Shadowed Image Particle Profiling Evaluation Recorder (SIPPER) Plankton Abundance Data from Northern Gulf of Mexico, 2012
Funded By:
Gulf of Mexico Research Initiative
Funding Cycle:
Florida Institute of Oceanography (FIO)
Research Group:
Baseline for Impact Assessment of Zooplankton and Imaging Oil Droplet Detection on the West Florida Shelf
Kendra Daly
University of South Florida / College of Marine Science
kdaly@usf.edu
zooplankton, phytoplankton, plankton, suspended particles, detritus, marine snow, larval fish, abundance, density, distribution, lower trophic food web
Abstract:
Phytoplankton, zooplankton, and larval fish abundance and distributions were collected from the Northern Gulf of Mexico using the SIPPER (Shadowed Image Particle Profiling Evaluation Recorder) camera imaging system on 2 cruises in Spring 2012. This dataset also includes water quality and chemistry data collected during cruises. This data was collected to assess changes in plankton distribution and abundance.
Suggested Citation:
Daly, Kendra. 2015. Shadowed Image Particle Profiling Evaluation Recorder (SIPPER) Plankton Abundance Data from Northern Gulf of Mexico, 2012. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N78P5XFP
Publications:
Purpose:
To assess the seasonal and interannual changes in zooplankton abundance and distribution after the Deepwater Horizon oil spill.
Data Parameters and Units:
Date (local and GMT), time (local and GMT), Latitude (degrees minutes), Longitude (degrees minutes), station, depth of tow (m), volume filtered (m3), marine snow, phytoplankton, and zooplankton abundance of species and taxa (number/m3) (major taxa include: cladoceran, copepod, eumalacostracan, ostracod, echnioderm, mollusc, diatoms, polychaete, protist), temperature (degrees Celsius), salinity, density (kg/m3), fluorescence (mg/m3), fluorescence sensor (volts), oxygen (ml/L), oxygen (umol/kg), transmisivity (% light), turbidity (NTU), CDOM fluorescence ppb QSD
Methods:
The SIPPER camera imaging system was developed by the University of South Florida, Center for Ocean Technology and described in Samson et al. (2001) and Remsen et al. (2004). The towed platform carried several environmental sensors (CTD, oxygen, chlorophyll fluorescence, transmissometer: see Supplemental Information- Instruments). SIPPER used a high speed Dalsa Piranha-2 line-scan camera and a pseudo-collimated LED generated light sheet to image the shadows and outlines of resolvable particles that passed through a 100 cm2 field of view. The operational optical resolution of the system is ~65 m. SIPPER was towed at speeds between 2-3 knots in an oblique profile through the water column, spending approximately equal amounts of time at each meter of depth between the surface and 300 m. At stations with a bottom depth shallower than 300 m, SIPPER was towed within approximately 5 m from the seafloor. Imaging and environmental data were stored internally on a Firewire hard drive and processed upon retrieval of the SIPPER instrument from a deployment using a customized software package called the Plankton Image Classification and Extraction Software (PICES). PICES was used to extract images of interest, classify them using user-specified training libraries and to manage the SIPPER images and environmental data collected. Currently, the PICES manages information for over 137 million SIPPER images. SIPPER and environmental data are reported by cruise in excel files. Each deployment is reported in a separate tab in cruise files. Every SIPPER deployment data sheet shows the same set of classes in order to evaluate the spatial and temporal variability of image classes. Zero abundances in any class means that no images were observed for those classes. The SIPPER data are from the downcast, unless otherwise noted. Environmental data are reported to the far right of the SIPPER abundance data in the excel spreadsheet.There are several types of images classes: (1) dual classifier classes, (2) rare or uncommon classes, and (3) other image classes resulting from the dual classification. Examples of images for these classes are available on http://www.marine.usf.edu/zooplankton/. (1) Dual Classifier Classes. The following training library classes were used in at least one of the final dual classifications. These 25 classes had numerous images in at least one or more deployments. These were the more common classes that made up about 90% of the images. (2) Rare or uncommon classes. The following classes were rare or uncommon classes used in the comprehensive MFS classifier run (Step 3). These classes were all manually validated. This process was done to identify and label true positive examples of rare and uncommon image classes before running the final dual classification, which only identified common classes. (3) Other Image Classes. There are several image classes that only result from running the dual classifier using a hierarchical naming schema. The image classes below are populated by images that result from a disagreement between the two classifiers in the dual classifier where the two guesses share part of the class name in common. These images are then classified to the level of agreement within the naming structure. An example might be when a classifier could not agree between crustacean_ostracod and crustacean_cladoceran_evadne. Both guesses share the 1st order root crustacean in common, so the dual classifier would classify such an image as crustacean.
Instruments:
SIPPER Environmental Sensors: Environmental data were collected simultaneously with the SIPPER imaging system during each deployment. Sensors included a Seabird 19Plus CTD, Seabird SBE43 oxygen sensor, and WET Labs FLNTURTD chlorophyll fluorescence and turbidity, and a transmissometer. AWET Labs CDOM sensor also was used on a few cruises. Sensors were calibrated at Seabird and WET Labs and then integrated into the SIPPER towed platform.