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Abstract Inorganic mercury (iHg) is an anthropogenic pollutant that forms monomethylmercury, a neurotoxicant affecting human health through seafood consumption. Despite iHg emissions reductions, the impact on oceanic concentrations remains unclear due to limited long-term data. Here, we present a four-year weekly time series of oceanic iHg concentrations at Scripps Pier in La Jolla, California, capturing interannual and seasonal variability. Interannual variability is driven by wet season precipitation, with wet years exhibiting sevenfold higher iHg concentration variance than dry years, potentially linking to El Niño-Southern Oscillation. Seasonally, precipitation and wave dynamics influence iHg inputs, with wet seasons driven by precipitation and runoff and dry seasons by upwelling. These parameters informed a model built to reconstruct a 20-year record of iHg concentrations, suggesting a long-term decline of 0.005 pM yr⁻¹due to climate-driven effects alone. This study highlights challenges in detecting long-term trends and emphasizes the need for sustained monitoring of oceanic iHg. 

Abstract The coastal region of the Western Antarctic Peninsula is considered a biological hotspot with high levels of phytoplankton productivity and krill biomass. Recent in situ observations and particle modeling studies of Palmer Canyon, a deep bathymetric feature in the region, demonstrated the presence of a recirculating eddy that traps particles, retaining a distinct particle layer over the summer season. We applied metagenomic sequencing and Imaging Flow Cytobot (IFCB) analysis to characterize the microbial community in the particle layer. We sampled across the upper water column (< 200 m) along a transect to identify the locations of increased particle density, categorizing particles into either living cells or cellular detritus via IFCB. An indicator species analysis of community composition demonstrated the diatomCorethronand the bacteriaSulfitobacterwere significantly highly abundant in samples with high levels of living cells, while the mixotrophic dinoflagellateProrocentrum texanumand prokaryotes Methanomassiliicoccales andFluviicola taffensiswere significantly more abundant in samples with high detritus within the particle layer. From our metagenomic analysis, the significantly differentially abundant metabolic pathway genes in the particle layer of Palmer Canyon included pathways for anaerobic metabolism, such as methanogenesis and sulfate reduction. Overall, our results indicate that distinct microbial species and metabolic pathway genes are present in the retained particle layer of Palmer Canyon. 

Environmental DNA (eDNA) is an increasingly useful method for detecting pelagic animals in the ocean but typically requires large water volumes to sample diverse assemblages. Ship-based pelagic sampling programs that could implement eDNA methods generally have restrictive water budgets. Studies that quantify how eDNA methods perform on low water volumes in the ocean are limited, especially in deep-sea habitats with low animal biomass and poorly described species assemblages. Using 12S rRNA and COI gene primers, we quantified assemblages comprised of micronekton, coastal forage fishes, and zooplankton from low volume eDNA seawater samples (n = 436, 380–1800 mL) collected at depths of 0–2200 m in the southern California Current. We compared diversity in eDNA samples to concurrently collected pelagic trawl samples (n = 27), detecting a higher diversity of vertebrate and invertebrate groups in the eDNA samples. Differences in assemblage composition could be explained by variability in size-selectivity among methods and DNA primer suitability across taxonomic groups. The number of reads and amplicon sequences variants (ASVs) did not vary substantially among shallow (<200 m) and deep samples (>600 m), but the proportion of invertebrate ASVs that could be assigned a species-level identification decreased with sampling depth. Using hierarchical clustering, we resolved horizontal and vertical variability in marine animal assemblages from samples characterized by a relatively low diversity of ecologically important species. Low volume eDNA samples will quantify greater taxonomic diversity as reference libraries, especially for deep-dwelling invertebrate species, continue to expand. 

Abstract Microbial ecological functions are an emergent property of community composition. For some ecological functions, this link is strong enough that community composition can be used to estimate the quantity of an ecological function. Here, we apply random forest regression models to compare the predictive performance of community composition and environmental data for bacterial production (BP). Using data from two independent long-term ecological research sites—Palmer LTER in Antarctica and Station SPOT in California—we found that community composition was a strong predictor of BP. The top performing model achieved an R2 of 0.84 and RMSE of 20.2 pmol L−1 hr−1 on independent validation data, outperforming a model based solely on environmental data (R2 = 0.32, RMSE = 51.4 pmol L−1 hr−1). We then operationalized our top performing model, estimating BP for 346 Antarctic samples from 2015 to 2020 for which only community composition data were available. Our predictions resolved spatial trends in BP with significance in the Antarctic (P value = 1 × 10−4) and highlighted important taxa for BP across ocean basins. Our results demonstrate a strong link between microbial community composition and microbial ecosystem function and begin to leverage long-term datasets to construct models of BP based on microbial community composition. 

