Calculated optical Nitrate along RV MARIA S. MERIAN cruise MSM97/2

During R/V Maria S. Merian cruise MSM97/2 a sensor box (AddOn Box) was attached to a PocketFerryBox (4H Jena, Germany) in-line obtaining waters from the ships two autonomous measurement systems (RSWS). For the measurement of underway absorption spectra to calculate optical nitrate, the AddOn Box was equipped with two UV-process spectrophotometer (ProPS and OPUS, TriOS Mess- und Datentechnik GmbH, Germany). Data were recorded continuously in a ten-minute interval along the cruise track with an optical path length of 10 mm. The integration time was 256 ms. The ProPS photometer is equipped with a Deuterium lamp as light source whereas the OPUS photometer is equipped with a Xenon flash lamp. Baseline calibrations were done for both UV-photometer using ultrapure water. For the ProPS, the calibration was done in the laboratory before the cruise whereas the calibration for the OPUS was done by the manufacturer. The water inlet of the RSWS is allocated at approx. 6.5 m below the sea surface. While one box is measuring, the other box is being cleaned. The boxes switch after a user-defined measuring and cleaning interval. On MSM97/2, the boxes were alternating every 12 hours, including one short cleaning procedure during measurements after 4 hours. Absorption spectra obtained by the AddOn Box during the alternation process of the two RSWS, as well as during the internal cleaning procedure are not included. Spectra from station work are included. Within this dataset, absorption spectra were cut to a relevant wavelength range (from 189-360 nm (ProPS) and 199-360 nm (OPUS) to 210-260 nm). No further correction was done for the absorbance spectra in this processing step. After the cruise, gathered absorption spectra were used to improve current processing algorithms of optical nitrate detection for coastal and open ocean waters. Processing was performed according to Zielinski et al. (2011) and Frank et al. (2014) using MATLAB (R2018a). Detailed processing steps for the calculation of optical nitrate can be found on Zenodo (doi 10.5281/zenodo.4091420 ). Temperature and salinity data are necessary to compute nitrate values from derived UV-spectra and were taken from the attached PocketFerryBox using a SBE45 probe (Sea Bird Scientific, USA). A linear CDOM-offset correction was carried out. Nitrate reference spectra and salinity reference spectra were measured in the laboratory before the cruise. Corresponding nitrate reference samples using wet chemical analysis will be published separately

Continuous wave and tide observations at DynaCom artificial islands in the back-barrier tidal flat, Spiekeroog, Germany, 2021-05

Data presented here were collected between January 2021 to October 2021 within the research unit DynaCom (Spatial community ecology in highly dynamic landscapes: From island biogeography to metaecosystems, (https://uol.de/dynacom/ ) of the Universities of Oldenburg, Göttingen, and Münster, the iDiv Leipzig and the Nationalpark Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were created in the back barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog. Local tide and wave conditions were recorded with a RBRduo TDǀwave sensor (RBR Ltd., Ontario/Canada). The sensor was bottom mounted in a shallow tidal creek (0.78 m NHN) through a steel girder (buried 0.3m deep in the sediment) and was positioned 10 cm above sediment surface, as was determined by using a portable differential GPS. This resulted in the sensor falling dry during low tide. For accurate depth calculations, raw pressure data were manually corrected for atmospheric pressure derived from a locally installed weather station. The sensor was pre-calibrated by the manufacturer and the sampling rate was 3 Hz with 1024 samples per burst at a sample interval of 10 min. Recorded data were internally logged until the readout with the Ruskin (V1.13.13) software. Date and time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, and (c) visually checks. Low-tide data is not removed, but were easily identified through the manually calculated water depth data, where all depths < 0.05m represented low tide data

Influence of Support Acidity and Ir Content on the Selective Ring Opening of Decalin over Ir/SiO 2 –Al 2 O 3

The influence of the addition of HCl and Ir (1 wt %) to different SiO2−Al2O3 supports of varying silica content was studied in the reaction of selective ring opening of decalin. The addition of HCl to silica−alumina supports containing 70 and 80 wt % SiO2 was found to have little influence in the distribution of reaction products compared to the calcined supports. The incorporation of Ir to the silica−alumina catalysts has a beneficial effect, increasing the decalin conversion, being this effect more noticeable in the low acidity supports, i.e., those containing 30−40 wt % SiO2. The iridium-containing materials display the highest yield of cracking products, ring opening products, and ring contraction products. Increasing the reaction temperature promotes cracking and dehydrogenation but markedly decreases the selectivity to ring contraction products. At 350 °C a slight decrease in selectivity to ring opening products occurs, though the overall increase in conversion results in an increased yield of these products. An optimum ratio between the acid sites and metal activity that favors the formation of ring opening products was found. At lower acid sites/metal activity ratios the isomerization reaction which leads to C5 cycle isomers is low, and ring opening by hydrogenolysis is limited as a consequence. On the other hand, at high acid sites/metal activity ratios the cracking reactions are favored, decreasing the yield of RO products.Fil: D'ippolito, Silvana Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigaciones en Catálisis y Petroquímica ; ArgentinaFil: Ballarini, Adriana Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigaciones en Catálisis y Petroquímica ; ArgentinaFil: Pieck, Carlos Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigaciones en Catálisis y Petroquímica ; Argentin

