Paper No. 8
Presentation Time: 3:25 PM


REAVIE, Euan D.1, KIRETA, Amy1, CHRAÏBI, Victoria2 and ALLINGER, Lisa1, (1)Natural Resources Research Institute, University of Minnesota Duluth, 1900 East Camp Street, Ely, MN 55731, (2)Department of Earth and Atmospheric Sciences, University of Nebraska-Lincoln, 312 Bessey Hall, Lincoln, NE 68588,

The EPA is now in its 30th year of comprehensive monitoring of the Great Lakes. Great Lakes algal monitoring data have revealed significant changes in whole-lake conditions, particularly within the last decade. In most cases trends indicate a drop in algal abundance resulting from the effects of invasive species and changing water quality. Lake Erie is an exception, where pelagic algal abundance is on the rise. Not surprisingly, those responsible for tracking and maintaining ecosystem services on the Great Lakes are concerned about the ecological trajectories of the lakes.

Contemporary monitoring alone is not always sufficient to answer important management questions, so we are employing paleolimnology to put modern conditions in a long-term context. Retrospective data are needed to distinguish natural from human trends, and to reveal the causes and magnitudes of environmental insults that inform management matters regarding climate change, pollution and invasive species. The cornerstone of many previous paleolimnological investigations has been the use of diatoms, known powerful indicators of environmental change. The diatom algae from the Great Lakes have been calibrated to nutrients, and a diatom-based phosphorus model was used in a paleolimnological investigation of Lake Superior to reconstruct its trophic history. Changes in climate are also affecting the physical properties of Superior, which is in turn causing a shift in species composition. Investigations are continuing to describe the anthropogenic history of degradation and remediation in all of the lakes. It is anticipated that algal indicators and paleoecological applications will serve to address the myriad of environmental issues that require long-term data in order to make remedial decisions.