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  • Energy Research
  • 13. Climate action
  • 8. Economic growth
  • Energy Research
  • European Marine Science

  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Nardone, Jessica A; Patel, Shrey; Siegel, Kyle R; Tedesco, Dana; +7 Authors

    Barnacles are dominant members of marine intertidal communities. Their success depends on firm attachment provided by their proteinaceous adhesive and protection imparted by their calcified shell plates. Little is known about how variations in the environment affect adhesion and shell formation processes in barnacles. Increased levels of atmospheric CO2 have led to a reduction in the pH of ocean waters (i.e., ocean acidification), a trend that is expected to continue into the future. Here, we assessed if a reduction in seawater pH, at levels predicted within the next 200 years, would alter physiology, adhesion, and shell formation in the cosmopolitan barnacle Amphibalanus (=Balanus) amphitrite. Juvenile barnacles, settled on silicone substrates, were exposed to one of three static levels of pHT, 8.01, 7.78, or 7.50, for 13 weeks. We found that barnacles were robust to reduced pH, with no effect of pH on physiological metrics (mortality, tissue mass, and presence of eggs). Likewise, adhesive properties (adhesion strength and adhesive plaque gross morphology) were not affected by reduced pH. Shell formation, however, was affected by seawater pH. Shell mass and base plate area were higher in barnacles exposed to reduced pH; barnacles grown at pHT 8.01 exhibited approximately 30% lower shell mass and 20% smaller base plate area as compared to those at pHT 7.50 or 7.78. Enhanced growth at reduced pH appears to be driven by the increased size of the calcite crystals that comprise the shell. Despite enhanced growth, mechanical properties of the base plate (but not the parietal plates) were compromised at the lowest pH level. Barnacle base plates at pHT 7.50 broke more easily and crack propagation, measured through microhardness testing, was significantly affected by seawater pH. Other shell metrics (plate thickness, relative crystallinity, and atomic disorder) were not affected by seawater pH. Hence, a reduction in pH resulted in larger barnacles but with base plates that would crack more readily. It is yet to be determined if such changes would alter the survival of A. amphitrite in the field, but changes in the abundance of this ecologically dominant species would undoubtedly affect the composition of biofouling communities. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2019) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-09-18.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEA - Data Publi...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    B2FIND
    Dataset . 2018
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PANGAEA
    Dataset . 2018
    License: CC BY
    Data sources: PANGAEA
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PANGAEA
    Dataset . 2018
    Data sources: PANGAEA
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEA - Data Publi...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      B2FIND
      Dataset . 2018
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      PANGAEA
      Dataset . 2018
      License: CC BY
      Data sources: PANGAEA
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      PANGAEA
      Dataset . 2018
      Data sources: PANGAEA
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  • Authors: Kilcher, Levi;

    During the summer field season in 2012, Benthic GeoScience Inc. (Benthic) mobilized under contract with Ocean Renewable Power Company (ORPC) in order to conduct precise geospatial measurements of the seafloor accomplishing a preliminary Site Characterization Study for the ORPC East Forelands Tidal Energy Power Project. This study included a high-density bathymetric survey, acoustic reflective intensity imagery, and an assessment of the physical character of the ORPC East Forelands Tidal Energy Power Project environment. The Multibeam Echosounder (MBES) survey included a large area surrounding the East Forelands of Cook Inlet in the vicinity of Nikiski, Alaska. Included in this submission are the report for the East Forelands Site Characterization Study and the accompanying data from the survey as described below. The digital deliverables from this effort include: - Comprehensive Site Characterization Report (Format: PDF, Ver. 1.1, March 2013) - Comprehensive 3D Fledermaus Presentation (Format: SCENE, Ver. 1.1, March 2013) - Bathymetric Surface (Format: ASCVer. 1, March 2013) - Slope Gradient Surface (Format: ASCVer. 1, March 2013) - Comprehensive Acoustic Intensity Image (Format: TIF/TWFVer. 1, March 2013) - Geologic Seafloor Interpretation Surface (Format: ASCVer. 1.0, March 2013) - Comprehensive Google Earth Presentation (Format: KMZVer. 1.1, March 2013)

