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This dataset contains methane and nitrous oxide dissolved gas concentration, dissolved methane carbon isotope, and ancillary hydrographic data from research cruises in the North American Arctic Ocean between 2015-2018. Ocean samples for methane and nitrous oxide analysis were collected from Niskin bottles mounted on a CTD rosette. Water was collected into glass serum bottles and allowed to overflow three times before preserving with mercuric chloride and sealing with with butyl rubber stoppers and aluminum crimp seals. Gas concentrations were determined using a purge and trap system coupled to a gas chromatograph/mass spectrometer, following the method of Capelle et al. (2015). Equilibrium dry atmospheric concentrations were 328.25, 329.14, 330.11, and 330.96 ppb for N2O and 1919.64, 1933.67, 1934.92, and 1933.50 ppb for CH4 in 2015, 2016, 2017, and 2018, respectively. Equilibrium dissolved concentrations were calculated from the measured temperature and salinity following Wiesenburg and Guinasso (1979) for CH4 and Weiss and Price (1980) for N2O. Equilibrium concentrations were calculated based on sample temperature and salinity and the atmospheric N2O or CH4 concentrations measured at Barrow, Alaska by the NOAA Earth System Research Laboratory Global Monitoring Division (Dlugokencky et al., 2020a,b), with corrections to local sea level pressure and 100% humidity. Oxygen concentration was determined using an oxygen sensor mounted on the Niskin rosette, calibrated with discrete samples analyzed by Winkler titration. The mixed layer depth was defined based on a potential density difference criterion of 0.125 kg/m³ relative to the density at 5 m depth, using CTD profiles binned to 1 m. The mixed layer depth was set to 5 m as a minimum. The instantaneous gas transfer velocities and fluxes are based on the instantaneous wind speed at the time of sampling. The 30-day weighted gas transfer velocities and fluxes are integrated over the residence time of the gas in the mixed layer, using up to the prior 30 days of observations, following the method of Teeter et al. (2018) as described in the main manuscript of Manning et al. (2022). The 60-day weighted gas transfer velocities and fluxes are integrated over the residence time of the gas in the mixed layer, using the prior 60 days of observations, following the method of Teeter et al. (2018) as described in the main manuscript of Manning et al. (2022). Atmospheric sea level pressure was obtained from the NCEP/NCAR reanalysis product, which is provided by the NOAA-ESRL Physical Sciences Laboratory (https://psl.noaa.gov/data/gridded). Fractional ice cover was obtained from the EUMETSAT Ocean and Sea Ice Satellite Application Facility (https://osi-saf.eumetsat.int). Sea ice concentration product AMSR-2 (identifier OSI-408) was used in 2017–2018 and SSMIS (identifier OSI-401-b) was used in 2015–2016.

1. Ballast water has been identified as a leading vector for introduction of non-indigenous species (NIS). Recently, the International Maritime Organization (IMO) implemented management standards – D-2 – where all large, commercial ships trading internationally are required to adopt an approved treatment system using technologies such as ultraviolet radiation or chlorination. However, current management regulations are based only on the total abundance of viable taxa transported (i.e., total propagule pressure), largely ignoring species richness (i.e., colonization pressure).2. To determine the efficacy of chlorine treatment in reducing invasion risks and changes in transported biological communities inside ballast tanks, we used DNA metabarcoding-based approaches to estimate colonization pressure (here, the number of species/Operational Taxonomic Units (OTUs) introduced) and relative propagule pressure (relative abundance of each species/OTU) of zooplankton communities in control and chlorine treated tanks during four transatlantic voyages. 3. Our study demonstrated that transport itself did not significantly reduce colonization pressure of zooplankton species, nor did chlorine treatment. Chlorine treatment altered community structure by reducing relative propagule pressure of some taxa such as Mollusca and Rotifera, while increasing relative propagule pressure of some Oligohymenophorea and Copepoda species.4. Synthesis and applications. Chlorine treatment may not reduce invasion risks as much as previously thought. Reduction in total propagule pressure does not mean reduction in abundance of all species equally. While some taxa might experience drastically reduced abundance, others might not change at all or increase due to hatching from dormant stages initiated by chlorine exposure. Therefore, management strategies should consider changes in total propagule pressure and colonization pressure when forecasting risk of new invasions. We therefore recommend adopting new approaches, such as DNA metabarcoding-based methods, to assess the whole biodiversity discharged from ballast water. As species responses to chlorine treatment are variable and affected by concentration, we also recommend a combination of different technologies to reduce introduction risks of aquatic organisms. Supplement to: Lin, Yaping; Zhan, Aibin; Hernandez, Marco R; Paolucci, Esteban; MacIsaac, Hugh J; Briski, Elizabeta (2020): Can chlorination of ballast water reduce biological invasions? Journal of Applied Ecology, 57(2), 331-343 The zip file includes:1. raw_data_clean.fasta: Raw sequence reads of zooplankton in ballast water samples2. raw_data.fasta: OTU representative sequences3. OTU_table.xlsx: OTU table

