Contaminant biomonitoring programs in the Great Lakes region: Review of approaches and critical factors

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Abstract

Since the 1970s, several formal biomonitoring programs have been initiated to monitor temporal and spatial trends of persistent, bioaccumulative, and (or) toxic chemicals (PBTs) in the Great Lakes. Researchers have used a variety of approaches to deal with common issues that arise in these programs and there is considerable debate in the literature as to the most appropriate methods to use. Here, we critically review factors of importance in biomonitoring programs and common methods used for dealing with them under three main categories: organism-specific factors (lipid, age, size, sex, growth and bioenergetics, diet, and chemical biotransformation), study design (choice of tissue type, compositing, replication and length of monitoring program, sampling frequency, selection of contaminants to include in monitoring programs, and use of specimen banks for retrospective studies), and data analysis (accounting for changes in analytical methodology, treat- ment of censored data, assessment of compound classes, comparison of empirical models, mechanistic models, and spatial assessments). We use data from the literature as well as longterm measurements of polychlorinated biphenyls (PCBs) in lake trout (Salvelinus namaycush) collected in Lake Ontario as part of monitoring programs run by Environment Canada, the On- tario Ministry of the Environment, and the United States Environmental Protection Agency to illustrate these factors. We find that, in general, there are several defensible methods, ranging from simple to complex, to deal with the issues consid- ered here, with each having specific advantages and disadvantages. The optimal approach depends largely on the program objectives, particularly if the results are meant for the public (understandable without a scientific background) or for re- search purposes (balance between complexity versus simplicity). Given that data analysis typically requires fewer resources compared to other aspects of monitoring programs, it may be feasible to use more than one data analysis approach to in- crease credibility of the results and to improve comparability of data among studies. The importance of conducting prelimi- nary surveys and (or) pilot studies and regular review of ongoing programs (e.g., through a power analysis) is emphasized.

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