
Name: Type
Units: unitless
Description: <p>Sampling type (Cast)</p>
http://lod.bco-dmo.org/id/dataset-parameter/867558.rdf
Name: YYYY_MM_DD
Units: unitless
Description: <p>Date of sampling in YYY_MM_DD format</p>
http://lod.bco-dmo.org/id/dataset-parameter/867559.rdf
Name: hhmm
Units: unitless
Description: <p>Time of sampling in hhmm format. The number is a timestamp unformatted. In excel it represents a time frame and other applications can interpret that (Like ODV). If the format of the column is changed to 'Time' it should show a hh:mm format.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867560.rdf
Name: Longitude
Units: decimal degrees
Description: <p>Longitude of sampling location, west is negative</p>
http://lod.bco-dmo.org/id/dataset-parameter/867561.rdf
Name: Latitude
Units: decimal degrees
Description: <p>Latitude of sampline location, south is negative</p>
http://lod.bco-dmo.org/id/dataset-parameter/867562.rdf
Name: Bot_Depth
Units: m
Description: <p>Maxium depth at sampling station</p>
http://lod.bco-dmo.org/id/dataset-parameter/867563.rdf
Name: Depth
Units: m
Description: <p>Depth of sampling in each stration</p>
http://lod.bco-dmo.org/id/dataset-parameter/867564.rdf
Name: time_ISO8601
Units: unitless
Description: <p>Time of sampling in iso format. Time zone is UTC+2.<br />
</p>
http://lod.bco-dmo.org/id/dataset-parameter/867565.rdf
Name: Cruise_nr
Units: unitless
Description: <p>Cruise number (1 to 12)</p>
http://lod.bco-dmo.org/id/dataset-parameter/867566.rdf
Name: Cast
Units: unitless
Description: <p>Cast number</p>
http://lod.bco-dmo.org/id/dataset-parameter/867567.rdf
Name: ID
Units: unitless
Description: <p>Sample specific ID</p>
http://lod.bco-dmo.org/id/dataset-parameter/867568.rdf
Name: Altimeter
Units: m
Description: <p>height</p>
http://lod.bco-dmo.org/id/dataset-parameter/867569.rdf
Name: Density
Units: kg/m^3
Description: <p>Water density as a function of temperature and pressure</p>
http://lod.bco-dmo.org/id/dataset-parameter/867570.rdf
Name: Fluorescence
Units: AU
Description: <p>Biological excitation, a proxy for chlorophyll content.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867571.rdf
Name: Oxygen_Sat
Units: %
Description: <p>Percentage of dissolved oxygen in the water</p>
http://lod.bco-dmo.org/id/dataset-parameter/867572.rdf
Name: Oxygen
Units: umol/L
Description: <p>Concentration of dissolved oxygen in the water</p>
http://lod.bco-dmo.org/id/dataset-parameter/867573.rdf
Name: Pressure
Units: db desibar
Description: <p>Physical pressure on the water mass</p>
http://lod.bco-dmo.org/id/dataset-parameter/867574.rdf
Name: Salinity
Units: psu Practical Salinity Unit
Description: <p>Concentration of dissolved salt in the water</p>
http://lod.bco-dmo.org/id/dataset-parameter/867575.rdf
Name: Temperature
Units: ℃ degrees celsius
Description: <p>Water temperature</p>
http://lod.bco-dmo.org/id/dataset-parameter/867576.rdf
Name: Par
Units: W/m2
Description: <p>Photosynthetically active radiation designates the spectral range of solar radiation from 400 to 700 nanometers.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867577.rdf
Name: Turbidity
Units: ftu Formazin Turbidity Units
Description: <p>An optical characteristic of water and is a measurement of the amount of light that is scattered by material in the water</p>
http://lod.bco-dmo.org/id/dataset-parameter/867578.rdf
Name: PicoEukaryotes
Units: Number of cells in a 1 ml of water cell/ml
Description: <p>Cell count of PicoEukaryotes in the water sample. Count was done using flow cytometry.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867579.rdf
Name: Prochloroccocus
Units: Number of cells in a 1 ml of water cell/ml
Description: <p>Cell count of Prochloroccocus in the water sample. Count was done using flow cytometry.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867580.rdf
Name: Synechococcus
Units: Number of cells in a 1 ml of water cell/ml
Description: <p>Cell count of Synechococcus in the water sample. Count was done using flow cytometry.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867581.rdf
Name: PicoEuk_SD
Units: Number of cells in a 1 ml of water cell/ml
Description: <p>The standard deviation between the triplicate samples analyzed.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867582.rdf
Name: Pro_SD
Units: Number of cells in a 1 ml of water cell/ml
