Phytoplankton thermal trait parameterization alters community structure and biogeochemical processes in a modeled ocean.

Phytoplankton exhibit diverse physiological responses to temperature which influence their fitness in the environment and consequently alter their community structure. Here, we explored the sensitivity of phytoplankton community structure to thermal response parameterization in a modelled marine phytoplankton community. Using published empirical data, we evaluated the maximum thermal growth rates (µmax ) and temperature coefficients (Q10 ; the rate at which growth scales with temperature) of six key Phytoplankton Functional Types (PFTs): coccolithophores, cyanobacteria, diatoms, diazotrophs, dinoflagellates, and green algae. Following three well-documented methods, PFTs were either assumed to have (1) the same µmax and the same Q10 (as in to Eppley, 1972), (2) a unique µmax but the same Q10 (similar to Kremer et al., 2017), or (3) a unique µmax and a unique Q10 (following Anderson et al., 2021). These trait values were then implemented within the Massachusetts Institute of Technology biogeochemistry and ecosystem model (called Darwin) for each PFT under a control and climate change scenario. Our results suggest that applying a µmax and Q10 universally across PFTs (as in Eppley, 1972) leads to unrealistic phytoplankton communities, which lack diatoms globally. Additionally, we find that accounting for differences in the Q10 between PFTs can significantly impact each PFT's competitive ability, especially at high latitudes, leading to altered modeled phytoplankton community structures in our control and climate change simulations. This then impacts estimates of biogeochemical processes, with, for example, estimates of export production varying by ~10% in the Southern Ocean depending on the parameterization. Our results indicate that the diversity of thermal response traits in phytoplankton not only shape community composition in the historical and future, warmer ocean, but that these traits have significant feedbacks on global biogeochemical cycles.

Imaging Technologies Build Capacity and Accessibility in Phytoplankton Species Identification Expertise for Research and Monitoring: Lessons Learned During the COVID-19 Pandemic.

As primary producers, phytoplankton play an integral role in global biogeochemical cycles through their production of oxygen and fixation of carbon. They also provide significant ecosystem services, by supporting secondary production and fisheries. Phytoplankton biomass and diversity have been identified by the Global Ocean Observing System (GOOS) as Essential Ocean Variables (EOVs), properties that need to be monitored to better understand and predict the ocean system. Phytoplankton identification and enumeration relies on the skills and expertise of highly trained taxonomic analysts. The training of new taxonomic analysts is intensive and requires months to years of supervised training before an analyst is able to independently and consistently apply identification skills to a sample. During the COVID-19 pandemic, access to laboratories was greatly restricted and social distancing requirements prevented supervised training. However, access to phytoplankton imaging technologies such as the Imaging FlowCytobot (IFCB), FlowCam, and PlanktoScope, combined with open online taxonomic identification platforms such as EcoTaxa, provided a means to continue monitoring, research, and training activities remotely when in-person activities were restricted. Although such technologies can not entirely replace microscopy, they have a great potential for supporting an expansion in taxonomic training, monitoring, surveillance, and research capacity. In this paper we highlight a set of imaging and collaboration tools and describe how they were leveraged during laboratory lockdowns to advance research and monitoring goals. Anecdotally, we found that the use of imaging tools accelerated the training of new taxonomic analysts in our phytoplankton analysis laboratory. Based on these experiences, we outline how these technologies can be used to increase capacity in taxonomic training and expertise, as well as how they can be used more broadly to expand research opportunities and capacity.

Lagrangian betweenness as a measure of bottlenecks in dynamical systems with oceanographic examples.

The study of connectivity patterns in networks has brought novel insights across diverse fields ranging from neurosciences to epidemic spreading or climate. In this context, betweenness centrality has demonstrated to be a very effective measure to identify nodes that act as focus of congestion, or bottlenecks, in the network. However, there is not a way to define betweenness outside the network framework. By analytically linking dynamical systems and network theory, we provide a trajectory-based formulation of betweenness, called Lagrangian betweenness, as a function of Lyapunov exponents. This extends the concept of betweenness beyond the context of network theory relating hyperbolic points and heteroclinic connections in any dynamical system to the structural bottlenecks of the network associated with it. Using modeled and observational velocity fields, we show that such bottlenecks are present and surprisingly persistent in the oceanic circulation across different spatio-temporal scales and we illustrate the role of these areas in driving fluid transport over vast oceanic regions. Analyzing plankton abundance data from the Kuroshio region of the Pacific Ocean, we find significant spatial correlations between measures of diversity and betweenness, suggesting promise for ecological applications.

