Science

The GLEAMS team has assembled a unique group of expertise that includes environmental chemistry, biology that specializes in genomes and ecosystems, remote sensing of freshwater and geospatial information technology. Some pioneering discoveries in respect to gene expression as a function of environmental contaminate, fate and transport of PCBs due to anthropogenic recreational boat traffic, a new satellite algorithm to estimate productivity (chl, doc, and sm) for the Great Lakes, and a new geospatial end-to-end model that provides human health consequence as a function of contamination have been generated as a part of this program.  These important scientific results need to be communicated in a timely fashion while they await the lengthy refereed publication process.  A list of those GLEAMS publications that have completed the peer-reviewed referee process is also available.

This section of the portal is designed to communicate ongoing scientific research being conducted by the GLEAMS team and, where possible, to provide access to results, publications and data that is generated by that research. This section has been organized into the following categories that correspond to ongoing research:

Genomics & Toxicology – Describes ongoing research into how environmental contaminants, such as PCBs, alter development and function and how gene expression may serve as a biomarker of exposure and damage, including an overview of research that observed genomic expression in carp caught in the Kalamazoo River.

Environmental Chemistry – Describes the ongoing environmental sampling of the sediment-water systems of the Kalamazoo River and associated efforts to characterize the bioavailability, fate and transport of major contaminants, including PCBs.

ALWAS Technology – Describes a highly portable, multi-parameter, water quality buoy designed to help make water quality sampling cost effective and efficient, through automatic ingestion of the resulting data into a GIS environment.

Remote Sensing of Productivity – Describes an ongoing effort to develop, calibrate and validate an algorithm to derive productivity estimates of the Great Lakes from satellite remote sensing.