Geology topics

Lori M. Fuller

Publications and source records attributed to Lori M. Fuller.

7 recordsLinked to original sources

USGS2017

Detection of microcystin and other cyanotoxins in lakes at Isle Royale National Park, Pictured Rocks National Lakeshore, and Sleeping Bear Dunes National Lakeshore, northern Michigan, 2012–13

Although cyanotoxins released during algal blooms have become an increasing concern in surface waters across the United States, the presence of cyanotoxins in northern Michigan lakes had not been evaluated in detail. The U.S. Geological Survey and National Park Service (NPS) led a 2-year study (2012 and 2013) to determine the presence of microcystin and other algal toxins in several inland lakes at Isle Royale National Park (hereafter referred to as ISRO, Pictured Rocks National Lakeshore (hereafter referred to as PIRO), and Sleeping Bear Dunes National Lakeshore (hereafter referred to as SLBE). Samples also were collected at four sites in Lake Michigan within the SLBE. The two analytical techniques used in the study were enzyme-linked immunosorbent assays (ELISA) for microcystin, cylindrospermopsin, and saxitoxin; and liquid chromatography/tandem mass spectrometry (LC/MS/MS) for a larger suite of algal toxins. Neither cylindrospermopsin nor saxitoxin were detected in the 211 samples. Microcystin was detected in 31 percent of samples (65 of 211 samples) analyzed by the ELISA method, but no sample results exceeded the World Health Organization recreational health advisory standard for microcystin (10 micrograms per liter [µg/L]). However, about 10 percent of the samples (21 of 211 samples) that were collected from PIRO and SLBE and were analyzed by ELISA for microcystin had concentrations greater than the U.S. Environmental Protection Agency (EPA) drinking water 10-day health advisory of 0.3 µg/L for children preschool age and younger (less than 6-years old). One sample collected in 2012 from SLBE exceeded the EPA drinking water 10-day health advisory of 1.6 µg/L for school-age children through adults (6-years old and older). In 2012, the highest concentration of 2.7 µg/L was detected in Florence Lake within SLBE. Many visitors enjoy recreation in or on the water and camp in the backcountry at these national parks where the most common source of drinking water is filtered surface water. Approximately 18 percent of the samples (39 of 211 samples) were analyzed by LC/MS/MS to confirm the ELISA results and to evaluate the samples for a larger suite of algal toxins. In general, the microcystin results between the ELISA and LC/MS/MS methods were similar; although, the ELISA results tended to be slightly higher than the summation of LC/MS/MS microcystin congeners. The slightly higher ELISA results might be because the ELISA microcystin method is reactive with the ADDA functional group common to all microcystins, and because not all microcystin congeners are included in the LC/MS/MS method. The LC/MS/MS method indicated that the congener microcystin-LR was the most frequently detected, followed by microcystin-WR and microcystin-YR. Sixteen of the lakes included in this study also were monitored by the NPS for nutrients. Total phosphorus (TP) concentrations were, on average, highest at the ISRO lakes, whereas total nitrogen (TN) concentrations were highest at SLBE. The average annual TN:TP ratios for the 16 lakes within the national park and national lakeshores ranged from ratios of 20 to 89. Overall, results indicated a slight increase in percentage of microcystin detections with an increase in the TN:TP ratio (R-squared 0.269 and 0.340, respectively [2012 and 2013 combined dataset] derived from linear regression). This study also indicated that even in the absence of visible algal blooms, microcystin may be present. Most microcystin concentrations did not exceed the EPA’s 10-day health advisory drinking-water benchmark. In general, these results provide a useful baseline with which to evaluate potential future changes in algal toxin concentrations.

Michigan↗

USGS2016

Estimation of a Trophic State Index for selected inland lakes in Michigan, 1999–2013

