IS14D:
Moving Beyond Technology: How Quantitative Image-Based Methods Help Reveal Ocean Ecology II Posters

Session ID#: 85212

Session Description:
Over the past few decades, numerous methods (high-resolution optical or acoustic imaging) have been developed to image organisms and marine snow. These methods are typically used to detect, measure, and enumerate organisms and particles from samples, or directly in situ. The increasing use of imaging systems has permitted description of planktonic communities with unprecedented levels of spatial and temporal resolution, together with their linkages with biogeochemical cycles and environmental constraints.

However, beyond the technological challenge of obtaining high quality images for scientific purposes, there is a need to scale up such measurements to obtain globally standardized observations, aided by advanced Machine Learning methods for image classification.

These developments will bring significant challenges for the coming years: 1) management,  integration, and cross-calibration of the massive data flow originating from a network of different instruments; 2) automation of the classification of objects into taxonomic/morphological categories of scientific interest and import; 3) processing of data in near-real time, in particular for sensors embedded in autonomous platforms; 4) provision of collaborative pathways to visualize, annotate, quality control, and share the resulting data; and 5) integration of such data with existing multidisciplinary environmental sciences databases.

 

We invite presentations focusing on imaging and Machine Learning methods, but extending beyond pure technological challenges, in order to provide insights into ecological and biogeochemical processes in the ocean environment.

Co-Sponsor(s):
  • ME - Marine Ecology and Biodiversity
  • OB - Ocean Biology and Biogeochemistry
Index Terms:

1942 Machine learning [INFORMATICS]
4855 Phytoplankton [OCEANOGRAPHY: BIOLOGICAL]
4890 Zooplankton [OCEANOGRAPHY: BIOLOGICAL]
4894 Instruments, sensors, and techniques [OCEANOGRAPHY: BIOLOGICAL]
Primary Chair:  Fabien Lombard, Sorbonne University, Laboratoire d'Oceanographie de Villefranche sur Mer, Villefranche Sur Mer, France
Co-chairs:  Mark D Ohman, Scripps Institution of Oceanography, UC San Diego, La Jolla, CA, United States, Heidi M Sosik, Woods Hole Oceanographic Institution, Woods Hole, MA, United States and Anya M Waite, Ocean Frontier Institute, Dalhousie University, Halifax, NS, Canada
Primary Liaison:  Fabien Lombard, Sorbonne University, Laboratoire d'Oceanographie de Villefranche sur Mer, Villefranche Sur Mer, France
Moderators:  Mark D Ohman, University of California San Diego, Scripps Institution of Oceanography, La Jolla, CA, United States and Heidi M Sosik, Woods Hole Oceanographic Institution, Woods Hole, MA, United States
Student Paper Review Liaison:  Fabien Lombard, Sorbonne University, Laboratoire d'Oceanographie de Villefranche sur Mer, Villefranche Sur Mer, France

Abstracts Submitted to this Session:

 
Quantitative size and biomass distributions from particle images: An improved algorithm applied to IFCB observations (652440)
Heidi M Sosik1, Emily Peacock1, E Taylor Crockford1, Kevin Archibald2, Bethany Fowler3 and Alexi Shalapyonok1, (1)Woods Hole Oceanographic Institution, Woods Hole, MA, United States, (2)University of California Santa Barbara, Department of Ecology, Evolution, and Marine Biology, Santa Barbara, United States, (3)Woods Hole Oceanographic Institution, Biology, Woods Hole, MA, United States
 
Leveraging Unsupervised Methods to Train Image Classification Networks with Fewer Labelled Inputs: Application to Species Classification of Phytoplankton Imagery from an Imaging Flow Cytometer (656929)
Emmett Culhane, Yale University, New Haven, CT, United States, Nils Haëntjens, University of Maine, Orono, ME, United States, Alison P Chase, University of Maine, School of Marine Science, Orono, ME, United States, Peter Gaube, Applied Physics Laboratory at the University of Washington, Air-Sea Interaction and Remote Sensing, Seattle, WA, United States and Jason Morrill, University of Maine, Orono, United States
 
