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Use of the zebra mussel (Dreissena polymorpha) as an indicator of previously elevated bacteria concentrations in a watershed was examined. The ability of the zebra mussel to accumulate and purge Escherichia coli over several days was investigated in both laboratory and field experiments. In laboratory experiments, periodic enumeration of E. coli in mussels that had been exposed to a dilute solution of raw sewage demonstrated that (i) maximum concentrations of E. coli are reached within a few hours of exposure to sewage, (ii) the tissue concentration attained is higher than the concentration in the ambient water, and (iii) the E. coli concentrations take several days to return to preexposure concentrations when mussels are subsequently placed in sterile water. In field experiments conducted in southeast Michigan in the Clinton River watershed, brief increases in E. coli concentrations in the water were accompanied by increases in mussel concentrations of E. coli that lasted 2 or 3 d. The ability of mussels to retain and to concentrate E. coli made it possible to detect E. coli in the environment under conditions that conventional monitoring may often miss. Sampling caged mussels in a river and its tributaries may enable watershed managers to reduce the sampling frequency normally required to identify critical E. coli sources, thereby providing a more cost-effective river monitoring strategy for bacterial contamination.

Under the US-Canada Great Lakes Water Quality Agreement, a Remedial Action Plan (RAP) Program was formalized to identify and implement actions needed to restore beneficial uses in the most polluted areas of the Great Lakes (i.e. Areas of Concern). It was further required that individual RAPs embody a systematic and comprehensive ecosystem approach (i.e. an approach which accounts for interrelationships among land, air, water and all living things, including humans, and involves user groups in comprehensive management). Careful review and analysis of the RAP Program offers an opportunity to gain a better understanding of ecosystem-based management for other watersheds, and to identify important principles and elements which contribute to effective implementation. Principles which are considered essential for effective implementation of ecosystem-based management include: (1) broad-based stakeholder involvement; (2) commitment of top leaders; (3) agreement on information needs and interpretation; (4) action planning within a strategic framework; (5) human resource development; (6) results and indicators to measure progress; (7) systematic review and feedback; and (8) stakeholder satisfaction. The Great Lakes RAP experience with ecosystem-based management also demonstrates the need for a transition from a traditional,command-and-control,regulatory approach of governmentalagencies toward a more co-operative,value-added,support-basedrole. Review of RAPs in all 42 Areas of Concern provides compelling evidence that successful application of ecosystem-based management is dependent on broad-based stakeholder involvement in decision making, along with strong partnerships which encourage collaboration, co-operation and adaptability in management actions.

The accuracy of estimating total phosphorus (TP) loads to receiving waters usually is constrained by availability of concentration data, as discharge (flow) data normally are comparatively abundant. Using 4 years of daily observations from three tributaries to the Great Lakes (Grand, Saginaw, and Sandusky Rivers), annual TP loads were tested for accuracy by five methods, including regression, ratio, and robust estimators. Monte Carlo methods were employed to simulate replicated flow‐stratified sampling of the datasets with various allocations of samples to flow strata. Each of the load calculation methods was applied to each group of simulated samples, and response was quantitated as load estimation error (computed minus “true” load). The results show the most consistently accurate estimator was Beale's stratified ratio estimator. It was, however, the only stratified estimator tested and should have been more accurate. Most accurate of the unstratified estimators was a straightforward least squares regression (log‐log) method. The response of estimation bias to flow cut point and sample allocation manipulations indicated (1) beneficial results generally (but not always) obtained from high flow weighting of sampling and (2) postsampling stratification generally may yield improved accuracy for load estimation and deserves additional research.

An international workshop held in the spring of 2002 convened a group of technical experts to address monitoring, modeling, and management of PCBs within the Detroit River-Western Lake Erie basin. Participants shared and discussed a diverse set of research data bases pertaining to PCB levels within the region, discussed observed changes within different components of the local ecosystem, and identified several primary issues impacting future PCB management strategies. Results presented at the workshop indicate dramatic reductions in PCB contamination levels have been observed in much of study area between the late 1970s and mid-1990s. Estimates of loadings attributable to water and atmospheric sources have generally declined, as have PCB concentrations in herring gull eggs, smelt and walleye. Nevertheless, additional improvements have not been observed during recent years and elevated contamination levels remain a concern within local hot spots, particularly in the lower Detroit River and Trenton Channel. A primary recommendation broadly supported by workshop participants is the need to maintain, support, and coordinate a comprehensive ecosystem monitoring program for the Detroit River-Western Lake Erie basin, one that incorporates both near-field and far-field monitoring elements. Such a program is crucial to provide necessary data in support of understanding ecosystem trends, calculating annual mass loadings to the system, assessing impacts of remediation actions, developing improved modeling frameworks, and formulating cost-effective management strategies for the future.