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  • PANGAEA  (82)
  • ASLO (Association for the Sciences of Limnology and Oceanography)  (3)
  • InterSus Sustainability Services  (1)
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  • 1
    Publication Date: 2021-02-08
    Description: Ocean acidification (OA) is generally assumed to negatively impact calcification rates of marine organisms. At a local scale however, biological activity of macrophytes may generate pH fluctuations with rates of change that are orders of magnitude larger than the long-term trend predicted for the open ocean. These fluctuations may in turn impact benthic calcifiers in the vicinity. Combining laboratory, mesocosm and field studies, such interactions between OA, the brown alga Fucus vesiculosus, the sea grass Zostera marina and the blue mussel Mytilus edulis were investigated at spatial scales from decimetres to 100s of meters in the western Baltic. Macrophytes increased the overall mean pH of the habitat by up to 0.3 units relative to macrophyte-free, but otherwise similar, habitats and imposed diurnal pH fluctuations with amplitudes ranging from 0.3 to more than 1 pH unit. These amplitudes and their impact on mussel calcification tended to increase with increasing macrophyte biomass to bulk water ratio. At the laboratory and mesocosm scales, biogenic pH fluctuations allowed mussels to maintain calcification even under acidified conditions by shifting most of their calcification activity into the daytime when biogenic fluctuations caused by macrophyte activity offered temporal refuge from OA stress. In natural habitats with a low biomass to water body ratio, the impact of biogenic pH fluctuations on mean calcification rates of M. edulis was less pronounced. Thus, in dense algae or seagrass habitats, macrophytes may mitigate OA impact on mussel calcification by raising mean pH and providing temporal refuge from acidification stress.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
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  • 2
    Publication Date: 2019-09-23
    Description: Die Meeresstrategie-Rahmenrichtlinie (MSRL) will durch gezielte Maßnahmen bis 2021 den guten Umweltzustand in den europäischen Meeren erreichen. Dazu sind die Kosten und die Nutzen derartiger Schutzmaßnahmen zu ermitteln und abzuwägen. Die Ziele des Forschungsprojektes waren deshalb zweierlei: zum einen der Frage nachzugehen, welche ökonomischen Nutzen durch Maßnahmen zur Belastungsreduktion entstehen, und zum anderen zu untersuchen, wie die Nutzen einer Maßnahme zur Verbesserung der Meeresumwelt nach heutigem Wissensstand quantifiziert werden können. Mit der Kostenseiten befasst sich das Vorhaben nicht. Um die genannten Ziele zu erreichen, wurden im Projekt methodische Grundlagen und darauf basierend ein Mengengerüst zur Monetarisierung von ökonomischen Nutzen durch maritime Schutzmaßnahmen im Rahmen der MSRL-Implementierung entwickelt. Dieses methodische Vorgehen ist daraufhin in zwei Fallstudien (zur Müllreduzierung in der Nordsee und zur Eutrophierungsreduzierung in der Ostsee) auf seine Praktikabilität und Einfachheit hin getestet worden, um die Ergebnisse in die Entwicklung einer praktikablen Handlungsanleitung einfließen zu lassen. Flankierend wurde im Rahmen des Projekts eine Zahlungsbereitschaftsanalyse zur Eutrophierungsreduktion in der Ostsee durchgeführt, deren Ergebnisse in die Arbeiten des internationalen Forschungsnetzwerks BalticSTERN sowie in einer der o.g. Fallstudien eingeflossen sind. Die Ergebnisse des Vorhabens waren demnach eine Abschätzung der Nutzen durch Reduktionsmaßnahmen der Belastungen "Mariner Abfall" und "Eutrophierung", sowie eine Diskussion der damit verbundenen Unsicherheiten und Datenlücken. Außerdem ist über die Zahlungsbereitschaftsanalyse die Wertschätzung der deutschen Bevölkerung für eine Reduzierung der Eutrophierung der Ostsee erhoben worden. Die Erkenntnisse, die im Rahmen des Projektes gesammelt wurden, sind schließlich in die Handlungsanleitung eingeflossen.