Supplement to: Callbeck, Cameron; Lavik, Gaute; Ferdelman, Timothy G; Fuchs, Bernhard M; Gruber-Vodicka, Harald R; Hach, Philipp F; Littmann, Sten; Schoffelen, Niels J; Kalvelage, Tim; Thomsen, Soeren; Schunck, Harald; Löscher, Carolin R; Schmitz, Ruth A; Kuypers, Marcel MM (2018): Oxygen minimum zone cryptic sulfur cycling sustained by offshore transport of key sulfur oxidizing bacteria. The data set includes, sulfide and sulfur concentrations, SUP05 cell densities, as well as denitrification and carbon fixation rates (based on 15N- and 13C-labelled in situ incubation experiments). The transect extends from the sulfidic upper shelf into the sulfide-free offshore oxygen minimum zone.

This dataset contains methane and nitrous oxide dissolved gas concentration, dissolved methane carbon isotope, and ancillary hydrographic data from research cruises in the North American Arctic Ocean between 2015-2018. Ocean samples for methane and nitrous oxide analysis were collected from Niskin bottles mounted on a CTD rosette. Water was collected into glass serum bottles and allowed to overflow three times before preserving with mercuric chloride and sealing with with butyl rubber stoppers and aluminum crimp seals. Gas concentrations were determined using a purge and trap system coupled to a gas chromatograph/mass spectrometer, following the method of Capelle et al. (2015). Equilibrium dry atmospheric concentrations were 328.25, 329.14, 330.11, and 330.96 ppb for N2O and 1919.64, 1933.67, 1934.92, and 1933.50 ppb for CH4 in 2015, 2016, 2017, and 2018, respectively. Equilibrium dissolved concentrations were calculated from the measured temperature and salinity following Wiesenburg and Guinasso (1979) for CH4 and Weiss and Price (1980) for N2O. Equilibrium concentrations were calculated based on sample temperature and salinity and the atmospheric N2O or CH4 concentrations measured at Barrow, Alaska by the NOAA Earth System Research Laboratory Global Monitoring Division (Dlugokencky et al., 2020a,b), with corrections to local sea level pressure and 100% humidity. Oxygen concentration was determined using an oxygen sensor mounted on the Niskin rosette, calibrated with discrete samples analyzed by Winkler titration. The mixed layer depth was defined based on a potential density difference criterion of 0.125 kg/m³ relative to the density at 5 m depth, using CTD profiles binned to 1 m. The mixed layer depth was set to 5 m as a minimum. For methane δ13C, samples were pre-concentrated through a purge and trap system (Finnigan PreCon Trace Gas Pre-Concentrator) and measured with a Finnigan Delta XP Plus mass spectrometer following the method of Damm et al. (2015).

