Spatio-temporal model to quantify seasonal changes in streamflow across the northeast United States

Oregon Convention Center 

Studying the impacts of climate on the distribution and composition of fish communities is a recent priority of monitoring programs throughout the Northeast. Climate-mediated shifts in seasonal activities such as spawning have the potential to greatly influence a monitoring program's ability to distinguish changes in abundance or occupancy from shifts in phenology due to climate change. For fish, seasonal shifts in streamflow have the potential to affect growth, reproductive success, recruitment, abundance, and population size structure. In this work we develop a spatio-temporal model to quantify the spatial and temporal change in streamflow across the Northeast. Our approach captures spatial dependence and temporal dynamics through spatially and temporally-varying coefficients. We apply the model to streamflow data collected across 858 gauges in the northeast United States for the years 1965 to 2022. Formal model inference enables the identification of regions experiencing significant changes in seasonal cycles of streamflow. Further, it will inform supplemental sampling designs necessary for monitoring programs to track climate change impacts on fish populations.