Description: <p>The standard deviation between the triplicate samples analyzed.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867583.rdf
Name: Syn_SD
Units: Number of cells in a 1 ml of water cell/ml
Description: <p>The standard deviation between the triplicate samples analyzed.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867584.rdf
Name: HNA
Units: Number of cells in a 1 ml of water cell/ml
Description: <p>A distinctive count of cells with high nucleic amino acids (HNA) content. Count was done using flow cytometry.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867585.rdf
Name: LNA
Units: Number of cells in a 1 ml of water cell/ml
Description: <p>A distinctive count of cells with low nucleic amino acids (LNA) content. Count was done using flow cytometry.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867586.rdf
Name: HNA_SD
Units: Number of cells in a 1 ml of water cell/ml
Description: <p>The standard deviation between the triplicate samples analyzed.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867587.rdf
Name: LNA_SD
Units: Number of cells in a 1 ml of water cell/ml
Description: <p>The standard deviation between the triplicate samples analyzed.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867588.rdf
Name: Cell_Count
Units: Number of cells in a 1 ml of water cell/ml
Description: <p>Count of total cells in the water sample. Count was done using flow cytometry.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867589.rdf
Name: Cell_Count_SD
Units: Number of cells in a 1 ml of water cell/ml
Description: <p>The standard deviation between the triplicate samples analyzed.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867590.rdf
Name: Primary_production
Units: ug C/L/d
Description: <p>The assimilation rate of carbon by autotrophic biological processes in the water samples.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867591.rdf
Name: Primary_production_SD
Units: ug C/L/d
Description: <p>The standard deviation between the triplicate samples analyzed.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867592.rdf
Name: Bacterial_production
Units: ug C/L/d
Description: <p>The assimilation rate of carbon by heterotrophic biological processes in the water samples.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867593.rdf
Name: Bacterial_production_SD
Units: ug C/L/d
Description: <p>The standard deviation between the triplicate samples analyzed.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867594.rdf
Name: Tchla
Units: ug/L
Description: <p>The total concentration of the pigment chlorophyl-a. measurements was done using a NanoDrop.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867595.rdf
Name: Total_Chlorophylla
Units: Area under the peak of the signal derived from the questined pigment. A proxy of conncentration.
Description: <p>The area under peak signal of the pigment chlorophyl-a. measurements was done using UPLC.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867596.rdf
Name: DVChlTa_TotalChla
Units: Area under the peak of the signal derived from the questined pigment. A proxy of conncentration.
Description: <p>The area under peak signal of the pigment Divinyl chlorophyl-a relative to chlorophyl-a. measurements was done using UPLC.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867597.rdf
Name: Total_19Hex_19But
Units: Area under the peak of the signal derived from the questined pigment. A proxy of conncentration.
Description: <p>The area under peak signal of the pigments 19-butanoyloxyfucoxanthin and 19-hexanoyloxyfucoxanthin relative to chlorophyl-a. measurements was done using UPLC.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867598.rdf
Name: Per_Total
Units: Area under the peak of the signal derived from the questined pigment. A proxy of conncentration.
Description: <p>The area under peak signal of the pigment Peridinin relative to chlorophyl-a. measurements was done using UPLC.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867599.rdf
Name: Total_19But
Units: Area under the peak of the signal derived from the questined pigment. A proxy of conncentration.
Description: <p>The area under peak signal of the pigment 19-butanoyloxyfucoxanthin relative to chlorophyl-a. measurements was done using UPLC.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867600.rdf
Name: Fuco_Total
Units: Area under the peak of the signal derived from the questined pigment. A proxy of conncentration.
