Catlett
Dylan
Catlett
Dylan
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ArticleSatellite remote sensing and the Marine Biodiversity Observation Network: current science and future steps(Oceanography Society, 2021-11-09) Kavanaugh, Maria T. ; Bell, Tom W. ; Catlett, Dylan ; Cimino, Megan A. ; Doney, Scott C. ; Klajbor, Willem ; Messie, Monique ; Montes, Enrique ; Muller-Karger, Frank E. ; Otis, Daniel ; Santora, Jarrod A ; Schroeder, Isaac D. ; Trinanes, Joaquin ; Siegel, David A.Coastal ecosystems are rapidly changing due to human-caused global warming, rising sea level, changing circulation patterns, sea ice loss, and acidification that in turn alter the productivity and composition of marine biological communities. In addition, regional pressures associated with growing human populations and economies result in changes in infrastructure, land use, and other development; greater extraction of fisheries and other natural resources; alteration of benthic seascapes; increased pollution; and eutrophication. Understanding biodiversity is fundamental to assessing and managing human activities that sustain ecosystem health and services and mitigate humankind’s indiscretions. Remote-sensing observations provide rapid and synoptic data for assessing biophysical interactions at multiple spatial and temporal scales and thus are useful for monitoring biodiversity in critical coastal zones. However, many challenges remain because of complex bio-optical signals, poor signal retrieval, and suboptimal algorithms. Here, we highlight four approaches in remote sensing that complement the Marine Biodiversity Observation Network (MBON). MBON observations help quantify plankton community composition, foundation species, and unique species habitat relationships, as well as inform species distribution models. In concert with in situ observations across multiple platforms, these efforts contribute to monitoring biodiversity changes in complex coastal regions by providing oceanographic context, contributing to algorithm and indicator development, and creating linkages between long-term ecological studies, the next generations of satellite sensors, and marine ecosystem management.
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ArticleSatellite detection of dinoflagellate blooms off California by UV reflectance ratios(University of California Press, 2021-06-09) Kahru, Mati ; Anderson, Clarissa ; Barton, Andrew D. ; Carter, Melissa L. ; Catlett, Dylan ; Send, Uwe ; Sosik, Heidi M. ; Weiss, Elliot L. ; Mitchell, B. GregoryAs harmful algae blooms are increasing in frequency and magnitude, one goal of a new generation of higher spectral resolution satellite missions is to improve the potential of satellite optical data to monitor these events. A satellite-based algorithm proposed over two decades ago was used for the first time to monitor the extent and temporal evolution of a massive bloom of the dinoflagellate Lingulodinium polyedra off Southern California during April and May 2020. The algorithm uses ultraviolet (UV) data that have only recently become available from the single ocean color sensor on the Japanese GCOM-C satellite. Dinoflagellates contain high concentrations of mycosporine-like amino acids and release colored dissolved organic matter, both of which absorb strongly in the UV part of the spectrum. Ratios <1 of remote sensing reflectance of the UV band at 380 nm to that of the blue band at 443 nm were used as an indicator of the dinoflagellate bloom. The satellite data indicated that an observed, long, and narrow nearshore band of elevated chlorophyll-a (Chl-a) concentrations, extending from northern Baja to Santa Monica Bay, was dominated by L. polyedra. In other high Chl-a regions, the ratios were >1, consistent with historical observations showing a sharp transition from dinoflagellate- to diatom-dominated waters in these areas. UV bands are thus potentially useful in the remote sensing of phytoplankton blooms but are currently available only from a single ocean color sensor. As several new satellites such as the NASA Plankton, Aerosol, Cloud, and marine Ecosystem mission will include UV bands, new algorithms using these bands are needed to enable better monitoring of blooms, especially potentially harmful algal blooms, across large spatiotemporal scales.
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ArticleTemperature dependence of parasitoid infection and abundance of a diatom revealed by automated imaging and classification(National Academy of Sciences, 2023-07-03) Catlett, Dylan ; Peacock, Emily E. ; Crockford, E. Taylor ; Futrelle, Joe ; Batchelder, Sidney ; Stevens, Bethany L. F. ; Gast, Rebecca J. ; Zhang, Weifeng Gordon ; Sosik, Heidi M.Diatoms are a group of phytoplankton that contribute disproportionately to global primary production. Traditional paradigms that suggest diatoms are consumed primarily by larger zooplankton are challenged by sporadic parasitic “epidemics” within diatom populations. However, our understanding of diatom parasitism is limited by difficulties in quantifying these interactions. Here, we observe the dynamics of Cryothecomonas aestivalis (a protist) infection of an important diatom on the Northeast U.S. Shelf (NES), Guinardia delicatula, with a combination of automated imaging-in-flow cytometry and a convolutional neural network image classifier. Application of the classifier to >1 billion images from a nearshore time series and >20 survey cruises across the broader NES reveals the spatiotemporal gradients and temperature dependence of G. delicatula abundance and infection dynamics. Suppression of parasitoid infection at temperatures <4 °C drives annual cycles in both G. delicatula infection and abundance, with an annual maximum in infection observed in the fall-winter preceding an annual maximum in host abundance in the winter-spring. This annual cycle likely varies spatially across the NES in response to variable annual cycles in water temperature. We show that infection remains suppressed for ~2 mo following cold periods, possibly due to temperature-induced local extinctions of the C. aestivalis strain(s) that infect G. delicatula. These findings have implications for predicting impacts of a warming NES surface ocean on G. delicatula abundance and infection dynamics and demonstrate the potential of automated plankton imaging and classification to quantify phytoplankton parasitism in nature across unprecedented spatiotemporal scales.
