气候变化领域集成服务门户

We conducted a survey of the Lake Michigan nearshore using towed electronic instrumentation to collect data that were spatially highly resolved. The tow was 1049 km in length along the 20-m depth contour and was supplemented with grab samples at 15 sites (on average every 75 km). There was low frequency variability in the alongshore reach represented by macroscopic trends across large distance scales (over 100 s km) with local variability or high frequency changes at much smaller distances (5-10 km). We found that large scale spatial patterns in some water quality parameters were strongly correlated with adjacent landscape characterization. Landscape attributes most frequently retained in step-wise regression models for each water quality parameter were agricultural chemical factors, followed by shoreline modifications and point source attributes. Specific conductivity had the greatest amount of variability explained by landscape character (78%)with beam attenuation next (51%), and followed by chlorophyll and zooplankton (each similar to 30%). We combined our chemistry samples with data from the recent National Coastal Condition Assessment (2010 NCCA) and compared nearshore chemistry data with the Great Lakes National Program Office (GLNPO) offshore fixed monitoring sites. There was a significant distinction in both mean values and variability between the nearshore (<30 m depth) and offshore waters. We also used historical data and found that the distinction between near shore and offshore waters has persisted and that the same long-term trends in parameter concentrations found in the offshore were also found in the near shore. Published by Elsevier B.V. on behalf of International Association for Great Lakes Research.