Description: <p>The area under peak signal of the pigment Fucoxanthin relative to chlorophyl-a. measurements was done using UPLC.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867601.rdf
Name: Total_19Hex
Units: Area under the peak of the signal derived from the questined pigment. A proxy of conncentration.
Description: <p>The area under peak signal of the pigment 19-hexanoyloxyfucoxanthin relative to chlorophyl-a. measurements was done using UPLC.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867602.rdf
Name: Diato_Total
Units: Area under the peak of the signal derived from the questined pigment. A proxy of conncentration.
Description: <p>The area under peak signal of the pigment Diatoxanthin relative to chlorophyl-a. measurements was done using UPLC.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867603.rdf
Name: Zea_Total
Units: Area under the peak of the signal derived from the questined pigment. A proxy of conncentration.
Description: <p>The area under peak signal of the pigment Zeaxanthin relative to chlorophyl-a. measurements was done using UPLC.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867604.rdf
Name: chlB_Total
Units: Area under the peak of the signal derived from the questined pigment. A proxy of conncentration.
Description: <p>The area under peak signal of the pigment chlorophyl-b relative to chlorophyl-a. measurements was done using UPLC.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867605.rdf
Name: Phosphate
Units: uM
Description: <p>Concentration of Phosphate in the water.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867606.rdf
Name: TOxN
Units: uM
Description: <p>Concentration of total Nitrogen in the water.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867607.rdf
Name: Si
Units: uM
Description: <p>Concentration of Silica in the water.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867608.rdf
Name: Ammonia
Units: uM
Description: <p>Concentration of Ammonia in the water.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867609.rdf
Name: NO2
Units: uM
Description: <p>Concentration of Nitrit in the water.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867610.rdf
Name: N_P_ratio
Units: AU
Description: <p>Ration of nitrogen to Phospate in the water.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867611.rdf
Name: TDP
Units: nM
Description: <p>Concentration of total dissolved Phosphorus in the water.</p>
http://lod.bco-dmo.org/id/dataset-parameter/867612.rdf
Name: DOP
Units: nM
Description: <p>Concentration of dissolved organic Phosphate in the water.</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
5940532
https://darchive.mblwhoilibrary.org/bitstream/1912/27901/1/dataset-866995_sommos-dataset__v1.tsv
download
https://doi.org/10.26008/1912/bco-dmo.866995.1
download
onLine
dataset
<p><strong>Cruises and sample collection</strong></p>
<p>Water samples were collected as part of the SoMMoS project during twelve cruises, from February 2018 until January 2019. Each cruise took samples at two THEMO (Texas-Haifa Eastern Mediterranean Observatory) stations.</p>
<p>THEMO2, an open ocean station at a depth of ~1500 m (~50 Km from the coast, 32.820 N, 34.380 E), and THEMO1 which is positioned at the edge of the continental shelf at ~125m depth (~10 Km from the coast, 33.040 N, 34.950 E). THEMO2 was sampled from 12:00-22:00 (local time), while THEMO1 was sampled during the night, typically 00:00-02:00 (local time). Here, we will present information from data collected at the offshore THEMO2 station.</p>
<p>Start and end data of the cruises and sampling research vessel (no specific cruise IDs):</p>
<p>07/02/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 08/02/2018: R/V Bat-Galim<br />
05/03/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 06/03/2018: R/V Mediterranean Explorer<br />
09/04/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 10/04/2018: R/V Mediterranean Explorer<br />
14/05/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 15/05/2018: R/V Bat-Galim<br />
18/06/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 19/06/2018: R/V Mediterranean Explorer<br />
09/07/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 10/07/2018: R/V Mediterranean Explorer<br />
06/08/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 07/08/2018: R/V Bat-Galim<br />
05/09/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 06/09/2018: R/V Mediterranean Explorer<br />
