Microbial biofilm communities are composed of fungi, bacteria, and phytoplankton taxonomic groups (e.g., cyanobacteria, diatoms, and chlorophytes), 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 presence, nutritional quality, quantity, pigment characteristics, and likely taxonomic groups of biofilms 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 coupled 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). Using a suite of modeling approaches, we used these data to develop and scale algorithms of each parameter to the South Bay using an AVIRIS-NG image collected on April 15, 2021. See child items for more information. 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.

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. This raster dataset represents the likely presence and absence of biofilm located on the mudflats of South San Francisco Bay in Spring 2021, during peak shorebird migration. To produce this dataset, we used a multiscalar remote sensing approach, which coupled in-situ data with hyperspectral 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 calculated the B-index (Biofilm presence or absence index) based on the depth of the chlorophyll-a absorption feature at 680nm. We calibrated the index with HySpex spectra paired with in-situ measurements of biofilm chlorophyll-a concentrations (ng/g), a proxy for biofilm biomass. After validating the index with HySpex images, we defined a threshold index value to represent biofilm presence. Threshold B-index values of 0.015, 0.02 and 0.025 were set to represent sparse to abundant biofilm presence. We applied the B-index to the AVIRIS-NG image collected on April 15, 2021 over South San Francisco Bay. 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.

Microbial biofilm communities are composed of fungi, bacteria, and phytoplankton taxonomic groups (e.g., cyanobacteria, diatoms, and chlorophytes), 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 nutritional quality, quantity and pigment characteristics of biofilms 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 chlorophyll-a (chl-a; indicator of biomass), lipids, total organic carbon (TOC), carbohydrates and pigments (indicators of taxonomic groups). Using multiple and single response partial least squares regression, we modeled the nutritional quality components (chl-a, lipids, TOC, carbohydrates) with field spectra and scaled models to the South Bay using an AVIRIS-NG image collected on April 15, 2021. Pigments (chl-b, fucoxanthin, diadioxanthin, zeaxanthin) were likewise modeled and scaled to the South Bay. Results indicated high biomass and nutritional quality component concentrations within a tidal marsh restoration site and some creek outflows. 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.

Intertidal microbial biofilms, or microphytobenthos, support estuarine biogeochemical cycling, the physical stability of mudflats, and food webs, particularly those of migratory shorebirds. Photosynthetic biofilms dominated by diatoms, cyanobacteria and chlorophytes represent a significant fraction of biofilm biomass and contain pigments that can be detected with remote sensing. These diverse biofilm community types vary in indicator pigments and functional traits related to biogeochemical cycling and nutritional quality. We modeled and mapped the spatial variation in intertidal biofilm distribution, quantity, diversity, and functional traits using multi-scale spectroscopic data collected within southern San Francisco Bay, California, USA (South Bay). We developed single and multiple response partial least squares regression (PLS) models of chlorophyll-a (chl-a; biomass indicator), indicator pigments: fucoxanthin and diadinoxanthin (diatoms), zeaxanthin (cyanobacteria), and chl-b (chlorophytes), and functional traits: carbohydrates, lipids, and total organic carbon from paired in-situ biofilm data and field spectra collected with an ASD full-spectrum Field Spec Pro. Biofilm abundance, trait, and pigment data were obtained by analyzing biofilm samples in a lab. The PLS models were scaled to the South Bay with a 3.7m AVIRIS-NG (Airborne Visible/Infrared Imaging Spectrometer-Next Generation) hyperspectral image. The model %RMSE calculated from AVIRIS-NG test samples ranged from 12.7% for chl-a to 49% for chl-b; for six of the eight models, %RMSE was 23% or below. This data release contains .csv files for the paired ASD field spectra-biofilm calibration/validation dataset and the paired AVIRIS-NG-biofilm validation. This data release is associated with another data release that contains the published biofilm maps (Byrd et al. 2024, https://doi.org/10.5066/P13ZIMYC).

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).