In order to understand how ocean acidification (OA) and enhanced irradiance levels might alter phytoplankton eco-physiology, productivity and species composition, we conducted an incubation experiment with a natural plankton assemblage from sub-surface Subarctic waters (Davis Strait, 63°N). The phytoplankton assemblage was exposed to 380 and 1,000 µatm pCO2 at both 15 and 35% surface irradiance over 2 weeks. The incubations were monitored and characterized in terms of their photo-physiology, biomass stoichiometry, primary production and dominant phytoplankton species. We found that the phytoplankton assemblage exhibited pronounced high-light stress in the first days of the experiment (20-30% reduction in photosynthetic efficiency, Fv/Fm). This stress signal was more pronounced when grown under OA and high light, indicating interactive effects of these environmental variables. Primary production in the high light treatments was reduced by 20% under OA compared to ambient pCO2 levels. Over the course of the experiment, the assemblage fully acclimated to the applied treatments, achieving similar bulk characteristics (e.g., net primary production and elemental stoichiometry) under all conditions. We did, however, observe a pCO2-dependent shift in the dominant diatom species, with Pseudonitzschia sp. dominating under low and Fragilariopsis sp. under high pCO2 levels. Our results indicate an unexpectedly high level of resilience of Subarctic phytoplankton to OA and enhanced irradiance levels. The co-occurring shift in dominant species suggests functional redundancy to be an important, but so-far largely overlooked mechanism for resilience toward climate change. Supplement to: Hoppe, Clara Jule Marie; Schuback, Nina; Semeniuk, David M; Maldonado, Maria T; Rost, Björn (2017): Functional Redundancy Facilitates Resilience of Subarctic Phytoplankton Assemblages toward Ocean Acidification and High Irradiance. Frontiers in Marine Science, 4, 14 pp

Underway temperature and salinity data was collected along the cruise track with two autonomous measurement systems. Usually, the systems are changed after 6 hours. While temperature is taken at the water inlet in about 6.5 m depth, salinity is estimated within the interior measurement container from conductivity and interior temperature. No temperature and salinity calibration were performed. For details to all processing steps see Data Processing Report.

This dataset contains raw palynomorphs counts at ODP Holes 887A and 887C, including dinocyst assemblage, as well counts of others palynomorphs such as acritarchs, pollen grains and tasmanites. Precise depths and estimated age are also provided for each sample. Supplement to: Zorzi, Coralie; Matthiessen, Jens; de Vernal, Anne (2020): Palynology, biostratigraphy, and paleoceanography of the Plio-Pleistocene at Ocean Drilling Program Site 887, Gulf of Alaska. Palaeogeography, Palaeoclimatology, Palaeoecology, 109605

1. Environmental stress can influence species traits and performance considerably. Using a seaweed-snail system from NW (Nova Scotia) and NE (Helgoland) Atlantic rocky shores, we examined how physical stress (wave exposure) modulates traits in the seaweed Fucus vesiculosus and indirectly in its main consumer, the periwinkle Littorina obtusata. 2. In both regions, algal tissue toughness increased with wave exposure. Reciprocal-transplant experiments showed that tissue toughness adjusts plastically to the prevailing level of wave exposure. 3. Choice experiments tested the feeding preference of snails from sheltered, exposed, and very exposed habitats for algae from such wave exposures. Snails from exposed and very exposed habitats consumed algal tissues at similar rates irrespective of the exposure of origin of the algae. However, snails from sheltered habitats consumed less algal tissues from very exposed habitats than tissues from sheltered and exposed habitats. Choice assays using reconstituted algal food (triturated during preparation) identified high thallus toughness as the explanation for the low preference of snails from sheltered habitats for algae from very exposed habitats. 4. Ultrastructural analyses of radulae indicated that rachidian teeth were longest and the number of cusps in lateral teeth (grazing-relevant traits) was highest in snails from very exposed habitats, suggesting that radulae are best suited to rupture tough algal tissues in such snails. 5. No-choice feeding experiments revealed that these radular traits are also phenotypically plastic, as they adjust to the toughness of the algal food. 6. Synthesis. This study indicates that the observed plasticity in the feeding ability of snails is mediated by wave exposure through phenotypic plasticity in the tissue toughness of algae. Thus, plasticity in consumers and their resource species may reduce the potential effects of physical stress on their interaction. Measurements on the rocky shores in Tor Bay, Nova Scotia, Canada (between 45.10644-45.11153 N and 61.21160-61.21700 W) and Helgoland (Helgoland (Bunker: 54.18806 N, 7.87436 E; Augusta Mole: 54.18931 N 7.89972 E; Nord-Ost Hafen, 54.18311 N, 7.88947 E, and Südhafen, 54.17819 N, 7.89417 E) to quantify1. maximum water velocity2. puncture force of Fucus vesiculosus thalli from sites of different wave exposure3. Littorina obtusata consumption of Fucus vesiculosus (fresh (both shores) and reconsituted (only Nova Scotia) from sites of different wave exposure 4. morphological traits (central teeth cusp length, number of cusps on lateral teeth) of field collected Littorina obtusata radula from different sites of wave exposure (only Nova Scotia) 5. morphological traits (central teeth cusp length, number of cusps on lateral teeth) of the Littorina obtusata radula from different sites of wave exposure feed with Fucus vesiculosus from different sites of wave exposre (only Nova Scotia) Supplement to: Molis, Markus; Scrosati, Ricardo A; El-Belely, Ehab F; Lesniowski, Thomas; Wahl, Martin (2015): Wave-induced changes in seaweed toughness entail plastic modifications in snail traits maintaining consumption efficacy. Journal of Ecology, 103(4), 851-859