08/10/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 09/10/2018: R/V Mediterranean Explorer<br />
05/11/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 06/11/2018: R/V Bat-Galim<br />
03/12/2018&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 04/12/2018: R/V Mediterranean Explorer<br />
21/01/2019&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 22/01/2019: R/V Mediterranean Explorer</p>
<p>Samples were collected using a 12-bottle rosette with 8 L Niskin bottles. Samples were collected at 20-24 depths across the entire water column (11-12 bottles between the surface and 200 m, which we define here as the photic zone). Sampling depths were selected based on real-time data of Conductivity, Temperature, Depth (CTD) profiler (Seabird 19 Plus) from the down-cast before each sample collection in the up-cast, an oxygen optode (on some cruises) and a fluorescence meter (Turner designs, Cyclops-7). The continuous data was processed using the Sea-Bird data conversion software, and minimized using bin averaging. One bin of data lines was defined as a change of 1 decibar (db) between each bin. The first two meters of measurements were compiled together to account for sensors and CTD pump adjustment time and rosette depth while at sea surface.</p>
<p><strong>Nutrients</strong></p>
<p>Nutrient samples were collected in acid-washed 500 ml plastic containers and immediately filtered through 0.22 μm Nalgene rapid-flow filter units. The first two filtrates were discarded, and the final sub- samples collected in new 50 ml falcon tubes and stored in the dark at 4 ◦C in racks. The samples were transported to the analytical lab at the marine station at Sdot-Yam within 12–15 h of sampling and dissolved nutrients determined using a SEAL AA-3 autoanalyzer system (SEAL, 2011). To minimize crosscontamination in the laboratory, ammonium was analyzed first alone using an automated ophthalaldehyde (OPA) fluorescence method. Samples were placed in the sample trays and only opened immediately before the sample probe took the sample. The baseline water used for ammonium determination was freshly prepared Milli-Q (MQ) water. The next parameters to be determined were dissolved nitrate and silicate. The methods used were Cd reduction and diazo dye for nitrate &amp; nitrite (hereafter referred to as Nox), and molybdate blue in the presence of oxalic acid for Silicate. The baseline water used for these determinations was also MQ water. For the August cruise nitrite was also determined by carrying out a run also using coloured diazo dye but without Cd reduction. Finally, a 3rd run was carried out using an ultra-low level phosphate (DIP) method involving using a 100 cm long flow cell (LWCC) and molybdate blue determination derived from Murphy and Riley (1962). The blank used for phosphate determination was surface seawater, whose DIP value was determined in a previous experiment in which we determined a refractive index correction by removing the ascorbic acid reagent. It was not possible to use MQ as the baseline, as has been used elsewhere because the MQ water in our lab (derived from desalinated water) contains ~20 nM DIP.</p>
<p>40 ml subsamples for Total Dissolved Phosphorus (TDP) were taken from the filtered samples on-board, acidified with 0.2 ml of 2M sulfuric acid and frozen immediately in racks. The samples were transported to the laboratory at the Sdot Yam marine station and stored at −4 ◦C until later analysis. After thawing the samples, 4 ml of acidified potassium persulphate was added to each sample in a glass autoclavable bottle. The closed bottles were autoclaved for at least 30 min and allowed to cool overnight. The samples were then transferred to 50 ml Falcon tubes and analyzed using the same procedure as described for DIP. In order to determine the reagent blank, a similar procedure was used substituting MQ (and 50 nM and 100 nM phosphate) for the sample, adding 4 ml of acidified potassium persulphate into glass autoclave bottles. The reagent blank was treated the same way as the seawater samples.</p>
<p><strong>Bacterial and primary productivity</strong></p>
