Methodology:
\nPlankton samples were collected from discrete depths during CTD casts using a high-capacity, diaphragm pump with an intake hose mounted to the CTD Rosette. Subsamples of sample contents were manually counted, identified, and measured in the laboratory
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Sampling and analytical procedures:
\nFor each sample, the pump was run for a timed period of nominally 5 min. The flow rate of the pump was usually measured immediately prior to sampling, by recording the time required to fill a barrel of known volume. Samples were preserved and stored in 5% buffered formalin. The laboratory protocol was to separate samples into two size fractions by passing them through large (200 or 500 \u03bcm) then small (64 \u03bcm) mesh sieves; split, dilute, and sub-sample each size fraction as needed; count and identify all plankters (minimum n = 50) in each subsample; and estimate the length and width of exactly 100 plankters (the first 50 from the large and small fraction, respectively) to the nearest 50 \u03bcm using a dissecting microscope. Three replicate small size fractions per sample were processed starting in 2006.
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Data column "vol" was calculated as follows:
\nvol = length(unique(replicate)*aliquot/beaker/2^splits*50/s_per_50l*d_min*60*1e-3
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Data column "flag" contains the following codes:
\nflag 1: length & width were not measured, but estimated from similar samples
\nflag 2: shallow & deep samples not labeled, but deduced from sample contents
\nflag 3: depth estimate less accurate than usual (\u00b1 ~3 m)
\nflag 4: time estimate less accurate than usual (\u00b1 ~15 min)
\nflag 5: pump flow rate estimated by nominal flow rate
Data processing:
\nNominal sampling time and depth were corrected by analysis of CTD upcast data. CTD pressure sensor measurements at depth were adjusted to compensate for non-zero readings on deck of the research vessel over the course of each cruise. Bottom depth was estimated from filtered CTD altimeter and pressure data. Longitude and latitude were taken from the vessel\u2019s MIDAS system or a separate GPS unit at the time the CTD was turned on. Inconsistent taxonomic identifications (e.g., misspelled or misleading colloquial categories) were corrected by manually creating and automatically applying a lookup table. All data processing was performed using the R language and environment for statistical computing.
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BCO-DMO Data Manager Processing Notes:
\n* added a conventional header with dataset name, PI name, version date
\n* modified parameter names to conform with BCO-DMO naming conventions
\n* added ISO Timestamp column
\n* rounded decimal places of columns. Number of decimal places provided by data contributor.
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Data version 1: 2018-09-12 replaced by data version 2: 2018-10-22. Dataset was modified to use unique ctd profile identifiers and remove redundant time/date columns (y,m,d,h,m,s).