Research is the gathering of information to further knowledge. For the purposes of the Coeur d’Alene Lake Collaborative, research is undertaken to investigate different ways of looking at the Coeur d’Alene system; understand social, physical, and biological factors in the Coeur d’Alene basin; and help us refine the application of our science program.
“Collaborative” is the key term in our efforts on Coeur d’Alene Lake. The State of Idaho and Coeur d’Alene Tribe communicate regularly with educational institutions in the region, including North Idaho College, the University of Idaho, and Washington State University, to identify potential research projects and funding sources for research. We also communicate with Flathead Research Station staff, Idaho Fish and Game, and University of California at Riverside faculty for potential projects in the future.
State of Idaho lake management team members have been working on special studies to look at productivity of the lake as well as nutrients and metals in the ecosystem. Ongoing studies include: Nutrients and metals in rooted aquatic plants Macroinvertebrates (small animals without backbones that can be seen with the naked eye) on the lakebed and metals concentrations in lakebed soils Picoplankton (tiny microorganisms in the lake).
We hope to gain more insight into potential pathways for nutrients and metals to enter the water, their impacts on lake ecology, and to develop improved indicators of lake productivity.
The Coeur d’Alene Tribe’s Lake Management Department is collaborating with the University of Idaho on a potential project that would enhance the existing ELCOM CAEDYM model for Coeur d’Alene Lake. The project includes two major components. The first is integration of data into the ELCOM/CAEDYM model, including MIKEFLOOD modeling results on floodplain deposition and bank scour, and the transport of water, sediment and phosphorous.
The second component involves enclosure experiments in the lake to see how the ecosystem responds to various levels of zinc and nutrients in the water column. The information collected would be incorporated into the ELCOM CAEDYM model to refine its predictive capabilities.