http://lod.bco-dmo.org/id/dataset/840147
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
2021-02-08
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Biomass of taxonomic groups from manually corrected live Imaging FlowCytobot (IFCB) analysis of water samples collected from surface and chlorophyll maximum depths during R/V Pt. Sur cruise PS 18-09 in the western Gulf of Mexico, Sept-Oct 2017
2021-02-08
publication
2021-02-08
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2021-06-09
publication
https://doi.org/10.26008/1912/bco-dmo.840147.1
Lisa Campbell
Texas A&M University
principalInvestigator
Darren W. Henrichs
Texas A&M University
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: Campbell, L., Henrichs, D. W. (2021) Biomass of taxonomic groups from manually corrected live Imaging FlowCytobot (IFCB) analysis of water samples collected from surface and chlorophyll maximum depths during R/V Pt. Sur cruise PS 18-09 in the western Gulf of Mexico, Sept-Oct 2017. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2021-02-08 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.840147.1 [access date]
HRR-IFCB manual biomass Dataset Description: Methods and Sampling: <p>On each of 2 cruise legs 01 and 03, samples were collected at 7 stations (S01, S06, S11, S16, S21, SS and GI) from 2 depths [surface and chlorophyll maximum depth when possible; see HRR-bottle data]) by CTD-rosette. At each station, triplicate 5-ml samples pre-filtered through 150 µm Nitex were analyzed immediately with an onboard Imaging FlowCytobot.&nbsp; All image data can be viewed on the TOAST dashboard: <a href="https://toast.tamu.edu/timeline?dataset=HRR_cruise" target="_blank">https://toast.tamu.edu/timeline?dataset=HRR_cruise</a>.</p>
<p>Image analysis and feature extraction were performed using software developed by Sosik and colleagues which is available on github (<a href="https://github.com/hsosik/ifcb-analysis/" target="_blank">https://github.com/hsosik/ifcb-analysis/</a>). The automated classification approach of Sosik &amp; Olson (2007), as modified and described by Anglès et al. (2019), was employed and the automated classification results were then inspected visually and <strong>manually</strong> corrected into a total of 102 categories that included 35 categories of diatoms, 30 categories of dinoflagellates, 10 categories of ciliates, 10 categories of flagellates, and 17 ‘others’, which included filamentous cyanobacteria, freshwater chlorophytes, coccolithophorids, and small cells that could not be identified taxonomically from images (refer to Fiorendino et al. 2021. for more details). See related dataset.</p>
<p>For comparison with the Texas Observatory for Algal Succession Time series (TOAST), IFCB images were also classified automatically into one of 112 classes utilizing a custom convolutional neural network (<strong>CNN</strong>) trained on a curated set of images (Henrichs et al. 2021.). See related dataset.</p>
<p><strong>This dataset: Biomass</strong> for each image was estimated using the algorithm developed by Moberg &amp; Sosik (2012) to calculate cellular volume from the extracted image features and then convert to total carbon per image (Menden-Deuer &amp; Lessard 2000) and summed for each class..</p>
