The statistical power to detect regional temporal trends in riverine contaminants in the Chesapeake Bay Watershed, USA

Chemical contamination of riverine ecosystems is largely a result of urbanization, industrialization, and agricultural activities occurring on adjacent terrestrial landscapes. Land management activities (e.g., Best Management Practices) are an important tool used to reduce point and non-point sources of pollution. However, the ability to confidently make inferences about the efficacy of land management activities on reducing in-stream chemical concentrations is poorly understood. We estimated regional temporal trends and components of variation for commonly used herbicides (atrazine and metolachlor), total estrogenicity, and riverine sediment concentrations of total PCBs for rivers in the Chesapeake Bay Watershed, USA. We then used the estimated variance components to perform a power analysis and evaluated the statistical power to detect regional temporal trends under different monitoring scenarios. Scenarios included varying the magnitude of the annual contaminant decline, the number of sites sampled each year, the number of years sampled, and sampling frequency. Monitoring for short time periods (e.g., 5 years) was inadequate for detecting regional temporal trends, regardless of the number of sites sampled or the magnitude of the annual declines. Even when monitoring over a 20-year period, sampling a relatively large number of sites each year was required (e.g., >50 sites) to achieve adequate statistical power for smaller trend magnitudes (declines of 5-7%/year). Annual sampling frequency had little impact on power for any monitoring scenario. All sampling scenarios were underpowered for sediment total PCBs. Power was greatest for total estrogenicity, suggesting that this aggregate measure of estrogenic activity may be a useful indicator. This study provides information that can be used to help (1) guide the development of monitoring programs aimed at detecting regional declines in riverine chemical contaminant concentrations in response to land management actions, and (2) set expectations for the ability to detect changes over time.

Targeted and non-targeted analysis of young-of-year smallmouth bass using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry

Smallmouth bass in the Susquehanna River Basin, Chesapeake Bay Watershed, USA, have been exhibiting clinical signs of disease and reproductive endocrine disruption (e.g., intersex, male plasma vitellogenin) for over fifteen years. Previous histological and targeted chemical analyses have identified infectious agents and pollutants in fish tissues including organic contaminants, mercury, and perfluorinated compounds, but a common causative link for the observed signs of disease across this widespread area has not been determined. This study examines 146 young-of-year smallmouth bass collected from 14 sampling sites in the Susquehanna River Basin, Pennsylvania, USA with varying levels of disease prevalence. Whole fish were extracted by a recently developed modification to the quick, easy, cheap, effective, rugged, and safe extraction method and analyzed by comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry. A targeted analysis was conducted to identify the presence and quantity of 127 known contaminants, including polychlorinated biphenyls, brominated diphenyl ethers, organochlorinated pesticides, and pharmaceutical and personal care products. A non-targeted analysis was conducted on the same data set to identify analytes of interest not included on routine target compound lists. Chromatographic alignment through Statistical Compare (ChromaTOF GC) was followed by Fisher ratio and principal component analysis to reduce the data set from thousands of peaks per sample to a final data set of 65 analytes of interest. Comparisons of these 65 compounds between Normal (no observed health anomalies) and Lesioned (observed health anomaly at time of collection) fish revealed increased levels of three chemical families in Lesioned fish including esters, ketones, and nitrogen containing compounds.

Groundwater discharges as a source of phytoestrogens and other agriculturally derived contaminants to streams

Groundwater discharge zones in streams are important habitats for aquatic organisms. The use of discharge zones for thermal refuge and spawning by fish and other biota renders them susceptible to potential focused discharge of groundwater contamination. Currently, there is a paucity of information about discharge zones as a potential exposure pathway of chemicals to stream ecosystems. Using thermal mapping technologies to locate groundwater discharges, shallow groundwater and surface water from three rivers in the Chesapeake Bay Watershed, USA were analyzed for phytoestrogens, pesticides and their degradates, steroid hormones, sterols and bisphenol A. A Bayesian censored regression model was used to compare groundwater and surface water chemical concentrations. The most frequently detected chemicals in both ground and surface water were the phytoestrogens genistein (79%) and formononetin (55%), the herbicides metolachlor (50%) and atrazine (74%), and the sterol cholesterol (88%). There was evidence suggesting groundwater discharge zones could be a unique exposure pathway of chemicals to surface water systems, in our case, metolachlor sulfonic acid (posterior mean concentration = 150 ng/L in groundwater and 4.6 ng/L in surface water). Our study also demonstrated heterogeneity of chemical concentration in groundwater discharge zones within a stream for the phytoestrogen formononetin, the herbicides metolachlor and atrazine, and cholesterol. Results support the hypothesis that discharge zones are an important source of exposure of phytoestrogens and herbicides to aquatic organisms. To manage critical resources within the Chesapeake Bay Watershed, more work is needed to characterize exposure in discharge zones more broadly across time and space.

Modeling estrogenic activity in streams throughout the Potomac and Chesapeake Bay watersheds

Endocrine-disrupting compounds (EDCs), specifically estrogenic endocrine-disrupting compounds, vary in concentration and composition in surface waters under the influence of different landscape sources and landcover gradients. Estrogenic activity in surface waters may lead to adverse effects in aquatic species at both individual and population levels, often observed through the presence of intersex and vitellogenin induction in male fish. In the Chesapeake Bay Watershed, located on the mid-Atlantic coast of the USA, intersex has been observed in several sub-watersheds where previous studies have identified specific landscape sources of EDCs in tandem with observed fish health effects. Previous work in the Potomac River Watershed (PRW), the largest basin within the Chesapeake Bay Watershed, was leveraged to build random forest regression models to predict estrogenic activity at unsampled reaches in both the Potomac River and larger Chesapeake Bay Watersheds (CBW). Model outputs including important variables, partial dependence plots, and predicted values of estrogenic activity at unsampled reaches provide insight into drivers of estrogenic activity at different seasons and scales. Using the US Environmental Protection Agency effects-based threshold of 1.0 ng/L 17 β-estradiol equivalents, catchments predicted to exceed this value were categorized as at risk for adverse effects from exposure to estrogenic compounds and evaluated relative to healthy watersheds and recreation access locations throughout the PRW. Results show immediate catchment scale models are more reliable than upstream models, and the best predictive variables differ by season and scale. A small percentage of healthy watersheds (< 13%) and public access sites were classified as at risk using the "Total" (annual) model in the CBW. This study is the first Potomac River Watershed assessment of estrogenic activity, providing a new foundation for future risk assessment and management design efforts, with additional context provided for the entire Chesapeake Bay Watershed.