25 May 2018 On plankton distributions and biophysical interactions in diverse coastal and limnological environments
Author Affiliations +
Digital holography provides a unique perspective towards studying aquatic particles/organisms. The ability to sample particles in undisturbed conditions, coupled with the ability to generate 3-D spatial distributions is currently unmatched by any other technique. To leverage these advantages, field experiments with the goal of characterizing aquatic particle properties in situ, were conducted using a submersible holographic imaging system. Diverse aquatic environments were sampled over 3 separate deployments between 2014 and 2017. The areas included: (a) The Gulf of Mexico (GoM), in the vicinity of the Mississippi river plume; (b) Lake Erie; and (c) East Sound in the US Pacific Northwest. A database of more than two million different types of particles in the 10-10000 m size range, was created after processing > 100,000 holograms. Particle size distributions (PSDs) exhibited a Junge-type distribution when characterized by size grouping into logarithmically spaced bins. Particles/plankton were also classified into different groups (e.g. diatoms, copepods). Results presented will be broadly grouped into two parts: (a) PSDs at different depths within the water column during the occurrence of a Microcystis bloom at Lake Erie and individual cell counts within these colonies; and (b) Vertical structure of plankton in East Sound, specifically the presence of diatom thin layers. Finally, the rich diversity in species composition in the GoM and successful data collection towards creating a training set to implement automated classification routines will be briefly discussed.
Conference Presentation
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Aditya R. Nayak, Aditya R. Nayak, Malcolm N. McFarland, Malcolm N. McFarland, Michael S. Twardowski, Michael S. Twardowski, James M. Sullivan, James M. Sullivan, "On plankton distributions and biophysical interactions in diverse coastal and limnological environments", Proc. SPIE 10631, Ocean Sensing and Monitoring X, 106310P (25 May 2018); doi: 10.1117/12.2309798; https://doi.org/10.1117/12.2309798

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