<p>Sampling locations:</p>
<table border="1" cellpadding="0" cellspacing="0">
<tbody>
<tr>
<td>
<p>Sample ID</p>
</td>
<td>
<p>Station</p>
</td>
<td>
<p>Leg</p>
</td>
<td>
<p>Location&nbsp;&nbsp;&nbsp;</p>
<p>Lat <sup>o</sup>N/Long <sup>o</sup>W</p>
</td>
</tr>
<tr>
<td>
<p>L1_S01</p>
</td>
<td>
<p>S01</p>
</td>
<td>
<p>1</p>
</td>
<td rowspan="2">
<p>27.2286 &nbsp;-97.2686</p>
</td>
</tr>
<tr>
<td>
<p>L3_S01</p>
</td>
<td>
<p>S01</p>
</td>
<td>
<p>3</p>
</td>
</tr>
<tr>
<td>
<p>L1_S06</p>
</td>
<td>
<p>S06</p>
</td>
<td>
<p>1</p>
</td>
<td rowspan="2">
<p>27.8358 &nbsp;-96.9874</p>
</td>
</tr>
<tr>
<td>
<p>L3_S06</p>
</td>
<td>
<p>S06</p>
</td>
<td>
<p>3</p>
</td>
</tr>
<tr>
<td>
<p>L1_S11</p>
</td>
<td>
<p>S11</p>
</td>
<td>
<p>1</p>
</td>
<td rowspan="2">
<p>28.2614&nbsp; -96.4129</p>
</td>
</tr>
<tr>
<td>
<p>L3_S11</p>
</td>
<td>
<p>S11</p>
</td>
<td>
<p>3</p>
</td>
</tr>
<tr>
<td>
<p>L1_S16</p>
</td>
<td>
<p>S16</p>
</td>
<td>
<p>1</p>
</td>
<td rowspan="2">
<p>28.5366 &nbsp;-95.8656</p>
</td>
</tr>
<tr>
<td>
<p>L3_S16</p>
</td>
<td>
<p>S16</p>
</td>
<td>
<p>3</p>
</td>
</tr>
<tr>
<td>
<p>L1_S21</p>
</td>
<td>
<p>S21</p>
</td>
<td>
<p>1</p>
</td>
<td rowspan="2">
<p>28.7644 &nbsp;-95.2978</p>
</td>
</tr>
<tr>
<td>
<p>L3_S21</p>
</td>
<td>
<p>S21</p>
</td>
<td>
<p>3</p>
</td>
</tr>
<tr>
<td>
<p>L1_SS</p>
</td>
<td>
<p>SS</p>
</td>
<td>
<p>1</p>
</td>
<td rowspan="2">
<p>28.9600 &nbsp;-95.0946</p>
</td>
</tr>
<tr>
<td>
<p>L3_SS</p>
</td>
<td>
<p>SS</p>
</td>
<td>
<p>3</p>
</td>
</tr>
<tr>
<td>
<p>L1_GI</p>
</td>
<td>
<p>GI</p>
</td>
<td>
<p>1</p>
</td>
<td rowspan="2">
<p>29.0649 &nbsp;-94.9000</p>
<p>&nbsp;</p>
</td>
</tr>
<tr>
<td>
<p>L3_GI</p>
</td>
<td>
<p>GI</p>
</td>
<td>
<p>3</p>
</td>
</tr>
</tbody>
</table>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1760620 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1760620
completed
Lisa Campbell
Texas A&M University
979-845-5706
3146 TAMU, Department of Oceanography Texas A&M University
College Station
Texas
77843
USA
lisacampbell@tamu.edu
pointOfContact
Darren W. Henrichs
Texas A&M University
979-845-5738
3146 TAMU, Department of Oceanography Texas A&M University
College Station
Texas
77843
USA
dhenrichs@tamu.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
Major_Category
Class
L1GI_1
L1GI_2
L1GI_3
L1SS_1
L1SS_2
L1SS_3
L1S21_1
L1S21_2
L1S21_3
L1S16_1
L1S16_2
L1S16_3
L1S11_1
L1S11_2
L1S11_3
L1S06_1
L1S06_2
L1S06_3
L1S01_1
L1S01_2
L1S01_3
L3GI_1
L3GI_2
L3GI_3
L3SS_1
L3SS_2
L3SS_3
L3S21_1
L3S21_2
L3S21_3
L3S16_1
L3S16_2
L3S16_3
L3S11_1
L3S11_2
L3S11_3
L3S06_1
L3S06_2
L3S06_3
L3S01
Image FlowCytobot (McLane Research Laboratories, Inc.)
theme
None, User defined
taxon
wet_weight_biomass
featureType
BCO-DMO Standard Parameters
Imaging FlowCytobot
Niskin bottle
instrument
BCO-DMO Standard Instruments
PS1809
service
Deployment Activity
Western Gulf of Mexico, Continental Shelf, Louisiana and Texas coasts
place
Locations
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.
