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The extent and ecological significance of intraspecific functional diversity within marine microbial populations is still poorly understood, and it remains unclear if such strain-level microdiversity will affect fitness and persistence in a rapidly changing ocean environment. In this study, we cultured 11 sympatric strains of the ubiquitous marine picocyanobacteriumSynechococcusisolated from a Narragansett Bay (RI) phytoplankton community thermal selection experiment. Thermal performance curves revealed selection at cool and warm temperatures had subdivided the initial population into thermotypes with pronounced differences in maximum growth temperatures. Curiously, the genomes of all 11 isolates were almost identical (average nucleotide identities of >99.99%, with >99% of the genome aligning) and no differences in gene content or single nucleotide variants were associated with either cool or warm temperature phenotypes. Despite a very high level of genomic similarity, sequenced epigenomes for two strains showed differences in methylation on genes associated with photosynthesis. These corresponded to measured differences in photophysiology, suggesting a potential pathway for future mechanistic research into thermal microdiversity. Our study demonstrates that present-day marine microbial populations can harbor cryptic but environmentally relevant thermotypes which may increase their resilience to future rising temperatures.

 

This dataset consists of primary production measurements based on uptake of carbon-13 added as 13C-bicarbonate during 24-h deckboard incubations of seawater. Sampling occurred on cruises along the Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect during summer, fall, and winter, starting in summer 2019. Net primary production (NPP) was determined from particulate organic carbon (POC) content and associated stable isotope enrichment. Three data tables are included: 1. Depth-specific primary productivity based on fractional light levels of the surface irradiance with reference to the profile of photosynthetically active radiation (PAR). 2. Integrated primary productivity. 3. Natural abundance POC. The tables derive from the raw data included as other entities. 

Diatoms are among the most abundant phytoplankton that inhabit coastal ecosystems, forming large blooms that fuel coastal food webs. Although diatoms are often large and morphologically distinct, many are small or morphologically cryptic making it difficult to understand the temporal dynamics of whole diatom communities and the environmental factors that drive them. Here, we investigated diatom diversity and its environmental correlates using 6 yr of monthly surface water samples from the Narragansett Bay Plankton Time Series to investigate the seasonal and annual variability of diatom species occurrence. High‐throughput amplicon sequencing of filtered biomass yielded 658 diatom amplicon sequence variants (ASVs), of which 347 were identified to species. Of the 49 diatom genera in the sequencing dataset, 33% had never been observed in the time series using microscopy (1959–2014). We observed a weak quadratic relationship between ASV richness and chlorophyll‐aconcentrations, suggesting that richness decreases during blooms. There was a significant difference in diatom ASV richness by season and we identified distinct assemblages associated with different seasons. These assemblages were remarkably synchronous, exhibiting a sinewave‐like pattern, over 6 yr with an annual periodicity that correlated significantly with seasonal changes in temperature, light, and dissolved inorganic nitrogen. The annual cycle of diatom assemblages suggests stability in a key component of the estuarine food web known to influence ecosystem resilience and function. Deviations from the annual cycle of recurrence could be used to distinguish between changes in community structure driven by annual fluctuations in the environment and those driven by climate‐change stressors.

 

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 (μ_max) 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 sameμ_maxand the sameQ₁₀(as in to Eppley, 1972), (2) a uniqueμ_maxbut the sameQ₁₀(similar to Kremer et al., 2017), or (3) a uniqueμ_maxand a uniqueQ₁₀(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 aμ_maxandQ₁₀universally across PFTs (as in Eppley, 1972) leads to unrealistic phytoplankton communities, which lack diatoms globally. Additionally, we find that accounting for differences in theQ₁₀between 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.

 

In 2016-17, shellfish harvesting closed for the first time in Narragansett Bay, Rhode Island, USA, from domoic acid (DA), a neurotoxin produced by diatoms of the Pseudo-nitzschia genus. Pseudo-nitzschia have occurred frequently for over 60 years in Narragansett Bay’s Long-Term Plankton Time Series (NBPTS), therefore it is surprising that the first closure only recently occurred. Pseudo-nitzschia species are known to vary in their toxin production, thus species identification is critical for understanding the underlying ecological causes of these harmful algal blooms (HABs). DNA in plankton biomass can be preserved for many years, so molecular barcoding of archived samples is useful for delineation of taxa over time. This study used amplification of the Pseudo-nitzschia -specific 18S-5.8S rDNA internal transcribed spacer region 1 (ITS1) in plankton samples and high throughput sequencing to characterize Pseudo-nitzschia species composition over a decade in Narragansett Bay, including eight years before the 2016-17 closures and two years following. This metabarcoding method can discriminate nearly all known Pseudo-nitzschia species. Several species recur as year-round residents in Narragansett Bay ( P. pungens var. pungens, P. americana, P. multiseries , and P. calliantha ). Various other species increased in frequency after 2015, and some appeared for the first time during the closure period. Notably, P. australis , a species prevalent in US West Coast HABs and known for high DA production, was not observed in Narragansett Bay until the 2017 closure but has been present in several years after the closures. Annual differences in Pseudo-nitzschia composition were correlated with physical and chemical conditions, predominantly water temperature. The long-term composition trends of Pseudo-nitzschia in Narragansett Bay serve as a baseline for identifying the introduction of new species, understanding shifting assemblages that contributed to the 2016-17 closures, and monitoring species that may be cause for future concern. 