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Coni, Ericka O C; Nagelkerken, Ivan; Ferreira, Camilo M; Connell, Sean D; +1 Authors

    Poleward range extensions by warm-adapted sea urchins are switching temperate marine ecosystems from kelp-dominated to barren-dominated systems that favour the establishment of range-extending tropical fishes. Yet, such tropicalization may be buffered by ocean acidification, which reduces urchin grazing performance and the urchin barrens that tropical range-extending fishes prefer. Using ecosystems experiencing natural warming and acidification, we show that ocean acidification could buffer warming-facilitated tropicalization by reducing urchin populations (by 87%) and inhibiting the formation of barrens. This buffering effect of CO2 enrichment was observed at natural CO2 vents that are associated with a shift from a barren-dominated to a turf-dominated state, which we found is less favourable to tropical fishes. Together, these observations suggest that ocean acidification may buffer the tropicalization effect of ocean warming against urchin barren formation via multiple processes (fewer urchins and barrens) and consequently slow the increasing rate of tropicalization of temperate fish communities. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2021) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2021-07-26.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEA - Data Publi...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    B2FIND
    Dataset . 2021
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PANGAEA
    Dataset . 2021
    License: CC BY
    Data sources: PANGAEA
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PANGAEA
    Dataset . 2021
    Data sources: PANGAEA
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEA - Data Publi...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      B2FIND
      Dataset . 2021
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      PANGAEA
      Dataset . 2021
      License: CC BY
      Data sources: PANGAEA
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      PANGAEA
      Dataset . 2021
      Data sources: PANGAEA
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Marangon, Emma; Goldenberg, Silvan U; Nagelkerken, Ivan;

    Marine prey and predators will respond to future climate through physiological and behavioral adjustments. However, our understanding of how such direct effects may shift the outcome of predator–prey interactions is still limited. Here, we investigate the effects of ocean warming and acidification on foraging behavior and biomass of a common prey (shrimps, Palaemon spp.) tested in large mesocosms harboring natural resources and habitats. Acidification did not alter foraging behavior in prey. Under warming, however, prey showed riskier behavior by foraging more actively and for longer time periods, even in the presence of a live predator. No effects of longer-term exposure to climate stressors were detected on prey biomass. Our findings suggest that ocean warming may increase the availability of some prey to predators via a behavioral pathway (i.e., increased risk-taking by prey), likely by elevating metabolic demand of prey species. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2020) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-12-08.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEA - Data Publi...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    B2FIND
    Dataset . 2020
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PANGAEA
    Dataset . 2020
    License: CC BY
    Data sources: PANGAEA
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PANGAEA
    Dataset . 2020
    Data sources: PANGAEA
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PANGAEA - Data Publi...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      B2FIND
      Dataset . 2020
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      PANGAEA
      Dataset . 2020
      License: CC BY
      Data sources: PANGAEA
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      PANGAEA
      Dataset . 2020
      Data sources: PANGAEA
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Schalkhausser, Burgel; Bock, Christian; Stemmer, Kristina; Brey, Thomas; +2 Authors

    In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Lavigne and Gattuso, 2011) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2013-10-14.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ B2FINDarrow_drop_down
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    B2FIND
    Dataset . 2013
    Data sources: B2FIND
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PANGAEA
    Dataset . 2013
    License: CC BY
    Data sources: PANGAEA
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PANGAEA
    Dataset . 2013
    Data sources: PANGAEA
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ B2FINDarrow_drop_down
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      B2FIND
      Dataset . 2013
      Data sources: B2FIND
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      PANGAEA
      Dataset . 2013
      License: CC BY
      Data sources: PANGAEA
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      PANGAEA
      Dataset . 2013
      Data sources: PANGAEA
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Nicolaus, Marcel; Anhaus, Philipp; Arndt, Stefanie; Hoppmann, Mario; +2 Authors