    Type: Report , NonPeerReviewed
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  • 3
    Publication Date: 2023-02-08
    Description: The plea for using more “realistic,” community‐level, investigations to assess the ecological impacts of global change has recently intensified. Such experiments are typically more complex, longer, more expensive, and harder to interpret than simple organism‐level benchtop experiments. Are they worth the extra effort? Using outdoor mesocosms, we investigated the effects of ocean warming (OW) and acidification (OA), their combination (OAW), and their natural fluctuations on coastal communities of the western Baltic Sea during all four seasons. These communities are dominated by the perennial and canopy‐forming macrophyte Fucus vesiculosus—an important ecosystem engineer Baltic‐wide. We, additionally, assessed the direct response of organisms to temperature and pH in benchtop experiments, and examined how well organism‐level responses can predict community‐level responses to the dominant driver, OW. OW affected the mesocosm communities substantially stronger than acidification. OW provoked structural and functional shifts in the community that differed in strength and direction among seasons. The organism‐level response to OW matched well the community‐level response of a given species only under warm and cold thermal stress, that is, in summer and winter. In other seasons, shifts in biotic interactions masked the direct OW effects. The combination of direct OW effects and OW‐driven shifts of biotic interactions is likely to jeopardize the future of the habitat‐forming macroalga F. vesiculosus in the Baltic Sea. Furthermore, we conclude that seasonal mesocosm experiments are essential for our understanding of global change impact because they take into account the important fluctuations of abiotic and biotic pressures.
    Type: Article , PeerReviewed
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  • 4
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    ASLO (Association for the Sciences of Limnology and Oceanography) | Wiley
    Publication Date: 2024-06-07
    Description: The simulation of deep-sea conditions in laboratories is technically challenging but necessary for experiments that aim at a deeper understanding of physiological mechanisms or host-symbiont interactions of deep-sea organisms. In a proof-of-concept study, we designed a recirculating system for long-term culture (〉2 yr) of deep-sea mussels Gigantidas childressi (previously Bathymodiolus childressi). Mussels were automatically (and safely) supplied with a maximum stable level of ~60 μmol L−1 methane in seawater using a novel methane–air mixing system. Experimental animals also received daily doses of live microalgae. Condition indices of cultured G. childressi remained high over the years, and low shell growth rates could be detected, too, which is indicative of positive energy budgets. Using stable isotope data, we demonstrate that G. childressi in our culture system gained energy, both, from the digestion of methane-oxidizing endosymbionts and from digesting particulate food (microalgae). Limitations of the system, as well as opportunities for future experimental approaches involving deep-sea mussels, are discussed.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
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  • 5
    Publication Date: 2017-07-03
    Repository Name: EPIC Alfred Wegener Institut
    Type: PANGAEA Documentation , notRev
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  • 6
    Publication Date: 2023-03-14
    Description: This dataset is part of a dataset collection. Please read the documentation in Kiel fjord carbonate chemistry data between 2015 (February) and 2016 (January) doi:10.1594/PANGAEA.876551 for details on sampling, measurement and data processing.
    Keywords: Alkalinity, total; Carbon, inorganic, dissolved; Carbon dioxide, partial pressure; CO2S; CO2 Sensor; DATE/TIME; DEPTH, water; interpolated; Kiel Fjord; Kiel-Fjord_GEOMAR; pH; Phosphate; Salinity; Silicate; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 232 data points
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  • 7
    Publication Date: 2023-03-17
