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We collected specimens of Ulva sp. (green algae), Saccharina sp. (brown algae), Grateloupia sp., and Gelidium sp. (both red algae) during all four seasons from a coastal reef in Weihai, China, and analyzed their surface-colonizing bacteria in comparison to surrounding seawater and sediment controls. 16S rRNA amplicon sequencing, extensive plate cultivation, sequencing of selected strains, and sequencing of 23 metagenomes were performed in this study. Besides composition, we analyzed the potential of phycosphere bacteria to degrade algal polysaccharides and to produce bioactive secondary metabolites. This comprehensive dataset represents a significant stepping stone towards a better understanding of macroalgal phycosphere bacteria and paves the way to functional studies on representative strains.

Tools for interacting with the publicly available California Delta Fish Salvage Database, including continuous deployment of data access, analysis, and presentation.

Tools for interacting with the publicly available California Delta Fish Salvage Database, including continuous deployment of data access, analysis, and presentation.

Tools for interacting with the publicly available California Delta Fish Salvage Database, including continuous deployment of data access, analysis, and presentation.

Tools for interacting with the publicly available California Delta Fish Salvage Database, including continuous deployment of data access, analysis, and presentation.

Tools for interacting with the publicly available California Delta Fish Salvage Database, including continuous deployment of data access, analysis, and presentation.

Tools for interacting with the publicly available California Delta Fish Salvage Database, including continuous deployment of data access, analysis, and presentation.

Tools for interacting with the publicly available California Delta Fish Salvage Database, including continuous deployment of data access, analysis, and presentation.

{"references": ["Hassell, D., Gregory, J., Blower, J., Lawrence, B. N., and Taylor, K. E.: A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1), Geosci. Model Dev., 10, 4619\u20134646, https://doi.org/10.5194/gmd-10-4619-2017, 2017.", "Hassell et al., (2020). cfdm: A Python reference implementation of the CF data model. Journal of Open Source Software, 5(54), 2717, https://doi.org/10.21105/joss.02717"]} A CF-compliant Earth Science data analysis library Version 3.14.0 is the first to use Dask.

This data set includes four files (CSV format) containing observational data from two oceanographic moorings, BB and FF, located in the Southern Adriatic Sea from the period between March 2012 and June 2020. The stand-alone moorings are equipped with a 300 kHz ADCP-RDI system, which measures currents along the last 100 meters of the water column and a CTD recorder equipped with SeaPoint turbidity meter sensor located approximatively 10 m above the bottom. The turbidity sensor measures in a range of 0-25 FTU. Moorings were configured and maintained for continuous long-term monitoring following the approach of the CIESM Hydrochanges Program (www.ciesm.org/marine/programs/hydrochanges.html). The moorings are currently operational as from 2021 they have joined the southern Adriatic Sea submarine observatory system of the EMSO-ERIC European Consortium. The data were subjected to quality control (QC) and the coding numbers used, shown in a dedicated column, follow the SeaDataNet L20 measurement qualifiers flags. QC applied on echo data consists of detecting signal anomalies due to interactions with the seafloor and identifying if the signal falls below a minimum threshold for which the value is no longer considered reliable. For turbidity data, QC is addressed to the detections of possible spikes, anomalies, and sensor saturation in the recordings.