Geology Reports⌕ Search
Home/Archive/USGS

USGS · 5223915

Contaminant exposure and effects: Terrestrial vertebrates database: Trends and data gaps for Atlantic Coast estuaries

Barnett A. Rattner·J.L. Pearson·N. H. Golden·J.B. Cohen·R.M. Erwin·M. A. Ottinger
View original source ↗Export metadata ↓

Abstract

In order to examine the condition of biota in Atlantic coast estuaries, "Contaminant Exposure and Effects—Terrestrial Vertebrates" database (CEE-TV) has been compiled through computerized search of published literature, review of existing databases, and solicitation of unpublished reports from conservation agencies, private groups, and universities. Summary information has been entered into the database, including species, collection date (1965–present), site coordinates, estuary name, hydrologic unit code, sample matrix, contaminant concentrations, biomarker and bioindicator responses, and reference source, utilizing a 98-field character and numeric format. Currently, the CEE-TV database contains 3699 geo-referenced records representing 190 vertebrate species and >140,000 individuals residing in estuaries from Maine through Florida. This relational database can be directly queried or imported into a Geographic Information System to examine spatial patterns, identify data gaps and areas of concern, generate hypotheses, and focus ecotoxicological field assessments. Information on birds made up the vast majority (83%) of the database, with only a modicum of data on amphibians (<0.1%). Of the >75,000 chemical compounds in commerce, only 118 commonly measured environmental contaminants were quantified in tissues of terrestrial vertebrates. There were no CEE-TV data records in 15 of the 67 estuaries located along the Atlantic coast and Florida Gulf coast. The CEE-TV database has a number of potential applications including focusing biomonitoring efforts to generate critically needed ecotoxicological data in the numerous "gaps" along the coast, reducing uncertainty about contaminant risk, identifying areas for mitigation, restoration or special management, and ranking ecological conditions of estuaries.

Explore related subjects

Environmental Monitoring and AssessmentArticle

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Barnett A. Rattner, J.L. Pearson, N. H. Golden, J.B. Cohen, R.M. Erwin, M. A. Ottinger. 2000. Contaminant exposure and effects: Terrestrial vertebrates database: Trends and data gaps for Atlantic Coast estuaries. https://doi.org/10.1023/a%3A1006458811235

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2025

From sample to sonde to Sentinel-2: Insights from a multi-scale chlorophyll-a monitoring effort in the Hudson River, New York

Monitoring cyanobacteria and other nuisance phytoplankton in the Hudson River is of great interest given its societal and ecological importance. Satellite remote sensing provides a cost-effective method to monitor chlorophyll- a (chl-a), a common proxy for algal biomass; however, the dynamic nature of rivers complicates approaches traditionally applied to lakes and oceans. During 2021–2023, we collected discrete samples for laboratory measurement of chl-a and measured in situ chl-a fluorescence during a series of longitudinal boat surveys along a 220-km reach of the lower Hudson River. Surveys were timed to coincide with Sentinel-2 satellite overpasses. We first investigated relations between laboratory-measured chl-a concentration and field-measured chl-a fluorescence, observing a weak correlation ( r 2 = 0.25) that improved substantially after splitting data by day (mean r 2 = 0.53). Separately, to estimate chl-a fluorescence using satellite data, we developed a series of random forest models leveraging the rich fluorescence dataset collected. We tested three model types: individual day models, leave-one-out models trained on all days except a holdout test day, and a single pooled model trained on all days. Generally, individual day models exhibited lowest error (mean of mean absolute error [MAE] = 0.16 relative fluorescence units [RFU]), followed by the single pooled model (MAE = 0.22 RFU). Daily holdout models showed highest error (mean MAE = 0.40 RFU); this approach was intended to represent model performance on a day unseen in the training set, providing a more conservative estimate of performance than the more traditional pooled approach. Findings from both analyses emphasize the importance of considering temporal variability when modeling riverine systems.

New Jersey, New York↗
USGS2025

Irrigated agriculture influences selenium levels in an endangered marsh bird

Selenium bioaccumulation in aquatic food webs poses risks to wildlife, particularly in wetlands receiving irrigation runoff. The Salton Sea, California’s largest lake, is primarily sustained by agricultural drainage. This drainage creates wetland habitat along the lakeshore that many bird species depend on, including the federally endangered Yuma Ridgway’s rail ( Rallus obsoletus yumanensis ). However, these marshes may pose an ecological trap – attracting rails despite high selenium exposure. We captured rails during the 2020–2023 breeding seasons and compared rail selenium levels within three types of marshes (fed with irrigation runoff, Colorado River water, or groundwater). We collected blood, breast feathers, and head feathers of rails in all three water sources for selenium comparisons. We tagged adult rails with GPS transmitters to locate nests and foraging locations where we collected eggshells, unhatched eggs, and prey. We assessed selenium exposure by collecting multiple prey species commonly eaten by rails in all three water sources. Selenium concentrations varied among sampling locations. Selenium concentrations in most sample types were predominately influenced by water source and marsh inflow velocity (sometimes in combination with marsh size). Distance to inflow, however, did not influence selenium concentrations in any sample type. Selenium concentrations were highest in agricultural-fed marshes compared to river-fed and spring-fed marshes. Increased marsh inflow velocities resulted in lower selenium concentrations. Given the risk of an ecological trap, our results suggest that supplementing wetlands with Colorado River water could mitigate selenium bioaccumulation in Yuma Ridgway’s rails.

California↗
USGS2025

Regional high-frequency monitoring revealed chloride concentrations in exceedance of ecological benchmarks in urban streams across the Delaware River Basin, USA

Rising chloride concentrations pose critical risks to freshwater stream ecosystems in temperate regions like the Delaware River Basin (DRB), USA, where winter deicer applications ( i.e. , road salt) are common. Increasing chloride concentrations have been documented in the region, but the extent to which chloride exceeds regulatory benchmarks remains unclear because detection of exceedances requires continuous monitoring of chloride ( i.e. , hourly or daily). A network of 82 non-tidal continuous specific conductance (SC) monitoring sites, spanning varied land use and geological settings, was established across the DRB to address this research need. First, a cluster analysis was conducted to group sites based on their watershed characteristics. Next, regression models for sites and clusters were developed to predict chloride using SC as a proxy. Finally, daily mean and hourly mean chloride concentration predictions were made for a three-year period (2020–2022) at the 82 study sites and analyzed to determine where and when chloride exceeded federal regulatory benchmarks. Chloride exceedance events occurred at 35% of the sites, all of which had 5% impervious cover or greater. Seasonally elevated chloride also was predicted at sites with less than 5% impervious cover. Variability in chloride patterns likely was influenced by deicer material types, winter weather patterns, geological settings, and gaps in data coverage. This study demonstrated the value of SC as a proxy for predicting chloride concentrations and showed how SC-chloride regression relationships vary across settings. More broadly, this study highlighted the value of continuous water quality monitoring to assess effects of freshwater salinization at a regional scale.

Delaware, Maryland, New Jersey, New York, Pennsylv↗