Continuous meteorological observations at DynaCom automatic weather station, Spiekeroog, Germany (2021-11)

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

Continuous meteorological observations at DynaCom automatic weather station, Spiekeroog, Germany (2021-06)

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

Continuous meteorological observations at DynaCom automatic weather station, Spiekeroog, Germany (2021-12)

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

Continuous meteorological observations at DynaCom automatic weather station, Spiekeroog, Germany (2021-03)

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

Continuous meteorological observations at DynaCom automatic weather station, Spiekeroog, Germany (2020-09)

Meteorological data were collected near the DynaCom experimental setup, with a locally installed weather station located approximately 500m north of the southern shoreline of Spiekeroog. The weather station system used here was a ClimaSensor US 4.920x.00.00x that was pre-calibrated by the manufacturer (Adolf Thies GmbH & Co. KG, D-Göttingen). Data were recorded and saved within the Meteo-Online (V4.5.0.20253) software in a sampling interval of 1 min, with an averaging time of 10 s. Date and time were given in UTC and the position was derived from the internal GPS system. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, defined as data exhibiting changes of more than two standard deviations within one time step, and (c) visually checks

Continuous wave and tide observations at DynaCom artificial islands in the back-barrier tidal flat, Spiekeroog, Germany, 2021-03

Data presented here were collected between January 2021 to October 2021 within the research unit DynaCom (Spatial community ecology in highly dynamic landscapes: From island biogeography to metaecosystems, (https://uol.de/dynacom/ ) of the Universities of Oldenburg, Göttingen, and Münster, the iDiv Leipzig and the Nationalpark Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were created in the back barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog. Local tide and wave conditions were recorded with a RBRduo TDǀwave sensor (RBR Ltd., Ontario/Canada). The sensor was bottom mounted in a shallow tidal creek (0.78 m NHN) through a steel girder (buried 0.3m deep in the sediment) and was positioned 10 cm above sediment surface, as was determined by using a portable differential GPS. This resulted in the sensor falling dry during low tide. For accurate depth calculations, raw pressure data were manually corrected for atmospheric pressure derived from a locally installed weather station. The sensor was pre-calibrated by the manufacturer and the sampling rate was 3 Hz with 1024 samples per burst at a sample interval of 10 min. Recorded data were internally logged until the readout with the Ruskin (V1.13.13) software. Date and time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, and (c) visually checks. Low-tide data is not removed, but were easily identified through the manually calculated water depth data, where all depths < 0.05m represented low tide data

Continuous wave and tide observations at DynaCom artificial islands in the back-barrier tidal flat, Spiekeroog, Germany, 2021-08

Data presented here were collected between January 2021 to October 2021 within the research unit DynaCom (Spatial community ecology in highly dynamic landscapes: From island biogeography to metaecosystems, (https://uol.de/dynacom/ ) of the Universities of Oldenburg, Göttingen, and Münster, the iDiv Leipzig and the Nationalpark Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were created in the back barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog. Local tide and wave conditions were recorded with a RBRduo TDǀwave sensor (RBR Ltd., Ontario/Canada). The sensor was bottom mounted in a shallow tidal creek (0.78 m NHN) through a steel girder (buried 0.3m deep in the sediment) and was positioned 10 cm above sediment surface, as was determined by using a portable differential GPS. This resulted in the sensor falling dry during low tide. For accurate depth calculations, raw pressure data were manually corrected for atmospheric pressure derived from a locally installed weather station. The sensor was pre-calibrated by the manufacturer and the sampling rate was 3 Hz with 1024 samples per burst at a sample interval of 10 min. Recorded data were internally logged until the readout with the Ruskin (V1.13.13) software. Date and time is given in UTC. Data handling was performed according to Zielinski et al. (2018): Post-processing of collected data was done using MATLAB (R2018a). Quality control was performed by (a) erasing data covering maintenance activities, (b) removing outliers, and (c) visually checks. Low-tide data is not removed, but were easily identified through the manually calculated water depth data, where all depths < 0.05m represented low tide data