USGS Ohio Water Science Center

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Microbiology & Ecology Projects

Evaluation of rapid viability-polymerase chain reaction (RV-PCR) for Bacillus globigii spores in water matrices
Evaluation of rapid viability-polymerase chain reaction (RV-PCR) for Bacillus globigii spores in water matrices

Rapid water-quality tests for microorganisms are needed to quickly ensure that water is safe for consumption. This study will test a rapid-viability, quantitative polymerase chain reaction (RV-PCR) method for the detection of Bacillus spores. The method will be tested in large-volume drinking water samples that are concentrated by ultrafiltration, as well as in water that has been disinfected with chlorine. Results from the rapid viability method will be compared to results from traditional bacteria-culturing methods. This study is in cooperation with the U.S. Environmental Protection Agency, National Homeland Security Research Center.

> Rebecca Bushon, rnbushon@usgs.gov

 


Evaluation of rapid viability-polymerase chain reaction (RV-PCR) for Bacillus globigii spores in water matrices
Implementation of microbiological sampling in NAWQA Cycle 3: Groundwater used as a source of drinking water

The National Water Quality Assessment Program (NAWQA) has been sampling public supply wells and domestic wells for a broad suite of microbiological indicators including total coliform, E. coli, enterococci, somatic coliphage, and f-specific coliphage. USGS scientists in Ohio and Massachusetts are collaborating on the analysis of microbiological data in environmental samples and will report on the occurrence of microbiological indicators in the Nation's groundwater.

> Rebecca Bushon, rnbushon@usgs.gov

 

 

 

 

 

 


Microbial Source Tracking
Microbial Source Tracking

The USGS Water Microbiology Laboratory in Columbus has been working with numerous agencies and USGS Water Science Centers to analyze water samples for microbial source tracking (MST) markers using the quantitative polymerase chain reaction (qPCR) method. Results from MST analyses help to characterize the effects of various sources of fecal contamination in a watershed. Currently, water samples can be analyzed for DNA markers that are associated with humans, cows and other ruminants, dogs, and waterfowl. In addition to MST marker analyses, other steps are generally taken as part of a multi-tiered approach to source tracking. These steps include conducting sanitary surveys, determining the distributions of bacterial indicators in the watershed, and understanding how hydrologic and meteorological processes affect the distributions of indicators and MST markers.

> Chris Kephart, ckephart@usgs.gov

 


Development of a model for predicting recreational water quality of the Cuyahoga River in the Cuyahoga Valley National Park based on real-time turbidity and stage data 
Development of a model for predicting recreational water quality of the Cuyahoga River in the Cuyahoga Valley National Park based on real-time turbidity and stage data  (website)

Cuyahoga Valley National Park officials are seeking a rapid method for estimating bacteria levels in the Cuyahoga River that would allow for more recreational use of the river. USGS and National Park Service personnel will use real-time turbidity data in a predictive model for recreational water quality. The model will provide predictions 7 days per week during the recreational season and will be accessible via the Ohio Nowcast Web site (www.ohionowcast.info).

> Amie Brady, amgbrady@usgs.gov

 

 


Modeling Aquatic Species Distributions on the Basis of Physical Habitat and Climate Change
Modeling Aquatic Species Distributions on the Basis of Physical Habitat and Climate Change (website)

Gap analysis is a coarse-scale assessment of aquatic biodiversity and conservation, the results of which can be used to guide biological field studies and monitoring programs. Potential species distribution models were developed for 130 fish, 70 bivalve, and 17 native crayfish species on the basis of a physical habitat-based classification of the perennial streams in Ohio. A more recent study has integrated fish-habitat classifications and associated fish-community data with downscaled (regional) climate predictions under different climate-change scenarios to identify vulnerable river systems and to project likely climate-driven changes to important fish species.

> Alex Covert, sacovert@usgs.gov

 


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