Cytoplasmic long noncoding RNAs are differentially regulated and translated during human neuronal differentiation.

The expression of long noncoding RNAs is highly enriched in the human nervous system. However, the function of neuronal lncRNAs in the cytoplasm and their potential translation remains poorly understood. Here we performed Poly-Ribo-Seq to understand the interaction of lncRNAs with the translation machinery and the functional consequences during neuronal differentiation of human SH-SY5Y cells. We discovered 237 cytoplasmic lncRNAs up-regulated during early neuronal differentiation, 58%-70% of which are associated with polysome translation complexes. Among these polysome-associated lncRNAs, we find 45 small ORFs to be actively translated, 17 specifically upon differentiation. Fifteen of 45 of the translated lncRNA-smORFs exhibit sequence conservation within Hominidea, suggesting they are under strong selective constraint in this clade. The profiling of publicly available data sets revealed that 8/45 of the translated lncRNAs are dynamically expressed during human brain development, and 22/45 are associated with cancers of the central nervous system. One translated lncRNA we discovered is LINC01116, which is induced upon differentiation and contains an 87 codon smORF exhibiting increased ribosome profiling signal upon differentiation. The resulting LINC01116 peptide localizes to neurites. Knockdown of LINC01116 results in a significant reduction of neurite length in differentiated cells, indicating it contributes to neuronal differentiation. Our findings indicate cytoplasmic lncRNAs interact with translation complexes, are a noncanonical source of novel peptides, and contribute to neuronal function and disease. Specifically, we demonstrate a novel functional role for LINC01116 during human neuronal differentiation.

Synoptic Mesoscale to Basin Scale Variability in Biological Productivity and Chlorophyll in the Kuroshio Extension Region.

The Kuroshio current separates from the Japanese coast to become the eastward flowing Kuroshio Extension (KE) characterized by a strong latitudinal density front, high levels of mesoscale (eddy) energy, and high chlorophyll a (Chl). While satellite measurements of Chl show evidence of the impact of mesoscale eddies on the standing stock of phytoplankton, there have been very limited synoptic, spatially resolved in situ estimates of productivity in this region. Here, we present underway measurements of oxygen/argon supersaturation (ΔO2/Ar), a tracer of net biological productivity, for the KE made in spring, summer, and early autumn. We find large seasonal differences in the relationships between ΔO2/Ar, Chl, and sea level anomaly (SLA), a proxy for local thermocline depth deviations driven by mesoscale eddies derived from satellite observations. We show that the KE is a pronounced hotspot of high ΔO2/Ar in spring, but corresponding surface Chl values are low and have no correlation with ΔO2/Ar. In summer, there is a hotspot of productivity associated with the Oyashio front, where ΔO2/Ar and Chl are strongly positively correlated. In autumn, ΔO2/Ar and Chl are consistently low throughout the region and also positively correlated. By combining our analysis of the in situ ΔO2/Ar data with complementary Argo, BGC-Argo, repeat hydrography, and SLA observations, we infer the combination of physical and biological controls that drive the observed distributions of ΔO2/Ar and Chl. We find that the KE and Oyashio currents both act to supply nutrients laterally, fueling regions of high productivity in spring and summer, respectively.

SeaFlow data v1, high-resolution abundance, size and biomass of small phytoplankton in the North Pacific.

SeaFlow is an underway flow cytometer that provides continuous shipboard observations of the abundance and optical properties of small phytoplankton (<5 µm in equivalent spherical diameter, ESD). Here we present data sets consisting of SeaFlow-based cell abundance, forward light scatter, and pigment fluorescence of individual cells, as well as derived estimates of ESD and cellular carbon content of picophytoplankton, which includes the cyanobacteria Prochlorococcus, Synechococcus and small-sized Crocosphaera (<5 µm ESD), and picophytoplankton and nanophytoplankton (2-5 µm ESD). Data were collected in surface waters (≈5 m depth) from 27 oceanographic cruises carried out in the Northeast Pacific Ocean between 2010 and 2018. Thirteen cruises provide high spatial resolution (≈1 km) measurements across 32,500 km of the Northeast Pacific Ocean and 14 near-monthly cruises beginning in 2015 provide seasonal distributions at the long-term sampling site (Station ALOHA) of the Hawaii Ocean Time-Series. These data sets expand our knowledge of the current spatial and temporal distributions of picophytoplankton in the surface ocean.

