Dataset: ZooSCAN Images BATS: M3 to M13

Name: ZooSCAN images of zooplankton collected during BATS MOCNESS tows during R/V Atlantic Explorer cruises AE1614, AE1712, AE1830, and AE1819 in the vicinity of the Bermuda Atlantic Time-series Study from 2016 to 2018
Published: 2021-10-07
Keywords: oceans

Cite This Dataset

DOI:10.26008/1912/bco-dmo.853440.1

Spatial Extent: N:32.3065 E:-64.0621 S:31.666 W:-64.7935

Temporal Extent: 2016-07-11 - 2018-10-30

Project:

Bermuda Institute of Ocean Sciences Simons Collaboration on Ocean Processes and Ecology (BIOSSCOPE)

Collaborative Research: Diel physiological rhythms in a tropical oceanic copepod (Zooplankton Diel Rhythm)

Quantifying the drivers of midwater zooplankton community structure (Zooplankton Gradients)

Principal Investigator:

Leocadio Blanco-Bercial (Bermuda Institute of Ocean Sciences, BIOS)

Co-Principal Investigator:

Amy Maas (Bermuda Institute of Ocean Sciences, BIOS)

Technician:

Hannah Gossner (Bermuda Institute of Ocean Sciences, BIOS)

BCO-DMO Data Manager:

Amber D. York (Woods Hole Oceanographic Institution, WHOI BCO-DMO)

Version:

Version Date:

2021-10-07

Restricted:

Validated:

Yes

Current State:

Final no updates expected

ZooSCAN images of zooplankton collected during BATS MOCNESS tows during R/V Atlantic Explorer cruises AE1614, AE1712, AE1830, and AE1819 in the vicinity of the Bermuda Atlantic Time-series Study from 2016 to 2018

Abstract:

ZooSCAN images from BATS MOCNESS tows during R/V Atlantic Explorer cruises AE1614, AE1712, AE1830, and AE1819 in the vicinity of the Bermuda Atlantic Time-series Study (BATS) in July of 2016, 2017, and 2018 as well as October 2018 (eight casts in total, 63 discrete nets). These data were published in Maas et al. (2021).

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Archival Copy

Version Date	Archive	Persistent Identifier (PID)	Date PID Issued
2021-10-07	Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)	10.26008/1912/bco-dmo.853440.1	2021-11-05

Methods & Sampling

Methodology: To obtain samples, a 1 m Multiple Opening/Closing Net and Environmental Sensing System (MOCNESS; Wiebe et al., 1985) equipped with 150 µm nets was deployed during the mid-day and mid-night on cruises carried out in the vicinity of the Bermuda Atlantic Time-series Study site (BATS) in July of 2016, 2017, and 2018 as well as October 2018 (eight casts in total, 63 discrete nets). The net sampling plan used adaptive profiling, modifying the depth of closure to capture eight distinct ecological zones from surface to 1000 m depth: e.g. the thermocline, deep chl-a maximum (DCM), above the O2 minimum, within the O2 minimum core, and below the O2 minimum (Maas et al., 2014, Steinberg et al., 2008a). The actual tow depths were set on a cruise-by-cruise basis, using CTD profiles to determine the depths of each ecological zone. Upon retrieval, the catch from each of the eight discrete nets were divided into splits. Half were preserved in 95% undenatured ethanol and the remainder preserved in buffered 4% formalin in seawater.

A representative subsample of the zooplankton community from each net were imaged from the formalin-preserved samples, then measured, using a ZooSCAN ver. 3 at 4,800 dpi (following the methods in: Gorsky et al., 2010, Vandromme et al., 2012). In order to better represent all size classes in the images, the original sample was divided into three size categories. All individuals larger than 2 cm were selected by eye and scanned separately from all the others. The remainder of the sample was sieved through a 1-mm mesh sieve, and both size fractions were individually scanned. From these smaller size fractions, at least 1500 particles were scanned after subsampling using a Motoda splitter (Motoda, 1959), requiring generation of two separate scans for both size classes. This resulted in a total of five images per net.

Image names:

Image names include:
cruise#_mocnessID_net#_sizefraction_ and _a|b if a replicate and end in _1.tif

Multiple images of the same size fraction were sometimes taken to obtain a sufficient number of particles. These replicates are named a or b. If there is no replicate they don’t have a letter in the image name. An a and b scan were always done for size classes d2 and d3. This was important because the split size is for the sum of a+b (e.g. if a is ¼ and b is ¼, the acq_sub_part will be 0.5).

Example of image names:

ae1830_m13_n4_d3_a_1.tif [a replicate]

ae1830_m13_n4_d3_b_1.tif [a replicate]

ae1830_m13_n5_d1_1.tif [no replicate]

Related Datasets may contain the "object_id" (the particle/organism id) which is constructed the same way as the image name except it as an additional _# at the end. This additional number in the object_id is added by the Zooprocess software (Hydroptic, 2016).
e.g.
object_id: ae1614_m3_n1_d2_a_1_100
image_name: ae1614_m3_n1_d2_a_1.tif

Problem report: During the July 2018 cruise the top net of the night cast failed, and consequently images from this net are absent.

Data Processing Description

BCO-DMO Data Manager Processing Notes:
* Images bundled for download in the Data Files section. A tar.gz file per cruise was made.
* "date" and "time" column converted to ISO 8601 format in image sample information which is time zone AST (UTC-4)/ADT (UTC-3).
* ISO_DateTime_UTC column added in ISO 8601 format in time zone utc.
* Image sample information attached as a supplemental file "image_sample_information.csv".

