The number of fish collected in routine monitoring surveys often varies from year to year, from lake to lake, and from location to location within a lake. Although some variability in fish catches is expected across factors such as location and season, we know less about how large-scale disturbances like climate change will influence population variability. The Laurentian Great Lakes in North America are the largest group of freshwater lakes in the world, and they have experienced major changes due to fluctuations in pollution and nutrient loadings, exploitation of natural resources, introductions of non-native species, and shifting climatic patterns. In this project, we analyzed established long-term data about important fish populations from across the Great Lakes basin, including from Oneida Lake in NY, Lake Michigan, and the Bay of Quinte in Lake Ontario. Our objective was to evaluate spatial and temporal variation in fish catches from large freshwater lakes that have experienced large-scale changing conditions. We evaluated analytical approaches with the potential to disentangle sources of variability in standardized monitoring data. Specifically, we considered 1) how the decomposition of spatial and temporal variation in fish catches can be used to measure a response to perturbation; 2) how truncation of population age structure can alter population oscillations which may shift how a population is affected by environmental fluctuations; and 3) how the composition of a fish community may respond to a suite of environmental drivers through time. Using long-term gill-net data for walleye, we found that average catch and variance structure differed before and after large-scale perturbations. More generally, our results suggest that fish population responses to changing environments can be complex, but that long-term monitoring combined with modeling approaches can allow for detection of quantifiable changes.
Irwin, B., T. Wagner, and J. R. Bence. 2017. Characterization of spatial and temporal variability in fishes in response to climate change. Northeast Climate Science Center project completion report.
- 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.
- Vidal, T., 2017. Understanding the role of variability in fish population and community response to changing environmental conditions. PhD dissertation, University of Georgia, Athens, Georgia.
- 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, B. Variance structure and ecological change. Computational Ecology and Epidemiology Study Group Seminar Series, University of Georgia, Athens, GA. 2014.
- Irwin, B. Quantifying variance to inform decision making. Cornell University Biological Field Station Summer Seminar Series, Bridgeport, NY. 2014.
- Irwin et al. Shifting Variance Structure as an Indicator of Large-scale Ecological Change. 2014 ESA meeting.
- Vidal, T., C. Jansch, B. J. Irwin, T. Wagner, J. R. Bence, J. R. Jackson, L. G. Rudstam, and W. W. Fetzer. Using variance structure as statistical indicators of large scale ecological change. American Fisheries Society, Québec City, Québec, Canada. 2014.
- 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
- Irwin, B., and T. Vidal. Accounting for variability & uncertainty when informing natural resource management. NE Climate Science Center webinar, University of Massachusetts, Amherst, MA. 2015.
- 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.
- Vidal, T. E., B. J. Irwin, and C. P. Madenjian. Disentangling exogenous drivers of Alewife population dynamics in Lake Michigan. Joint meeting of the GA-AL chapters of the American Fisheries Society, Columbus, GA. 2016.
- 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. 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, 2016.
- 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. Viewing fisheries from a decision-analytic perspective. Northeast Climate Science Center Regional Science Meeting, Amherst, MA. 2017.
- Irwin, B. J. Spatial and temporal variability in fish populations. Northeast Climate Science Center Regional Science Meeting, Amherst, MA. 2017.
Irwin, B. et al. Engaged with potential partners in the Great Lakes region via conference calls and other exchanges to setup an in-person project meeting, which was held 3-4 August 2017 on the campus of the University of Georgia