Scalable clustering algorithms for continuous environmental flow cytometry.

MOTIVATION: Recent technological innovations in flow cytometry now allow oceanographers to collect high-frequency flow cytometry data from particles in aquatic environments on a scale far surpassing conventional flow cytometers. The SeaFlow cytometer continuously profiles microbial phytoplankton populations across thousands of kilometers of the surface ocean. The data streams produced by instruments such as SeaFlow challenge the traditional sample-by-sample approach in cytometric analysis and highlight the need for scalable clustering algorithms to extract population information from these large-scale, high-frequency flow cytometers. RESULTS: We explore how available algorithms commonly used for medical applications perform at classification of such a large-scale, environmental flow cytometry data. We apply large-scale Gaussian mixture models to massive datasets using Hadoop. This approach outperforms current state-of-the-art cytometry classification algorithms in accuracy and can be coupled with manual or automatic partitioning of data into homogeneous sections for further classification gains. We propose the Gaussian mixture model with partitioning approach for classification of large-scale, high-frequency flow cytometry data. AVAILABILITY AND IMPLEMENTATION: Source code available for download at https://github.com/jhyrkas/seaflow_cluster, implemented in Java for use with Hadoop. CONTACT: hyrkas@cs.washington.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Light-driven synchrony of Prochlorococcus growth and mortality in the subtropical Pacific gyre.

Theoretical studies predict that competition for limited resources reduces biodiversity to the point of ecological instability, whereas strong predator/prey interactions enhance the number of coexisting species and limit fluctuations in abundances. In open ocean ecosystems, competition for low availability of essential nutrients results in relatively few abundant microbial species. The remarkable stability in overall cell abundance of the dominant photosynthetic cyanobacterium Prochlorococcus is assumed to reflect a simple food web structure strongly controlled by grazers and/or viruses. This hypothesized link between stability and ecological interactions, however, has been difficult to test with open ocean microbes because sampling methods commonly have poor temporal and spatial resolution. Here we use continuous techniques on two different winter-time cruises to show that Prochlorococcus cell production and mortality rates are tightly synchronized to the day/night cycle across the subtropical Pacific Ocean. In warmer waters, we observed harmonic oscillations in cell production and mortality rates, with a peak in mortality rate consistently occurring ∼6 h after the peak in cell production. Essentially no cell mortality was observed during daylight. Our results are best explained as a synchronized two-component trophic interaction with the per-capita rates of Prochlorococcus consumption driven either directly by the day/night cycle or indirectly by Prochlorococcus cell production. Light-driven synchrony of food web dynamics in which most of the newly produced Prochlorococcus cells are consumed each night likely enforces ecosystem stability across vast expanses of the open ocean.

Evaluation of the Gammarus pulex in situ feeding assay as a biomonitor of water quality: robustness, responsiveness, and relevance.

Biomonitoring using benthic macroinvertebrates has been used to assess water quality in Europe since the early 20th century. Most methods use community-level measurements, and the use of single-species responses has been limited, despite their potential benefits as sensitive, early warning indicators. Here we evaluate a single-species in situ assay in which the response is feeding inhibition of the freshwater amphipod Gammarus pulex. The assay was deployed in uncontaminated reference sites to quantify background variability in feeding rates and to elucidate sources of this variation. The ability of the assay to detect impacts of point-source discharges was assessed and the ecological relevance of the assay determined by comparing assay responses to aspects of community structure and functioning. Water temperature accounted for 76% of the variation in the feeding rate of animals deployed at uncontaminated sites, and summer deployments had a >90% power to detect a 30% inhibition in feeding. Inhibition of the situ feeding rate of G. pulex deployed downstream of a variety of point-source discharges ranged from 27 to 99.6%. Gammarus pulex is an important detritivore in stream communities, and a strong positive correlation existed between in situ feeding rate measured over 6 d and leaf decomposition measured over 28 d. A positive correlation also existed between in situ feeding and macroinvertebrate diversity and a biotic index. The G. pulex in situ feeding assay is a short-term sublethal biomonitor of water quality that is indicative of community- and ecosystem-level responses occurring over longer time periods. It is robust, responsive, and relevant.