DOI: 10.5061/dryad.f4qrfj732
title: Prey morphotype and abundance controls plastid retention and bloom dynamics for a mixotrophic dinoflagellate

description: Dinophysis is an obligate mixotroph that relies on consumption of the
 ciliate, Mesodinium rubrum, to grow and form harmful algal blooms (HABs).
 In this study, blooms of Dinophysis acuminata in two NY, USA, estuaries
 were studied over the course of three years (2019-2021) using discrete
 samples and an Imaging FlowCytobot (IFCB) to capture images of plankton
 20-150 mm. The darkness of Dinophysis images on the IFCB was used to
 quantify the “fullness” or feeding state of Dinophysis cells. Culture
 experiments performed to ground truth this approach revealed a highly
 significant correlation (R=0.98; p&lt;0.001) between the darkness of
 Dinophysis cells and the abundance of Mesodinium. With a quantitative
 scale developed to track the fullness of Dinophysis cells, ecosystem
 observations revealed the percentage of “full” Dinophysis cells increased
 during blooms of a large-morphotype Mesodinium that preceded the
 initiation of Dinophysis blooms. A smaller morphotype Mesodinium appeared
 during Dinophysis bloom peaks suggesting they supported bloom maintenance.
 While the relative abundance of diatoms was elevated before Dinophysis
 blooms, other dinoflagellates and tintinnids increased in abundance during
 these HABs indicating they emerged within a consortium of heterotrophs and
 mixotrophs that may have collectively filled the same open niche as
 Dinophysis. This study reveals the manner in which different Mesodinium
 populations co-bloom with Dinophysis to support plastid acquisition, bloom
 initiation and bloom maintenance and contextualizes these changes within
 the larger plankton community succession associated with these HABs.
description: Water from Cold Spring Harbor (40.863374° N, -73.46334° W) and
 Northport Harbor (40.899593° N, -73.35302° W; Figure S1) was collected
 weekly prior to the onset of the <em>Dinophysis</em> blooms
 (May) and continued through the demise of the blooms (July-August) in
 2019, 2020, and 2021. Temperature, salinity, and
 dissolved oxygen were measured on site with a YSI 556 handheld
 sonde. To prepare samples for IFCB analyses, 1 L of
 water was gently concentrated on a 20 mm sieve to ensure cells were never
 dried and resuspended into 15 mL or 40 mL of filtered seawater.
 Concentrated, 3 mL live samples were analyzed with IFCB configured to
 capture images of targets that exceeded trigger thresholds on light
 scattering (side angle) or chlorophyll a fluorescence.
 Images were analyzed with the ifcb-analysis MATLAB code package
 (Sosik and Olson 2007, Sosik et al. 2016). Taxa were
 identified to lowest possible taxonomic level and were broadly grouped
 into diatoms, dinoflagellates (excluding <em>Dinophysis</em>),
 aloricate ciliates (excluding <em>Mesodinium</em>),
 tintinnids, larval zooplankton, and rotifers. Relative abundances of these
 taxa as well as <em>Mesodinium</em> and
 <em>Dinophysis</em> were calculated relative to the total
 plankton count. Two types of <em>Mesodinium</em> were
 identified and classified based on size (small: ~10 mm, large:
 ~25mm). Used the feature
 "texture_average_gray_level" (TAGL) as a proxy
 for <em>Dinophysis</em> feeding. The TAGL can rangefrom 0-255
 where 0 is black and 255 is white. All <em>Dinophysis</em>
 images during this study ranged from 51 to 204 on this scale and were,
 therefore, binned into three levels that provided near equal observations
 across the bins; 51-100 (full), 100-110 (partially full), 110-204
 (partially empty; Figure 1). The average TAGL for each
 <em>Dinophysis</em> imaged on each date was then sorted into
 one of the three levels and the percentage of the total images that were
 within each level was determined. A
 <em>Dinophysis acuminata </em>strain isolated from
 Meetinghouse Creek, NY, (DANY; Hattenrath-Lehmann and Gobler, 2015;
 Hattenrath-Lehmann et al., 2021; Ayache et al., 2023) was fed
 <em>Mesodinium rubrum</em> (strain JAMR) that was fed
 <em>Teleaulax amphioxia</em> (strain JATA), both isolated from
 Inokushi Bay, Oita Prefecture, Japan, in 2007 (Nishitani et al., 2008).
