**The title, authors, and abstract for this completion report are provided below. For a copy of the completion report, please contact the GLFC via e-mail or via telephone at 734-662-3209**
Enhancing Fishery Stock Assessment Modeling in the Great Lakes
James R. Bence2 and Travis O. Brenden2
2 Quantitative Fisheries Center, Department of Fisheries and Wildlife, Michigan State University
East Lansing, Michigan 48824
We developed and offered stock assessment training to a cohort of natural resource professionals. This training included an online course on maximum likelihood methods (MLE), two workshops following a short-course format on stock assessment methods and initial work on individual projects, and a third workshop intended to help participants finish projects and interact with other professionals about their work. Participants for the stock assessment training opportunity were identified through an e-mail that was distributed to Council of Lake Committee members, Lake Technical Committee chairs, and others involved in Great Lakes fishery science and management. We received a total of 12 applications during our application time-frame and all were accepted into program. The accepted participants represented Ontario, one federal agency (USGS), and four US states (WI, MN, MI, PA). One participant withdrew prior to the onset of the course and an additional participant withdrew after completing the online maximum likelihood training and the first workshop. Eight of the 10 who completed the program were working fishery biologists on the Great Lakes who expected to be engaged in fish stock assessment activities. The other two participants were wildlife biologists hoping to apply age-structured stock assessment methods to mammals. The ten students who completed the course worked on nine “capstone” projects as part of the training (the two wildlife professionals shared a common project). These projects all involved development or refinement of catch-at-age assessments. Stocks worked on included walleye, yellow perch, lake whitefish, lake trout, as well as mammals, and geographically spanned four Great Lakes (all but Ontario) and terrestrial habitat in Michigan. Feedback on the MLE online course was collected via surveys completed during the course, and in June 2011, participants in the stock assessment training program were asked to complete an anonymous online survey. The training program met its overall goals and thus was successful. We base this conclusion on the fact that all surveyed respondents strongly agreed or agreed that they learned new information on stock assessment and population dynamics and that they believed they would be able to apply this new information in the future. We further judge the training program to have been a success due to most students having made good progress on their capstone projects. Thus, as a result of this training, there are nine new or improved SCAA models upon which natural resource managers potentially could use to help manage fish and wildlife populations in the Laurentian Great Lakes region. While the training program was successful, our experiences and the surveys of participants suggest ways to improve similar training programs in the future.