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Data from: Global temperature homogenization can obliterate temporal...11 Digital ObjectsClimate change is expected to increase the spatial autocorrelation of temperature, resulting in greater synchronization of climate variables worldwide. Possibly such...https://doi.org/10.25850/nioz/7b.b.dg Version 3
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NIOZ jetty hourly data for temperature and salinity for 20221 Digital ObjectNIOZ jetty LON=4.789E LAT=53.002N, using EXO sensor at depth of -1.5 meter NAP. Derived product from 10 second calibrated data. Separate calibration measurement at 2 week...https://doi.org/10.25850/nioz/7b.b.cg Version 3
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ADCP data Whittard Canyon 64PE453-532 Digital ObjectsThis dataset covers ADCP data collected in Whittard Canyon at 2200 m water depth. THe 75 kHz ADCP was upward looking and deployed in Whittard to monitor daily to seasonal...https://doi.org/10.25850/nioz/7b.b.7c Version 4
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Fe-binding ligands, voltammetric methods comparison - PS1003 Digital ObjectsCompetitive ligand exchange ??? adsorptive cathodic stripping voltammetry (CLE-AdCSV) is a widely used technique to determine dissolved iron (Fe) speciation in seawater, and...https://doi.org/10.25850/nioz/7b.b.7 Version 4
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Organic ligands are a key factor determining availability of dissolved-Fe (DFe) in the high nutrient low chlorophyll (HNLC) areas of the Southern Ocean. In this study, organic...https://doi.org/10.25850/nioz/7b.b.5 Version 4
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The establishment of young organisms in harsh environments often requires a Window of Opportunity (WoO). That is, a short time window in which environmental conditions drop long...https://doi.org/10.25850/nioz/7b.b.3c Version 4
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Counting using deep learning regression gives value to ecological surveys.13 Digital ObjectsMany ecological studies rely on count data and involve manual counting of objects of interest, which is time-consuming and especially disadvantageous when time in the field or...https://doi.org/10.25850/nioz/7b.b.0c Version 4