Taxon-specific fine-scale distribution, abundance, and environmental affinity of gelatinous zooplankton during Fall, Spring, and Summer in the northern Gulf of Mexico, 2015-10-30 to 2016-07-26
Number of Cold Storage Files:
Cold Storage File Size:
csv, R, tif
Gulf of Mexico Research Initiative (GoMRI)
University of Southern Mississippi / Department of Coastal Sciences
2015-10-30 to 2016-07-26
jellyfish, zooplankton, environmental affinity, habitat partitioning, taxon-specific abundace, taxon-specific distribution, gelatinous zooplankton, In-situ Ichthyoplankton Imaging System (ISIIS)
The dataset examines the fine-scale patterns of distribution, abundance, and environmental affinities of different gelatinous zooplankton taxa in three different seasons - Fall (October 30, 2015) Spring (March 30 and April 4, 2016) and Summer (July 26, 2016), along a ~60 km transect south of Perdido Bay, Florida. As part of the CONCORDE field sampling campaign, an in situ imaging system (ISIIS) was used to sample along 3 north to south transects spanning about 54 km. This dataset examines the eastern-most transect for fine-scale distribution, abundances, and environmental affinities of 26 gelatinous zooplankton taxa within five major groups: hydromedusae, ctenophores, siphonophores, salps, and doliolids. Particles above a 2000 pixel size threshold (~3.3 mm equivalent spherical diameter) were automatically extracted and manually identified with the highest taxonomic resolution possible (in many cases, to genus level). The ISIIS collected images of plankton were merged with high-resolution physical oceanographic using the nearest time stamp. The goal of the study was to describe patterns of spatial distribution and abundance, as well as to establish taxon-specific environmental affinities of the gelatinous zooplankton community within and among seasons. This information is useful for understanding potential oil exposure rates for different organisms inhabiting the shelf ecosystem.
Chiaverano, Luciano, Adam Greer, Valerie Cruz, Olivia Lestrade, Christian Biseno-Avena, Frank Hernandez, Monty Graham, and Robert Cowen. 2021. Taxon-specific fine-scale distribution, abundance, and environmental affinity of gelatinous zooplankton during Fall, Spring, and Summer in the northern Gulf of Mexico, 2015-10-30 to 2016-07-26. Distributed by: Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC), Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/n7-eftc-7p89
The goal of the study was to describe patterns of spatial distribution and abundance, as well as to establish taxon-specific environmental affinities of the gelatinous zooplankton community to understand potential oil exposure rates for different groups inhabiting the shelf ecosystem.
Data Parameters and Units:
The folder named “Zooplankton Data (.csv and R-script files)” contains count data (files with “BioPhys” in their name, csv files) and abundance data (files with “concentration” in their names, csv files) per taxa paired with physical data, as well as R-script files with the codes used to process the raw data. There is one R-script file per main taxonomic group (ctenophora, siphonophora, hydromedusae, and tunicates), per transect (one transect in the Fall, two transects in Spring, and one transect in Summer). The folder named “Classified zooplankton images” contains subfolders with images taken by the ISIIS. The images represent segments extracted from raw images, and each segment represents, in most cases, one zooplankton individual. Segment folders are sorted by season. Folders named “ECorr XXXXX All zooplankton 3mm-12cm” contain all the image segments classified into taxonomic groups for this study, while the rest of the folders only contain the classified segments that corresponded to gelatinous zooplankton. Description of columns in “biophys” csv files: Nearjul: nearest Julian time in the physical dataset used to merge with biological data, Julian: julian time of the biological data(CDT), ID: final taxonomic identification, Other: broader taxonomic classification, Junk: N/A, Label: image file name, Slice: image number within an image stack of 430 images, Xloc = x pixel location within the larger frame, Yloc = y pixel location within the larger frame, Width = width of bounding box (pixels), Height = height of bounding box (pixels), UTC: time, timestamp: same as “label”, Alt: distance from benthos (m), Temp: temperature (Celsius degrees), Depth (m), Flour: chlorophyll-a fluorescence (raw voltage), Fvel: