ALBERT

Beschreibung: Foraminifera are a species-rich phylum of rhizarian protists that are highly abundant in most marine environments. Molecular methods such as metabarcoding have revealed a high, yet undescribed diversity of Foraminifera. However, so far only one molecular marker, the 18S ribosomal RNA, was available for metabarcoding studies on Foraminifera. Primers that allow amplification of foraminiferal mitochondrial cytochrome oxidase I (COI) and identification of Foraminifera species were recently published. Here we test the performance of these primers for the amplification of whole foraminiferal communities, and compare their performance to that of the highly degenerate LerayXT primers, which amplify the same COI region in a wide range of eukaryotes. We applied metabarcoding to 48 samples taken along three transects spanning a North Sea beach in the Netherlands from dunes to the low tide level, and analysed both sediment samples and meiofauna samples, which contained taxa between 42 mm and 1 mm in body size obtained by decantation from sand samples. We used single-cell metabarcoding (Girard et al., 2022) to generate a COI reference library containing 32 species of Foraminifera, and used this to taxonomically annotate our community metabarcoding data. Our analyses show that the highly degenerate LerayXT primers do not amplify Foraminifera, while the Foraminifera primers are highly Foraminifera- specific, with about 90% of reads assigned to Foraminifera and amplifying taxa from all major groups, i.e., monothalamids, Globothalamea, and Tubothalamea. We identified 176 Foraminifera ASVs and found a change in Foraminifera community composition along the beach transects from high tide to low tide level, and a dominance of single-chambered monothalamid Foraminifera. Our results highlight that COI metabarcoding can be a powerful tool for assessing Foraminiferal communities.

Beschreibung: Laboratory O2 clumped-isotope data (as D36 values measured at Rice University) for air occluded in ice core GISP2-D spanning gas ages of 18000-21000 ky BP for the Last Glacial Maximum (LGM). Modeled atmospheric history for the LGM via outputs of the GISS-E2.1 driven and Data Assimilation (DAv2.0) driven chemical transport model incorporated into a 2-box model of the atmosphere.

Beschreibung: Within the European Space Agency funded Oceanographic datasets for acidification (OceanSODA) project, the University of Exeter (UNEXE) produced the OceanSODA-UNEXE dataset (v1.0) which is an optimal dataset of the surface ocean carbonate system in the Amazon and Congo River outflows. All four main carbonate system variables, total alkalinity (TA), dissolved inorganic carbon (DIC), the partial pressure of carbon dioxide (pCO2) and pH are provided on monthly 1° × 1° grids along with additional carbonate system parameters. The uncertainties within these data have been assessed using independent in situ database (Land et.al 2022). A paper detailing the methodology used to optimally construct and then evaluate this dataset is currently being written. Each netCDF4 dataset file contains 10 or more years of data; the full carbonate system is provided for 2010-2020 in the Amazon outflow (defined as 2°S and 24°N and between 70°W and 31°W) datasets and the full carbonate system is provided for the period 2002-2016 in the Congo outflow (defined as 10°S and 4°N and between 2°W and 16°E). Variables are stored on a 180° by 360° latitude grid with a time dimension (defined as the months from January 1957 to December 2021). Following the methodology of Land et al. (2019), TA and DIC were derived using empirical algorithms from the published literature that use combinations of inputs that include sea surface temperature (SST), sea surface salinity (SSS) datasets and nutrients (silicate (SiO4-), nitrate (NO3-), phosphate (PO4-) or dissolved oxygen (DO). TA and the inputs used to derive it (e.g. SST and SSS) are within the netCDF files prefixed with _TA, whereas DIC and the inputs used to derive it (SST and SSS) are within the netCDF files prefixed with _DIC. The full carbonate system equations (calculating for surface waters) were run twice with PyCO2SYS V1.7 (Humphreys et al., 2022), using the same TA, DIC, SiO4- and PO4- along with the SST and SST datasets from the respective DIC or TA netCDF files. The variables computed with PyCO2SYS are the carbonate ion (CO3-2), the bicarbonate ion (HCO3-), hydrogen ions (H+) ,pH on the total scale, pH on the free scale, pH on the seawater scale, the partial pressure of carbon dioxide (pCO2), the fugacity of carbon dioxide (fCO2),the saturation state of calcite and the saturation state of aragonite. A full list of variables and references for all input data can be found in Table 1. All variable fields have an associated uncertainty field; this uncertainty has the same abbreviated variable name along with the suffix uncertainty (e.g. TA_uncertainty). SST, SSS and nutrient input data uncertainties come from their respective dataset accuracy assessments and dataset references (Table 1). TA and DIC uncertainty is the combined standard uncertainty from the algorithm and input data evaluation determined using the methods of Land et al. (2019) which are consistent with the uncertainty methods of (JCGM, 2008). Uncertainties for the remaining variables were determined by propagating the TA, DIC, SST and SSS uncertainties through PyCO2SYS using a forward finite difference approach (Humphreys et al., 2022).

