Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Data Files
• Related Publications
• Parameters
• Instruments
• Deployments
• Project Information
• Funding

This dataset includes zooplankton counts and abundances from meter net tows on multiple cruises on RV/Savannah in the South Atlantic Bight, Mid-Continental Shelf from August 2015 to December 2017.

Latitude and longitude data are included in version 3.

Zooplankton was collected from 31°N to 29°N aboard the R/V Savannah at the 25m and 40m isobaths using a 1M (mouth opening) 5M length 200 µm mesh cone plankton net equipped with a filtering (202 µm mesh) cod-end.  The mouth of the net was mounted in a swivel towing frame that allowed the opening of the net to track the water current. A mechanical flow meter (General Oceanics Part# 2030RC) was mounted in the center of the net. Flowmeter measurements for 2015 cruises (pdf) The net was deployed from a gently drifting ship and the entire water column was sampled by lowering the net to near the bottom and retrieving it (oblique tow).  Net speed was maintained at approximately 15 meters per minute. Once retrieved the contents of the net were collected on a 200 µm sieve and preserved in 60% non-denatured ethanol.

Samples were split twice to create four subsamples using a Folsom plankton splitter.

One of the subsamples was diluted to a known volume and stirred gently. Dilutions were adjusted depending on the density of zooplankton so that sufficient numbers of species were present in each sample to obtain a reliable estimate of the major taxonomic groups in each sample. Replicate aliquots from the subsample were counted under a dissecting microscope using a Bogorov counting chamber. The volume of sample counted was adjusted based on the density of zooplankton present but was generally 5 ml. A Stempel pipette was used to dispense the counted volume.

In the case where the identity was uncertain, representative examples of the unidentified zooplankton were identified by DNA barcoding.  DNA extractions were performed using the DNeasy Blood & Tissue Kit (Qiagen) according to manufacturer’s protocol except that samples were macerated and homogenized with Kimble/Kontes Cordless Motor, the proteinase K incubation was extended to ~24 hours (overnight) and the volume of elution buffer AE varied depending on sample size (60ul for most). For DNA quantitation and quality testing, one (1) ul of DNA was used to measure the 260/280 ratio using the Thermo Scientific™  NanoDrop Lite Spectrophotometer.  The presence of high molecular weight DNA in each extract was visually confirmed by agarose (1%) gel electrophoresis.  Good quality DNA extractions, inferred by 260/280 ratio and electrophoresis, were selected for amplification by Polymerase Chain Reaction (PCR) of a fragment of the mitochondrial cytochrome oxidase subunit I (mtCOI) gene.  A 708 base-pair mtCOI gene fragment was amplified using the consensus primer pairs LCO-1490 (5’-GGTCAACAAATCATAAAGATATTGG-3’) and HCO-2198 (5’-TAAACTTCAGGGTGACCAAAAAATCA-3’) (Folmer et al. 1994).  Amplification was facilitated using a Bio-Rad T100Thermocycler with GoTaq Hot Start Green Master Mix. Cycling conditions were: 10 min at 95 °C; 35 cycles of 30 sec at 95 °C, 1 min at 47 °C and 1 min at 72 °C; and 10 min at 72 °C. PCR product quality and quantity was assessed by 2% agarose gel electrophoresis and subsequently sequenced by Eurofins Genomics. DNA sequences obtained were compared to a reference database library using the Basic Local Alignment Search Tool (BLAST) (Altschul et al. 1990) available at the National Center for Biotechnology Information (NCBI) and Bold Systems Identification engine for CO1 gene. 

The abundance of each zooplankton group was estimated accounting for all sample dilution and extrapolated based on the calculated initial net sampling volume.  No further data processing was involved.  All data was reviewed by at least one other expert.  If outliers were identified all calculations were confirmed and in cases where errors were not obvious the sample was re-counted.

BCO-DMO Processing Notes:
Version 1 [2017-04-28]: (2015 data)
- added conventional header with dataset name, PI name, version date
- modified parameter names to conform with BCO-DMO naming conventions
- blank values were replaced with no data value 'nd'
- added columns for cruise id, station, date, time, lat, lon, volume filtered, cast, replicate, splits, taxon_1
Version 2 [2020-02-24] (2015-2017 data)
- added conventional header with dataset name, PI name, version date
- modified parameter names to conform with BCO-DMO naming conventions
- blank and ND values were replaced with 'nd'
- date was converted to yyyy-mm-dd and ISO_DateTime_UTC was added
- "Jekyll  Is" was replaced with "Jekyll Is" (one space between words)
- replaced blanks with zeroes in 'splits' column
Version 3 [2020-04-08] (2015-2017 data; includes lats/lons)
- added conventional header with dataset name, PI name, version date
- modified parameter names to conform with BCO-DMO naming conventions
- blanks, NO DATA, and ND values were replaced with 'nd'
- date was converted to yyyy-mm-dd and ISO_DateTime_UTC was added
- latitude and longitude were converted from degrees, minutes, seconds to decimal degrees.
 

Project description from NSF award abstract:
Gelatinous (soft-bodied) zooplankton can play a crucial role in food webs and in cycling of materials in the world's oceans, and it has been suggested that they may become even more important in the future. However, because they are so difficult to study, gelatinous species remain poorly understood. This is especially true for smaller filter feeding gelatinous animals such as pelagic tunicates (salps, larvaceans, and doliolids). For example, it remains unclear what and how much these abundant filter feeders eat in nature and who eats them. This project will address this large and significant knowledge gap by using a combination of new and traditional methods to investigate the diet of the gelatinous pelagic tunicate Dolioletti gegenbauri, a species common on productive continental shelves such as the South Atlantic Bight. This project will also help train the next generation of ocean scientists to be competent in classical biology, modern molecular biology, and ecosystem modeling. Training will also focus on increasing representation of African Americans in the future science, technology, engineering, and math (STEM) workforce.

This study will provide the first quantitative estimates of the in situ diet of a key continental shelf gelatinous zooplankton species, the doliolid Dolioletta gegenbauri. Large blooms of doliolids have the potential to control the trophic structure of shelf pelagic ecosystems by shunting primary production to the microbial food web and by limiting copepod production via the consumption of their eggs. The long-term objective is to understand the ecological role and significance of doliolids in continental shelf pelagic ecosystems, specifically the underlying processes that lead to their high level of spatial and temporal patchiness. The basic questions to be addressed here include: What do doliolids eat, in situ, at different life stages? Are early life stages of larger metazoans important components of their diets? Do doliolids act as trophic cascade agents promoting primary production and phytoplankton diversity? Because of methodological challenges, there have not yet been definitive studies addressing these fundamental questions. In this project, the investigators will conduct field-based studies that will combine state-of-the art molecular techniques with more traditional methods in zooplankton ecology to answer questions about trophic interactions. Monthly oceanographic expeditions in the South Atlantic Bight will allow the research team to study wild doliolids at different time points in their life cycle and under different plankton bloom conditions. Application of recently developed molecular diagnostic assays will enable the quantitative description of the diversity and quantity of prey consumed, unbiased by experimental manipulation. Additional experimental and theoretical modeling will allow the investigators to link these data with larger ecological significance and scale.