Data Files

File
ZooSCAN Images BATS AE1614 filename: ZooSCAN_Images_BATS_AE1614.tar.gz (GZIP (.gz), 31.83 GB) MD5:cd660ed602d8e4b984f9f946e6d536d6 Images acquired using the ZooSCAN imaging system during R/V Atlantic Explorer cruise AE1614 in the vicinity of the Bermuda Atlantic Time-series Study (BATS). The tar.gz bundle of compressed files contains 80 images in .tif format.
ZooSCAN Images BATS AE1712 filename: ZooSCAN_Images_BATS_AE1712.tar.gz (GZIP (.gz), 27.60 GB) MD5:4f6129527733c836d3787fced696d9d6 Images acquired using the ZooSCAN imaging system during R/V Atlantic Explorer cruise AE1712 in the vicinity of the Bermuda Atlantic Time-series Study (BATS). The tar.gz bundle of compressed files contains 68 images in .tif format.
ZooSCAN Images BATS AE1819 filename: ZooSCAN_Images_BATS_AE1819.tar.gz (GZIP (.gz), 25.94 GB) MD5:bd233160391542cc3185a15f28530124 Images acquired using the ZooSCAN imaging system during R/V Atlantic Explorer cruise AE1819 in the vicinity of the Bermuda Atlantic Time-series Study (BATS). The tar.gz bundle of compressed files contains 65 images in .tif format.
ZooSCAN Images BATS AE1830 filename: ZooSCAN_Images_BATS_AE1830.tar.gz (GZIP (.gz), 31.88 GB) MD5:d69a94a74fbf7a1bf4e3828482f4ddbe Images acquired using the ZooSCAN imaging system during R/V Atlantic Explorer cruise AE1830 in the vicinity of the Bermuda Atlantic Time-series Study (BATS). The tar.gz bundle of compressed files contains 81 images in .tif format.

Supplemental Files

File

Image Sample Metadata (ZooSCAN BATS M3 to M13)
filename: image_sample_information.csv

(Comma Separated Values (.csv), 30.56 KB)
MD5:1954f230c158230d25e019f37d82c19a

Image Sample Metadata for ZooSCAN images collected during R/V Atlantic Explorer cruises AE1614, AE1712, AE1819, AE1830 between 2016-2018.

Parameters (column name, description, units):

image_name,Image name, unitless

cruise_id,Cruise identifier, unitless

mocness_id,MOCNESS identifier,unitless

net_id,Net identifier,unitless

size_fraction,Size fraction (e.g. d3). See methodology,unitless

replicate,Replicate (see methodology),unitless

lat,Latitude,decimal degrees

lon,Longitude,decimal degrees

date, Date (local) in time zone AST (UTC-4)/ADT (UTC-3) in format YYYY-MM-DD,unitless

time, Time (local) in time zone AST (UTC-4)/ADT (UTC-3) in format hh:mm:ss

ISO_DateTime_UTC,Datetime in timezone UTC in ISO 8601 format YYYY-MM-DDThh:mm:ssZ

More Information about this dataset

Funding Sources

Funding Source	Award Number
NSF Division of Ocean Sciences	OCE-1948162
NSF Division of Ocean Sciences	OCE-1829318
Simons Foundation	unknown SCOPE Simons

Deployments

Deployment	Start Date	Platform	Investigator
AE1614	2016-07-09	R/V Atlantic Explorer	Craig A. Carlson (Chief Scientist)	data info
AE1712	2017-07-08	R/V Atlantic Explorer	Craig A. Carlson (Chief Scientist)	data info
AE1819	2018-07-03	R/V Atlantic Explorer	Craig A. Carlson (Chief Scientist)	data info
AE1830	2018-10-27	R/V Atlantic Explorer	Maureen H. Conte (Chief Scientist)	data info

Instruments

MOCNESS

Supplied Name: 1m MOCNESS

Supplied Description:

Instrument Type

Generic Name: MOCNESS

Community Identifier: http://vocab.nerc.ac.uk/collection/L22/current/NETT0097/

Generic Description:

The Multiple Opening/Closing Net and Environmental Sensing System or MOCNESS is a family of net systems based on the Tucker Trawl principle. There are currently 8 different sizes of MOCNESS in existence which are designed for capture of different size ranges of zooplankton and micro-nekton Each system is designated according to the size of the net mouth opening and in two cases, the number of nets it carries. The original MOCNESS (Wiebe et al, 1976) was a redesigned and improved version of a system described by Frost and McCrone (1974).(from MOCNESS manual) This designation is used when the specific type of MOCNESS (number and size of nets) was not specified by the contributing investigator.

ZooSCAN

Supplied Name: ZooSCAN ver. 3

Supplied Description:

http://www.hydroptic.com/index.php/public/Page/product_item/ZOOSCAN

Instrument Type

Generic Name: ZooSCAN

Generic Description:

Description excerpt from Hydroptic website
http://www.hydroptic.com/index.php/public/Page/product_item/ZOOSCAN

The ZooSCAN (CNRS patent) system makes use of scanner technology with custom lighting and a watertight scanning chamber into which liquid zooplankton samples can be placed. The scanner recovers a high-resolution, digitial image and the sample can be recovered without damage. These digital images can then be investigated by computer processing. While the resolution of the digitized zooplankton images is lower than the image obtained using a binocular microscope this technique has proved to be more than adequate for large sample sets. Identification of species is done by automatic comparison of the image (vignette) of each individual animal in the scanned image with a library data set which may be built by the investigator for each individual survey or imported from a previous survey. The latest machine learning algorithm allows high recognition levels even if we recommend complementary manual sorting to achieve a high number of taxonomic groups.

Parameters

None available yet

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Database

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Dataset: ZooSCAN Images BATS: M3 to M13