RAPID: Hurricane Impact on Phytoplankton Community Dynamics and Metabolic Response
https://osprey.bco-dmo.org/project/715170
RAPID: Hurricane Impact on Phytoplankton Community Dynamics and Metabolic Response
<p><em>NSF Award Abstract:</em><br />
Hurricane Harvey is the strongest hurricane to hit the Texas coast in decades and the resulting tidal surges, flooding and terrestrial runoff have had a severe impact on the coastal ocean. The effects on the phytoplankton, the first link in the food chain, may be unprecedented. To determine how the phytoplankton community will respond to such drastic changes in salinity, nutrient inputs, and potential toxins, immediate and continuous sampling is the only way to fully capture the effects and to identify when conditions return to "normal". An automated, continuous phytoplankton imaging instrument that is deployed on the Texas coast records images of the phytoplankton and permits calculation of the abundance of different species. Together with molecular information on the genes that have been "turned on", or expressed, outcomes of this project will help determine the responses of individual types of phytoplankton. Extreme storms are expected to increase in frequency with future climate change, so the responses identified now will be valuable in predicting how such events will affect these primary producers, which in turn support most of the food webs in marine ecosystems, in the future.</p>
<p>High temporal resolution observations from the Imaging FlowCytobot (IFCB) have revealed that hurricanes in the Gulf of Mexico cause drastic changes in the phytoplankton community structure. The objectives of this RAPID project are: 1) to characterize the dynamics of the phytoplankton species in relation to the environmental variables along the Texas coast; 2) to assess the short and long-term changes in the phytoplankton community; and 3) to identify the strategies of the phytoplankton community for resource acquisition. To accomplish these objectives, this project will utilize IFCB time series to follow phytoplankton community structure during the recovery period from Hurricane Harvey. In addition, two RAPID response cruises (in late September and early October) to sample at 5 sites along a transect from Galveston to Port Aransas, TX. At each station, CTD profiles and water samples from surface and the chlorophyll maximum will be collected for nutrients, carbonate chemistry, and RNA sequencing for metatranscriptomic analysis. Metatranscriptomics can provide an indication of the metabolic strategies employed and functional relationships within the plankton community in response to changes in the environment. The advantage of a metatranscriptomic approach is that the entire molecular response to the environment is captured. So, while the response of phytoplankton to increased nutrient inputs from floodwater runoff is targeted, the responses to other environmental stresses (toxics, hypoxia, acidification) are also captured. Analyses of this time series using multivariate statistical techniques, such as principal component analysis (PCA), and network analysis, a powerful technique for identifying potential interactions among taxa, will provide insights on the environmental factors and metabolic responses structuring the community during the aftermath of the hurricane.</p>
<p><strong>Related data from the The Texas Observatory for Algal Succession Time-Series (TOAST) can be found at the following: </strong><a href="https://toast.tamu.edu/timeline?dataset=HRR_Cruise" target="_blank">https://toast.tamu.edu/timeline?dataset=HRR_Cruise</a></p>
HRR
largerWorkCitation
project
eng; USA
biota
oceans
Western Gulf of Mexico, Continental Shelf, Louisiana and Texas coasts
-97.268
-94.9
27.2286
29.0649
2017-09-23
2017-10-01
Texas coast
0
BCO-DMO catalogue of parameters from Biomass of taxonomic groups from manually corrected live Imaging FlowCytobot (IFCB) analysis of water samples collected from surface and chlorophyll maximum depths during R/V Pt. Sur cruise PS 18-09 in the western Gulf of Mexico, Sept-Oct 2017