 All cultures were kept in f/2 media at salinity 25 and18 °C with ~80 µEin
 m<sup>-2</sup> s<sup>-1</sup> on a 12:12
 light:dark cycle. DANY was fed JAMR <em>ad libitum</em> prior
 to the first day of IFCB sampling. After one week, all
 <em>Mesodinium</em> were removed from the culture with a 20-mm
 sieve. IFCB samples were obtained and analyzed in triplicate using side
 scattering and chlorophyll <em>a</em> triggering modes
 concurrently the day following the last feeding and weekly for five weeks.
 The TAGL for each <em>Dinophysis</em> image was then analyzed
 for each week following the procedure described above.
description: # Tracking of heterotrophic feeding by the dinoflagellate, Dinophysis,
 reveals the role of differing Mesodinium populations in shaping harmful
 algal bloom dynamics
 [https://doi.org/10.5061/dryad.f4qrfj732](https://doi.org/10.5061/dryad.f4qrfj732) This contains data from a field study where bloom populations of *Dinophysis* *acuminata* and its prey species *Mesodinium* were tracked over the course of three years (2019-2021) at two locations using the Imaging FlowCytobot (IFCB). *Dinophysis* is a mixotroph and relies on consumption of *Mesodinium* (also a mixotroph) to acquire plastids for photosynthesis. The IFCB gathers images of live plankton samples (ROIs). The IFCB image post-processing steps collect a wide variety of image features for those images which can then be connected to taxonomic identification. One of those features is "texture_average_gray_level" (TAGL) which is the average pixel gray level after contrast adjustment within the area of the imaged cell. This study used this feature to quantify mixotrophic feeding of *Dinophysis* on *Mesodinium* in the field as well as ground truth it in the laboratory using cultures. The IFCB images all plankton between 10 and 150 microns within a sample. This study also analyzed the changes in major groups (diatoms, dinoflagellates, ciliates, tintinnids, rotifers, larval zooplankton) over the course of the bloom in relation to the target groups of *Dinophysis* and *Mesodinium*. Correlations between individually identified taxa were also established using IFCB image identifications (ROIs/ml) ## Description of the data and file structure The data labelled Texture_average_gray_level_Dinophysis are presented in an excel file where tabs represent the "texture_average_gray_level" (TAGL) for *Dinophysis* images found within each date sampled in the field (2019-2021) and the culture experiment to verify the method. The first column is the sample ID where DXXXXXXXX is the date sampled (e.g.D20210524T175845_IFCB119 is May 25th, 2021), the second column is the average TAGL for the *Dinophysis* within that sample (for the field samples only) and the following data are the individual TAGLs for each *Dinophysis* image. Samples taken on the same day were combined into one sample for the TAGL analysis. Blank cells are due to the fact that some samples have more *Dinophysis* images than others. The data labelled IFCB_taxa are presented in an excel with grouping tabs for each year for the PCA (images/L) and individual taxa tabs for each year representing the individual ROIs of identified taxa used in the correlation matrix. The grouped data are presented where the first column is the date and the following columns are the groups where each number is the total ROIs/L of that group. ROIs/L of the groups were established by adding up all the ROIs for the individually identified taxa for that group, dividing by the mls analyzed, and multiplying by the concentration factor and 1000. The individual data are presented where the first column is the number of mls analyzed (this is IFCB metadata), the second column is the sample ID set up in the same way as that for the Texture_average_gray_level file, the third column is the concentration factor (since these samples were concentrated), and the following data are each of the taxonomic classifications within our classification list and the number of ROIs classified within each of those classifications for each sample.