    The data set has been processed and contains quality flags for different kinds for erroneous data. Flag values are the sum of individual error codes. The value of 0 refers to no error. Quality flag, sun: If the suns position is close to the horizon, the radiometers measure a very noisy signal. Radiometer measurements and variables which are computed from them are flagged +1 if the sun elevation is below 10 degrees; +2 if the broad band albedo exceeds the threshold 1.05 .This buoy had no own GPS source. It was located at the Central Observertory (CO1) of MOSAiC. The drift track of CO1 is published here:Nicolaus, Marcel; Riemann-Campe, Kathrin; Bliss, Angela; Hutchings, Jennifer K; Granskog, Mats A; Haas, Christian; Hoppmann, Mario; Kanzow, Torsten; Krishfield, Richard A; Lei, Ruibo; Rex, Markus; Li, Tao; Rabe, Benjamin (2021): Drift trajectory of the Central Observatory 1 (CO1) of the Distributed Network of MOSAiC 2019/2020. Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA, https://doi.org/10.1594/PANGAEA.937184 Solar radiation over and under sea ice was measured by radiation station 2020R13, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 3) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 06 May 2020 and 15 May 2020 in sample intervals of 10 minutes. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance.

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    PANGAEA
    Dataset . 2022
    Data sources: PANGAEA
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      PANGAEA
      Dataset . 2022
      Data sources: PANGAEA
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    Authors: Karjalainen, Olli; Luoto, Miska; Aalto, Juha; Etzelmüller, Bernd; +4 Authors

    This dataset contains spatial predictions of the potential environmental spaces for pingos, ice-wedge polygons and rock glaciers across the Northern Hemisphere permafrost areas. The potential environmental spaces, i.e. conditions where climate, topography and soil properties are suitable for landform presence, were predicted with statistical ensemble modelling employing geospatial data on environmental conditions at 30 arc-second resolution (~1 km). In addition to the baseline period (1950-2000), the predictions are provided for 2041-2060 and 2061-2080 using climate-forcing scenarios (Representative Concentration Pathways 4.5 and 8.5). The resulting dataset consists of five spatial predictions for each landform in GeoTIFF format.The data provide new information on 1) the fine-scale spatial distribution of permafrost landforms in the Northern Hemisphere, 2) the potential future alterations in the environmental suitability for permafrost landforms due to climate change, and 3) the circumpolar distribution of various ground ice types, and can 4) facilitate efforts to inventory permafrost landforms in incompletely mapped areas.

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    B2FIND
    Dataset . 2020
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2020
    License: CC BY
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2020
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2020
      License: CC BY
      Data sources: PANGAEA
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  • Authors: Salgueiro, Emília; Magalhães, Vítor; Rebotim, Andreia; Matos, Lélia; +4 Authors