The paper presents oxygen and hydrogen isotopes of 284 precipitation event samples systematically collected in Irkutsk, in the Baikal region (southeast Siberia), between June 2011 and April 2017. This is the first high-resolution dataset of stable isotopes of precipitation from this poorly studied region of continental Asia, which has a high potential for isotope-based palaeoclimate research. The dataset revealed distinct seasonal variations: relatively high δ¹⁸O (up to -4‰) and δD (up to -40‰) values characterize summer air masses, and lighter isotope composition (-41‰ for δ¹⁸O and -322‰ for δD) is characteristic of winter precipitation. Our results show that air temperature mainly affects the isotope composition of precipitation, and no significant correlations were obtained for precipitation amount and relative humidity. A new temperature dependence was established for weighted mean monthly precipitation: +0.50‰/°C (r² = 0.83; p < 0.01; n = 55) for δ¹⁸O and +3.8‰/°C (r² = 0.83, p < 0.01; n = 55) for δD. Secondary fractionation processes (e.g., contribution of recycled moisture) were identified mainly in summer from low d excess. Backward trajectories assessed with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model indicate that precipitation with the lowest mean δ¹⁸O and δD values reaches Irkutsk in winter related to moisture transport from the Arctic. Precipitation originating from the west/southwest with the heaviest mean isotope composition reaches Irkutsk in summer, thus representing moisture transport across Eurasia. Generally, moisture transport from the west, that is, the Atlantic Ocean predominates throughout the year. A comparison of our new isotope dataset with simulation results using the European Centre/Hamburg version 5 (ECHAM5)-wiso climate model reveals a good agreement of variations in δ¹⁸O (r² = 0.87; p < 0.01; n = 55) and air temperature (r² = 0.99; p < 0.01; n = 71). However, the ECHAM5-wiso model fails to capture observed variations in d excess (r² = 0.14; p < 0.01; n = 55). This disagreement can be partly explained by a model deficit of capturing regional hydrological processes associated with secondary moisture supply in summer. Supplement to: Kostrova, Svetlana S; Meyer, Hanno; Fernandoy, Francisco; Werner, Martin; Tarasov, Pavel E (2020): Moisture origin and stable isotope characteristics of precipitation in southeast Siberia. Hydrological Processes, 34(1), 51-67

Field investigations were performed in four areas: a treeless mountainous tundra (16-KP-04; Lake Rauchuagytgyn area), tundra-taiga transition zone (16-KP-01, Lake Ilirney area) and a northern taiga (18-BIL-01, 18-BIL-02). In total, 39 sites were investigated. The sites were placed to cover different vegetation communities that characterise central Chukotka. Fifteen-meter radius sample plots (sites) were demarcated in the most homogeneous locations. Heterogeneity was accommodated by roughly assorting vegetation into two to three vegetation types per sampling plot. Within each area of roughly estimated vegetation types we selected one 0.5 x 0.5 m subplot for representative ground-layer above-ground biomass (ABG) harvesting (major taxa and other). For moss and lichen AGB harvesting inside 0.5 x 0.5 m subplots representative 0.1 x 0.1 m subplots were chosen. All harvested AGB samples were weighed fresh in the field. In general, AGB samples with a weight of more than 15 g were subsampled. All samples were oven dried (60 °C, 24 h for ground-layer and moss and lichen samples, 48 h for shrub and tree branch samples) and weighed again. This dataset contains the raw data of dry weight for each sub-ground vegetation type sampling plot. All data was collected by scientists from Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research and University of Potsdam, Germany, The Institute for Biological problems of the Cryolithozone, Russian Academy of Sciences, Siberian branch, and The Institute of Natural Sciences, North-Eastern Federal University of Yakutsk, Yakutsk, Russia. The AGB data calculations for the plot area including tree and tall shrubs can be found at https://doi.org/10.1594/PANGAEA.923719.