USING THE IMAGING FLOW CYTOBOT (IFCB) TO BETTER UNDERSTAND PARTICLE SIZE DISTRIBUTION AND BLOOM DYNAMICS IN CENTRAL CALIFORNIA. Kendra Hayashi and Raphael Kudela University of California, Santa Cruz, Santa Cruz, CA Introduction Imaging flow cytobots (IFCBs) are powerful tools for understanding bloom dynamics in marine and freshwater environments. In addition to autonomously generating high resolution images, particle size and volume are derived during image analysis and provide important components to assessing the ecology of aquatic systems. Particle size distribution (PSD) is critical for calculating radiative transfer and often drives trophic dynamics. Here we use PSD derived from estimated spherical diameter (ESD) calculated from IFCB images to assess IFCB performance and phytoplankton community dynamics at the Santa Cruz Wharf (SCW) and San Francisco Bay (SFB). IFCB settings and PSD Conclusions Universal PMT settings on IFCBs do not yield similar results; each instrument must be optimized for its deployment environment and specific data acquisition requirements. Over the 3 years analyzed, PSDs in SFB appeared to be stable and consistently follow a power law model, even in the central bay where ocean water and tidal mixing strongly influence the phytoplankton community. Variations from the global mean are associated with unusual events in a geographic location. Unlike SFB, the SCW PSDs are less consistent with a fair amount of daily variation complicating simple analyses of PSDs. SCW PSDs reflect an increase of dinoflagellates in the phytoplankton community documented in 2018 (Fisher et al. 2020) and continuing to the present. The dinoflagellate “signature” is seen at all levels of the data (from individual samples to global averages). IFCBs are being used more widely, with automated image classification lagging as the image libraries are being built and tested. PSDs could be a quick and easy way to assess phytoplankton community dynamics in novel locations as we wait for the classifiers to come online. They could also be used as a rapid QA/QC test to assess data quality of larger datasets. Literature Cited • Fisher et al. 2020. Return of the “age of dinoflagellates” in Monterey Bay: Drivers of dinoflagellate dominance examined using automated imaging flow cytometry and long- term time series analysis. Limnol. Oceanogr. 65: 2125-2141. • Reynolds et al. 2010. Measurements and characterization of particle size distributions in coastal waters. JGR. 115: C08024. • Zhou et al. 2022. _fdapace: Functional Data Analysis and Empirical Dynamics_. R package version 0.5.9, https://CRAN.R-project.org/package=fdapace. Acknowledgments Thank you to John Negrey and the Kudela Lab for comments, suggestions, and statistical analysis (JN). This work was supported by Cal-HABMAP which represents multiple organizations and partners who contribute to the operation and maintenance of the IFCB network. Core funding has been provided by NOAA, including the IOOS, ECOHAB, and MERHAB programs, NASA, California Sea Grant, California Ocean Protection Council, and numerous in-kind contributions from our partners and stakeholders. Initial purchase and development of the IFCBs was supported by NA16NMF4270263 (Saltonstall Kennedy) and NA14NOS0120148 (NOAA OTT). Results • IFCBs detected varying sizes of microspheres as expected based on the specifications of the instrument (Fig 1) • The IFCBs performed similarly to other particle imaging systems (Reynolds et al. 2010). • ESD measurements of the beads were different from the expected values but were consistent within any given size. • Two instruments sampling side by side with identical PMT values yielded different PSDs and phytoplankton communities (Fig 2). • Sensitive PMT settings increase the ESD range and detect higher numbers of smaller particles (Fig 2a). • PMT settings strongly influence the phytoplankton community structure (Fig 2b). Results SCW PSDs do not consistently follow a simple power law