    The CARBO-ACID research cruise (EUROFLEETS+ SEA02_10) was carried out on the RV Ramón Margalef between August 2nd and August 11st, with departing from Vigo – Spain and ending in Lisbon – Portugal. The main objective of this cruise was to collect data and samples to study the potential effects of ocean acidification on carbonate marine organisms (coccolithophores, pteropods, planktonic and benthic foraminifera, and corals) along the Iberian margin. With this objective, oceanographic data and water samples, plankton, cold-water corals and sediment samples were collected during an upwelling season, along two transects coinciding with the two persistent upwelling filaments off the Iberia Margin: the Cape Finisterra and the Cape Roca. In this dataset is guiven all the acquired data recollected onboad. During the CARBO-ACID cruise we did a total of 7 stations, 4 stations along the Cape Finisterra transect (from W to E: CA3, CA2, CA7, CA8) and 3 stations at the Cape Roca (from W to E: CA6, CA5, CA4) transect (Fig). At each station we usually started with a multibeam survey, a CTD and Rosette cast. These initial operations allowed to identify the different water masses present in this area, characterize their physical properties and to recover seawater samples at specific depth levels. The seawater samples were onboard subsampled, preserved in cold conditions or with chemicals and/ or filtered for several further analysis in the shore-based laboratories: DNA, chlorophyll, fitoplankton, coccolithophores, pH, alkalinity, stable isotopic composition, trace elements concentration and Suspend Particulate Matter. Subsequently to these operations, at each station, two vertical tows with a plankton multinet (with 5 nets) were done on the top 700 m of the water column to sample the planktonic communities of the different water depths. After this, sediment samples were recovered with a box-corer to study the past oceanographic conditions, between the pre-industrial Era and the Present, with multi-proxies used in paleoceanography and sedimentology. A total of 10 box-cores were recollected and each of them was onboard sub-sampled for eDNA, enzymes and benthic foraminifera. Fifteen shipek grab samples were recollected at the Fontanelas seamount (Estremadura Spur), station CA6, to characterize the sedimentary cover and to evaluate the presence of deep cold-water corals. Preliminary results show that the stations CA7, CA8 and CA4, located close to the coast, as expected, are the most influenced by the coastal upwelling, exhibiting colder surface water, higher values of fluorescence, and more zooplankton content reflecting higher phyto-zooplankton concentrations, as typical of the upwelling waters. At station CA4 temperature was higher and fluorescence showed lower values, indicative of less phytoplankton, and interpreted as indicating a different upwelling source water from that upwelled further north. Based on the CTD data, the Cape Roca transect is more influenced by the subtropical East North Atlantic Central Water (ENACWst), while the Cape Finisterra transect is more under the influence of the subpolar branch (ENACWsp). Seafloor sediment samples showed significant differences between the stations. Along the northern transect (Cape Finisterra) the seafloor sediments show an increase in grain size from the offshore to the coast. The offshore stations CA3 and CA2 revealed finer grained sediments, CA8 were composed of coarser sand and the station CA7, the shallowest station 77 m, presented the sediment composed mainly of shell fragments and coarse grain sand. Along the southern transect (Cape Roca), the offshore station CA6 (Fontanelas seamount) has coarser sandy sediments with rock clasts and cold-water coral fragments, and the stations CA5 and CA4 with fine sand to muddy sediments. The detailed CA6 bathymetry allowed to verify the existence of small plateaus on the slope of the Fontanelas seamount, where the fossil cold-water corals fragments were found, suggesting that this area is a very interesting system deserving further study with a ROV, and to characterize the corals fields and verify if there are live corals. These recollected data and samples will allow not only to reconstruct the pH variability under different environmental conditions, but also to estimate the biogeochemical changes along the coastal ocean waters as the anthropogenic influence increases. These results will contribute to better understand and model the effects on the biota under the future expected oceans pH changes.

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    Authors: Friedrichs-Manthey, Martin; Langhans, Simone D; Borgwardt, Florian; Hein, Thomas; +4 Authors

    The data contains vulnerability estimates (climate niche factor analysis) for 49 native fish species in the upper Danube River basin. The upper Danube River basin is mainly located in Germany and Austria. The time frame covered is 300 years from 1800 to 2100 including two Representative Concentration Pathways, RCP 4.5 and RCP 8.5. Vulnerability estimates are calculated for three time frames (1800-1830; 1900-1930and 2070-2100 (including two RCPs)) with the time frame 1970-2000 as the baseline. In all files the zone column gives the basin ID for the master basins layer. The mean column gives the mean vulnerability estimate for a sub-basin for a certain species. For the future scenarios the different predictions based on the different GCM-RCM combinations have to be combined using the median and the zone as unique identifier.

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    B2FIND
    Dataset . 2021
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2021
    License: CC BY
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2021
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2021
      License: CC BY
      Data sources: PANGAEA
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Nicolaus, Marcel; Gerland, Sebastian;

    Solar radiation over and under sea ice was measured by an autonomous platform, installed on drifting sea ice in the Arctic Ocean during the SV TARA drift campaign in 2007 (station name 2007R24). The resulting time series describes radiation measurements as a function of place and time between 28 April 2007 and 05 September 2007 in sample intervals of 30 minutes. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm) and photosynthetically active radiation (PAR, 400 to 700 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 2 m above the sea ice surface. The third sensor was mounted 1.4 m underneath the sea ice measuring the downward transmitted irradiance. The data set has been processed and contains quality flags for different kinds for erroneous data. Flag values are the sum of individual error codes. The value of 0 refers to no error. Quality flag, sun: If the suns position is close to the horizon, the radiometers measure a very noisy signal. Radiometer measurements and variables which are computed from them are flagged +1 if the sun elevation is below 10 degrees; +2 if the broad band albedo exceeds the threshold 1.05 .