Automated observations of phytoplankton communities from open water moorings (656167)
Andrew David Barton1, Uwe Send2, Alexi Shalapyonok3, Romain Heux4, Alaina Smith5, Paul Chua5 and Heidi M Sosik3, (1)Scripps Institution of Oceanography, Section of Ecology, Behavior and Evolution, La Jolla, CA, United States, (2)University of California San Diego, Scripps Institution of Oceanography, La Jolla, United States, (3)Woods Hole Oceanographic Institution, Woods Hole, MA, United States, (4)Scripps Institution of Oceanography, La Jolla, CA, United States, (5)Scripps Institution of Oceanography, La Jolla, United States
 
Morphological Diversity of Phytoplankton: Identification of Traits, Morphological Succession and Periodicities from Imagery in Narragansett Bay, U.S. (651856)
Virginie Sonnet, University of Rhode Island, Graduate School of Oceanography, Narragansett, RI, United States, Lionel Guidi, Laboratoire d'Océanographie de Villefranche (LOV), UMR 7093, Sorbonne Université, Villefranche-sur-Mer, France, Colleen B Mouw, University of Rhode Island, Narragansett, RI, United States and Sakina-Dorothée Ayata, LOV UPMC/CNRS, Villefranche sur mer Cedex, France
 
Contributing datasets from the Imaging Flow Cytobot for Essential Ocean Variables (647133)
Katherine Qi1,2, Stace Beaulieu3, Joe Futrelle4, Emily Peacock4 and Heidi M Sosik4, (1)University of California San Diego, La Jolla, United States, (2)Woods Hole Oceanographic Institution, Woods Hole, United States, (3)Woods Hole Oceanographic Institution, Biology, Woods Hole, MA, United States, (4)Woods Hole Oceanographic Institution, Woods Hole, MA, United States
 
Optical and Environmental Signatures of Cochlodinium polykrikoides in Narragansett Bay, Rhode Island (657302)
Jessica Carney1, Colleen B Mouw2, Audrey Ciochetto2 and Jan Rines1, (1)University of Rhode Island, Graduate School of Oceanography, Narragansett, RI, United States, (2)University of Rhode Island, Narragansett, RI, United States
 
Observing and understanding harmful algal blooms using autonomous underwater imaging (650721)
Kasia M Kenitz1, Eric Coughlin Orenstein2, Paul Roberts2, Peter J. S. Franks3, Jules S Jaffe1, Melissa Carter1 and Andrew David Barton4, (1)Scripps Institution of Oceanography, La Jolla, CA, United States, (2)Monterey Bay Aquarium Research Institute, Moss Landing, United States, (3)Scripps Institution of Oceanography, La Jolla, United States, (4)Scripps Institution of Oceanography, Section of Ecology, Behavior and Evolution, La Jolla, CA, United States
 
Structure and Dynamics of Pico-, Nano- and Microplankton by Combining Together Flow Cytometry Data and Imaging (651088)
Gerald Gregori1, Tina Silovic2,3, Melilotus Thyssen1 and Michel Denis1, (1)Aix Marseille University, CNRS, Mediterranean Institute of Oceanography, Marseille, France, (2)Aix Marseille University, Mediterranean Institute of Oceanography, Marseille, France, (3)Cytobuoy b.v., Woerden, Netherlands
 
