James Bence, Ph.D.
- Ph.D., Biological Sciences, University of California, Santa Barbara, 1985
- M.A., Applied Statistics, University of California, Santa Barbara, 1985
- B.S., Biology, University of Notre Dame, 1979
My position, prior to retirement, was part of the Partnership for Ecosystem Health and Management. My research is in the general area of quantitative fisheries with an emphasis on Great Lakes applications. Recent work has focused on evaluation of age-structured stock assessment methods and use of simulation models to evaluate different harvest policies and other management choices. My work has covered a broad range of topics including environmental impact assessments, bioenergetics applications, stock assessments and policy analyses for specific Great Lakes stocks, general assessment of methods, sea lamprey control/management, and population dynamics theory and modeling. For nearly 30 years I taught a graduate course in fish population dynamics.
I am currently employed part time in a fixed-term position and expect to continue in that role through June of 2025, working on finishing off old projects. I am no longer accepting new graduate students. Prospective graduate students interested in the type of quantitative work I do should see the Quantitative Fisheries Center website for information on assistantships and other opportunities working with other QFC faculty.
- Fishery stock assessment methods
- Fishery management
- Use of simulation tools in evaluating management strategies
- Great Lakes fisheries
- Environmetrics and environmental assessment
- Population and community dynamics
J.X. He and J.R. Bence. 2023. Systematic change and random variations: understanding lake trout (Salvelinus namaycush) growth dynamics in US waters of Lake Huron. Journal of Great Lakes Research 49(3) 737-745. https://doi.org/10.1016/j.jglr.2023.03.008
Liljestrand, E.M., J.R. Bence, and J.J. Deroba. 2023. Applying a novel state-space stock assessment framework using a fisheries-dependent index of fishing mortality. Fisheries Research 264: August 2023, article 106707. https://doi.org/10.1016/j.fishres.2023.106707.
C. Song, S.D. Peacor, C.W. Osenberg, and J.R. Bence. 2022. An assessment of statistical methods for non-independent data in ecological meta-analyses: Comment. Ecology 103(1):e03578. https://doi.org/10.1002/ecy.3578
N.C. Fisch, J.R. Bence, J.T. Myers, E.K. Berglund, and D.L. Yule. 2019. A comparison of age- and size-structured assessment models applied to a stock of cisco in Thunder Bay, Ontario. Fisheries Research 209:86-100.
D.G. Fielder and J.R. Bence. 2014. Integration of auxiliary information in statistical catch-at-age (SCA) analysis of the Saginaw Bay stock of Walleye in Lake Huron. North American Journal of Fisheries Management 34: 970-987.
J.R. Bence, M.W. Dorn, B.J. Irwin, and A.E. Punt. 2008. Recent advances in the evaluation and implementation of harvest policies. Fisheries Research 94: 207-209
MSU Quantitative Fisheries Center meeting dire modeling, decision-making needs for Great Lakes fishery management
Published on February 1, 2021
MSU Quantitative Fisheries Center honored by Great Lakes Fishery Commission
Published on May 24, 2018
The Big Catch: Quantitative center is making every fish count
Published on November 2, 2014