Data were collected to evaluate the efficacy of quantitative polymerase chain reaction (qPCR) as a rapid, alternative method for monitoring recreational water at select beaches and rivers of Sleeping Bear Dunes National Lakeshore (SLBE), in Empire, Michigan. Water samples were collected between August 4 and September 18, 2014 (N=297) from four locations (Esch Rd, Otter Creek, Platte Bay, and Platte River). The samples were analyzed for indicator bacteria, E. coli and enterococci, by both culture-based (membrane filtration, MF; traditional method) and non-culture based (qPCR; rapid method). Recreational water quality standards (RWQS) and beach action values (BAV) were used as indices to compare water quality standard exceedances for MF and qPCR methods; for enterococci: 70 colony-forming units (MF) and 1,000 calibrator cell equivalents and for E. coli: 235 colony-forming units (MF); currently, there are no established RWQS based for qPCR (i.e., CCE) results. The CultureBasedData data include E. coli and enterococci culture-based bacterial counts. Data from the qpcr_v3 file includes results from quantitative polymerase chain reaction (qPCR) method for estimation of E. coli and enterococci counts by DNA-based methods. The Lat_Long file includes information regarding sampling sites at each of the four locations and their corresponding latitude and longitudes.

Dataset describes measurements of host-associated qPCR genetic markers along with other water quality parameters and precipitation from samples collected at marine, estuary, and freshwater recreational sites. Additional details provided in attached Dataset Description document. “This research dataset has been reviewed in accordance with U.S. Environmental Protection Agency (U.S. EPA), Office of Research and Development, and approved for release. Mention of brand names or vendors does not constitute an endorsement of products or services by the U.S. EPA.”

Due to the recognized proliferation and spread of antibiotic resistance genes by anthropogenic use of antibiotics for human, agriculture and aquaculture purposes, antibiotic resistance genes have been defined as an emerging contaminant (Laxminarayan and others, 2013; Rodriguez-Rojas and others, 2013; Niu and others, 2016). The presence and spread of these genes in non-clinical and non-agricultural environments has created the need for background investigations to enhance our understanding of the magnitude and risks associated with this emerging field (Allen and others, 2010). The current global economic costs of antibiotic resistant microorganisms is about 5.8 trillion USD, which is approximately equivalent to the combined GDP of Germany and the United Kingdom (Taylor and others, 2014). In this study researchers screened soil and sediment samples for the presence of 15 antibiotic resistance gene targets and 5 species of Vibrio (a marker of marine inundation) to determine natural background concentrations. These data provide a foundation to address background prevalence of these genetic targets in the northeastern United States (U.S.) to address regional influences (sources of pollutants) and to contrast future influences due to sea-level rise and large scale storms.

qPCR assay measurements using the pilot reference material and NIST SRM 2917. This dataset is associated with the following publication: Willis, J., M. Sivaganesan, R. Haugland, J. Kralj, S. Servetas, M.E. Hunter, S.A. Jackson, and O. Shanks. Performance of NIST SRM® 2917 with 13 Recreational Water Quality Monitoring qPCR Assays. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 212: 118114, (2022).

The data contain the raw quantitative polymerase chain reaction (qPCR) results after pre-amplification by polymerase chain reaction for all Ceracystis lukuohia and huliohia testing of environmental DNA (eDNA) collected in Passive Environmental Samplers (PES).

The data contain the raw quantitative polymerase chain reaction (qPCR) results after pre-amplification by polymerase chain reaction for all Ceracystis lukuohia and huliohia testing of environmental DNA (eDNA) collected in Passive Environmental Samplers (PES).

This dataset is the evaluation of eutrophication in rivers based on quantitative polymerase chain reactions (qPCRs) of phytoplankton. The qPCR data of 2017, 2018, and 2019 are included in the current dataset. The 2917, 2018, and 2019 physicochemical and biological data generated by the USGS are also included in the current file. This dataset is associated with the following publication: Zhang, C., K. McIntosh, N. Sienkiewicz, E.A. Stelzer, J.L. Graham, and J. Lu. qPCR-based phytoplankton abundance and chlorophyll a: A multi-year study in twelve large freshwater rivers across the United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 954: 175067, (2024).

Tabular amplification data for individual technical replicates of tissue and water samples collected from Glacier National Park in 2020 and amplified with a Lednia tumana species-specific qPCR assay. Reported results include fractional detection rates, mean quantification cycles, and estimated gene copies per reaction.

Tabular amplification data for individual technical replicates of tissue and water samples collected from Glacier National Park in 2020 and amplified with a Lednia tumana species-specific qPCR assay. Reported results include fractional detection rates, mean quantification cycles, and estimated gene copies per reaction.

They are qPCR data for opportunistic pathogens and drinking water parameters. This dataset is associated with the following publication: Zhang, C., I. Struewing, J. Mistry, D. Wahman, J. Pressman, and J. Lu. Legionella and other opportunistic pathogens in full-scale chloraminated municipal drinking water distribution systems. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 205: 117571, (2021).