Global plankton diversity and size structure revealed by quantitative imaging approaches during the Tara Oceans expeditions (647816)
Fabien Lombard1, Fererico Ibarbalz2, Manoela Brandão3,4, Severine Martini5, Nicolas Henry6, Fabio Benedetti7,8, Amanda Elineau9, Laetitia Jalabert9, Marc Picheral5, Lars Stemmann10, Lucie Zinger2, Chris Bowler11 and G Gorsky12, (1)Sorbonne University, Laboratoire d'Oceanographie de Villefranche sur Mer, Villefranche Sur Mer, France, (2)Ecole Normale Supérieure Paris, Institut de biologie de l’École normale supérieure (IBENS), Paris, France, (3)Sorbonne université, Laboratoire d'océanographie de villefranche sur mer, Villefranche sur mer, France, (4)IFREMER, Centre Bretagne, Unité Dynamiques des Ecosystèmes Côtiers, Plouzané, France, (5)Laboratoire d’Océanographie de Villefranche (LOV), UMR 7093, Sorbonne Université, Villefranche-sur-Mer, France, (6)Sorbonne Université, CNRS, Station Biologique de Roscoff, Roscoff, France, (7)ETH Zurich Swiss Federal Institute of Technology Zurich, Zurich, Switzerland, (8)Sorbonne Université, Laboratoire d'Océanographie de Villefranche sur Mer, Villefranche Sur Mer, France, (9)Sorbonne Université, Institut de la Mer de Villefranche (IMEV), France, (10)Laboratoire d’Océanographie de Villefranche (LOV), UMR 7093, Sorbonne Université, Villefranche sur mer, France, (11)Ecole Normale Supérieure, Institut de Biologie/Ecology and Evolutionary Biology Section, Paris, France, (12)CNRS, Laboratoire d'Océanographie de Villefranche-sur-Mer, Villefranche-sur-Mer, France
 
Analyzing Spatial Variations of Zooplankton Community Size Structures on the Northeast US Shelf (657294)
Jonathan Low1, Sarah G Glancy2, Emily Peacock2, Heidi M Sosik2 and Joel Llopiz3, (1)University of Tampa, Biology, Tampa, FL, United States, (2)Woods Hole Oceanographic Institution, Woods Hole, MA, United States, (3)Woods Hole Oceanographic Institution, Woods Hole, United States
 
Allometric estimates of midwater zooplankton metabolism and vertical flux from image data (641104)
Hannah Gossner, Bermuda Institute of Ocean Sciences - Arizona State University, Julie Ann Wrigley Global Futures Laboratory, St.George's, Bermuda, Dr. Amy E Maas, PhD, Bermuda Institute of Ocean Sciences, St.George's, Bermuda and Leocadio Blanco Bercial, Bermuda Institute of Ocean Sciences, Arizona State University, St. George's, Bermuda
 
Mesozooplankton predator-prey interactions: encounter rates and variable Diel Vertical Migration as detected by Zooglider (656649)
Benjamin Michael Whitmore, Scripps Institution of Oceanography, UCSD, La Jolla, CA, United States and Mark D Ohman, Scripps Institution of Oceanography, La Jolla, CA, United States
 
High-resolution sampling of a broad marine life size spectrum to examine shelf biophysical coupling (646199)
Adam T Greer1,2, Alexis C Hagemeyer3,4, John C Lehrter3,5, Malcolm McFarland6, Aditya R Nayak6, Nicole Stockley6, Benjamin Michael Binder7, Ana E Rice8, Kevin M Boswell7, Igor Shulman8, Sergio DeRada8 and Bradley Penta8, (1)The University of Southern Mississippi, Division of Marine Science, Stennis Space Center, MS, United States, (2)Skidaway Institute of Oceanography, Marine Sciences, Savannah, GA, United States, (3)Dauphin Island Sea Lab, Dauphin Island, AL, United States, (4)University of South Alabama, Marine Sciences, Mobile, AL, United States, (5)University of South Alabama / Dauphin Island Sea Lab, Dauphin Island, AL, United States, (6)Florida Atlantic University, Harbor Branch Oceanographic Institute, Fort Pierce, FL, United States, (7)Florida International University, Biological Sciences, North Miami, FL, United States, (8)Naval Research Laboratory, Stennis Space Center, MS, United States
 
Bottom focused cameras on the OOI Endurance Array and their potential value to ocean ecology (652615)
Chris Holm, Oregon State University, CEOAS, Corvallis, OR, United States, Kristin Politano, Oregon State University, Integrative Biology, Corvallis, OR, United States, Jonathan P Fram, Oregon State University, College of Earth, Ocean, and Atmospheric Sciences, Corvallis, OR, United States and Edward Paul Dever, Oregon State University, Corvallis, OR, United States
 
A Novel Real-Time Monitoring System for Coral Larvae Detection Using In Situ Imaging (657600)
Alessandra Gomes, Leandro Ticlia de la Cruz and Rubens Mendes Lopes, University of Sao Paulo, Department of Biological Oceanography, Sao Paulo, Brazil