<p>Heterotrophic prokaryotic productivity (hereafter referred to as bacterial productivity, BP) was estimated using the <sup>3</sup>H-leucine incorporation method (Simon and Azam, 1989; Smith and Azam, 1992). Triplicate 1.7 ml of ocean water were taken from each sampled depth and incubated with a 7:1 mixture of ‘cold’ leucine and ‘hot’ <sup>3</sup>H-leucine, respectively (final concentration 100 nmol leucine L<sup>-1</sup>) for 4 h at room temperature in the dark immediately after sampling. Preliminary experiments show that this was the saturating level of leucine in the offshore water of the SE Mediterranean Sea. After incubation, incorporation was terminated by adding 100 μl trichloroacetic acid (TCA). As a negative control for non-specific binding, another set of triplicates were sampled from a surface layer and treated with TCA immediately after the addition of the radioactive tracer. At the end of each cruise, the samples were processes using the micro-centrifugation protocol and 1ml scintillation cocktail (ULTIMA-GOLD) was added to all samples before counted using TRI-CARB 2100 TR (PACKARD) scintillation counter. A conversion factor of 3 kg C per mole of leucine incorporated and an isotopic dilution of 2.0 were used to calculate the C incorporated (Simon and Azam, 1989).</p>
<p>Net daily photosynthetic carbon fixation rates were estimated using the <sup>14</sup>C incorporation method (Nielsen, 1952), with several modifications (Hazan et al., 2018). Triplicate 50 ml samples were taken from each depth within the photic zone and from one aphotic depth using sterile vials and kept at surface light and temperature conditions. The ‘dark’ sample served as blank and was kept under the same temperature as the ‘light’ samples. Radioactive spiking was done at ~08:00 AM the day following of the cruise in order to start a 24h incubation for all samples (including those collected at THEMO-1 station, not shown) at the same time. Early work by Letelier and colleagues (1996) at station HOT showed that prolonged on-deck incubations, similarly to the protocol used in this study, may result in underestimated PP rates as it cannot precisely mimic the temperature and illumination levels in-situ. Our preliminary tests concur with this conclusion and found that ashore incubations underestimate PP rates by up to ~20% compared to incubations onto a mooring rope tied to the ship (Figure S2). Samples were spiked with 50μl (5 μCi) of NaH<sup>14</sup>CO<sub>3</sub> tracer and were incubated for 24 h under 3 light regimes: surface illumination (samples from the upper mixing depths), 50% illumination (samples from below the mixing depth to the DCM) and ~1% illumination (samples from the DCM and below). Shading was performed using neutral density nets, thus changing light intensity but not spectral properties. Water samples were then filtered through GF/F filters (0.7 μm nominal pore size, 25 mm diameter) using low vacuum pressure (&lt; 50 mmHg) and rinsed 3 times with filtered sea water. Filters from each sample were then put in scintillation vials where 50 μl of 32%HCl solution was immediately added in order to remove excess <sup>14</sup>C-bicarbonate and kept overnight for incubation. After incubation 5 mL scintillation cocktail (ULTIMA-GOLD) was added to the samples and counted using TRI-CARB 2100 TR (PACKARD) scintillation counter. Three random aliquots were counted immediately after the addition of the radiotracer (without incubation) with ethanolamine to serve as added activity measurements.</p>
<p><strong>Picophytoplankton abundance using flow-cytometry</strong></p>
<p>Triplicates water samples (1.5 ml) were collected from each sampling depth, put in cryo-vials (Nunc), and supplemented with 7.5 µl 25% glutaraldehyde (Sigma). Vials were incubated in the dark for 10 min, flash-frozen in liquid nitrogen, and stored in -80 <sup>o</sup>C freezer. Before analysis, samples were thawed in the dark at room temperature. Each sample was run twice on a BD Canto II flow-cytometer with 2 μm diameter fluorescent beads (Polysciences, Warminster, PA, USA) as a size and fluorescence standard. In the first run three types of phytoplankton cells were identified based on their natural auto-fluorescence: <em>Prochlorococcus</em>, <em>Synechococcus</em> and picoeukaryotes. Cells were differentiated based on cell chlorophyll (Ex482nm/Em676nm, PerCP channel) and phycoerythrin fluorescence (Ex564nm/Em574nm), and by the size of cell (forward scatter). Before the second FCM, run samples were stained with SYBR Green I (Molecular Probes/ ThermoFisher) to enable counting followed by detection at Ex494nm/Em520nm (FITC channel). This provided counts of the total bacterial population (phytoplankton + heterotrophic bacteria and archaea) as well as a distinction between cells with High or Low DNA content (not shown). Data were processed using FlowJo software. Flow rates were determined several times during each running session by weighing tubes with double-distilled water, and counts of the standard beads were used to verify a consistent flow rate.</p>
