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 (NCEI Accession 0277870)

This dataset contains biological data collected on R/V Point Sur during cruise PS1809 from 2017-09-23 to 2017-10-01. These data include biomass 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 manual biomass

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). See related dataset.

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.

This 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..

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