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/840159.rdf
Name: Major_Category
Units: unitless
Description: <p>5 major groups of microplankton</p>
http://lod.bco-dmo.org/id/dataset-parameter/840160.rdf
Name: Class
Units: unitless
Description: <p>Taxonomic names of the species or genus (if known) or group identified</p>
http://lod.bco-dmo.org/id/dataset-parameter/840161.rdf
Name: L1GI_1
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station GI; replicate 1</p>
http://lod.bco-dmo.org/id/dataset-parameter/840162.rdf
Name: L1GI_2
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station GI; replicate 2</p>
http://lod.bco-dmo.org/id/dataset-parameter/840163.rdf
Name: L1GI_3
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station GI; replicate 3</p>
http://lod.bco-dmo.org/id/dataset-parameter/840164.rdf
Name: L1SS_1
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station SS; replicate 1</p>
http://lod.bco-dmo.org/id/dataset-parameter/840165.rdf
Name: L1SS_2
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station SS; replicate 2</p>
http://lod.bco-dmo.org/id/dataset-parameter/840166.rdf
Name: L1SS_3
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station SS; replicate 3</p>
http://lod.bco-dmo.org/id/dataset-parameter/840167.rdf
Name: L1S21_1
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station S21; replicate 1</p>
http://lod.bco-dmo.org/id/dataset-parameter/840168.rdf
Name: L1S21_2
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station S21; replicate 2</p>
http://lod.bco-dmo.org/id/dataset-parameter/840169.rdf
Name: L1S21_3
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station S21; replicate 3</p>
http://lod.bco-dmo.org/id/dataset-parameter/840170.rdf
Name: L1S16_1
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station S16; replicate 1</p>
http://lod.bco-dmo.org/id/dataset-parameter/840171.rdf
Name: L1S16_2
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station S16; replicate 2</p>
http://lod.bco-dmo.org/id/dataset-parameter/840172.rdf
Name: L1S16_3
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station S16; replicate 3</p>
http://lod.bco-dmo.org/id/dataset-parameter/840173.rdf
Name: L1S11_1
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station S11; replicate 1</p>
http://lod.bco-dmo.org/id/dataset-parameter/840174.rdf
Name: L1S11_2
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station S11; replicate 2</p>
http://lod.bco-dmo.org/id/dataset-parameter/840175.rdf
Name: L1S11_3
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station S11; replicate 3</p>
http://lod.bco-dmo.org/id/dataset-parameter/840176.rdf
Name: L1S06_1
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station S06; replicate 1</p>
http://lod.bco-dmo.org/id/dataset-parameter/840177.rdf
Name: L1S06_2
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station S06; replicate 2</p>
http://lod.bco-dmo.org/id/dataset-parameter/840178.rdf
Name: L1S06_3
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station S06; replicate 3</p>
http://lod.bco-dmo.org/id/dataset-parameter/840179.rdf
Name: L1S01_1
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station S01; replicate 1</p>
http://lod.bco-dmo.org/id/dataset-parameter/840180.rdf
Name: L1S01_2
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station S01; replicate 2</p>
http://lod.bco-dmo.org/id/dataset-parameter/840181.rdf
Name: L1S01_3
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 1 station S01; replicate 3</p>
http://lod.bco-dmo.org/id/dataset-parameter/840182.rdf
Name: L3GI_1
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station GI; replicate 1</p>
http://lod.bco-dmo.org/id/dataset-parameter/840183.rdf
Name: L3GI_2
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station GI; replicate 2</p>
http://lod.bco-dmo.org/id/dataset-parameter/840184.rdf
Name: L3GI_3
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station GI; replicate 3</p>
http://lod.bco-dmo.org/id/dataset-parameter/840185.rdf
Name: L3SS_1
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station SS; replicate 1</p>
