Geology topics

Julie Kinzelman

Publications and source records attributed to Julie Kinzelman.

5 recordsLinked to original sources

USGS2022

Human and ecosystem health in coastal systems

U.S. coastal economies and communities are facing an unprecedented and growing number of impacts to coastal ecosystems including beach and fishery closures, harmful algal blooms, loss of critical habitat, as well as shoreline damage. This paper synthesizes our present understanding of the dynamics of human and ecosystem health in coastal systems with a focus on the need to better understand nearshore physical process interactions with coastal pollutants and ecosystems (e.g. fate and transport, circulation, depositional environment, climate change). It is organized around two major topical areas and six subtopic areas: 1) Identifying and mitigating coastal pollutants, including fecal pollution, nutrients and harmful algal blooms, and microplastics; and 2) Resilient coastal ecosystems, which focuses on coastal fisheries, shellfish and natural and nature-based features (NNBF). Societal needs and the tools and technologies needed to address them are discussed for each subtopic. Recommendations for scientific research, observations, community engagement, and policies aim to help prioritize future research and investments. A better understanding of coastal physical processes and interactions with coastal pollutants and resilient ecosystems (e.g. fate and transport, circulation, depositional environment, climate change) is a critical need. Other research recommendations include the need to quantify potential threats to human and ecosystem health through accurate risk assessments and to quantify the resulting hazard risk reduction of natural and nature-based features; improve pollutant and ecosystem impacts forecasting by integrating frequent and new data points into existing and novel models; collect environmental data to calibrate and validate models to predict future impacts on coastal ecosystems and their evolution due to anthropogenic stressors (land-based pollution, overfishing, coastal development), climate change, and sea level rise; and develop lower cost and rapid response tools to help coastal managers better respond to pollutant and ecosystem threats.

Shore and Beach↗

USGS2020

Utilization of multiple microbial tools to evaluate efficacy of restoration strategies to improve recreational water quality at a Lake Michigan Beach (Racine, WI)

Hydro-meteorological conditions facilitate transport of fecal indicator bacteria (FIB) to the nearshore environment, affecting recreational water quality. North Beach (Racine, Wisconsin, United States), is an exemplar public beach site along Lake Michigan, where precipitation-mediated surface runoff, wave encroachment, stormwater and tributary outflow were demonstrated to contribute to beach advisories. Multiple restoration actions, including installation of a stormwater retention wetland, were successfully deployed to improve recreational water quality. Implementation of molecular methods (e.g. human microbial source tracking markers and Escherichia coli ( E. coli ) qPCR) assisted in identifying potential pollution sources and improving public health response time. However, periodic water quality failures still occur. As local beach managers reassess restoration measures in response to climatic changes, use of expanded microbial methods (including bacterial community profiling) may contribute to a better understanding of these dynamic environments. In this 2-year study (2015 and 2019), nearshore/offshore Lake Michigan, stormwater, and tributary samples were collected to determine if, 1) the constructed wetland (~50 m from the shoreline) continued to provide stormwater separation/retention and 2) mixing between onshore sources, Root River and Lake Michigan, was increasing due to rising precipitation/lake levels. Monthly rainfall totals were 1.5× higher in 2019 than 2015, coinciding with a 0.63 m lake-level rise. The prevalence of more intense, onshore winds also increased, facilitating interaction between potential reservoirs of FIB with nearshore water through wind driven waves and lake intrusion, e.g. beach sands and the adjacent Root River. While a strong relationship existed between wet weather wetland and North Beach nearshore E. coli concentrations (all sites), bacterial communities were strikingly different. Conversely, bacterial community overlap existed between the Root River mouth and nearshore/offshore sites. These results suggest the constructed wetland can accommodate the climate-related changes observed in this study. Future restoration activities could be directed towards upstream tributary sources in order to minimize microbial contaminants entering Lake Michigan.

Wisconsin↗

USGS2019

Standardized data quality acceptance criteria for a rapid Escherichia coli qPCR method (Draft Method C) for water quality monitoring at recreational beaches