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    B2FIND
    Dataset . 2022
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2022
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2022
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2022
      Data sources: PANGAEA
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Nardone, Jessica A; Patel, Shrey; Siegel, Kyle R; Tedesco, Dana; +7 Authors

    Barnacles are dominant members of marine intertidal communities. Their success depends on firm attachment provided by their proteinaceous adhesive and protection imparted by their calcified shell plates. Little is known about how variations in the environment affect adhesion and shell formation processes in barnacles. Increased levels of atmospheric CO2 have led to a reduction in the pH of ocean waters (i.e., ocean acidification), a trend that is expected to continue into the future. Here, we assessed if a reduction in seawater pH, at levels predicted within the next 200 years, would alter physiology, adhesion, and shell formation in the cosmopolitan barnacle Amphibalanus (=Balanus) amphitrite. Juvenile barnacles, settled on silicone substrates, were exposed to one of three static levels of pHT, 8.01, 7.78, or 7.50, for 13 weeks. We found that barnacles were robust to reduced pH, with no effect of pH on physiological metrics (mortality, tissue mass, and presence of eggs). Likewise, adhesive properties (adhesion strength and adhesive plaque gross morphology) were not affected by reduced pH. Shell formation, however, was affected by seawater pH. Shell mass and base plate area were higher in barnacles exposed to reduced pH; barnacles grown at pHT 8.01 exhibited approximately 30% lower shell mass and 20% smaller base plate area as compared to those at pHT 7.50 or 7.78. Enhanced growth at reduced pH appears to be driven by the increased size of the calcite crystals that comprise the shell. Despite enhanced growth, mechanical properties of the base plate (but not the parietal plates) were compromised at the lowest pH level. Barnacle base plates at pHT 7.50 broke more easily and crack propagation, measured through microhardness testing, was significantly affected by seawater pH. Other shell metrics (plate thickness, relative crystallinity, and atomic disorder) were not affected by seawater pH. Hence, a reduction in pH resulted in larger barnacles but with base plates that would crack more readily. It is yet to be determined if such changes would alter the survival of A. amphitrite in the field, but changes in the abundance of this ecologically dominant species would undoubtedly affect the composition of biofouling communities. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2019) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-09-18.

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    B2FIND
    Dataset . 2018
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2018
    License: CC BY
    Data sources: PANGAEA
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    PANGAEA
    Dataset . 2018
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2018
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2018
      License: CC BY
      Data sources: PANGAEA
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      PANGAEA
      Dataset . 2018
      Data sources: PANGAEA
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  • Authors: Kilcher, Levi;

    During the summer field season in 2012, Benthic GeoScience Inc. (Benthic) mobilized under contract with Ocean Renewable Power Company (ORPC) in order to conduct precise geospatial measurements of the seafloor accomplishing a preliminary Site Characterization Study for the ORPC East Forelands Tidal Energy Power Project. This study included a high-density bathymetric survey, acoustic reflective intensity imagery, and an assessment of the physical character of the ORPC East Forelands Tidal Energy Power Project environment. The Multibeam Echosounder (MBES) survey included a large area surrounding the East Forelands of Cook Inlet in the vicinity of Nikiski, Alaska. Included in this submission are the report for the East Forelands Site Characterization Study and the accompanying data from the survey as described below. The digital deliverables from this effort include: - Comprehensive Site Characterization Report (Format: PDF, Ver. 1.1, March 2013) - Comprehensive 3D Fledermaus Presentation (Format: SCENE, Ver. 1.1, March 2013) - Bathymetric Surface (Format: ASCVer. 1, March 2013) - Slope Gradient Surface (Format: ASCVer. 1, March 2013) - Comprehensive Acoustic Intensity Image (Format: TIF/TWFVer. 1, March 2013) - Geologic Seafloor Interpretation Surface (Format: ASCVer. 1.0, March 2013) - Comprehensive Google Earth Presentation (Format: KMZVer. 1.1, March 2013)

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    Authors: Coni, Ericka O C; Nagelkerken, Ivan; Ferreira, Camilo M; Connell, Sean D; +1 Authors