http://lod.bco-dmo.org/id/dataset-parameter/840186.rdf
Name: L3SS_2
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station SS; replicate 2</p>
http://lod.bco-dmo.org/id/dataset-parameter/840187.rdf
Name: L3SS_3
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station SS; replicate 3</p>
http://lod.bco-dmo.org/id/dataset-parameter/840188.rdf
Name: L3S21_1
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station S21; replicate 1</p>
http://lod.bco-dmo.org/id/dataset-parameter/840189.rdf
Name: L3S21_2
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station S21; replicate 2</p>
http://lod.bco-dmo.org/id/dataset-parameter/840190.rdf
Name: L3S21_3
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station S21; replicate 3</p>
http://lod.bco-dmo.org/id/dataset-parameter/840191.rdf
Name: L3S16_1
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station S16; replicate 1</p>
http://lod.bco-dmo.org/id/dataset-parameter/840192.rdf
Name: L3S16_2
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station S16; replicate 2</p>
http://lod.bco-dmo.org/id/dataset-parameter/840193.rdf
Name: L3S16_3
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station S16; replicate 3</p>
http://lod.bco-dmo.org/id/dataset-parameter/840194.rdf
Name: L3S11_1
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station S11; replicate 1</p>
http://lod.bco-dmo.org/id/dataset-parameter/840195.rdf
Name: L3S11_2
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station S11; replicate 2</p>
http://lod.bco-dmo.org/id/dataset-parameter/840196.rdf
Name: L3S11_3
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station S11; replicate 3</p>
http://lod.bco-dmo.org/id/dataset-parameter/840197.rdf
Name: L3S06_1
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station S06; replicate 1</p>
http://lod.bco-dmo.org/id/dataset-parameter/840198.rdf
Name: L3S06_2
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station S06; replicate 2</p>
http://lod.bco-dmo.org/id/dataset-parameter/840199.rdf
Name: L3S06_3
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station S06; replicate 3</p>
http://lod.bco-dmo.org/id/dataset-parameter/840200.rdf
Name: L3S01
Units: micrograms carbon/liter
Description: <p>Biomass of class at Leg 3 station S01</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
15270
https://darchive.mblwhoilibrary.org/bitstream/1912/27199/1/dataset-840147_hrr-ifcb-manual-carbon__v1.tsv
download
https://doi.org/10.26008/1912/bco-dmo.840147.1
download
onLine
dataset
<p>On each of 2 cruise legs 01 and 03, samples were collected at 7 stations (S01, S06, S11, S16, S21, SS and GI) from 2 depths [surface and chlorophyll maximum depth when possible; see HRR-bottle data]) by CTD-rosette. At each station, triplicate 5-ml samples pre-filtered through 150 µm Nitex were analyzed immediately with an onboard Imaging FlowCytobot.&nbsp; All image data can be viewed on the TOAST dashboard: <a href="https://toast.tamu.edu/timeline?dataset=HRR_cruise" target="_blank">https://toast.tamu.edu/timeline?dataset=HRR_cruise</a>.</p>
<p>Image analysis and feature extraction were performed using software developed by Sosik and colleagues which is available on github (<a href="https://github.com/hsosik/ifcb-analysis/" target="_blank">https://github.com/hsosik/ifcb-analysis/</a>). The automated classification approach of Sosik &amp; Olson (2007), as modified and described by Anglès et al. (2019), was employed and the automated classification results were then inspected visually and <strong>manually</strong> corrected into a total of 102 categories that included 35 categories of diatoms, 30 categories of dinoflagellates, 10 categories of ciliates, 10 categories of flagellates, and 17 ‘others’, which included filamentous cyanobacteria, freshwater chlorophytes, coccolithophorids, and small cells that could not be identified taxonomically from images (refer to Fiorendino et al. 2021. for more details). See related dataset.</p>