forward velocity (m/sec), 0 indicates unreliable reading from Doppler Velocity Log (DVL), Heading: heading of the ISIIS vehicle (degrees), 02: oxygen concentration (invalid conversion to mg L - this conversion is made correctly in the R script), O2 volts (volts), PAR: photosynthetic active radiation(micro Einsteins/cm^2), Parvolts (volts), Pitch: pitch of ISIIS vehicle (degrees), Roll: roll of the ISIIS vehicle (degrees), Salinity (ppt), Lat = latitude (decimal degrees), Lon = longitude (decimal degrees), vertvel: vertical velocity (cm/sec), altok: binary variable that indicates if altitude data are valid (1-valid, 0-error), 02delay: oxygen in volts from the physical dataset, oxygen: oxygen concentration (mg / L). Note: we used the formula supplied by the oxygen sensor (Seabird electronics) to convert the oxygen voltage, temperature, salinity, and depth to dissolved oxygen concentration. Units were converted to mg/L by dividing the oxygen the mL/L concentration values by 0.75189 (see ICES unit conversion). The values for “O2” are incorrect due to an error in the software that converts the voltage. The appropriate conversions were made in the R scripts. Description of columns in “concentration” .csv files: Rdist: distance travelled by the ISIIS (m) from an initial reference point (distance zero). Each row on this column represents a different “transect bin”, each one of 19.25 m in length. This length is roughly equivalent to a sampled volume of 1 m^3 by the ISIIS. ID: taxonomic identification, mjul: mean julian time, pco: number of individuals per m3 (abundance), mdepth: mean depth (m), msal: mean salinity, mtemp: mean temperature (degrees Celsius), mlat: mean latitude, mfluor: mean chlorophyll-a fluorescence (raw voltage), moxyg: mean oxygen concentration (mg / L). ID codes (csv files): Hydromedusae: Aglantha: Aglantha elata, Aglaura: Aglaura hemistoma, Clytia: Clytia spp, Corymorpha: Corymorpha nutans, Eutima: Eutima variabilis, Halicreas: Halicreas sp (?), Liriope: Liriope tetraphylla, Octophialucium: Octophialucium spp, Pegantha: Cunina sp (?), Proboscidactyla: Proboscidactyla ornata, Solmaris: Solmaris sp, Solmundella: Solmundella bitentaculata. Ctenophores: Lobate: Mnemiopsis leidyi, Nuda: Beroe sp, Cydippid: Pleurobrachia sp., Venus: Cestum sp. Siphonophores: SiphoA: Abylopsis tetragona, SiphoB: Lensia sp (?) (eudoxid stage), SiphoC: Nanomia bijuga, Sipho D: Lensia sp (?) (poligastric stage), SiphoE: Spheronectes gracilis, SiphoF: Muggiaea kochi. Tunicates: Doliolid: Doliolum intermedium, Salp: all salps (all species included). Codes in images: Each image name follows the same format. For example: “chaeto_Plankton_20160726112037.919.tif_323_396_64_101_88”. This translates into : “ID_Plankton_YYYYMMDDHHMMSS.SSS. tif_Slice_xpos_ypos_xlength_ylength” - where the YYYY = year, MM = month, DD = day, HH = hour, MM = minute, SS.SSS = seconds to nearest thousandths of a second of the time of the first image in the image stack. The closer “ID” is to “Plankton”, the broader the classification category is. Note some files have two or more “ID” categories before “Plankton” in their names. Anemone: pelagic anthozoan larvae, Chaeto: chaetognaths, Cteno: ctenophores, Diatom: diatom chain, Fish: fish larva, Heterop: Heteropoda larva, Hydro: hydromedusa, Marinesnow: marine snow, Other: other zooplankton, Sipho: siphonophora, schlie: Schlieren effect in images, Shrimp: decapod shrimp, Salp: pelagic tunicate (salps and doliolids), Stoma: Stomatopoda larva, Unk: unknown, unidentifiable object. Slice is the frame number within the image stack. Xpos and ypos are the x and y position of the segment within the image. Xlength and ylength are the lengths (in pixels) of the box bounding the segment in the image.
Data collection: The ISIIS was towed behind the ship at a speed of ∼5 knots (matching the scan rate of the line scan camera) in a tow-yo fashion. Using motor-actuated wings, the vehicle moved between different depths or at one constant depth, as controlled by a shipboard operator.
All images and physical data were collected by the In-situ Ichthyoplankton Imaging System (ISIIS). The ISIIS vehicle contains a suite of instruments that collect salinity, temperature, depth (Sea-Bird Electronics 49 Fastcat CTD), dissolved oxygen (SBE 43), chlorophyll-a fluorescence (Wetlabs Eco FL-RT), PAR (QCP2300), and speed through the water via a Doppler velocity log (DVL, Navquest 600). All of these sensors acquired data at a rate of at least 4 Hz.