    Poleward range extensions by warm-adapted sea urchins are switching temperate marine ecosystems from kelp-dominated to barren-dominated systems that favour the establishment of range-extending tropical fishes. Yet, such tropicalization may be buffered by ocean acidification, which reduces urchin grazing performance and the urchin barrens that tropical range-extending fishes prefer. Using ecosystems experiencing natural warming and acidification, we show that ocean acidification could buffer warming-facilitated tropicalization by reducing urchin populations (by 87%) and inhibiting the formation of barrens. This buffering effect of CO2 enrichment was observed at natural CO2 vents that are associated with a shift from a barren-dominated to a turf-dominated state, which we found is less favourable to tropical fishes. Together, these observations suggest that ocean acidification may buffer the tropicalization effect of ocean warming against urchin barren formation via multiple processes (fewer urchins and barrens) and consequently slow the increasing rate of tropicalization of temperate fish communities. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2021) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2021-07-26.

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    B2FIND
    Dataset . 2021
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2021
    License: CC BY
    Data sources: PANGAEA
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    PANGAEA
    Dataset . 2021
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2021
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2021
      License: CC BY
      Data sources: PANGAEA
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      PANGAEA
      Dataset . 2021
      Data sources: PANGAEA
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    Authors: Marangon, Emma; Goldenberg, Silvan U; Nagelkerken, Ivan;

    Marine prey and predators will respond to future climate through physiological and behavioral adjustments. However, our understanding of how such direct effects may shift the outcome of predator–prey interactions is still limited. Here, we investigate the effects of ocean warming and acidification on foraging behavior and biomass of a common prey (shrimps, Palaemon spp.) tested in large mesocosms harboring natural resources and habitats. Acidification did not alter foraging behavior in prey. Under warming, however, prey showed riskier behavior by foraging more actively and for longer time periods, even in the presence of a live predator. No effects of longer-term exposure to climate stressors were detected on prey biomass. Our findings suggest that ocean warming may increase the availability of some prey to predators via a behavioral pathway (i.e., increased risk-taking by prey), likely by elevating metabolic demand of prey species. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2020) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-12-08.

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    B2FIND
    Dataset . 2020
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2020
    License: CC BY
    Data sources: PANGAEA
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    PANGAEA
    Dataset . 2020
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2020
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2020
      License: CC BY
      Data sources: PANGAEA
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      PANGAEA
      Dataset . 2020
      Data sources: PANGAEA
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    Authors: Schalkhausser, Burgel; Bock, Christian; Stemmer, Kristina; Brey, Thomas; +2 Authors

    In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Lavigne and Gattuso, 2011) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2013-10-14.

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    B2FIND
    Dataset . 2013
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2013
    License: CC BY
    Data sources: PANGAEA
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    PANGAEA
    Dataset . 2013
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2013
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2013
      License: CC BY
      Data sources: PANGAEA
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      PANGAEA
      Dataset . 2013
      Data sources: PANGAEA
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    Authors: Nicolaus, Marcel; Anhaus, Philipp; Arndt, Stefanie; Hoppmann, Mario; +2 Authors

    The data set has been processed and contains quality flags for different kinds for erroneous data. Flag values are the sum of individual error codes. The value of 0 refers to no error. Quality flag, sun: If the suns position is close to the horizon, the radiometers measure a very noisy signal. Radiometer measurements and variables which are computed from them are flagged +1 if the sun elevation is below 10 degrees; +2 if the broad band albedo exceeds the threshold 1.05 .This buoy had no own GPS source. It was located at the Central Observertory (CO1) of MOSAiC. The drift track of CO1 is published here:Nicolaus, Marcel; Riemann-Campe, Kathrin; Bliss, Angela; Hutchings, Jennifer K; Granskog, Mats A; Haas, Christian; Hoppmann, Mario; Kanzow, Torsten; Krishfield, Richard A; Lei, Ruibo; Rex, Markus; Li, Tao; Rabe, Benjamin (2021): Drift trajectory of the Central Observatory 1 (CO1) of the Distributed Network of MOSAiC 2019/2020. Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA, https://doi.org/10.1594/PANGAEA.937184 Solar radiation over and under sea ice was measured by radiation station 2020R13, an autonomous platform, installed on drifting First-Year-Ice (FYI) in the Arctic Ocean during MOSAiC (Leg 3) 2019/20. The resulting time series describes radiation measurements as a function of place and time between 06 May 2020 and 15 May 2020 in sample intervals of 10 minutes. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 1 m above the sea ice surface. The third sensor was mounted 0.5 m underneath the sea ice measuring the downward transmitted irradiance.