<p>For comparison with the Texas Observatory for Algal Succession Time series (TOAST), IFCB images were also classified automatically into one of 112 classes utilizing a custom convolutional neural network (<strong>CNN</strong>) trained on a curated set of images (Henrichs et al. 2021.). See related dataset.</p>
<p><strong>This dataset: Biomass</strong> for each image was estimated using the algorithm developed by Moberg &amp; Sosik (2012) to calculate cellular volume from the extracted image features and then convert to total carbon per image (Menden-Deuer &amp; Lessard 2000) and summed for each class..</p>
<p>Sampling locations:</p>
<table border="1" cellpadding="0" cellspacing="0">
<tbody>
<tr>
<td>
<p>Sample ID</p>
</td>
<td>
<p>Station</p>
</td>
<td>
<p>Leg</p>
</td>
<td>
<p>Location&nbsp;&nbsp;&nbsp;</p>
<p>Lat <sup>o</sup>N/Long <sup>o</sup>W</p>
</td>
</tr>
<tr>
<td>
<p>L1_S01</p>
</td>
<td>
<p>S01</p>
</td>
<td>
<p>1</p>
</td>
<td rowspan="2">
<p>27.2286 &nbsp;-97.2686</p>
</td>
</tr>
<tr>
<td>
<p>L3_S01</p>
</td>
<td>
<p>S01</p>
</td>
<td>
<p>3</p>
</td>
</tr>
<tr>
<td>
<p>L1_S06</p>
</td>
<td>
<p>S06</p>
</td>
<td>
<p>1</p>
</td>
<td rowspan="2">
<p>27.8358 &nbsp;-96.9874</p>
</td>
</tr>
<tr>
<td>
<p>L3_S06</p>
</td>
<td>
<p>S06</p>
</td>
<td>
<p>3</p>
</td>
</tr>
<tr>
<td>
<p>L1_S11</p>
</td>
<td>
<p>S11</p>
</td>
<td>
<p>1</p>
</td>
<td rowspan="2">
<p>28.2614&nbsp; -96.4129</p>
</td>
</tr>
<tr>
<td>
<p>L3_S11</p>
</td>
<td>
<p>S11</p>
</td>
<td>
<p>3</p>
</td>
</tr>
<tr>
<td>
<p>L1_S16</p>
</td>
<td>
<p>S16</p>
</td>
<td>
<p>1</p>
</td>
<td rowspan="2">
<p>28.5366 &nbsp;-95.8656</p>
</td>
</tr>
<tr>
<td>
<p>L3_S16</p>
</td>
<td>
<p>S16</p>
</td>
<td>
<p>3</p>
</td>
</tr>
<tr>
<td>
<p>L1_S21</p>
</td>
<td>
<p>S21</p>
</td>
<td>
<p>1</p>
</td>
<td rowspan="2">
<p>28.7644 &nbsp;-95.2978</p>
</td>
</tr>
<tr>
<td>
<p>L3_S21</p>
</td>
<td>
<p>S21</p>
</td>
<td>
<p>3</p>
</td>
</tr>
<tr>
<td>
<p>L1_SS</p>
</td>
<td>
<p>SS</p>
</td>
<td>
<p>1</p>
</td>
<td rowspan="2">
<p>28.9600 &nbsp;-95.0946</p>
</td>
</tr>
<tr>
<td>
<p>L3_SS</p>
</td>
<td>
<p>SS</p>
</td>
<td>
<p>3</p>
</td>
</tr>
<tr>
<td>
<p>L1_GI</p>
</td>
<td>
<p>GI</p>
</td>
<td>
<p>1</p>
</td>
<td rowspan="2">
<p>29.0649 &nbsp;-94.9000</p>
<p>&nbsp;</p>
</td>
</tr>
<tr>
<td>
<p>L3_GI</p>
</td>
<td>
<p>GI</p>
</td>
<td>
<p>3</p>
</td>
</tr>
</tbody>
</table>
Specified by the Principal Investigator(s)
<p><strong>- BCO-DMO Processing Notes:</strong><br />
-&nbsp;data submitted in Excel file "manual_carbon_ifcb.xlsx" sheet "Biomass" extracted to csv<br />
- added conventional header with dataset name, PI name, version date<br />
-&nbsp;modified parameter names to conform with BCO-DMO naming conventions<br />
- rounded values to 2 decimal places</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
Image FlowCytobot (McLane Research Laboratories, Inc.)
Image FlowCytobot (McLane Research Laboratories, Inc.)
PI Supplied Instrument Name: Image FlowCytobot (McLane Research Laboratories, Inc.) Instrument Name: Imaging FlowCytobot Instrument Short Name:IFCB Instrument Description: The Imaging FlowCytobot (IFCB) is an in-situ automated submersible imaging flow cytometer that generates images of particles in-flow taken from the aquatic environment. https://mclanelabs.com/imaging-flowcytobot/
PI Supplied Instrument Name: PI Supplied Instrument Description:Used to collect samples Instrument Name: Niskin bottle Instrument Short Name:Niskin bottle Instrument Description: A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends. The bottles can be attached individually on a hydrowire or deployed in 12, 24, or 36 bottle Rosette systems mounted on a frame and combined with a CTD. Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc. Community Standard Description: http://vocab.nerc.ac.uk/collection/L22/current/TOOL0412/
Cruise: PS1809
PS1809
R/V Point Sur
Community Standard Description
International Council for the Exploration of the Sea
R/V Point Sur
vessel
PS1809
Lisa Campbell
Texas A&M University
R/V Point Sur
Community Standard Description
International Council for the Exploration of the Sea
R/V Point Sur
vessel