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  • 1
    Publication Date: 2022-07-06
    Description: Identifying and quantifying nitrogen pools is essential for understanding the nitrogen cycle in aquatic ecosystems. The ubiquitous diatoms represent an overlooked nitrate pool as they can accumulate nitrate intracellularly and utilize it for nitrogen assimilation, dissipation of excess photosynthetic energy, and Dissimilatory Nitrate Reduction to Ammonium (DNRA). Here, we document the global co-occurrence of diatoms and intracellular nitrate in phototrophic microbial communities in freshwater (n = 69), coastal (n = 44), and open marine (n = 4) habitats. Diatom abundance and total intracellular nitrate contents in water columns, sediments, microbial mats, and epilithic biofilms were highly significantly correlated. In contrast, diatom community composition had only a marginal influence on total intracellular nitrate contents. Nitrate concentrations inside diatom cells exceeded ambient nitrate concentrations ∼100–4000-fold. The collective intracellular nitrate pool of the diatom community accounted for 〈1% of total nitrate in pelagic habitats and 65–95% in benthic habitats. Accordingly, nitrate-storing diatoms are emerging as significant contributors to benthic nitrogen cycling, in particular through Dissimilatory Nitrate Reduction to Ammonium activity under anoxic conditions.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed , info:eu-repo/semantics/article
    Format: application/pdf
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  • 2
    Publication Date: 2024-02-07
    Description: In this paper, we outline the need for a coordinated international effort toward the building of an open-access Global Ocean Oxygen Database and ATlas (GO2DAT) complying with the FAIR principles (Findable, Accessible, Interoperable, and Reusable). GO2DAT will combine data from the coastal and open ocean, as measured by the chemical Winkler titration method or by sensors (e.g., optodes, electrodes) from Eulerian and Lagrangian platforms (e.g., ships, moorings, profiling floats, gliders, ships of opportunities, marine mammals, cabled observatories). GO2DAT will further adopt a community-agreed, fully documented metadata format and a consistent quality control (QC) procedure and quality flagging (QF) system. GO2DAT will serve to support the development of advanced data analysis and biogeochemical models for improving our mapping, understanding and forecasting capabilities for ocean O2 changes and deoxygenation trends. It will offer the opportunity to develop quality-controlled data synthesis products with unprecedented spatial (vertical and horizontal) and temporal (sub-seasonal to multi-decadal) resolution. These products will support model assessment, improvement and evaluation as well as the development of climate and ocean health indicators. They will further support the decision-making processes associated with the emerging blue economy, the conservation of marine resources and their associated ecosystem services and the development of management tools required by a diverse community of users (e.g., environmental agencies, aquaculture, and fishing sectors). A better knowledge base of the spatial and temporal variations of marine O2 will improve our understanding of the ocean O2 budget, and allow better quantification of the Earth’s carbon and heat budgets. With the ever-increasing need to protect and sustainably manage ocean services, GO2DAT will allow scientists to fully harness the increasing volumes of O2 data already delivered by the expanding global ocean observing system and enable smooth incorporation of much higher quantities of data from autonomous platforms in the open ocean and coastal areas into comprehensive data products in the years to come. This paper aims at engaging the community (e.g., scientists, data managers, policy makers, service users) toward the development of GO2DAT within the framework of the UN Global Ocean Oxygen Decade (GOOD) program recently endorsed by IOC-UNESCO. A roadmap toward GO2DAT is proposed highlighting the efforts needed (e.g., in terms of human resources).
    Type: Article , PeerReviewed
    Format: text
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  • 3
    Publication Date: 2023-07-22
    Description: In March/April 2018 during a cruise on R/V Sally Ride, SR1805, 15N-NH4+ incubations in 60mL glass serum bottles were performed to measure ammonium oxidation rates to nitrite and nitrous oxide in different depth at 3 different stations in the oxygen deficient zone (ODZ) of the Eastern Tropical North Pacific off the coast of Mexico. Water samples were collected from 30L Niskin bottles deployed with a conductivity-temperature-depth profiler (CTD, Seabird Electronics). The goal was to get a better understanding on the controls of nitrous oxide (N2O) production. The N2O production rate experiments were performed according to Bourbonnais et al. 2021 (https://doi.org/10.3389/fmars.2021.611937). Furthermore, ammonium (NH4+), nitrite (NO2-) and nitrate (NO3-) as well as N2O concentrations were determined using standard fluorometric (Holmes et al. 1999, https://doi.org/10.1139/f99-128), photometric (Strickland and Parsons 1972, hdl:10013/epic.46454.d001), chemiluminescent (Braman and Hendrix 1989, doi:10.1021/ac00199a007) and mass spectrometric techniques (McIlvin and Casciotti 2010, https://doi.org/10.4319/lom.2010.8.54), respectively. The N2O yield per nitrite produced was calculated. The archaeal ammonia monooxygenase gene subunit A (amoA) copy numbers/mL were determined using qPCR as described previously (Peng et al. 2015, https://doi.org/10.1002/2015GB005278).
    Keywords: 15N-tracer; 15N tracer incubations (Bourbonnais et al. 2021); Ammonium; Ammonium, labelled, fraction; Ammonium, oxidation rate; Ammonium, oxidation rate, standard error; ammonium oxidation; amoA gene, copy number; amoA gene, copy number, standard deviation; Bottle number; Calculated; Cast number; Chemiluminescence detection (Braman and Hendrix 1989); Comment; CTD, Sea-Bird; CTD/Rosette; CTD-RO; DATE/TIME; Density, sigma-theta (0); Depth, bottom/max; DEPTH, water; eastern tropical north pacific; Event label; Fluorometry (Holmes et al. 1999); greenhouse gas; Identification; LATITUDE; LONGITUDE; Mass spectrometry (McIlvin and Casciotti 2010); N2O production rates; Nitrate; Nitrite; nitrogen cycle; Nitrous oxide, dissolved; Nitrous oxide, hybrid; Nitrous oxide, hybrid, standard error; Nitrous oxide, standard deviation; Nitrous oxide, yield; Nitrous oxide, yield, standard error; Nitrous oxide production; Nitrous oxide production, standard error; North Pacific Ocean; ocean; Oxygen; Photometry (Strickland & Parsons, 1972); Radiation, photosynthetically active; Real-time quantitative polymerase chain reaction (qPCR); Salinity; Sally Ride; SR1805; SR1805_PS1_CTD16; SR1805_PS1_CTD5; SR1805_PS2_CTD32; SR1805_PS2_CTD45; SR1805_PS3_CTD71; SR1805_PS3_CTD84; Station label; STOX; Switchable trace oxygen sensor; Temperature, water; Treatment
    Type: Dataset
    Format: text/tab-separated-values, 796 data points
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