<p><strong>Algal pigment markers</strong></p>
<p>Eight litters of seawater were collected from all photic sample depths and one from a dark depth (depth varies between cruises). Water was filtered onto GF/F filters (0.7 μm nominal pore size, 47mm diameter, Waters) using a peristaltic pump until either all 8 L were filtered or the filter became blocked, in which case the volume filtered was recorded. Filters were placed in cryo-vials and flash frozen in liquid nitrogen until they could be stored in a -80 <sup>o</sup>C freezer. Pigments were extracted in 1ml 100% methanol for 3 h at room temperature and clarified using syringe filters (Acrodisc CR, 13 mm, 0.2 μm PTFE membranes, Pall Life Sciences). Total chlorophyll was measured spectrophotometrically using a NanoDrop 2000c (Thermo Sciences) at 632, 652, 665 and 695 nm, and the concentration of chlorophyll a was calculated (Ritchie 2008). Ultra high-pressure Liquid Chromatography (UPLC) was performed on an ACQUITY UPLC system (Waters) equipped with a photodiode array detector. A C8 column (1.7 μm particle size, 2.1 mm internal diameter, 50 mm column length, ACQUITY UPLC BEH, 186002877) was used. The chromatography method was adapted for UPLC from the LOV method (Hooker et al., 2005). Samples were preheated to 30 °C and column to 50 °C before each run. Running buffers were a 70:30 mixture of methanol and 0.5M ammonium acetate (buffer A) and 100% methanol (buffer B). The program consisted of an isocratic run using a 80:20 mixture of buffers A:B for 2min, followed by a linear gradient to 50:50 for 7 minutes and an increase to 100% solvent B. The flow rate was 0.5ml/min. Pigment standards from DHI (Denmark) were used to identify the UPLC peaks (chlorophyll a, divinyl-chlorophyll a, chlorophyll b,&nbsp; zeaxanthin,&nbsp; diatoxanthin, fucoxanthin, peridinin, 19’- butanoyloxyfucoxanthin and 19’- hexanoyloxyfucoxanthin). Due to potential degradation of the pigment standards, we present the total chlorophyll measured spectrophotometrically and the pigment ratios within each UPLC run.</p>
Specified by the Principal Investigator(s)
<p>Data processing has been done with the following programs: Seabird processing programs, FlowJo, Excel ad Waters UPLC software.</p>
<p>BCO-DMO processing notes:</p>
<p>* Removed column time_ISO_Depth after discussion with submitter. This column&nbsp;was created to be used in other applications that can interpret&nbsp;both parameters from a single cell, but is redundant when publishing it for reuse.</p>
<p>&nbsp;</p>
Specified by the Principal Investigator(s)
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
CTD profiler Seabird 19 Plus
CTD profiler Seabird 19 Plus
PI Supplied Instrument Name: CTD profiler Seabird 19 Plus PI Supplied Instrument Description:CTD profiler Seabird 19 Plus Instrument Name: CTD Sea-Bird SBE SEACAT 19plus Instrument Short Name:Sea-Bird SEACAT 19 Plus Instrument Description: Self contained self powered CTD profiler. Measures conductivity, temperature and pressure in both profiling (samples at 4 scans/sec) and moored (sample rates of once every 5 seconds to once every 9 hours) mode. Available in plastic or titanium housing with depth ranges of 600m and 7000m respectively. Minature submersible pump provides water to conductivity cell.
BD Canto II flow-cytometer
BD Canto II flow-cytometer
PI Supplied Instrument Name: BD Canto II flow-cytometer PI Supplied Instrument Description:BD Canto II flow-cytometer with 2 μm diameter fluorescent beads (Polysciences, Warminster, PA, USA) Instrument Name: Flow Cytometer Instrument Short Name:Flow Cytometer Instrument Description: Flow cytometers (FC or FCM) are automated instruments that quantitate properties of single cells, one cell at a time. They can measure cell size, cell granularity, the amounts of cell components such as total DNA, newly synthesized DNA, gene expression as the amount messenger RNA for a particular gene, amounts of specific surface receptors, amounts of intracellular proteins, or transient signalling events in living cells.