Beschreibung: Data presented here were collected between January 2021 to December 2021 within the research unit DynaCom (Spatial community ecology in highly dynamic landscapes: From island biogeography to metaecosystems, https://uol.de/dynacom/ ) of the Universities of Oldenburg, Göttingen, and Münster, the iDiv Leipzig and the Nationalpark Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were created in the back barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog. Meteorological data were collected near the experimental setup, with a locally installed weather station located approximately 500m north of the southern shoreline. The weather station system used here was a ClimaSensor US 4.920x.00.00x that was pre-calibrated by the manufacturer (Adolf Thies GmbH & Co. KG, D-Göttingen). Data were recorded and saved within the Meteo-Online (V4.5.0.20253) software in a sampling interval of 1 min, with an averaging time of 10 s. Date and time were given in UTC and the position was derived from the internal GPS system. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Beschreibung: Underway bio-optical sensor measurements of chlorophyll a and turbidity were acquired along the cruise track of RV MARIA S. MERIAN cruise MSM97/2. Measurements were collected with two autonomous measurement systems (RSWS), which are located at 6.5 m below the sea surface. Usually, the RWS-System with measuring container 1 and 2 (MC1 and MC2) interchanged after 6 hours. Only en route data was collected and quality controlled. No data from stationary measurements (in situ) were included. Quality Control specifically for biogeochemical measurements had been applied. For details to all processing steps see Data Processing Report.

Beschreibung: Data presented here were collected between Januar 2021 to November 2021 within the research unit DynaCom (Spatial community ecology in highly dynamic landscapes: From island biogeography to metaecosystems, https://uol.de/dynacom/) of the Universities of Oldenburg, Göttingen, and Münster, the iDiv Leipzig and the Nationalpark Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were created in the back barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog. Sediment samples for the determination of pH, water content and loss on ignition were taken bi-/monthly in surface sediments (0-3 cm depth). Samples were measured in the laboratory within two months after sampling.

Beschreibung: Hydrographic (CTD) profiles of Temperature, Salinity, Dissolved Oxygen, Chlorophyll A fluorescence and Coloured Dissolved Organic Matter (CDOM) collected in the Arctic Ocean, over the western Eurasian Basin and Lomonosov Ridge, between 2 August and 11 September 2021, from I/B Oden. This is the Swedish contribution to the international Synoptic Arctic Survey. This dataset merges the full-depth physical CTD and the shallow biological CTD profiles. Both systems had the standard SeaBird SBE911 plus system with dual sensors to measure in-situ temperature and conductivity and single sensors measuring pressure and oxygen. The physical CTD also had a CDOM sensor (Turner Cyclops fluorometer), while the Chl-A fluorometer (WET Labs, ECO-AFL/FL) was moved throughout the expedition between the two systems. Salinity, Oxygen, Chl-A fluorescence and CDOM were calibrated against sample data collected and analysed by the co-authors: - Salinity samples from the deep stations were analysed post-cruise using a salinometer (Guildline Autosal) and IAPSO standard seawater at the GEOMAR, Germany. - Dissolved oxygen was determined onboard using an automatic Winkler titration setup with UV detection (Scripps Institute of Oceanography Oxygen Titration System version 2.35m). - Chl-A concentration was determined post-cruise from flow cytometry (FCM) at Linnaeus University, Sweden. The samples consisted of 4 mL cryovials, of which 3.8 mL was sample water and 76 μL 25% EM grade glutaraldehyde solution (Glu stock). The samples incubated at room temperature for 5 minutes before flash freezing in liquid nitrogen and then placing in the -80 °C freezer in cryoboxes. - CDOM was determined post-cruise at the National Institute of Aquatic Resources - DTU Aqua, Denmark, following the method of Lawaetz and Stedmon (2009) This dataset contains the 1-m bin-averaged profiles. For more information about each sensor and their calibration, the reader is invited to check the cruise report (final version submitted on 20 September; shareable version with DOI coming soon)

Beschreibung: Data presented here were collected within the research unit DynaCom (Spatial community ecology in highly dynamic landscapes: From island biogeography to metaecosystems, https://uol.de/dynacom/ ) of the Universities of Oldenburg, Göttingen, and Münster, the iDiv Leipzig and the Nationalpark Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were created in the back barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog. Meteorological data were collected near the experimental setup, with a locally installed weather station located approximately 500m north of the southern shoreline. The weather station system used here was a ClimaSensor US 4.920x.00.00x that was pre-calibrated by the manufacturer (Adolf Thies GmbH & Co. KG, D-Göttingen). Data were recorded and saved within the Meteo-Online (V4.5.0.20253) software in a sampling interval of 1 min, with an averaging time of 10 s. Date and time were given in UTC and the position was derived from the internal GPS system. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks.

Beschreibung: The Deep-sea Sponge Microbiome Project is a large-scale study, integrating 16S amplicon sequencing data with oceanographic data. The present dataset contains 66 full water conductivity-temperature-depth (CTD) profiles which were recorded in different ocean regions world wide. The profiles were trimmed to a starting depth of 20 m below the ocean surface and reach down to ~ 5 m above the ocean floor.