    Description: 2014-2019: Since September 2014, temperature, salinity, pH (only 2014-2015) and oxygen data were additionally logged in 10-minutes intervals at the GEOMAR pier (54°19'48.8N 10°08'59.6E) (AANDERAA oxygen sensor 3835 & SEABIRD SBE 37-SI MicroCAT CT(D)). The sensor system is mounted to a floating platform so that a continuous depth of 1 m is guaranteed at every time point. Oxygen data were corrected for salinity, temperature and depth following the manual for Aanderaa Optodes using the salinity and temperature measurements from the SEABIRD SBE 37-SI MicroCAT CT(D) sensor. pH was also corrected for salinity, temperature and depth following Martz et al. (2010). After cleaning and other re-boots of the sensor package, temperature, salinity and oxygen data tend to deviate from true values. Hence, 60 minutes of data after any re-boot (after sensor servicing with re-deployment, data download or power failure) were deleted. Furthermore, salinity data lower than 8 and pH data lower than 5 and larger than 10 were removed from the data set as these values were identified as outliers. On May 22nd 2018 as well as on May 26th (22:00) til 27th (15:00) 2019 oxygen data were identified as outliers and removed from the data set. The logged oxygen data were plotted against titration data (doi:10.1594/PANGAEA.930974) to check for drifts in the optode's data. But no drift pattern could be detected and the fit of the regression was very good R2adj. = 0.673, p 〈 0.001)
    Keywords: Corrected; CTD, Sea-Bird, SBE 37-SI MicroCAT; DATE/TIME; DEPTH, water; Kiel-Fjord_GEOMAR-Pier; Monitoring station; MONS; Number; Oxygen; Oxygen, dissolved; Oxygen optode, Aanderaa type 3835; Oxygen saturation; pH; Salinity; Temperature, water
    Type: Dataset
    Format: text/tab-separated-values, 1621988 data points
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  • 8
    Publication Date: 2023-03-08
    Description: 2005-2019 CTD (48M, Sea & Sun Technology GmbH, Trappenkamp, Germany) measurements and water samples at the surface (0 m depth), at 7 m and 18 m depth were taken biweekly between 2005 and 2019 at the “Wittlingskuhle” a bit off the GEOMAR pier in the Inner Kiel Fjord (N 54°19.69, E 10°09.06). The oxygen concentration of these water samples was measured by the Winkler- iodometric titration method (Winkler 1888) in mg/L and are converted to oxygen-saturation values by correcting for temperature, salinity and pressure.
    Keywords: CTD, Sea & Sun Technology, Germany, 48M; CTD/Rosette; CTD-RO; DATE/TIME; DEPTH, water; Event label; Kiel Fjord; Oxygen; Oxygen, dissolved; Oxygen saturation; PF2005; PF2005_Kiel-fjord; PF2006; PF2006_Kiel-fjord; PF2007; PF2007_Kiel-fjord; PF2008; PF2008_Kiel-Fjord; PF2009; PF2009_Kiel-fjord; PF2010; PF2010_Kiel-fjord; PF2011; PF2011_Kiel-fjord; PF2012; PF2012_Kiel-fjord; PF2013; PF2013_Kiel-fjord; PF2014; PF2014_Kiel-fjord; PF2015; PF2015_Kiel-fjord-2; PF2016; PF2016_Kiel-fjord; PF2017; PF2017_Kiel-fjord; PF2018; PF2018_Kiel-fjord; PF2019; PF2019_Kiel-fjord; Polarfuchs; Salinity; Temperature, water; Titration, Winkler
    Type: Dataset
    Format: text/tab-separated-values, 16044 data points
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  • 9
    Publication Date: 2023-01-13
    Description: A HydroC® CO2 sensor was deployed from a pontoon at the waterfront of the GEOMAR west shore building into Kiel Fjord, Western Baltic Sea (Kiel, Germany; 54°19'48.78"N, 010° 8'59.44"E). Since the pontoon is floating the deployment depth of the sensor was constant at 1m. Data of two deployment intervals are published here: February 2015 – May 2015 and August 2015 – January 2016.
    Keywords: CO2S; CO2 Sensor; Kiel Fjord; Kiel-Fjord_GEOMAR
    Type: Dataset
    Format: application/zip, 3 datasets
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  • 10
    Publication Date: 2023-01-13
    Description: The HydroC® CO2 sensor was deployed from a pontoon at the waterfront of the GEOMAR west shore building into Kiel Fjord, Western Baltic Sea (Kiel, Germany; 54°19'48.78"N, 010° 8'59.44"E). Since the pontoon is floating the deployment depth of the sensor was constant at 1m. Data of two deployment intervals are published here: 1) February 2015 - May 2015 2) August 2015 - January 2016 This dataset is part of a dataset collection. Please read the documentation in Kiel fjord carbonate chemistry data between 2015 (February) and 2016 (January) doi:10.1594/PANGAEA.876551 for details on sampling, measurement and data processing.
    Keywords: Carbon dioxide, partial pressure; CO2S; CO2 Sensor; DATE/TIME; DEPTH, water; HydroC pCO2 sensor, CONTROS; Kiel Fjord; Kiel-Fjord_GEOMAR
    Type: Dataset
    Format: text/tab-separated-values, 605356 data points
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