There is growing interest in the application of rapid quantitative polymerase chain reaction (qPCR) and other PCR-based methods for recreational water quality monitoring and management programs. This interest has strengthened given the publication of U.S. Environmental Protection Agency (EPA)-validated qPCR methods for enterococci fecal indicator bacteria (FIB) and has extended to similar methods for Escherichia coli ( E. coli ) FIB. Implementation of qPCR-based methods in monitoring programs can be facilitated by confidence in the quality of the data produced by these methods. Data quality can be determined through the establishment of a series of specifications that should reflect good laboratory practice. Ideally, these specifications will also account for the typical variability of data coming from multiple users of the method. This study developed proposed standardized data quality acceptance criteria that were established for important calibration model parameters and/or controls from a new qPCR method for E. coli (EPA Draft Method C) based upon data that was generated by 21 laboratories. Each laboratory followed a standardized protocol utilizing the same prescribed reagents and reference and control materials. After removal of outliers, statistical modeling based on a hierarchical Bayesian method was used to establish metrics for assay standard curve slope, intercept and lower limit of quantification that included between-laboratory, replicate testing within laboratory, and random error variability. A nested analysis of variance (ANOVA) was used to establish metrics for calibrator/positive control, negative control, and replicate sample analysis data. These data acceptance criteria should help those who may evaluate the technical quality of future findings from the method, as well as those who might use the method in the future. Furthermore, these benchmarks and the approaches described for determining them may be helpful to method users seeking to establish comparable laboratory-specific criteria if changes in the reference and/or control materials must be made.

Water Research↗

USGS2019

Evaluation of multiple laboratory performance and variability in analysis of recreational freshwaters by a rapid Escherichia coli qPCR method (Draft Method C)

There is interest in the application of rapid quantitative polymerase chain reaction (qPCR) methods for recreational freshwater quality monitoring of the fecal indicator bacteria Escherichia coli ( E. coli ). In this study we determined the performance of 21 laboratories in meeting proposed, standardized data quality acceptance (QA) criteria and the variability of target gene copy estimates from these laboratories in analyses of 18 shared surface water samples by a draft qPCR method developed by the U.S. Environmental Protection Agency (EPA) for E. coli . The participating laboratories ranged from academic and government laboratories with more extensive qPCR experience to “new” water quality and public health laboratories with relatively little previous experience in most cases. Failures to meet QA criteria for the method were observed in 24% of the total 376 test sample analyses. Of these failures, 39% came from two of the “new” laboratories. Likely factors contributing to QA failures included deviations in recommended procedures for the storage and preparation of reference and control materials. A master standard curve calibration model was also found to give lower overall variability in log 10 target gene copy estimates than the delta-delta Ct (ΔΔCt) calibration model used in previous EPA qPCR methods. However, differences between the mean estimates from the two models were not significant and variability between laboratories was the greatest contributor to overall method variability in either case. Study findings demonstrate the technical feasibility of multiple laboratories implementing this or other qPCR water quality monitoring methods with similar data quality acceptance criteria but suggest that additional practice and/or assistance may be valuable, even for some more generally experienced qPCR laboratories. Special attention should be placed on providing and following explicit guidance on the preparation, storage and handling of reference and control materials.

Water Research↗

USGS2016

Multi-laboratory survey of qPCR enterococci analysis method performance in U.S. coastal and inland surface waters

Quantitative polymerase chain reaction (qPCR) has become a frequently used technique for quantifying enterococci in recreational surface waters, but there are several methodological options. Here we evaluated how three method permutations, type of mastermix, sample extract dilution and use of controls in results calculation, affect method reliability among multiple laboratories with respect to sample interference. Multiple samples from each of 22 sites representing an array of habitat types were analyzed using EPA Method 1611 and 1609 reagents with full strength and five-fold diluted extracts. The presence of interference was assessed three ways: using sample processing and PCR amplifications controls; consistency of results across extract dilutions; and relative recovery of target genes from spiked enterococci in water sample compared to control matrices with acceptable recovery defined as 50 to 200%. Method 1609, which is based on an environmental mastermix, was found to be superior to Method 1611, which is based on a universal mastermix. Method 1611 had over a 40% control assay failure rate with undiluted extracts and a 6% failure rate with diluted extracts. Method 1609 failed in only 11% and 3% of undiluted and diluted extracts analyses. Use of sample processing control assay results in the delta–delta Ct method for calculating relative target gene recoveries increased the number of acceptable recovery results. Delta–delta tended to bias recoveries from apparent partially inhibitory samples on the high side which could help in avoiding potential underestimates of enterococci — an important consideration in a public health context. Control assay and delta–delta recovery results were largely consistent across the range of habitats sampled, and among laboratories. The methodological option that best balanced acceptable estimated target gene recoveries with method sensitivity and avoidance of underestimated enterococci densities was Method 1609 without extract dilution and using the delta–delta calculation method. The applicability of this method can be extended by the analysis of diluted extracts to sites where interference is indicated but, particularly in these instances, should be confirmed by augmenting the control assays with analyses for target gene recoveries from spiked target organisms.

Journal of Microbiological Methods↗