Sequence reads (16S rDNA- and 16S rRNA-based) were processed and analyzed using Mothur software. The results presented in the attached Excel file. Also, the other MS word file includes taxonomic summary tables for bacterial communities on biofilms from the MAIFAS reactor as well as the detailed description of Materials & Methods. This dataset is associated with the following publication: Church, J., H. Ryu, A. Sadmani, A. Randall, J. Santodomingo, and W.H. Lee. Multiscale investigation of a symbiotic microalgal-integrated fixed film activated sludge (MAIFAS) process for nutrient removal and photo-oxygenation. Bioresource Technology. Elsevier Online, New York, NY, USA, 268: 128-138, (2018).

These data are bacterial 16S rRNA sequences and a taxonomic summary table for biofilm samples from the bio-reactors. The data may provide background/supporting information for other researchers who have a similar experimental plan with a microbial electrochemical cell reactor. This dataset is associated with the following publication: Santodomingo, J., H. Lee, B. Dhar, J. An, B. Rittmann, H. Ren, and J. Chae. The Roles of Biofilm Conductivity and Donor Substrate Kinetics in a Mixed-Culture Biofilm Anod. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 50(23): 12799-12807, (2016).

These data include raw sequencing data (bacterial 16S and eukaryote 18S rRNA genes) and a summary result table for bacteria classification in an Excel file. This dataset is associated with the following publication: Hwang, J., H. Ryu, K. Rodriguez, S. Fahad, J. SantoDomingo, A. Kushima, and W. Lee. A strategy for power generation from bilgewater using a photosynthetic microalgal fuel cell (MAFC). JOURNAL OF POWER SOURCES. Elsevier Science Ltd, New York, NY, USA, 484: 229222, (2021).

The excel spreadsheet includes sample IDs and labeling information for DNA sequencing raw data. In addition, DNA concentrations for all the biofilm samples analyzed are presented. This dataset is associated with the following publication: Jeon, Y., l. li, J. Calvillo, H. Ryu, J. Santo Domingo, O. Choi, J. Brown, and Y. Seo. Impact of algal organic matter on the performance, cyanotoxin removal, and biofilms of biologically-active filtration systems. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 184: 116120, (2020).

Data used to generate Figures 2, 3, and 4 as we ll as Table 3. This dataset is associated with the following publication: Banerji, A., M. Bagley, J. Shoemaker, D. Tettenhorst, C. Nietch, J. Allen, and J. Santodomingo. Evaluating putative ecological drivers of microcystin spatiotemporal dynamics using metabarcoding and environmental data. Harmful Algae. Elsevier B.V., Amsterdam, NETHERLANDS, 86: 84-95, (2019).

This data set includes water quality data and microbial community abundance tables for periphyton samples from this project. The data set also includes extensive R markdown code used to process the data and generate the results included in the report. This dataset is associated with the following publication: Hagy, J., R. Devereux, K. Houghton, D. Beddick, T. Pierce, and S. Friedman. Developing Microbial Community Indicators of Nutrient Exposure in Southeast Coastal Plain Streams using a Molecular Approach. US EPA Office of Research and Development, Washington, DC, USA, 2018.

The excel spreadsheet includes sample IDs and labeling information for DNA sequencing raw data. In addition, DNA concentrations for all the biofilm samples analyzed are presented. This dataset is associated with the following publication: Li, L., Y. Jeon, S. Lee, H. Ryu, J. Santodomingo, and Y. Seo. Dynamics of the Physiochemical and Community Structures of Biofilms under the Influence of Algal Organic Matter and Humic Substances. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 158: 136-145, (2019).

Data corresponding to the figures in the paper. This dataset is associated with the following publication: Xing, Y., A. Ellis, M. Magnuson, and W. Harper. Adsorption of bacteriophage MS2 to colloids: Kinetics and particle interactions. Colloids and Surfaces A: Physicochemical and Engineering Aspects. Elsevier B.V., Amsterdam, NETHERLANDS, 585: 124099, (2020).

PS_GenBank.fasta file contain the sequences of the bacterial 16S rRNA-encoding gene for each representative sequence. The sequence containing four hypervariable regions was amplified using the primer set Eub-8f and 787. PS_GenBank.xlsx file contains rows as sample and columns as entries representing the accession number (NCBI) deposited in GenBank for each representative sequence (i.e. unique sequences). PS_OTU.fasta file contain the sequences of the bacterial 16S rRNA-encoding gene for each Operational Taxonomic Unit (OTU). The sequence containing four hypervariable regions was amplified using the primer set Eub-8f and 787. This dataset is associated with the following publication: Revetta , R., V. Gomez-Alvarez, T. Gerke, J. Santodomingo , and N. Ashbolt. CHANGES IN BACTERIAL COMPOSITION OF BIOFILM IN A METROPOLITAN DRINKING WATER DISTRIBUTION SYSTEM. JOURNAL OF APPLIED MICROBIOLOGY. Blackwell Publishing, Malden, MA, USA, 121(1): 294-305, (2016).

Microbial biofilm communities are composed of fungi, bacteria, and phytoplankton taxonomic groups (e.g., chlorophytes, diatoms and cyanobacteria), which inhabit the surface of intertidal mudflats. Such biofilms have critical roles in shorebird diets, mudflat stabilization, primary productivity, and carbon storage. These raster datasets represent the likely relative proportion of three biofilm taxonomic groups – chlorophytes, diatoms, and cyanobacteria – located on the mudflats of South San Francisco Bay in Spring 2021, during peak shorebird migration. To produce these datasets, we used a multi-scalar remote sensing approach that coupled in-situ data with data from an ASD field spectrometer, a HySpex VNIR/SWIR imaging spectrometer (5 mm), and the AVIRIS-Next Generation (NG) airborne imaging spectrometer (3.7 m). We used these data to develop and scale algorithms of pigments that are indicators of the taxonomic groups – chlorophytes: chlorophyll-a (chl-a) and chl-b; diatoms: chl-a, fucoxanthin and diadinoxanthin; and cyanobacteria: chl-a and zeaxanthin. Using multiple and single response partial least squares regression, we modeled each pigment with field spectra and scaled models to the South Bay using an AVIRIS-NG image collected on April 15, 2021. Using the resulting pigment indicator maps, we generated maps of the proportions of each taxonomic group within each pixel, which was normalized by mapped chl-a concentrations. Maps created using hyperspectral remote sensing data will support managers’ need to visualize shorebird habitat quality and research on drivers of biofilm quality and quantity.