Currently, there exists much uncertainty regarding how climate change will influence different populations or ecosystems. To improve current understanding and forecasting of population responses to climate variability, the role of variability must be considered when examining system dynamics and species interactions. This project will use an analytical framework to quantitatively estimate how variation in fish populations may respond to climate change and other important changes regionally. This study also aims to communicate scientific uncertainties in ways that are useful to decision makers and to provide decision makers and managers with the ability to detect and predict impacts of climate change on fish populations.
Wagner, T., S. R. Midway, T. Vidal, B. J. Irwin, and J. R. Jackson. 2016. Detecting unusual temporal patterns in fisheries time series data. Transactions of the American Fisheries Society 145:786-794
- Vidal T. E., B. J. Irwin, T. Wagner, L. G. Rudstam, J. R. Jackson, J. R. Bence. 2017. Using variance structure to quantify responses to perturbation in fish catches. Transactions of the American Fisheries Society 146(4):584-593.
- Irwin, B.J., and T. Wagner. Shifting variance structure as a potential indicator of fish-population responses to large-scale perturbation. Southern Division, AFS, Nashville, TN. 2013.
- Irwin, B.J., and T. Wagner. Using mixed models to quantify variability in fish populations. GA Chapter of AFS, Jekyll Island, GA. 2013.
- Irwin et al. Shifting Variance Structure as an Indicator of Large-scale Ecological Change. 2014 ESA meeting.
- Irwin, B.J. Using uncertain information in conservation decision making. North Carolina State University – Southeast Climate Science Center Global Change Fellows seminar. North Carolina State University, Raleigh, NC. December 4, 2014.
- Irwin, B.J. Using quantitative models to support decision making. School of Fisheries, Aquaculture and Aquatic Science. Auburn University, Auburn, AL. 24-Oct-14
- Vidal, T., Irwin, B.J., Madenjian, C.P. (2016) Disentangling exogenous driver of alewife population dynamics in Lake Michigan. Warnell 2016 Symposium, University of Georgia, Athens, GA.
- Irwin. B., 2016. Analyzing data from gillnet monitoring programs: the Oneida Lake example. Cornell University Biological Field Station, Bridgeport, NY
- Irwin. B., T. Vidal, B. Crawford, T. Gancos Crawford, and C. Moore. 2016. Quantitative consideration of uncertainty and variability in decision analysis for conservation and management of ecological systems. Annual meeting of the Ecological Society of America, Fort. Lauderdale, FL
- Vidal, T., Irwin, B., and Madenjian, C. 2017. Demographic structure influences how environmental forcing affects Alewife recruitment in Lake Michigan. Southern Division AFS Conference, Oklahoma City, OK.
- Irwin, B. J. (May 2017). Northeast Climate Science Center’s Regional Science Meeting, Amherst, MA.