Dataset: zooplankton_taxonomy
Deployment: ZHNG09RR

Zooplankton taxonomic data from MOCNESS and IONESS tows

Principal Investigator:

Deborah K. Steinberg (Virginia Institute of Marine Science, VIMS)

Analyst:

Joseph Cope (Virginia Institute of Marine Science, VIMS)

BCO-DMO Data Manager:

Cynthia L. Chandler (Woods Hole Oceanographic Institution, WHOI BCO-DMO)

Project:

VERtical Transport In the Global Ocean (VERTIGO)

Current State:

Final no updates expected

Version:

24 February 2009

Deployment Synonyms:

RR_K2

Version Date:

2009-02-24

Data URL:

https://www.bco-dmo.org/dataset-deployment/452175/data

Expand/Collapse All

Description

Zooplankton taxonomic data from MOCNESS and IONESS tows

Methods & Sampling

Dataset acquisition description

 Methodology: Methodology

 Change history: YYMMDD
    080711: contributed by Joe Cope
    090213: Cruise_ID "K2" changed to "RR_K2" for consistency with other VERTIGO data sets
            "date" column header changed to "date_begin"
            "time" column header changed to "time_begin"
    090224: added to OCB database; Steve Gegg (sgegg@whoi.edu), BCO DMO

Deployment-specific acquisition description

 Methodology: Methodology

 Change history: YYMMDD
    080711: contributed by Joe Cope
    090213: Cruise_ID "K2" changed to "RR_K2" for consistency with other VERTIGO data sets
            "date" column header changed to "date_begin"
            "time" column header changed to "time_begin"
    090224: added to OCB database; Steve Gegg (sgegg@whoi.edu), BCO DMO

Data Processing Description

Dataset Processing Description

More information about this dataset deployment

Instruments

Intelligent Operative Net Sampling System

Supplied Description:

Instrument Type

Generic Name: Intelligent Operative Net Sampling System

Acronym: IONESS

Community Identifier: http://vocab.nerc.ac.uk/collection/L05/current/22/

Generic Description:

The Intelligent Operative Net Sampling System (IONESS) is a sampling net system similar to a MOCNESS that is towed through the water column and can be controlled to open and close over specified depth intervals.

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.

Parameters

Supplied Name	Supplied description	Supplied Units	Standard Name
Cruise_ID	VERTIGO cruise name	text	cruise_id
event	unique sampling event	dimensionless	event
date_begin	date at start of tow (UTC) in the format YYYYMMDD	unitless	date_begin
time_begin	time at start of tow (UTC) in the format HHMM	unitless	time_begin
depth_end	depth at end of tow	meters	depth_end
depth_begin	depth at start of tow	meters	depth_begin
vol_filt	volume filtered by net	meters^3	vol_filt
taxon	major taxonomic grouping	text	taxon
tax_dens	taxon density	#/meters^3	abundance
lon	longitude, negative denotes West	decimal degrees	lon
lat	latitude, negative denotes South	decimal degrees	lat

Database

Contribute Data

Dataset: zooplankton_taxonomy
Deployment: ZHNG09RR

Dataset acquisition description

Deployment-specific acquisition description

Dataset Processing Description

Database

Contribute Data

Dataset: zooplankton_taxonomyDeployment: ZHNG09RR

Dataset acquisition description

Deployment-specific acquisition description

Dataset Processing Description

Dataset: zooplankton_taxonomy
Deployment: ZHNG09RR