Geology topics

Erin Maloney

Publications and source records attributed to Erin Maloney.

2 recordsLinked to original sources

USGS2025

Leveraging invasive mussel contaminant survey data for stepwise prioritization of chemicals of potential concern in the Great Lakes basin

Historical and ongoing anthropogenic activities coupled with advancements in analytical techniques have led to the detection of large numbers of contaminants in the Laurentian Great Lakes. Consequently, identifying and prioritizing chemicals likely to cause ecological harm represents a challenge for natural resource managers. Previous prioritization efforts have focused on contaminants in sediment, water, and passive samplers, which may not be representative of compounds that bioaccumulate in aquatic organisms. Consequently, this study adopted a stepwise method to prioritize chemicals of potential concern detected in dreissenid mussels from samples collected across the Great Lakes from 2009–2018. The stepwise method considered environmental fate, detection frequency, and exceedance of toxicity quotients based on ecotoxicological effect concentrations. Overall, 153 compounds out of 267 analyzed were detected in dreissenid mussels, 47 of which had water quality effect concentrations, 56 had apical effect concentrations (Tier 1 ECOTOX or apical screening), 17 had nonapical effect concentrations (Tier 2 ECOTOX, Cytotoxic Burst, and ToxCast) and 33 had estimated effect concentrations (quantitative structure-activity relationship, estimated screening, and pharmacological potency). Of the compounds with water quality effect concentrations, nine were designated as high priority, including the herbicide atrazine and five polycyclic aromatic hydrocarbons that were previously identified as potentially hazardous within other matrices. Similar contaminants were identified as high priority in a related study of native unionid mussels in the Great Lakes. A total of 27 compounds were low priority, suggesting that these contaminants do not warrant further action based on this dataset. Overall, these findings will facilitate the development of management strategies to mitigate the effects of contaminants on aquatic organisms within the Great Lakes.

Great Lakes basin↗

USGS2025

Application of transcriptomics concentration-response modeling for prioritization of contaminants detected in tributaries of the North American Great Lakes

As part of the Great Lakes Restoration Initiative, chemical monitoring and surveillance efforts have detected approximately 330 chemicals in surface water of Great Lakes tributaries. There were 140 chemicals for which no empirical toxicity data were available. The aim of this study was to generate transcriptomic points of departure (tPODs) for 10 of these compounds and demonstrate how they could be applied in a screening-level prioritization. Organisms representing three trophic levels of the aquatic food web ( Pimephales promelas , Daphnia magna , and Raphidocelis subcapitata ) were exposed for 24 hr to a half-log dilution series of nominal exposure concentrations typically ranging from 66.7–0.021 µM of each chemical. In addition to observations of apical effects (e.g., survival and morphology), whole body transcriptomic responses (tPODs) to each chemical were evaluated with targeted analysis using TempO-seq for P. promelas and D. magna and nontargeted RNA-seq for R. subcapitata . The tPODs ranged from 0.18–10.8 µM for P. promelas and 0.32–29 µM for D. magna , with the most potent of the chemicals tested being fipronil carboxamide for both species. For R. subcapitata , the tPODs ranged from 0.04–1.77 µM, with gabapentin as the most potent chemical tested. Empirically derived tPODs from these data-poor chemicals were compared with concentrations detected in the Great Lakes basin. Environmental concentrations were less than the tPODs except for R. subcapitata and 3,4-dichlorophenyl isocyanate. Similarly, tPODs from previously tested data-rich chemicals were compared with environmental concentrations, in which case tPODs from several chemicals overlapped environmental concentrations. This work demonstrates the potential utility of emerging ecological high-throughput transcriptomics assays to support screening and prioritization of data-poor environmental contaminants.

Environmental Toxicology and Chemistry↗