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David M. Dolan Scholarship
The scholarship was established in 2014 in memory of David M. Dolan, whose work in applied mathematics, statistics and computer modeling served to provide a quantitative basis for phosphorus management on the Great Lakes. The award is given to a student conducting graduate research in statistics, mathematical modeling, data analysis, and/or quantitative decision support that advances understanding and management of Great Lakes ecosystems. The scholarship is awarded annually at a value of $3,000.* (See press release announcing the award for more information.)
About the Scholarship
On June 18, 2013, IAGLR and the Great Lakes community suffered a great loss when Dr. David M. Dolan passed away unexpectedly. Dave Dolan served IAGLR in many ways, including a term on the IAGLR Board of Directors. An expert applied environmental statistician, he devoted his career to Great Lakes research to further the understanding of phosphorus loadings to the Great Lakes through modeling and statistics. He earned a B.S. in Chemical Engineering and M.S. in Environmental Engineering at Notre Dame University, an M.A. in Statistics at the University of Michigan, and a Ph.D. in Mathematics at MacMaster University in Hamilton, Ontario.
He was a full professor at the University of Wisconsin-Green Bay, and prior to joining the university worked for 27 years as an Environmental Statistician for the U.S. Environmental Protection Agency and the International Joint Commission. Using applied mathematics, including statistics and computer modeling, he was instrumental in developing a quantitative understanding of the Great Lakes that could inform policy decisions and influence management actions.
How to Apply
Students interested in applying for this scholarship should review the Regulations and Application Procedures.
* IAGLR reserves the right to vary the number of scholarships awarded and their value based on the funds available from the memorial endowment set up by IAGLR for this purpose.
Recipients
| 2023 | Sabrina Jaffe, University of Toledo, Application of Bayesian hierarchical models in grass carp and harmful algal bloom management |
| 2022 | Emily Liljestrand, Michigan State University, How Data Availability and Quality Influence Output in State Space Stock Assessment Models Applied to Great Lakes Fisheries |
| 2021 | Stephanie Figary, Cornell University, Zooplankton as indicators: Understanding the Great Lakes through decades of zooplankton monitoring |
| 2020 | Polly Peterson, University of Toledo, Dept Environmental Science, Bayesian modeling applications for addressing algal bloom issues in Lake Erie |
| 2019 | Yuan Hui, University at Buffalo, SUNY, Dynamics of Phosphorus in Lake Ontario and its effects on Cladophora resurgence |
| 2018 | Kaitlin Reinl, University of Minnesota-Duluth, Water Resources Science - Limnology and Oceanography, Assessing future risk of cyanobacteria blooms in western Lake Superior; a modeling approach |
| 2017 | Brandon Gerig, School of Notre Dame, Dept. of Biological Sciences, Swimming Upstream: Ecological implications of dam removal |
| 2017 | Ashley Hendricks, Michigan Technological University, Dept. of Civil and Environmental Engineering, A Bayesian approach for the uncertainty analysis of a mercury biogeochemical model applied for inland Upper Peninsula lakes |
| 2016 | Annie Scofield, Cornell University, Assessing the ecological importance of deep chlorophyll layer formation in the Great Lakes: Understanding a vertically restructured system |
| 2015 | Mark Dufour, University of Toledo, Hydroacoustic quantification of distribution and abundance of Lake Erie walleye (Sander vitreus): from measurement to prediction |