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    PANGAEA
    Dataset . 2022
    Data sources: PANGAEA
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      PANGAEA
      Dataset . 2022
      Data sources: PANGAEA
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    Authors: Karjalainen, Olli; Luoto, Miska; Aalto, Juha; Etzelmüller, Bernd; +4 Authors

    This dataset contains spatial predictions of the potential environmental spaces for pingos, ice-wedge polygons and rock glaciers across the Northern Hemisphere permafrost areas. The potential environmental spaces, i.e. conditions where climate, topography and soil properties are suitable for landform presence, were predicted with statistical ensemble modelling employing geospatial data on environmental conditions at 30 arc-second resolution (~1 km). In addition to the baseline period (1950-2000), the predictions are provided for 2041-2060 and 2061-2080 using climate-forcing scenarios (Representative Concentration Pathways 4.5 and 8.5). The resulting dataset consists of five spatial predictions for each landform in GeoTIFF format.The data provide new information on 1) the fine-scale spatial distribution of permafrost landforms in the Northern Hemisphere, 2) the potential future alterations in the environmental suitability for permafrost landforms due to climate change, and 3) the circumpolar distribution of various ground ice types, and can 4) facilitate efforts to inventory permafrost landforms in incompletely mapped areas.

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    B2FIND
    Dataset . 2020
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2020
    License: CC BY
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2020
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2020
      License: CC BY
      Data sources: PANGAEA
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  • Authors: Salgueiro, Emília; Magalhães, Vítor; Rebotim, Andreia; Matos, Lélia; +4 Authors

    The CARBO-ACID research cruise (EUROFLEETS+ SEA02_10) was carried out on the RV Ramón Margalef between August 2nd and August 11st, with departing from Vigo – Spain and ending in Lisbon – Portugal. The main objective of this cruise was to collect data and samples to study the potential effects of ocean acidification on carbonate marine organisms (coccolithophores, pteropods, planktonic and benthic foraminifera, and corals) along the Iberian margin. With this objective, oceanographic data and water samples, plankton, cold-water corals and sediment samples were collected during an upwelling season, along two transects coinciding with the two persistent upwelling filaments off the Iberia Margin: the Cape Finisterra and the Cape Roca. In this dataset is guiven all the acquired data recollected onboad. During the CARBO-ACID cruise we did a total of 7 stations, 4 stations along the Cape Finisterra transect (from W to E: CA3, CA2, CA7, CA8) and 3 stations at the Cape Roca (from W to E: CA6, CA5, CA4) transect (Fig). At each station we usually started with a multibeam survey, a CTD and Rosette cast. These initial operations allowed to identify the different water masses present in this area, characterize their physical properties and to recover seawater samples at specific depth levels. The seawater samples were onboard subsampled, preserved in cold conditions or with chemicals and/ or filtered for several further analysis in the shore-based laboratories: DNA, chlorophyll, fitoplankton, coccolithophores, pH, alkalinity, stable isotopic composition, trace elements concentration and Suspend Particulate Matter. Subsequently to these operations, at each station, two vertical tows with a plankton multinet (with 5 nets) were done on the top 700 m of the water column to sample the planktonic communities of the different water depths. After this, sediment samples were recovered with a box-corer to study the past oceanographic conditions, between the pre-industrial Era and the Present, with multi-proxies used in paleoceanography and sedimentology. A total of 10 box-cores were recollected and each of them was onboard sub-sampled for eDNA, enzymes and benthic foraminifera. Fifteen shipek grab samples were recollected at the Fontanelas seamount (Estremadura Spur), station CA6, to characterize the sedimentary cover and to evaluate the presence of deep cold-water corals. Preliminary results show that the stations CA7, CA8 and CA4, located close to the coast, as expected, are the most influenced by the coastal upwelling, exhibiting colder surface water, higher values of fluorescence, and more zooplankton content reflecting higher phyto-zooplankton concentrations, as typical of the upwelling waters. At station CA4 temperature was higher and fluorescence showed lower values, indicative of less phytoplankton, and interpreted as indicating a different upwelling source water from that upwelled further north. Based on the CTD data, the Cape Roca transect is more influenced by the subtropical East North Atlantic Central Water (ENACWst), while the Cape Finisterra transect is more under the influence of the subpolar branch (ENACWsp). Seafloor sediment samples showed significant differences between the stations. Along the northern transect (Cape Finisterra) the seafloor sediments show an increase in grain size from the offshore to the coast. The offshore stations CA3 and CA2 revealed finer grained sediments, CA8 were composed of coarser sand and the station CA7, the shallowest station 77 m, presented the sediment composed mainly of shell fragments and coarse grain sand. Along the southern transect (Cape Roca), the offshore station CA6 (Fontanelas seamount) has coarser sandy sediments with rock clasts and cold-water coral fragments, and the stations CA5 and CA4 with fine sand to muddy sediments. The detailed CA6 bathymetry allowed to verify the existence of small plateaus on the slope of the Fontanelas seamount, where the fossil cold-water corals fragments were found, suggesting that this area is a very interesting system deserving further study with a ROV, and to characterize the corals fields and verify if there are live corals. These recollected data and samples will allow not only to reconstruct the pH variability under different environmental conditions, but also to estimate the biogeochemical changes along the coastal ocean waters as the anthropogenic influence increases. These results will contribute to better understand and model the effects on the biota under the future expected oceans pH changes.