Eukaryotic microalgae play critical roles in the structure and function of marine food webs. The contribution of microalgae to food webs can be tracked using compound‐specific isotope analysis of amino acids (CSIA‐AA). Previous CSIA‐AA studies have defined eukaryotic microalgae as a single functional group in food web mixing models, despite their vast taxonomic and ecological diversity. Using controlled cultures, this work characterizes the amino acidδ¹³C (δ¹³C_AA) fingerprints—a multivariate metric of amino acid carbon isotope values—of four major groups of eukaryotic microalgae: diatoms, dinoflagellates, raphidophytes, and prasinophytes. We found excellent separation of essential amino acidδ¹³C (δ¹³C_EAA) fingerprints among four microalgal groups (mean posterior probability reclassification of 99.2 ± 2.9%). We also quantified temperature effects, a primary driver of microalgal bulk carbon isotope variability, on the fidelity ofδ¹³C_AAfingerprints. A 10°C range in temperature conditions did not have significant impacts on variance inδ¹³C_AAvalues or the diagnostic microalgalδ¹³C_EAAfingerprints. Theseδ¹³C_EAAfingerprints were used to identify primary producers at the base of food webs supporting consumers in two contrasting systems: (1) penguins feeding in a diatom‐based food web and (2) mixotrophic corals receiving amino acids directly from autotrophic endosymbiotic dinoflagellates and indirectly from water column diatoms, prasinophytes, and cyanobacteria, likely via heterotrophic feeding on zooplankton. The increased taxonomic specificity of CSIA‐AA fingerprints developed here will greatly improve future efforts to reconstruct the contribution of diverse eukaryotic microalgae to the sources and cycling of organic matter in food web dynamics and biogeochemical cycling studies.

 

Diatoms are important components of the marine food web and one of the most species‐rich groups of phytoplankton. The diversity and composition of diatoms in eutrophic nearshore habitats have been well documented due to the outsized influence of diatoms on coastal ecosystem functioning. In contrast, patterns of both diatom diversity and community composition in offshore oligotrophic regions where diatom biomass is low have been poorly resolved. To compare the diatom diversity and community composition in oligotrophic and eutrophic waters, diatom communities were sampled along a 1,250 km transect from the oligotrophic Sargasso Sea to the coastal waters of the northeast US shelf. Diatom community composition was determined by amplifying and sequencing the 18S rDNA V4 region. Of the 301 amplicon sequence variants (ASVs) identified along the transect, the majority (70%) were sampled exclusively from oligotrophic waters of the Gulf Stream and Sargasso Sea and included the generaBacteriastrum,Haslea,Hemiaulus,Pseudo‐nitzschia, andNitzschia. Diatom ASV richness did not vary along the transect, indicating that the oligotrophic Sargasso Sea and Gulf Stream are occupied by a diverse diatom community. Although ASV richness was similar between oligotrophic and coastal waters, diatom community composition in these regions differed significantly and was correlated with temperature and phosphate, two environmental variables known to influence diatom metabolism and geographic distribution. In sum, oligotrophic waters of the western North Atlantic harbor diverse diatom assemblages that are distinct from coastal regions, and these open ocean diatoms warrant additional study, as they may play critical roles in oligotrophic ecosystems.

 

Phytoplankton support complex bacterial microbiomes that rely on phytoplankton-derived extracellular compounds and perform functions necessary for algal growth. Recent work has revealed sophisticated interactions and exchanges of molecules between specific phytoplankton–bacteria pairs, but the role of host genotype in regulating those interactions is unknown. Here, we show how phytoplankton microbiomes are shaped by intraspecific genetic variation in the host using global environmental isolates of the model phytoplankton host Thalassiosira rotula and a laboratory common garden experiment. A set of 81 environmental T. rotula genotypes from three ocean basins and eight genetically distinct populations did not reveal a core microbiome. While no single bacterial phylotype was shared across all genotypes, we found strong genotypic influence of T. rotula , with microbiomes associating more strongly with host genetic population than with environmental factors. The microbiome association with host genetic population persisted across different ocean basins, suggesting that microbiomes may be associated with host populations for decades. To isolate the impact of host genotype on microbiomes, a common garden experiment using eight genotypes from three distinct host populations again found that host genotype influenced microbial community composition, suggesting that a process we describe as genotypic filtering, analogous to environmental filtering, shapes phytoplankton microbiomes. In both the environmental and laboratory studies, microbiome variation between genotypes suggests that other factors influenced microbiome composition but did not swamp the dominant signal of host genetic background. The long-term association of microbiomes with specific host genotypes reveals a possible mechanism explaining the evolution and maintenance of complex phytoplankton–bacteria chemical exchanges.