Citation:

Vitense, K., B. Blackwell, Tim Collette, S. Corsi, C. Custer, E. Davenport, D. Ekman, S. Hummel, S. Kohno, L. Loken, E. Maloney, AND E. Perkins. Prioritizing Chemicals of Emerging Concern in the Great Lakes Using Covariance of Chemical Concentrations and Diverse Biological Responses. SETAC, Durham, NC, November 13 - 17, 2022. https://doi.org/10.23645/epacomptox.21381855

Impact/Purpose:

The purpose of the Great Lakes Restoration Initiative (GLRI) is to protect and restore the world’s largest system of fresh surface water. To better understand how environmental contaminants impact fish and wildlife in the Great Lakes Basin, a group of GLRI researchers collected information about environmental contaminants and biological responses in fish, clams, and birds at locations along the Maumee River in Ohio in 2016-2017. The goal of this study is to identify chemicals that are consistently related to a diverse set of biological responses across species and study designs, as well as chemicals that consistently are not linked to biological effects. The results from this work will enable agency partners and Great Lakes resource managers to identify high and low priority chemicals for future monitoring efforts based on observed relationships with biological effects and gaps in data availability. This work will also enable partners and managers to consider exposure to chemicals that are identified as being strongly associated with adverse biological effects when developing management plans for fish and wildlife.

Description:

The Great Lakes Restoration Initiative (GLRI) aims to protect and restore the nation's largest freshwater resource, including consideration of the adverse impacts of complex chemical mixtures and contaminants of emerging concern (CECs) on Great Lakes fish and wildlife. To address this issue, a multi-agency research consortium conducted field studies at sites along the Maumee River in Ohio, USA in 2016-2017, monitoring >700 organic compounds along with in vitro and in vivo biological effects (e.g., transcription factors, gene expression, metabolomics, and apical effects) in ecologically relevant species (fathead minnows, tree swallows, Asian clams). The goals of the present study are to: 1) identify chemicals that consistently covary with biological effects across studies and species to prioritize chemicals for future monitoring and management efforts, and 2) identify chemicals that consistently display a lack of covariance across studies and species to “shorten the list” of contaminants that require monitoring. To meet these goals, sparse partial least squares regression was used to identify chemicals with statistically significant relationships within each species-response group of interest, and strength of evidence for each chemical was quantified using selection frequency in models exhibiting the best predictive performance. The results were synthesized to quantify the strength of evidence of biological impacts across all studies and species responses. Detection frequency and the number of species-response groups analyzed were further incorporated to develop a weight-of-evidence approach to identify high and low priority chemicals for future monitoring and natural resource management in the Great Lakes.

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