The Antarctic marine environment is a dynamic ecosystem where microorganisms play an important role in key biogeochemical cycles. Despite the role that microbes play in this ecosystem, little is known about the genetic and metabolic diversity of Antarctic marine microbes. In this study we leveraged DNA samples collected by the Palmer Long Term Ecological Research (LTER) project to sequence shotgun metagenomes of 48 key samples collected across the marine ecosystem of the western Antarctic Peninsula (wAP). We developed an in silico metagenomics pipeline (iMAGine) for processing metagenomic data and constructing metagenome-assembled genomes (MAGs), identifying a diverse genomic repertoire related to the carbon, sulfur, and nitrogen cycles. A novel analytical approach based on gene coverage was used to understand the differences in microbial community functions across depth and region. Our results showed that microbial community functions were partitioned based on depth. Bacterial members harbored diverse genes for carbohydrate transformation, indicating the availability of processes to convert complex carbons into simpler bioavailable forms. We generated 137 dereplicated MAGs giving us a new perspective on the role of prokaryotes in the coastal wAP. In particular, the presence of mixotrophic prokaryotes capable of autotrophic and heterotrophic lifestyles indicated a metabolically flexible community, which we hypothesize enables survival under rapidly changing conditions. Overall, the study identified key microbial community functions and created a valuable sequence library collection for future Antarctic genomics research. 

This metadata links to 16S and 18S rRNA amplicon data (raw sequence reads, NCBI Accession PRJNA895866) for seawater, sea ice, meltwater, and experimental samples from the Central Arctic Ocean collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in which the RV (Research Vessel) Polarstern was tethered to drifting sea ice from October 2019 to September 2020. Seawater samples were collected from the water column using a CTD (conductivity-temperature-depth) rosette or underway seawater tap during legs 1, 2, 3, 4, and 5 of the expedition. Sea ice samples were collected via coring (FYI (first-year ice), SYI (second-year ice)) or scooped with a saw and/or sieve (new ice formation) during legs 1, 3, 4, and 5 of the expedition. Summer meltwater was from surface layers within leads or melt ponds and was collected using pump systems during legs 4 and 5 of the expedition. Experimental samples were filtered and processed post nutrient addition, stable isotope, or elevated methane incubations to pair community structure with biogeochemical measurements. Original data published with the National Center for Biotechnology Information: https://www.ncbi.nlm.nih.gov/bioproject/895866 ; Please contact data creators before use. 

This dataset contains water column oxygen measurements from multi-day bottle incubations collected in the Central Arctic Ocean during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition – in which the RV (Research Vessel) Polarstern was tethered to sea ice, drifting across the Central Arctic Ocean from October 2019 to September 2020. Water was collected from various depths in the water column for whole seawater respiration rates via oxygen evolution incubations during legs 1, 3, 4, and 5 of the expedition. Incubations took place in a 1 ºC (celsius) cold room onboard Polarstern. Due to temperature stability and bubble formation issues, most measurements were compromised and data has been flagged accordingly during quality checks. 

Abstract. Heterotrophic marine bacteria utilize organic carbon for growth and biomass synthesis. Thus, their physiological variability is key to the balancebetween the production and consumption of organic matter and ultimately particle export in the ocean. Here we investigate a potential link betweenbacterial traits and ecosystem functions in the rapidly warming West Antarctic Peninsula (WAP) region based on a bacteria-oriented ecosystemmodel. Using a data assimilation scheme, we utilize the observations of bacterial groups with different physiological traits to constrain thegroup-specific bacterial ecosystem functions in the model. We then examine the association of the modeled bacterial and other key ecosystemfunctions with eight recurrent modes representative of different bacterial taxonomic traits. Both taxonomic and physiological traits reflect thevariability in bacterial carbon demand, net primary production, and particle sinking flux. Numerical experiments under perturbed climate conditionsdemonstrate a potential shift from low nucleic acid bacteria to high nucleic acid bacteria-dominated communities in the coastal WAP. Our studysuggests that bacterial diversity via different taxonomic and physiological traits can guide the modeling of the polar marine ecosystem functionsunder climate change. 

Abstract The Arctic is warming faster than anywhere else on Earth, prompting glacial melt, permafrost thaw, and sea ice decline. These severe consequences induce feedbacks that contribute to amplified warming, affecting weather and climate globally. Aerosols and clouds play a critical role in regulating radiation reaching the Arctic surface. However, the magnitude of their effects is not adequately quantified, especially in the central Arctic where they impact the energy balance over the sea ice. Specifically, aerosols called ice nucleating particles (INPs) remain understudied yet are necessary for cloud ice production and subsequent changes in cloud lifetime, radiative effects, and precipitation. Here, we report observations of INPs in the central Arctic over a full year, spanning the entire sea ice growth and decline cycle. Further, these observations are size-resolved, affording valuable information on INP sources. Our results reveal a strong seasonality of INPs, with lower concentrations in the winter and spring controlled by transport from lower latitudes, to enhanced concentrations of INPs during the summer melt, likely from marine biological production in local open waters. This comprehensive characterization of INPs will ultimately help inform cloud parameterizations in models of all scales.