The University of Waikato

Projected warming and fish community responses in diverse Midwestern US lakes

Predicting the effects of climate change on the abundance of multiple fish species across diverse freshwater systems is fraught with challenges. We developed process-based models for simulating temperatures of tens of thousands of lakes under climate change. We collated fish relative abundance data collected by natural resource agencies and developed workflows to clean, restructure, and combine datasets using harmonized workflows. Finally, we developed a spatially explicit, joint species physiologically guided abundance (jsPGA) model that combines laboratory information on thermal preferences and tolerances with empirical data on fish relative abundance for predicting the effects of warming on multiple species concurrently. We apply these tools to predict the responses of eight freshwater fish species with differing distributions and thermal tolerances to future climate change in lakes throughout the Midwestern United States. Lake-specific predictions varied among lakes and species, although across all locations temperatures were predicted to increase and average projected changes in fish abundance were linked to species thermal tolerances. July surface water temperatures were projected to increase by an average of 2.3℃ by mid century and 4.26℃ by the end of the 21st century. Coldwater cisco projected responses were most severe, with abundance predicted to decline by 85% and an average extirpation probability of 46% by the end of the 21st century. Coolwater walleye and northern pike were predicted to decrease by an average of 33% and 24%, respectively, while warmwater bluegill and largemouth bass were projected to increase in abundance by 7 and 4%, respectively, by the end of the century. Smallmouth bass and black crappie predicted responses varied by lake, but average changes in abundance across the region were close to zero. These results were integrated into a web tool for conservation planning to prioritize habitat restoration activities in the region. Collectively, this work demonstrates the power of interdisciplinary approaches for analyzing large datasets to understand and predict community responses to environmental change across diverse ecosystems. Biography: Dr. Gretchen Hansen is an Associate Professor of Fisheries Ecology at the University of Minnesota, United States. Her research focuses on understanding how freshwater fish populations and lake ecosystems respond to rapid environmental change, including climate warming, invasive species, and landscape disturbance. She leads a diverse research program that integrates long-term monitoring data, physiological experiments, advanced statistical modeling, and emerging tools such as environmental DNA and forward-facing sonar. She has published more than 80 peer-reviewed papers and works closely with agencies, Tribal partners, and NGOs to ensure her science informs real-world management. Dr. Hansen is currently on sabbatical developing and applying data-fusion methods to combine uncertain ecological data streams for improved detection and conservation of threatened and managed species. Her sabbatical includes collaborations with researchers in Aotearoa New Zealand, including NIWA and the University of Waikato, to explore applications of these methods in diverse ecosystems with unique conservation challenges.