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ArticleToward a synthesis of phytoplankton communities composition methods for global-scale application(Association for the Sciences of Limnology and Oceanography (ASLO), 2024-02-23) Kramer, Sasha J. ; Bolanos, Luis M. ; Catlett, Dylan ; Chase, Alison P. ; Behrenfeld, Michael J. ; Boss, Emmanuel S. ; Crockford, E. Taylor ; Giovannoni, Stephen J. ; Graff, Jason R. ; Haentjens, Nils ; Karp-Boss, Lee ; Peacock, Emily E. ; Roesler, Collin S. ; Sosik, Heidi M. ; Siegel, David A.The composition of the marine phytoplankton community has been shown to impact many biogeochemical processes and marine ecosystem services. A variety of methods exist to characterize phytoplankton community composition (PCC), with varying degrees of taxonomic resolution. Accordingly, the resulting PCC determinations are dependent on the method used. Here, we use surface ocean samples collected in the North Atlantic and North Pacific Oceans to compare high-performance liquid chromatography pigment-based PCC to four other methods: quantitative cell imaging, flow cytometry, and 16S and 18S rRNA amplicon sequencing. These methods allow characterization of both prokaryotic and eukaryotic PCC across a wide range of size classes. PCC estimates of many taxa resolved at the class level (e.g., diatoms) show strong positive correlations across methods, while other groups (e.g., dinoflagellates) are not well captured by one or more methods. Since variations in phytoplankton pigment concentrations are related to changes in optical properties, this combined dataset expands the potential scope of ocean color remote sensing by associating PCC at the genus- and species-level with group- or class-level PCC from pigments. Quantifying the strengths and limitations of pigment-based PCC methods compared to PCC assessments from amplicon sequencing, imaging, and cytometry methods is the first step toward the robust validation of remote sensing approaches to quantify PCC from space.
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ArticlePhytoplankton composition from sPACE: Requirements, opportunities, and challenges(Elsevier, 2024-01-10) Cetinic, Ivona ; Rousseaux, Cecile S.G. ; Carroll, Ian T. ; Chase, Alison P. ; Kramer, Sasha J. ; Werdell, P. Jeremy ; Siegel, David A. ; Dierssen, Heidi Melita ; Catlett, Dylan ; Neeley, Aimee Renee ; Soto Ramos, Inia M. ; Wolny, Jennifer L. ; Sadoff, Natasha ; Urquhart, Erin A. ; Westberry, Toby K. ; Stramski, Dariusz ; Pahlevan, Nima ; Seegers, Bridget N. ; Sirk, Emerson ; Lange, Priscila Kienteca ; Vandermeulen, Ryan A. ; Graff, Jason R. ; Allen, James George ; Gaube, Peter ; McKinna, Lachlan I. W. ; McKibben, S. Morgaine ; Binding, Caren E. ; Sanjuan Calzado, Violeta ; Sayers, Michael J.Ocean color satellites have provided a synoptic view of global phytoplankton for over 25 years through near surface measurements of the concentration of chlorophyll a. While remote sensing of ocean color has revolutionized our understanding of phytoplankton and their role in the oceanic and freshwater ecosystems, it is important to consider both total phytoplankton biomass and changes in phytoplankton community composition in order to fully understand the dynamics of the aquatic ecosystems. With the upcoming launch of NASA's Plankton, Aerosol, Clouds, ocean Ecosystem (PACE) mission, we will be entering into a new era of global hyperspectral data, and with it, increased capabilities to monitor phytoplankton diversity from space. In this paper, we analyze the needs of the user community, review existing approaches for detecting phytoplankton community composition in situ and from space, and highlight the benefits that the PACE mission will bring. Using this three-pronged approach, we highlight the challenges and gaps to be addressed by the community going forward, while offering a vision of what global phytoplankton community composition will look like through the “eyes” of PACE.
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ArticleConcurrent DNA meta‐barcoding and plankton imaging reveal novel parasitic infection and competition in a diatom(Association for the Sciences of Limnology and Oceanography (ASLO), 2024-07-13) Catlett, Dylan ; Peacock, Emily E. ; Fontaine, Diana N. ; Crockford, E. Taylor ; McKenzie, Mary J. ; Rynearson, Tatiana A. ; Sosik, Heidi M.Little is known about diatom parasitism in marine systems. Guinardia delicatula, a biomass-dominant diatom on the Northeast US Shelf (NES), is regularly parasitized by the protistan nanoflagellate, Cryothecomonas aestivalis in this region. While G. delicatula is known to host other protistan parasites, direct observation of these interactions and their dynamics in nature remain elusive. Here, we integrate concurrent DNA meta-barcoding and automated imaging-in-flow cytometry observations to characterize the dynamics of G. delicatula infection by a second parasite, Pirsonia (likely Pirsonia verrucosa). In contrast with C. aestivalis infections, Pirsonia infections are observed sporadically and typically only in a small fraction of the G. delicatula population on the NES. An exception was found in February 2020, when an anomalous co-infection event was observed in G. delicatula featuring > 20% infection prevalence by Pirsonia and > 10% infection prevalence by C. aestivalis. Investigation of each parasite's infection dynamics' relationship with temperature and salinity suggested that C. aestivalis may consistently dominate G. delicatula infection dynamics due to its wider thermal tolerance range and more cosmopolitan distribution. Pirsonia only appeared capable of dominating G. delicatula infection at temperatures near or below 4°C, a known temperature threshold below which C. aestivalis infection is suppressed. Our results demonstrate the utility of integrating DNA meta-barcoding and plankton imaging to observe the dynamics of diatom–parasite interactions in marine systems and shed light on the diversity of infection dynamics in diatom–parasite systems and the forcings governing competition among diatom parasites for a single host.