A 15-year estimated Trophic State Index (eTSI) for Michigan inland lakes is available, and it spans seven datasets, each representing 1 to 3 years of data from 1999 to 2013. On average, 3,000 inland lake eTSI values are represented in each of the datasets by a process that relates field-measured Secchi-disk transparency (SDT) to Landsat satellite imagery to provide eTSI values for unsampled inland lakes. The correlation between eTSI values and field-measured Trophic State Index (TSI) values from SDT was strong as shown by R 2 values from 0.71 to 0.83. Mean eTSI values ranged from 42.7 to 46.8 units, which when converted to estimated SDT (eSDT) ranged from 8.9 to 12.5 feet for the datasets. Most eTSI values for Michigan inland lakes are in the mesotrophic TSI class. The Environmental Protection Agency (EPA) Level III Ecoregions were used to illustrate and compare the spatial distribution of eTSI classes for Michigan inland lakes. Lakes in the Northern Lakes and Forests, North Central Hardwood Forests, and Southern Michigan/Northern Indiana Drift Plains ecoregions are predominantly in the mesotrophic TSI class. The Huron/Erie Lake Plains and Eastern Corn Belt Plains ecoregions, had predominantly eutrophic class lakes and also the highest percent of hypereutrophic lakes than other ecoregions in the State. Data from multiple sampling programs—including data collected by volunteers with the Cooperative Lakes Monitoring Program (CLMP) through the Michigan Department of Environmental Quality (MDEQ), and the 2007 National Lakes Assessment (NLA)—were compiled to compare the distribution of lake TSI classes between each program. The seven eTSI datasets are available for viewing and download with eSDT from the Michigan Lake Water Clarity Interactive Map Viewer at http://mi.water.usgs.gov/projects/RemoteSensing/index.html .

Michigan↗

USGS2015

Estimation of monthly water yields and flows for 1951-2012 for the United States portion of the Great Lakes Basin with AFINCH

Monthly water yields from 105,829 catchments and corresponding flows in 107,691 stream segments were estimated for water years 1951–2012 in the Great Lakes Basin in the United States. Both sets of estimates were computed by using the Analysis of Flows In Networks of CHannels (AFINCH) application within the NHDPlus geospatial data framework. AFINCH provides an environment to develop constrained regression models to integrate monthly streamflow and water-use data with monthly climatic data and fixed basin characteristics data available within NHDPlus or supplied by the user. For this study, the U.S. Great Lakes Basin was partitioned into seven study areas by grouping selected hydrologic subregions and adjoining cataloguing units. This report documents the regression models and data used to estimate monthly water yields and flows in each study area. Estimates of monthly water yields and flows are presented in a Web-based mapper application. Monthly flow time series for individual stream segments can be retrieved from the Web application and used to approximate monthly flow-duration characteristics and to identify possible trends.

Great Lakes Basin↗

USGS2013

Geographic setting influences Great Lakes beach microbiological water quality

Understanding of factors that influence Escherichia coli (EC) and enterococci (ENT) concentrations, pathogen occurrence, and microbial sources at Great Lakes beaches comes largely from individual beach studies. Using 12 representative beaches, we tested enrichment cultures from 273 beach water and 22 tributary samples for EC, ENT, and genes indicating the bacterial pathogens Shiga-toxin producing E. coli (STEC), Shigella spp., Salmonella spp, Campylobacter jejuni/coli, and methicillin-resistant Staphylococcus aureus, and 108–145 samples for Bacteroides human, ruminant, and gull source-marker genes. EC/ENT temporal patterns, general Bacteroides concentration, and pathogen types and occurrence were regionally consistent (up to 40 km), but beach catchment variables (drains/creeks, impervious surface, urban land cover) influenced exceedances of EC/ENT standards and detections of Salmonella and STEC. Pathogen detections were more numerous when the EC/ENT Beach Action Value (but not when the Geometric Mean and Statistical Threshold Value) was exceeded. EC, ENT, and pathogens were not necessarily influenced by the same variables. Multiple Bacteroides sources, varying by date, occurred at every beach. Study of multiple beaches in different geographic settings provided new insights on the contrasting influences of regional and local variables, and a broader-scale perspective, on significance of EC/ENT exceedances, bacterial sources, and pathogen occurrence.

