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Lake Michigan nearshore: How modeling scenarios can improve dialog between modelers and ecologists
Citation:
Pauer, J., T. Brown, W. Melendez, T. Hollenhorst, AND L. Lowe. Lake Michigan nearshore: How modeling scenarios can improve dialog between modelers and ecologists. State of Lake Michigan, Green Bay, WI, November 07 - 10, 2017.
Impact/Purpose:
The nearshore region of the Great Lakes where most human interaction with this important resource occurs. Excessive eutrophication (algal growth driven by nutrient inputs) causing enhanced levels of nuisance algae including harmful algal blooms has plagued parts of the nearshore. Mathematical models are powerful tools to identify the main drivers of nearshore eutrophication and to assist stakeholders with management options to improve or maintain water quality. Here we analyzed the 2015 Lake Michigan Comprehensive Scientific and Monitoring Initiative (CSMI) observation data, complemented by a modeling effort in an area near the Grand River. Our preliminary results show the importance of hydrodynamics (water movement) to nearshore water quality, and demonstrate how models can be used to identify sampling locations to track the watershed signal and explore long term changes in the nearshore. This work also points out gaps in our understanding of the dynamics in this area, and shows how closer cooperation between modelers and ecologists could improve future Lake Michigan nearshore studies including the 2020 CSMI. It also contributes to a FY18 deliverable under SSWR 3.01D.
Description:
The nearshore of Lake Michigan, similarly to the other Great Lakes, experiences environmental concerns due to excessive eutrophication. Assessing the nearshore is challenging because fluctuating nutrient loads, and ever-changing currents cause this area to exhibit large spatial and temporal gradients. Mathematical models have the potential to identify the main drivers of nearshore eutrophication and to assist stakeholders with management options to improve or maintain water quality. Modeling results can also point out gaps in our understanding of the system, indicating where additional measurements and research are needed. All models have limitations, and modelers have been criticized for not being transparent in adequately communicating those limitations. This can lead to ecologists being overly dismissive of modeling results, potentially neglecting the value of this imperfect tool. Here we will discuss how examining the results of the 2015 Lake Michigan CSMI in conjunction with evaluating several model scenarios improved our insight of the nearshore. We will also point out present gaps in our understanding of this area, and discuss how closer cooperation between modelers and ecologists could improve future Lake Michigan nearshore studies including the 2020 CSMI.