Stream biofilms have been shown to be among the most sensitive indicators of environmental stress in aquatic ecosystems and several endpoints have been developed to measure biofilm adverse effects caused by environmental stressors. Here, we compare the effects of long-term exposure of stream biofilms to diuron, a commonly used herbicide, on several traditional ecotoxicological endpoints (biomass growth, photosynthetic efficiency, chlorophyll-a content, and taxonomic composition), with the effects measured by recently developed methods [community structure assessed by flow cytometry (FC-CS) and measurement of extracellular polymeric substances (EPS)]. Biofilms grown from local stream water in recirculating microcosms were exposed to a constant concentration of 20 μg/L diuron over a period of 3 weeks. During the experiment, we observed temporal variation in photosynthetic efficiency, biomass, cell size, presence of decaying cells and in the EPS protein fraction. While biomass growth, photosynthetic efficiency, and chlorophyll-a content were treatment independent, the effects of diuron were detectable with both FC and EPS measurements. This demonstrates that, at least for our experimental setup, a combination of different ecotoxicological endpoints can be important for evaluating biofilm environmental stress and suggests that the more recent ecotoxicological endpoints (FC-CS, EPS protein content and humic substances) can be a useful addition for stream biofilm ecotoxicological assessment.

Biofilms serve essential ecosystem functions and are used in different technical applications. Studies from stream ecology and waste water treatment have shown that biofilm functionality depends to a great extent on community structure. Here we present a fast and easy-to-use method for individual cell-based analysis of stream biofilms, based on stain-free flow cytometry and visualization of the high-dimensional data by viSNE. The method allows the combined assessment of community structure, decay of phototrophic organisms and presence of abiotic particles. In laboratory experiments, it allows quantification of cellular decay and detection of survival of larger cells after temperature stress, while in the field it enables detection of community structure changes that correlate with known environmental drivers (flow conditions, dissolved organic carbonDOC, calcium) and detection of microplastic contamination. The method can potentially be applied to other biofilm types, e.g. for inferring community structure for environmental and industrial research and monitoring.

The objective of the DISCOVR consortia is to develop an integrated algae strain screening platform for the discovery of high-productivity and resilient strains of algae that can be cultivated outdoors year-round via crop rotation. The data includes annual weather data, algae cultivation composition data, and pond water chemistry data between 2018 and 2021. This year-over-year cultivation data provides the underlying data in direct support of the annual State of Technology (SOT) analysis effort. These field experimental data and SOT reports are of interest to the U.S. Department of Energys (DOE) Energy Efficiency and Renewable Energys (EERE) Bioenergy Technologies office (BETO) in understanding current best algae agronomic practices in demonstrating progress towards future algae biomass productivity goals as outlined in the BETO Multi-Year Program Plan.

DNA barcoding gene sequences and files associated with their analysis

This dataset mapped 8 types of intertidal and shallow subtidal vegetation along saltwater shorelines in Skagit County and part of Island County in 1996 using an airborne multispectral scanner.  This is one element of a larger dataset that includes substrate type, wave & current energy, water regime and tidal datum lines as well as an ArcGIS layer file.  The complete dataset (all layers) can be accessed under "Download Data".

This data set contains variables measured during a survey of sediment-methane production rates in a eutrophic reservoir in southwestern Ohio. The measured production rates and a suite of predictor variables including water chemistry, sediment characteristics, and algal abundance are presented.. This dataset is associated with the following publication: Berberich, M., J. Beaulieu, T. Hamilton, S. Waldo, and I. Buffam. Spatial variability of sediment methane production and methanogen communities within a eutrophic reservoir: importance of organic matter source and quantity. LIMNOLOGY AND OCEANOGRAPHY. American Society of Limnology and Oceanography, Lawrence, KS, USA, 65(3): 1-23, (2020).