Great Lakes↗

USGS2013

Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches

Predictive models have been used at beaches to improve the timeliness and accuracy of recreational water-quality assessments over the most common current approach to water-quality monitoring, which relies on culturing fecal-indicator bacteria such as Escherichia coli (E. coli.) . Beach-specific predictive models use environmental and water-quality variables that are easily and quickly measured as surrogates to estimate concentrations of fecal-indicator bacteria or to provide the probability that a State recreational water-quality standard will be exceeded. When predictive models are used for beach closure or advisory decisions, they are referred to as “nowcasts.” During the recreational seasons of 2010-12, the U.S. Geological Survey (USGS), in cooperation with 23 local and State agencies, worked to improve existing nowcasts at 4 beaches, validate predictive models at another 38 beaches, and collect data for predictive-model development at 7 beaches throughout the Great Lakes. This report summarizes efforts to collect data and develop predictive models by multiple agencies and to compile existing information on the beaches and beach-monitoring programs into one comprehensive report. Local agencies measured E. coli concentrations and variables expected to affect E. coli concentrations such as wave height, turbidity, water temperature, and numbers of birds at the time of sampling. In addition to these field measurements, equipment was installed by the USGS or local agencies at or near several beaches to collect water-quality and metrological measurements in near real time, including nearshore buoys, weather stations, and tributary staff gages and monitors. The USGS worked with local agencies to retrieve data from existing sources either manually or by use of tools designed specifically to compile and process data for predictive-model development. Predictive models were developed by use of linear regression and (or) partial least squares techniques for 42 beaches that had at least 2 years of data (2010-11 and sometimes earlier) and for 1 beach that had 1 year of data. For most models, software designed for model development by the U.S. Environmental Protection Agency (Virtual Beach) was used. The selected model for each beach was based on a combination of explanatory variables including, most commonly, turbidity, day of the year, change in lake level over 24 hours, wave height, wind direction and speed, and antecedent rainfall for various time periods. Forty-two predictive models were validated against data collected during an independent year (2012) and compared to the current method for assessing recreational water quality-using the previous day’s E. coli concentration (persistence model). Goals for good predictive-model performance were responses that were at least 5 percent greater than the persistence model and overall correct responses greater than or equal to 80 percent, sensitivities (percentage of exceedances of the bathing-water standard that were correctly predicted by the model) greater than or equal to 50 percent, and specificities (percentage of nonexceedances correctly predicted by the model) greater than or equal to 85 percent. Out of 42 predictive models, 24 models yielded over-all correct responses that were at least 5 percent greater than the use of the persistence model. Predictive-model responses met the performance goals more often than the persistence-model responses in terms of overall correctness (28 versus 17 models, respectively), sensitivity (17 versus 4 models), and specificity (34 versus 25 models). Gaining knowledge of each beach and the factors that affect E. coli concentrations is important for developing good predictive models. Collection of additional years of data with a wide range of environmental conditions may also help to improve future model performance. The USGS will continue to work with local agencies in 2013 and beyond to develop and validate predictive models at beaches and improve existing nowcasts, restructuring monitoring activities to accommodate future uncertainties in funding and resources.

Great Lakes↗

USGS2009

Analysis of Water-Quality Trends for Selected Streams in the Water Chemistry Monitoring Program, Michigan, 1998-2005

In 1998, the Michigan Department of Environmental Quality and the U.S. Geological Survey began a long-term monitoring program to evaluate the water quality of most watersheds in Michigan. Major goals of this Water-Chemistry Monitoring Program were to identify streams exceeding or not meeting State or Federal water-quality standards and to assess if constituent concentrations reflecting water quality in these streams were increasing or decreasing over time. As part of this program, water-quality data collected from 1998 to 2005 were analyzed to identify potential trends. Sixteen water-quality constituents were analyzed at 31 sites across Michigan, 28 of which had sufficient data to analyze for trends. Trend analysis on the various water-quality data was done using the uncensored Seasonal Kendall test within the computer program ESTREND. The most prevalent trend detected throughout the state was for chloride. Chloride trends were detected at 8 of the 28 sites; trends at 7 sites were increasing and the trend at 1 site was decreasing. Although no trends were detected for various nitrogen species or phosphorus, these constituents were detected at levels greater than the U.S. Environmental Protection Agency recommendations for nutrients in water. The results of the trend analysis will help to establish a baseline to evaluate future changes in water quality in Michigan streams.

Scientific Investigations Report↗

USGS2007

Stream-water quality during storm-runoff events and low-flow periods in the St. Clair River/Lake St. Clair Basin, Michigan

This report, a product of the Lake St. Clair Regional Monitoring Project, describes four water-quality studies in the St. Clair River/Lake St. Clair Basin from the early 1970's through 2005. All the studies examined water quality of streams in the basin; the most recent studies focused primarily on water quality during high- and low-streamflows. This report explains how storm-runoff and low-flow periods affect water quality in the basin. Included is a summary of stream-water quality findings from the National Stream Quality Accounting Network (1973-95); the National Water-Quality Assessment (1996-98); the Oakland County Land-Use Change study (2001-03); and the Lake St. Clair Regional Monitoring Project (2004-05).

Michigan↗