(from: http://www.bio.umass.edu/micro/immunology/facs542/facswhat.htm) Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/LAB37/
JASCO fluorometer
JASCO fluorometer
PI Supplied Instrument Name: JASCO fluorometer PI Supplied Instrument Description:JASCO fluorometer Instrument Name: Fluorometer Instrument Short Name:Fluorometer Instrument Description: A fluorometer or fluorimeter is a device used to measure parameters of fluorescence: its intensity and wavelength distribution of emission spectrum after excitation by a certain spectrum of light. The instrument is designed to measure the amount of stimulated electromagnetic radiation produced by pulses of electromagnetic radiation emitted into a water sample or in situ. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/113/
TRI-CARB 2100 TR (PACKARD) scintillation counter
TRI-CARB 2100 TR (PACKARD) scintillation counter
PI Supplied Instrument Name: TRI-CARB 2100 TR (PACKARD) scintillation counter PI Supplied Instrument Description:TRI-CARB 2100 TR (PACKARD) scintillation counter Instrument Name: Liquid Scintillation Counter Instrument Short Name:LSC Instrument Description: Liquid scintillation counting is an analytical technique which is defined by the incorporation of the radiolabeled analyte into uniform distribution with a liquid chemical medium capable of converting the kinetic energy of nuclear emissions into light energy. Although the liquid scintillation counter is a sophisticated laboratory counting system used to quantify the activity of particulate emitting (ß and a) radioactive samples, it can also detect the auger electrons emitted from 51Cr and 125I samples.
Liquid scintillation counters are instruments assaying alpha and beta radiation by quantitative detection of visible light produced by the passage of rays or particles through a suitable scintillant incorporated into the sample. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/LAB21/
100 cm long flow cell (LWCC)
100 cm long flow cell (LWCC)
PI Supplied Instrument Name: 100 cm long flow cell (LWCC) PI Supplied Instrument Description:100 cm long flow cell (LWCC) Instrument Name: Liquid Waveguide Capillary Cells Instrument Short Name:LWCC Instrument Description: Liquid Waveguide Capillary Cells (LWCC) are optical sample cells that combine an increased optical pathlength (2-500 cm) with small sample volumes. They can be connected via optical fibers to a spectrophotometer with fiber optic capabilities. Similar to optical fibers, light is confined within the (liquid) core of an LWCC by total internal reflection at the core/wall interface. Ultra-sensitive absorbance measurements can be performed in the ultraviolet (UV), visible (VIS) and near-infrared (NIR) to detect low sample concentrations in a laboratory or process control environment. According to Beer’s Law the absorbance signal is proportional to chemical concentration and light path length.
NanoDrop 2000c (Thermo Sciences)
NanoDrop 2000c (Thermo Sciences)
PI Supplied Instrument Name: NanoDrop 2000c (Thermo Sciences) PI Supplied Instrument Description:NanoDrop 2000c (Thermo Sciences) Instrument Name: Spectrophotometer Instrument Short Name:Spectrophotometer Instrument Description: An instrument used to measure the relative absorption of electromagnetic radiation of different wavelengths in the near infra-red, visible and ultraviolet wavebands by samples. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/LAB20/
ACQUITY UPLC system (Waters)
ACQUITY UPLC system (Waters)
PI Supplied Instrument Name: ACQUITY UPLC system (Waters) PI Supplied Instrument Description:ACQUITY UPLC system (Waters) equipped with a photodiode array detector and a C8 column (1.7 μm particle size, 2.1 mm internal diameter, 50 mm column length, ACQUITY UPLC BEH, 186002877) Instrument Name: Ultra-high-performance liquid chromatography Instrument Short Name:UHPLC Instrument Description: Ultra high-performance liquid chromatography: Column chromatography where the mobile phase is a liquid, the stationary phase consists of very small (< 2 microm) particles and the inlet pressure is relatively high.