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    Authors: Friedrichs-Manthey, Martin; Langhans, Simone D; Borgwardt, Florian; Hein, Thomas; +4 Authors

    The data contains vulnerability estimates (climate niche factor analysis) for 49 native fish species in the upper Danube River basin. The upper Danube River basin is mainly located in Germany and Austria. The time frame covered is 300 years from 1800 to 2100 including two Representative Concentration Pathways, RCP 4.5 and RCP 8.5. Vulnerability estimates are calculated for three time frames (1800-1830; 1900-1930and 2070-2100 (including two RCPs)) with the time frame 1970-2000 as the baseline. In all files the zone column gives the basin ID for the master basins layer. The mean column gives the mean vulnerability estimate for a sub-basin for a certain species. For the future scenarios the different predictions based on the different GCM-RCM combinations have to be combined using the median and the zone as unique identifier.

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    B2FIND
    Dataset . 2021
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2021
    License: CC BY
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2021
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2021
      License: CC BY
      Data sources: PANGAEA
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    Authors: Nicolaus, Marcel; Gerland, Sebastian;

    Solar radiation over and under sea ice was measured by an autonomous platform, installed on drifting sea ice in the Arctic Ocean during the SV TARA drift campaign in 2007 (station name 2007R24). The resulting time series describes radiation measurements as a function of place and time between 28 April 2007 and 05 September 2007 in sample intervals of 30 minutes. The radiation measurements have been performed with spectral radiometers. All data are given in full spectral resolution interpolated to 1.0 nm, and integrated over the entire wavelength range (broadband, total: 320 to 950 nm) and photosynthetically active radiation (PAR, 400 to 700 nm). Two sensors, solar irradiance and upward reflected solar irradiance, were mounted on a on a platform about 2 m above the sea ice surface. The third sensor was mounted 1.4 m underneath the sea ice measuring the downward transmitted irradiance. The data set has been processed and contains quality flags for different kinds for erroneous data. Flag values are the sum of individual error codes. The value of 0 refers to no error. Quality flag, sun: If the suns position is close to the horizon, the radiometers measure a very noisy signal. Radiometer measurements and variables which are computed from them are flagged +1 if the sun elevation is below 10 degrees; +2 if the broad band albedo exceeds the threshold 1.05 .

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    B2FIND
    Dataset . 2022
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2022
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2022
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2022
      Data sources: PANGAEA
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