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Biological Effects–Based Tools for Monitoring Impacted Surface Waters in the Great Lakes: A Multiagency Program in Support of the Great Lakes Restoration Initiative
Citation:
Ekman, D., G. Ankley, V. Blazer, Tim Collette, N. Garcia-Reyero, L. Iwanowicz, Z. Jorgenson, K. Lee, P. Mazik, D. Miller, E. Perkins, E. Smith, J. Tietge, AND Dan Villeneuve. Biological Effects–Based Tools for Monitoring Impacted Surface Waters in the Great Lakes: A Multiagency Program in Support of the Great Lakes Restoration Initiative. ENVIRONMENTAL PRACTICE. Oxford University Press, Cary, NC, 15(4):409-426, (2013).
Impact/Purpose:
Article published in Environmental Practice.
Description:
There is increasing demand for the implementation of effects-based monitoring and surveillance (EBMS) approaches in the Great Lakes Basin to complement traditional chemical monitoring. Herein, we describe an ongoing multiagency effort to develop and implement EBMS tools, particularly with regard to monitoring potentially toxic chemicals and assessing Areas of Concern (AOCs), as envisioned by the Great Lakes Restoration Initiative (GLRI). Our strategy includes use of both targeted and open-ended/discovery techniques, as appropriate to the amount of information available, to guide a priori end point and/or assay selection. Specifically, a combination of in vivo and in vitro tools is employed by using both wild and caged fish (in vivo), and a variety of receptor- and cell-based assays (in vitro). We employ a work flow that progressively emphasizes in vitro tools for long-term or high-intensity monitoring because of their greater practicality (e.g., lower cost, labor) and relying on in vivo assays for initial surveillance and verification. Our strategy takes advantage of the strengths of a diversity of tools, balancing the depth, breadth, and specificity of information they provide against their costs, transferability, and practicality. Finally, a series of illustrative scenarios is examined that align EBMS options with management goals to illustrate the adaptability and scaling of EBMS approaches and how they can be used in management decisions.
