Cell abundances of taxonomic groups determined using a custom convolutional neural network from live Imaging FlowCytobot (IFCB) at seven stations sampled during R/V Pt. Sur cruise PS 18-09 in the western Gulf of Mexico, Sept-Oct 2017 (NCEI Accession 0278070)
This dataset contains biological and survey - biological data collected on R/V Point Sur during cruise PS1809 from 2017-09-23 to 2017-10-01. These data include abundance and taxon. The instruments used to collect these data include Imaging FlowCytobot and Niskin bottle. These data were collected by Darren W. Henrichs and Lisa Campbell of Texas A&M University as part of the "RAPID: Hurricane Impact on Phytoplankton Community Dynamics and Metabolic Response (HRR)" project. The Biological and Chemical Oceanography Data Management Office (BCO-DMO) submitted these data to NCEI on 2021-06-09.
The following is the text of the dataset description provided by BCO-DMO:
HRR-IFCB cnn counts
Dataset Description:
Acquisition Description:
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. All image data can be viewed on the TOAST dashboard: https://toast.tamu.edu/timeline?dataset=HRR_cruise .
Image analysis and feature extraction were performed using software developed by Sosik and colleagues which is available on github ( https://github.com/hsosik/ifcb-analysis/ ). The automated classification approach of Sosik & Olson (2007), as modified and described by Anglès et al. (2019), was employed and the automated classification results were then inspected visually and manually 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).
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 ( CNN ) trained on a curated set of images (Henrichs et al. 2021.). See related dataset.
Biomass for each image was estimated using the algorithm developed by Moberg & Sosik (2012) to calculate cellular volume from the extracted image features and then convert to total carbon per image (Menden-Deuer & Lessard 2000) and summed for each class. See related dataset.
Sampling locations:
Sample ID
Station
Leg
Location
Lat o N/Long o W
L1_S01
S01
1
27.2286 -97.2686
L3_S01
S01
3
L1_S06
S06
1
27.8358 -96.9874
L3_S06
S06
3
L1_S11
S11
1
28.2614 -96.4129
L3_S11
S11
3
L1_S16
S16
1
28.5366 -95.8656
L3_S16
S16
3
L1_S21
S21
1
28.7644 -95.2978
L3_S21
S21
3
L1_SS
SS
1
28.9600 -95.0946
L3_SS
SS
3
L1_GI
GI
1
29.0649 -94.9000
L3_GI
GI
3
The following is the text of the dataset description provided by BCO-DMO:
HRR-IFCB cnn counts
Dataset Description:
Acquisition Description:
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. All image data can be viewed on the TOAST dashboard: https://toast.tamu.edu/timeline?dataset=HRR_cruise .
Image analysis and feature extraction were performed using software developed by Sosik and colleagues which is available on github ( https://github.com/hsosik/ifcb-analysis/ ). The automated classification approach of Sosik & Olson (2007), as modified and described by Anglès et al. (2019), was employed and the automated classification results were then inspected visually and manually 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).
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 ( CNN ) trained on a curated set of images (Henrichs et al. 2021.). See related dataset.
Biomass for each image was estimated using the algorithm developed by Moberg & Sosik (2012) to calculate cellular volume from the extracted image features and then convert to total carbon per image (Menden-Deuer & Lessard 2000) and summed for each class. See related dataset.
Sampling locations:
Sample ID
Station
Leg
Location
Lat o N/Long o W
L1_S01
S01
1
27.2286 -97.2686
L3_S01
S01
3
L1_S06
S06
1
27.8358 -96.9874
L3_S06
S06
3
L1_S11
S11
1
28.2614 -96.4129
L3_S11
S11
3
L1_S16
S16
1
28.5366 -95.8656
L3_S16
S16
3
L1_S21
S21
1
28.7644 -95.2978
L3_S21
S21
3
L1_SS
SS
1
28.9600 -95.0946
L3_SS
SS
3
L1_GI
GI
1
29.0649 -94.9000
L3_GI
GI
3
Dataset Citation
- Cite as: Campbell, Lisa; Henrichs, Darren W. (2023). Cell abundances of taxonomic groups determined using a custom convolutional neural network from live Imaging FlowCytobot (IFCB) at seven stations sampled during R/V Pt. Sur cruise PS 18-09 in the western Gulf of Mexico, Sept-Oct 2017 (NCEI Accession 0278070). [indicate subset used]. NOAA National Centers for Environmental Information. Dataset. https://www.ncei.noaa.gov/archive/accession/0278070. Accessed [date].
Dataset Identifiers
ISO 19115-2 Metadata
gov.noaa.nodc:0278070
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NOAA National Centers for Environmental Information +1-301-713-3277 NCEI.Info@noaa.gov |
Dataset Point of Contact |
NOAA National Centers for Environmental Information ncei.info@noaa.gov |
Time Period | 2017-09-23 to 2017-10-01 |
Spatial Bounding Box Coordinates |
West: -97.268
East: -94.9
South: 27.2286
North: 29.0649
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Dataset Progress Status | Complete - production of the data has been completed Historical archive - data has been stored in an offline storage facility |
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Data Center keywords | NODC COLLECTING INSTITUTION NAMES THESAURUS NODC SUBMITTING INSTITUTION NAMES THESAURUS Global Change Master Directory (GCMD) Data Center Keywords |
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Last Modified: 2024-05-31T15:27:35Z
For questions about the information on this page, please email: ncei.info@noaa.gov
For questions about the information on this page, please email: ncei.info@noaa.gov